diff --git "a/data/CSV_data/labelled_dataset_with_score.csv" "b/data/CSV_data/labelled_dataset_with_score.csv" new file mode 100644--- /dev/null +++ "b/data/CSV_data/labelled_dataset_with_score.csv" @@ -0,0 +1,1934 @@ +id,title,cr1,cr2,cr3,cr4,cr5,cr6,cr7,cr8,cr9,label_1,label_2,label_3,label_4,label_5,label_6,label_7,label_8,label_9,total_score +2,Engineering edgeless human skin with enhanced biomechanical properties,Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.,,"The experimental setup, data reporting, and manuscript writing were performed in accordance with Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines.","Experimental design + We first developed a protocol to generate skin constructs in fully enclosed and anatomical shapes (WESCs), postulating that remaining faithful to the physiological geometry of the skin would influence their biological and mechanical properties. Then, we assessed the most important features of skin grafts such as (i) epidermal coverage, maturation, and permeability; (ii) the dermal composition, organization, and its mechanical properties; (iii) the potential for vascularization; and (iv) the feasibility for seamless transplantation onto an anatomically complex recipient site. + + The CAD models of body parts were obtained from online databases or literature (29) and converted into hollow shells with pores on the surface using Netfabb and nTopology softwares. The inlet and outlet ports of the scaffolds were designed and then added to the scaffold shelves using the Solidworks software. The scaffolds were 3D-printed using a Carbon DLS printer through Protolabs (Telford, UK) and CadBLU (New York, USA) with a biocompatible material, KeySplint Soft (keyprint). All scaffolds were designed to have one inlet and one outlet port for perfusion, a shell thickness of 0.7 mm, and 0.5-mm pores with an average pore-pore distance of 2 mm. The optimal pore diameter was dictated by practical exigences and the aim to achieve the largest possible interface area between the dermis and the medium present inside the scaffold. Pores with a diameter of >0.5 mm cause the culture medium to leak through the scaffold wall during perfusion, while the printing resolution of the 3D printer used would not allow to fabricate pores with a diameter of <0.1 mm. In addition, the rheological characteristics of the printing material after curing had to be taken into account to balance the pore density and wall thickness. Therefore, we adopted the highest pore density possible according to the aforementioned parameters. To generate the negative PDMS molds, the 3D model of each scaffold was enlarged with a 4-mm offset, divided in two parts on the horizontal plane roughly in the middle of the longitudinal axis, and 3D-printed in polylactic acid with a benchtop 3D printer (Sindoh 3DWOX). Subsequently, the positive print was enclosed in a 3D-printed chamber, which was filled with PDMS (Sylgard 184, Electron Microscopy Sciences, #24236-10) mixed with curing agent at a 10:1 ratio and cured at 60°C overnight. The molds were designed to have docking channels to accommodate the inlet and outlet port and stabilize the scaffolds in the proper position during WESC generation. + + FBs were expanded up to passage #3 (P3), harvested with trypsin and resuspended in a neutralized and salt-balanced collagen solution with collagen type I (3 mg/ml; EMD Millipore, #08-115) at a density of 250 × 103 cells/ml to form the dermis solution. The scaffold was plugged through the inlet/outlet ports in the docking channels of one mold, and then the two complementary molds were assembled together. The dermis solution was injected in the 4- mm space between the scaffold and the mold and incubated at 37°C for 1 hour for collagen polymerization, and then the scaffold bearing the dermis was removed from the mold and submerged in dermis medium. The volume of dermis solution used varies for each type of scaffold, with roughly 5, 6, and 12 ml for cylinder, hindlimb, and hand, respectively. The dermis was cultured for 14 days to allow + contraction and remodeling, replacing the medium every other day before seeding the KCs. KCs at P3 were harvested when 90% confluent with Accutase and resuspended at 10 × 106 cells/ml in EpilifeS7 medium. After removing the dermis medium, the construct was repositioned within the PDMS molds, and a KC solution of about 1 × 106 cells/ml was injected into the mold and incubated on a rocking platform with a speed of 2 rpm. After 4 hours, the skin construct was removed from the mold and submerged in EPI medium (18). As an alternative method, in some constructs, the KC suspension was pipetted on the surface of the dermis, and the WESC was left to rest in the incubator for 30 min to allow KC attachment. The culture vessel was then filled with enough EPI medium to completely cover the WESC. The construct was further cultured for 5 to 7 days, changing the medium every other day. The cylinder and hindlimb constructs were seeded with 4 × 106 KCs, while the hand construct was seeded with 8 × 106 KCs. After epidermalization, the construct was seeded with ECs for the sprouting assay or directly switched to ALI culture with CORN medium (18) to allow terminal KC differentiation and cornification for all the other experiments. The grafts were seeded with ECs the day before the grafting in ALI culture conditions. For EC seeding, HDBECs 90% confluent at P3 were harvested with 0.5% trypsin and resuspended in coculture medium at a density of 4 × 106 cells/ml. For the sprouting assay, the cylinder was positioned lying flat on one surface, and 500 μl of cell suspension was injected inside the scaffold through the perfusion port. After letting the cells settle for 1 hour, the cylinder was flipped, and an additional 500 μl was injected through the same perfusion port. After 1 hour, the construct was submerged in coculture medium and switched to ALI culture the following day. To seed the ECs in the to-be-grafted constructs, the procedure was similar; in this case, the constructs were first cultured in ALI for 2 days, then the perfusion was momentarily stopped, and the ECs were injected inside the construct through a valve in the perfusion system. The perfusion was restarted after 2 hours to allow EC attachment. To transition to ALI culture, the constructs were removed from the culture vessel and transferred to a 100-ml culture bottle with a custom-made lid that allowed the passage of the perfusion tubing and gas circulation. The constructs were suspended in the air hanging from the lid supported by the tubing. The medium was perfused with a multichannel peristaltic pump (Ismatec, #ISM936C) at a rate of 5 ml/min. The construct culture bottle was connected through the fluidic system with a reservoir bottle with analog features that contained the culture medium. + + FBs were harvested at P3 with trypsin and resuspended in a neutralized and salt-balanced collagen solution with collagen type I (3 mg/ ml; EMD Millipore, #08-115) at a density of 165 × 103 cells/ml to form the dermis solution. To achieve uniform contraction, first, 1 ml of the neutralized collagen solution not containing cells was poured inside a transwell insert in a six-well plate (polyethylene terephthalate high-density 3-μm pores, Corning, #353092), then immediately after polymerization of the acellular layer, 3 ml of the dermis solution was layered on the top and incubated at 37°C for 15 min to allow for collagen polymerization, and then the culture plate and the transwell insert were filled in dermis medium to submerge the dermis. The dermis was cultured for 14 days to allow contraction and remodeling, replacing the medium every other day, after which the CDCs were used for downstream assays. + + The study was blinded to personnel that performed surgeries, animal care, and analysis (randomizing sample + order for the analysis).","After isolation, cells were subcultured for three passages before being used in the experiments. FBs were cultured in Dulbecco’s modified Eagle’s medium (DMEM) with GlutaMAX and sodium pyruvate (Gibco, #10569010) supplemented with 10% fetal bovine serum (Gibco, #16000069) and antibioticantimycotic (Gibco, #15240062). KCs were cultured in collagen I peptide–coated dishes (Corning, #354450) with Epilife medium (Gibco, #MEPI500CA) supplemented with S7 (Gibco, #S0175). The normal adult HDBECs were purchased from Promocell (#C- 12225, used for prevascularization of hindlimb grafts), while the green fluorescent protein (GFP)–tagged HDBECs were purchased from Angioproteomie (#cAP-0005GFP, used in vitro to assess the development of the blood vasculature in our model). The HDBECs were grown on dishes coated with Quick Coating Solution (Angioproteomie, #cAP-01) using endothelial growth medium MV (Promocell, #C-22120) and expanded for three passages before being used in the experiments. FBs and HDBECs were dissociated using trypsin-EDTA 0.05% (Gibco, #25300054), while Accutase (Gibco, #A1110501) was used for KCs. + + We isolated each region of the hand skin construct with paraffin gel and sequentially applied 50 μl of Lucifer yellow dye solution (Invitrogen, #L453) at a concentration of 10 mg/ml with intervals of 1 hour between each region, collecting medium samples every 10 min. Dye permeation was quantified by measuring the fluorescent emission in the medium samples at 514 nm with the SpectraMax iD3 Multimode Microplate Reader (Molecular Devices). To avoid fluorescence from phenol red, we used phenol red–free DMEM and F12 as basal media to culture the samples tested in this assay. + + The in vitro studies were conducted using a minimum of three biological replicates, with newborn 1 (NB1) CDCs n = 4, NB1 cylindrical WDCs n = 3 (with two technical replicates for the stretch test), NB1 hindlimb WDCs n = 6 (with two technical replicates for the stretch test), NB2 CDC n = 4, NB2 CSC n = 4, NB2 WDC n = 4, NB2 WESC n = 4, A CDC n = 4, and A WDC n = 4. Using the software G*Power, we calculated that a total of 10 mice were required to conduct the in vivo studies (point biserial correlation, effect size of 0.8, of 0.05, and power of 0.9566). A total of 11 mice were used (5 nonvascularized controls and 6 vascularized constructs).","Neonatal FBs and KCs from two newborns were isolated in our laboratory from foreskins donated to the Presbyterian Hospital (Columbia University Institutional Review Board protocol AAAB2666). Adult FBs (Promocell) were from the abdominal skin of a 75-year-old female. + + After 3 days of ALI culture, the hindlimb constructs were grafted in the left limb of 8- to 12-week-old immunodeficient mice [males and females, weight of 20 to 30 g, athymic nude strain Crl:NU(NCr)-Foxn1nu, Charles River]. Eleven mice were used in this study. The mice were first anesthetized with isoflurane, and then the skin covering the left hindlimb of the mouse was removed using surgical scissors. At that point, the graft was removed from the incubator and brought to the surgery room. + + The mice were divided between male and females (six and five, respectively) and randomly selected for grafting with nonprevascularized or prevascularized WESC using the function “= RAND()” in Microsoft Excel. + + Inclusion and exclusion criteria, beside the aforementioned animal characteristics (strain and age), were limited to apparent good health (inclusion) and signs of distress (exclusion).","All assays were repeated at least in triplicate, and the data are presented as the mean - SD. Shapiro-Wilk normality test and one-way analysis of variance (ANOVA) test (P < 0.05) were performed in Prism (Prism Software, Irvine, CA) to establish statistical significance between groups for the tangent modulus, low modulus, and stress. The qPCR data were analyzed through the software Prism 8 by using multiple unpaired t tests, not assuming a consistent SD for all rows. For all statistical analyses, P < 0.05 was considered significantly different, where *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.","Competing interests: H.E.A. has a pending patent application on this technology. All the other authors declare that they have no competing interests. + + Funding: This project is partially funded by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS: 5K01AR072131 to H.E.A.) and Epicure Center at Columbia University Medical Center (5P30AR069632). A.R.H.’s work was supported by the National Science Foundation Graduate Research Fellowship under grant no. DGE-2036197.",,1,0,1,1,1,1,1,1,0,7 +3,A randomized controlled pilot study of Yoga Skills Training versus an attention control delivered during chemotherapy administration,"Data Statement + The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. + + Supplementary materials + Supplementary material associated with this article can be found in the online version at doi:10.1016/j. jpainsymman.2021.07.022.",This trial was registered (NCT02489422).,,"Active Intervention. The Yoga Skills Training (YST) intervention was administered individually in the outpatient clinic. Patients were encouraged to also practice YST daily at home. First-line chemotherapy for GI cancers was generally given during biweekly visits and participants completed baseline at the time of their first chemotherapy visit (week 0). YST was adapted for the current study as detailed in another publication. Briefly, YST consisted of four 30 minute in-person sessions (weeks 2, 4, 6, 8) that taught the following skills: awareness, movement, breathing practices, and meditation. Participants were also given a 16-minute audio recording of the YST and devices to play the recording. All yoga instructors (four total, one primary at each site with backups including S. J. S.) had completed accredited yoga teacher training programs and were experienced teaching patients with chronic illness. + + Attention Control (AC). An empathic attention control group was employed to account for time, added attention, and efficacy expectations of the YST, as used in previous studies. The location, number of sessions, recommended frequency of home practice, and home assessments matched YST. The AC was delivered by research staff who were trained to create and maintain a relationship by using techniques of active listening, reflection of statements, and avoiding negative judgments. They utilized standardized instructions to prompt the patient: “What were some of the events or circumstances that affected you in the past two weeks?” The instructions for daily diary entries were the same with reference to “the past day?” Participants were asked to “Think back over the past day and write down up to five events that had an impact on you.” + + Treatment Fidelity. A number of steps were taken to ensure treatment fidelity. The study team trained interventionists during an initial session and ongoing monthly meetings. Interventionists completed a written test to confirm understanding, documented each + in-person session with a checklist, and were video recorded during all sessions with 10% of the recordings randomly selected for review by S. J. S. Each interventionist noted any adverse events experienced during sessions. In addition, interventionists asked participants about any problems during home practices. + + Measures + Patient-reported assessments of fatigue, depressive symptoms, and potential mediators were collected in person at four time points that coincided with biweekly chemotherapy or other clinic appointments (baseline, before the final intervention on Week 8, Week 10, and Week 14). We determined a priori that fatigue at Week 10 was the primary outcome. Inflammatory cytokines were measured in EDTA plasma samples collected along with patients’ regularly scheduled blood draws at weeks 2 and 10. Additional variables were documented to assess study feasibility (recruitment, retention), intervention acceptability, and sample characteristics. + + Patient Reported Assessments. Fatigue was assessed with the seven-item measure of Fatigue from the PatientReported Outcomes Measurement Information System (PROMIS)-Cancer (item responses: 1 = never, 5 = always over the past seven days). Items are summed converted to a standardized T-score. Higher T-scores on this and all PROMIS measures indicate more of the construct measured. Depressive Symptoms was assessed with the 10-item PROMIS-Cancer Depressive symptoms short-form. We measured Psychological Stress with the 10-item Perceived Stress Scale (PSS) and higher scores indicated more stress. Sleep Disturbance was assessed with the eight-item PROMIS sleep disturbance short-form.","Blood Draws (Inflammation). Inflammatory cytokines (IL-6, sTNF-R1, TNF-a) that have been associated with fatigue during treatment for gastrointestinal cancer 3 or influenced by yoga practice 19 were measured in plasma extracted from whole blood drawn during regularly scheduled clinical blood draws. IL-6 and TNF-a were measured using high-sensitivity Quantikine immunoassay kits. The inter-assay and intra-assay CVs for IL-6 are 6.5% and 4.1% respectively, and for TNF-a are 6.5% and 2.0%, respectively. sTNF-R1 was measured using standard Quantikine kits. All samples were assayed in duplicate and the average of the two measures were used for data analyses. Inter-assay variability in this internal control was low (IL-6 CV = 3.1%, sTNFR1 CV = 4.2%, TNF-a CV = 5.4%), indicating that cytokine levels can be measured reliably over time. + + Intervention Acceptability. High Intervention Adherence was defined by completing 75% of the planned in-person sessions and greater than or equal to three days of home practice per week. Throughout the intervention, all participants were asked to keep daily paper logs of home practice (weeks 3-8). In addition, one item on home practice that day was sent daily via an automated survey for two weeks after the intervention (weeks 9 -10). For daily reports of home practice missing values were treated as zero and reported for those who completed at least one report and for those missing all reports. Intervention Satisfaction was assessed with three items (0 not at all to 4 very much). + + Demographics and Clinical Data. Age, gender, race, ethnicity, relationship status, education level, income, comorbidities, use of medication to control symptoms, ability to pay monthly bills, willingness to participate in a group setting, use of psychological services, and use of yoga in the last two weeks was self-reported at baseline. Cancer type, stage of disease, recurrence status, receipt of radiation, height, and weight were abstracted from medical charts. + + Data were cleaned and databases locked prior to data analysis by arm.","Sample Characteristics + Enrollment occurred September 2015 to October 2019 (S. J. S. relocated mid study). We approached 77 eligible patients and enrolled 44 participants (YST n = 23, AC n = 21; Fig. 1 study flow diagram), for an overall recruitment proportion of 57% (95% Confidence Interval [CI]: 46%, 68%). Ten participants were enrolled after expanding eligibility criteria (3 had poor prognosis cancers). Patients who declined participation and provided demographic information (n = 24) did not differ from those enrolled by age, gender, ethnicity, or race (Supplemental Table 1). Frequent reasons for declining included not interested (n = 16) or overwhelmed (n = 11). Participants had a mean age of 58 years, a majority were White (86%), and had colon cancer (75%). Approximately half of participants were men (48%; Table 1). The study was stopped when the primary objective to determine preliminary efficacy was completed. + + Sample size justification was based on informing standard deviation (SD) estimates for a subsequent larger study. With a sample size of 44, the probability is 0.80 that the relative error in the estimate of the standard deviation (SD) will be less than 10%.","Feasibility statistics were estimated with proportions and 95% confidence intervals. Participant characteristics, intervention satisfaction, and adherence were summarized. Enrolled participants were compared to those who declined using chi-square tests and t-tests. Key statistical tests involved between group differences of the changes from respective baseline values of the PROMIS fatigue, depressive symptoms, and sleep disturbance t-scores and psychological stress. These tests were evaluated using mixed-effects generalized linear modeling procedures with week (categorical), arm, week by arm interaction, and were adjusted for randomization strata. Differences by arm in change from baseline were estimated using linear contrasts. Estimates of MIDs for PROMIS measures of fatigue, depressive symptoms and sleep range from 2.0 to 5.0. The median MID estimate specific to longitudinal analyses of the primary outcome of Fatigue (sevenitems) in advanced cancer patients was a t-score of 2.4 and effect size of 0.29. Guidelines for interpreting Cohen’s d indicate that a value larger than 0.2 represents a MID. + + Inflammatory cytokine data were skewed and thus natural log transformed prior to analysis using the same mixed model framework. Due to the natural log transformation and back-transformation, the difference of change scores represent the ratio of the arms on the original scale at 10 weeks with + adjustment for baseline (YST: AC). Exploratory analyses examined intervention dose (i.e., days of in-person attendance plus total days of home practice reported with values of 0 imputed for incomplete assessments) with outcomes using Pearson correlation. SAS (v9.4, Cary, NC) was used for statistical analysis. + + Seventy-seven percent of participants completed the primary outcome assessment at Week 10, two weeks after the final YST session (95% CI: 65%, 90%; YST = 87%; AC = 67%). Common reasons for not completing follow-up assessments were passing away on study (n = 4) or change in cancer treatment plan (n = 4). + There was a larger change in the primary outcome of fatigue in the YST group than the AC group from baseline Week 10 (-2.4 t-score point difference, d = 0.30, Table 2). This difference was consistent with a MID. Greater changes in fatigue in YST from baseline were lower than a MID, although in a consistent direction at Weeks 8 and Week 14. There was also a larger decline in the secondary outcome of depressive symptoms in the YST group compared to the AC group at Week 10 (-2.5 t-score point difference, d = 0.30). The larger decline in depressive symptoms in the YST group was also evident at Week 8, although no longer present at Week 14. Changes in depressive symptoms were consistent with an estimated MID.","Study Limitations + Estimates of effects should be interpreted with the consideration that they may be unstable due to the small sample and patient-reported measures may be biased by social desirability. Although the participation rate demonstrated feasibility, many potential participants were deemed ineligible, which slowed accrual. We chose to maintain homogeneity of the sample in this study to minimize confounds introduced by differences in cancer type. However, expanding eligibility to include other cancer types would enhance feasibility and generalizability of results. Also, while our sample represented patients seen in the recruitment clinics, these clinics had limited racial and ethnic diversity. Since those who agreed to participate did not differ on these characteristics compared to those who declined, recruiting from more diverse clinics will likely improve representation of other groups. Availability of yoga instructors was somewhat limited since interventions were planned around patients’ treatment. Broadening the pool of instructors, hiring a full-time instructor, or flexibility for intervention delivery (e.g., video conferencing) could improve this issue. + + Disclosures and Acknowledgments + L. I. W. has income for patient-reported outcome consultation outside of the submitted work from Celgene Inc. and Athenex Inc. and R. L. R. previously received consulting fees from Abbott not related to the current work. The other authors have no conflicts of interest to report related to the content of this manuscript.",,1,1,0,1,1,1,1,1,0,7 +4,"A Randomized, Multicenter, Evaluator-blind Study to Evaluate the Safety and Effectiveness of VYC-12L Treatment for Skin Quality Improvements","Data Sharing Statement + AbbVie is committed to responsible data sharing regarding the clinical trials they sponsor. This includes access to anonymized, individual, and trial-level data (analysis data sets), as well as other information (e.g., protocols, clinical study reports, or analysis plans), as long as the trials are not part of an ongoing or planned regulatory submission. This includes requests for clinical trial data for unlicensed products and indications. These clinical trial data can be requested by any qualified researchers who engage in rigorous, independent, scientific research and will be provided following review and approval of a research proposal, Statistical Analysis Plan (SAP), and execution of a Data Sharing Agreement (DSA). Data requests can be submitted at any time after approval in the United States and Europe and after acceptance of this manuscript for publication. The data will be accessible for 12 months, with possible extensions considered. For more information on the process or to submit a request, visit the following link: https://www.abbvie.com/our-science/clinical-trials/clinical-trials-data-and-information-sharing/data-and-information-sharing-with-qualified-researchers.html","This study conformed to the ethical guidelines of the 1975 Declaration of Helsinki, was conducted in compliance with GCP, is registered at clinicaltrials.gov (NCT#03728309), and all participants provided informed consent before treatment. Institutional review board approval was obtained from Copernicus IRB (Cary, NC).",,"Treatment + Before treatment, the cheeks were thoroughly cleaned, prepped with alcohol/antiseptic, and topical anesthesia and/ or ice were applied at the discretion of the TI. VYC-12L was administered through multiple intradermal microdepot injections to both cheeks. The allowable treatment area + spanned from the zygomatic arch to the edge of the jaw, lateral from the nasolabial fold and oral commissures to the preauricular cheek (Supplemental Digital Content, Figure S4, http://links.lww.com/DSS/B258). VYC-12L was provided in sterile syringes prefilled to 1 mL. Needle length selection (32 G 1/20 or 32 G 3/160), total injection volume, and injection spacing (#5 mm, .5 mm to 1 cm, or .1 cm) were determined by the TI in accordance with the maximum volume restrictions of 4 mL for initial and repeat treatments and 2 mL for touch-up treatment. + + Effectiveness + Primary Endpoint Skin Smoothness + A blinded EI live-assessed changes in cheek skin smoothness through responder rate on the ACSS ($1-grade improvement from baseline on both cheeks) at months 1 (primary endpoint), 2, 4, and 6 after the final injection (initial or touch-up). + Secondary Endpoints Fine Lines + A blinded EI assessed changes in cheek fine lines through responder rate ($1-grade improvement from baseline on both cheeks) on the AFLS20 at months 1 (secondary end point), 2, 4, and 6 after the final injection (initial or touch-up). + Skin Hydration + Skin hydration was measured using a MoistureMeterD instrument (Delfin Technologies Ltd., Kuopio, Finland). The MoistureMeter instrument probe measures the effective hydration of the stratum corneum,21 and different instrument probes can be used to assess water content of the epidermis or dermis. The XS 5 probe (0.5 mm depth of effective measurement) was used to measure treatmentrelated changes in hydration of the epidermis at baseline and months 1, 2, 4, and 6 after the final injection. + Participant-Reported Outcomes + Participant-reported outcome measures will be reported in a separate article. + + This was a randomized, multicenter, evaluator-blind, delayed treatment control (DTC) study conducted at 14 US sites. Participants were randomized in 2:1 ratio to receive the investigational VYC-12L treatment or DTC. The VYC-12L group received initial treatment and optional touch-up at month 1 if needed to achieve optimal correction. DTC participants were followed for 1 month after randomization and then either completed the study or received optional treatment (initial and touch-up, if needed) in the delayed treatment period. For both groups, follow-up visits occurred 3 days after each treatment for safety assessments and at 1, 2, 4, and 6 months after last injection (initial or touch-up) for effectiveness assessments. The study schedule is summarized in Supplemental Digital Content, Figure S3 (http://links.lww.com/DSS/B258) + + Treatment Administration + Injection parameters are summarized in Supplemental Digital Content, Table S3 (http://links.lww.com/DSS/ B262). Briefly, the median total volume injected for initial and touch-up treatments combined was 4.0 mL for both cheeks in the VYC-12L (range, 0.8–6.0 mL) and DTC (range, 1.0–6.0 mL) groups; injection volumes were similar for left and right cheeks. The target plane of injection was intradermal, and the most common injection technique was microdepot. For both groups, 32-G 1/20 needles were used approximately twice as frequently as 32-G 3/160 needles","Procedural pain was assessed at the initial treatment by the participant using an 11-point scale ranging from 0 (no pain) to 10 (worst pain imaginable). Participants recorded the incidence, severity, and duration of injection site reactions (ISRs) in an e-diary for each cheek for up to 1 month after any treatment, starting on the day of treatment. Participants’ e-diaries were reviewed by the TI at the 3-day and 1-month follow-ups to determine whether the ISR qualified as an adverse event (AE). The TI could declare an ongoing ISR to be reported as an AE depending on the severity and complication of the ISR, and the type of intervention required to resolve the reaction. AEs were monitored throughout the study. Snellen visual acuity, confrontational visual field, and ocular motility tests were performed by the TI after the initial, touch-up, and repeat treatments and at 3-day and 1-month follow-up visits. The FACE-Q Recovery Early Life Impact questionnaire was completed by participants 3 days after the initial treatment to assess the degree of disruption VYC-12L treatment had on normal daily activities + + Mean pain scores reported immediately after initial treatment were 3.0 for the VYC-12L treatment group and 2.4 for the DTC group. During the 1-month period after initial treatment, at least 1 ISR was reported by 81.5% (110 of 135) of the VYC-12L group and 75.0% (48 of 64) of the DTC group (Supplemental Digital Content, Figure S6, http://links. lww.com/DSS/B258).","Participants + Eligible participants were healthy adults ($22 years) with both cheeks rated as moderate (2) or severe (3) on the ACSS,19 assessed live by the blinded evaluating investigator (EI). Participants must have had a FACE-Q Satisfaction with Skin score of #69 and the treating investigator (TI) must have agreed that optimal correction for both cheeks combined could be achieved with #6 mL of filler. Participants were excluded if they had received dermal fillers, mesotherapy, or other cosmetic procedures (e.g., laser) in the face within the 12 months of screening or were planning to undergo any such treatment during the study; had received any cross-linked HA filler in any anatomic area within 12 months of screening; had received botulinum toxin injections in the cheek area (including lateral canthal area) within 6 months of screening or were planning to undergo such a treatment during the study; had received semi-permanent or permanent facial implants; or had begun using any topical or oral (over-the-counter or prescription) antiwrinkle products on the face within 30 days of screening or were planning to during the study. + + Participants + Of 255 screened participants, 209 were randomized in 2:1 ratio to the VYC-12L (n 5 136) or DTC (n 5 73) groups. A total of 195 participants (VYC-12L, n 5 131; control, n 5 74) completed the month 1 control period, and 171 participants (81.8%) completed the study. Reasons for study discontinuation included lost to follow-up (n 5 16), participant withdrawal (n 5 10), COVID-19 (n 5 4), and non–treatment-related serious AE (n 5 1). + Of the 202 participants in the mITT population, the majority of participants were female (86.1%), Caucasian (87.6%), not of Hispanic ethnicity (72.3%), and with a mean age of 57.1 years (range, 31–83 years) (Supplemental Digital Content, Table S2, http://links.lww.com/DSS/ B261). The majority of participants had Fitzpatrick skin phototypes III/IV (58.8%), followed by I/II (32.0%), and V/ VI (9.2%). Based on EI assessments, 61.9% of participants + were moderate and 38.1% were severe on the ACSS. On the AFLS, 34.7% of participants were rated moderate and 34.7% were rated severe by the EI. + The VYC-12L treatment group comprised 135 participants who received initial treatment; 98 participants (72.6%) received touch-up treatment, and 79 (58.5%) received repeat treatment. The DTC group comprised 64 participants who received initial treatment; 44 (68.8%) received touch-up treatment. + + Results + ACSS and AFLS Validation + Ninety participants completed ACSS validation and 92 completed AFLS validation. Participants for both studies were majority female (ACSS: 52.2%; AFLS: 53.3%), White (ACSS: 81.1%; AFLS: 79.3%), not of Hispanic or Latino ethnicity (ACSS: 93.3%; AFLS; 89.1%), and had Fitzpatrick skin phototypes III (ACSS; 36.7%; AFLS: 37.0%) and IV (ACSS: 25.6%; AFLS: 26.1%). Median age was 54.0 and 52.5 years for ACSS and AFLS validation studies, respectively. + For ACSS validation, interrater agreement was almost perfect (ICC $ 0.80) and intrarater agreement was substantial (k $ 0.71). For AFLS validation, interrater agreement was almost perfect (ICC $ 0.84) and intrarater agreement was substantial (k $ 0.73) (Supplemental Digital Content, Table S1, http://links.lww.com/DSS/B260)","Statistical Analyses + The modified intent-to-treat (mITT) population includes all randomized participants minus a small cohort of participants (n 5 7) enrolled for safety assessments only. The safety population includes all participants who were randomized and received at least 1 study treatment (VYC- 12L treatment group) and participants who were randomized to DTC. Demographic and safety data are summarized descriptively. For the primary effectiveness end point, ACSS responder rate and corresponding 95% confidence interval (CI) are summarized; a 2-sided Fisher’s exact test with a 5 0.05 was used to test whether the ACSS responder rate at month 1 in the treatment group was significantly greater than that in the DTC group. AFLS responder rates and corresponding 95% CIs are summarized. + + Effectiveness + At month 1, the ACSS responder rate (Figure 1A) was significantly greater for the VYC-12L group (57.9%; 95% CI, 49.3%-66.6%) than for the DTC group (4.5%; 95% CI, 2 0.5%-9.4%), with a difference of 53.5% (95% CI, 43.5%- 63.5%; p , .001). At month 1, the median change from baseline in ACSS score was 21.0 (range, 22 to 1) in the VYC- 12L group and 0 (range, 21 to 1) in the DTC group, with a decrease in score indicating improvement. Responder rates remained consistent for the VYC-12L group throughout the study, with a 55.6% responder rate at month 6 (Figure 1B). + The AFLS responder rate at month 1 (Figure 2A) was significantly greater for the VYC-12L group (58.3%; 95% CI, 47.8%-68.9%) than for the DTC group (5.4%; 95% CI, 0.0%-12.7%), with a difference of 52.9% (95% CI, 40.1%- 65.7%; p , .001). AFLS responder rates remained consistent throughout the study, with a 63.2% responder rate at month 6 (Figure 2B). + At month 1, MoistureMeterD measurements of skin hydration (Supplemental Digital Content, Figure S5A, http://links.lww.com/DSS/B258) showed mean increases from baseline of 2.353 and 0.113 for the VYC-12L and DTC groups, respectively. The increase in skin hydration following VYC-12L treatment remained consistent throughout the study, with a mean increase from baseline of 2.995 at month 6 (Supplemental Digital Content, Figure S5B, http://links.lww.com/DSS/B258)","One potential limitation of this study is the small number of male participants because the 2:1 randomization design meant that only 8 male participants were allocated to the DTC group. However, the safety profile of VYC-12L treatment was similar between male and female participants. Future studies of male participants’ outcomes following treatment with VYC-12L are warranted. Another limitation of the study is the small number of participants + with Fitzpatrick skin phototypes V and VI, and future studies with increased diversity of participants are needed. Additionally, the full extent of treatment-related changes in skin smoothness and fine lines may be difficult to fully appreciate in 2D photographs. Of note, ACSS and AFLS ratings were assessed live during the participant’s follow-up visit, allowing for a more thorough assessment of posttreatment improvements. + + The design, study conduct, and financial support for the study were provided by Allergan plc, Dublin, Ireland before its acquisition by AbbVie Inc. AbbVie participated in the interpretation of data, review, and approval of the publication. Medical writing and editorial assistance were provided by Sarah J. Cross, PhD, of AbbVie, and funded by AbbVie Inc.",,1,1,0,1,1,1,1,1,0,7 +5,"Effect of Weekly Subcutaneous Semaglutide vs Daily Liraglutide + on Body Weight in Adults With Overweight or Obesity Without Diabetes","Data Sharing Statement: See Supplement 5 + + [HIDDEN LINKS] + + Supplemental content: https://jamanetwork.com/journals/jama/fullarticle/10.1001/jama.2021.23619?utm_campaign=articlePDF%26utm_medium=articlePDFlink%26utm_source=articlePDF%26utm_content=jama.2021.23619",Trial registration clinicaltrials.gov identifier: nct04074161,JAMA,"Methods + Trial Design and Oversight + See Supplement 1 and Supplement 2 for the trial protocol and statistical analysis plan, respectively. This phase 3, 68-week, randomized, open-label trial was conducted at 19 US sites from September 2019 (enrollment: September 11-November 26) to May 2021 (end of follow-up: May 11; eFigure 1 in Supplement 3). It complied with the International Conference on Harmonization Good Clinical Practice guidelines and the Declaration of Helsinki. The protocol and amendments were approved by the institutional review board or independent ethics committee at each site; all participants provided written informed consent.","Procedures + Participants were randomized(3:1:3:1) using a blocking schema (block size of 8) via an interactive web response system to receiveonce-weekly subcutaneous semaglutide,2.4mg,ormatching placebo, or once-daily subcutaneous liraglutide, 3.0 mg, or matching placebo, for 68 weeks, with a 7-week follow-up. + Randomization to semaglutide or liraglutide was not masked(due todosingdifferences),but active treatmentgroups were double-blinded against matching placebo groups to mitigate potential bias arising from open-label comparisons. The placebo groups also facilitated comparisons of semaglutide and liraglutide vs placebo (secondary trial objectives), allowing evaluation of trial results in the context of previous findings. + Semaglutide, initiated at 0.25 mg, was escalated to 2.4 mg (maintenance dose) over 16 weeks (eFigure 1 in Supplement 3). A 1.7-mg maintenance dose was permitted if 2.4 mg could not be tolerated; 1 or more attempts to reescalate was advised. Liraglutide was initiated at 0.6 mg and escalated to 3.0 mg over 4 weeks; escalation could be delayed by a week to aid tolerability. Commensurate with the prescribing information,6 treatment was discontinued if liraglutide, 3.0 mg, was not tolerated; treatment could be restarted, with reescalation over 4 weeks. Treatments were administered using a multidose pen injector; the semaglutide(andmatchedplacebo)group switched to a single-dose pen injector for weeks 44 to 68. + All participants received counseling(from qualified health care professionals, every 4-6 weeks, via in-person visits or telephone) to adhere to diet (500-kcal/d deficit relative to baseline estimated energy expenditure) and physical activity recommendations (≥150 minutes/week).","Participants + Adults (≥18 years old) with 1 or more self-reported unsuccessful dietary weight loss efforts and a body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) of 30 or greater or 27 or greater with 1 or more weight-related comorbidities (hypertension, dyslipidemia, obstructive sleep apnea, or cardiovascular disease) were eligible (eAppendix 1 in Supplement 3). Key exclusion criteria included diabetes, hemoglobin A1c (HbA1c) level of 6.5% (48 mmol/mol) or greater, and self-reported body weight changes of more than 5 kg 90 days or less before screening. For regulatory requirements, race and ethnicity were recorded, determined by each participant according to fixed selection categories (including “other”). + + Sample Size Calculation + The hypothesized superiority of semaglutide to liraglutide for the primary and confirmatory secondary end points was assessed using a predefined hierarchical gatekeeping approach (eTable 1 in Supplement 3), with a statistically superior result (2-sided at the 5% significance level) required for each end point before the next could be tested. Data from the 2 placebo groups were pooled to increase power for statistical analyses of active treatment vs placebo, while limiting the number of participants required. + The sample size calculations used a t test on the mean difference assuming equal variances for body weight changes, and a Pearson χ2 test for 2 independent proportions for categorical weight loss. The calculation included assumed differences between active treatment groups of 5.5 percentage points in body weight change and ratios of 1.6, 2.2, and 4.5 for the proportions achieving 10% or more, 15% or more, and 20% or more weightloss(eTable2in Supplement3).These assumptionswere based on previous trials. The assumed difference in weight loss was greater than the US Food and Drug Administration– recommended5%orgreaterdifference threshold. Under these assumptions, 126 participants in each active treatment group provided the desired power of more than 90%. + In the pooled placebo group, 84 participants (42 per separate group) gave more than 99% power for the semaglutide vs pooled placebo comparison, and 80% or more power for liraglutide vs pooled placebo, for the primary end point.","Statistical Analysis + Two estimands evaluated treatment efficacy from different perspectives and accounted for intercurrent events and missing data differently (eAppendix 3 in Supplement 3). Analyses in the statistical testing hierarchy addressed the treatment policy estimand (primary estimand) using data from all randomized participants from the in-trial period (time from randomization to last contact with trial site), regardless of treatment adherence or rescue intervention initiation (antiobesity medications or bariatric surgery). + Continuous end points were analyzed using analysis of covariance, with randomized treatment (semaglutide, liraglutide, or pooled placebo) as a factor and baseline value of the outcome measure of interest (eg, baseline body weight in kilograms for analysis of percentage change in body weight) as a covariate. Binary confirmatory secondary end points were analyzed using logistic regression, with the same factor, and baseline body weight as a covariate. Analyses included all randomized participants from all treatment groups. + Amultiple imputation approach16 was used in whichmissing data were imputed by sampling from available measurements at week 68 from participants in the same treatment group and with the same treatment completion status. Imputation used a linear regression model with baseline value and last available observation of the outcome measure of interest from theon-treatmentperiod as covariates.One thousand complete data sets were generated and analyzed, with results combined using Rubin’s rules17 to obtain overall estimates. + Sensitivity analyses of the primary end point included prespecified tipping-point and jump-to-reference analyses (eAppendix 4 in Supplement 3), and a post hoc mixed-effects regression analysis with site as a random effect (to account for the multicenter design). + The secondary estimand(the trialproduct estimand) evaluated the effect of taking the drug as intended. Analyses addressing this estimand used data from all randomized participants from the on-treatment period (receipt of any dose of treatment within the previous 2 weeks [49 days for safetyrelated analyses]) until first discontinuation or rescue intervention initiation. The statistical models for assessing this estimand (including the post hoc analysis of change in pulse at week 68) are described in eAppendix 5 in Supplement 3. + Efficacy and AE-related end points were assessed for the full analysis set (all randomized participants) and the safety analysis set (all randomized participants exposed to ≥1 doses of randomized treatment), respectively. + Only the primary and confirmatory secondary end points were controlled for multiplicity. Because of the potential for typeI error due tomultiple comparisons, findings for other secondary end points and analyses should be interpreted as exploratory.Two-sided 95% CIs and corresponding P values were calculated for all statistical analysis results. Statistical analyses were performed using SAS version 9.4 (SAS Institute Inc). Efficacy results are reported for the treatment policy estimand only(unless stated otherwise). Data for permanent treatmentdiscontinuations, achievement of 5% ormoreweight loss, AEs, and change in pulse at week 75 were summarized by descriptive statistics only.","Limitations + This trial has several limitations. First, the response to poor tolerance of the maintenance dose differed; semaglutide was administered at a lower dose, whereas liraglutide was discontinued and had to be reescalated if restarted. This difference ensured the liraglutide regimen was consistent with the approved prescribing information,6 but could have led to more participants permanently discontinuing liraglutide after an AE than semaglutide. Furthermore, weight loss achievable with liraglutide could have been affected as participants may have continued with treatment for a shorter period of time, thus deriving less benefit, and potentially introducing bias into the treatment comparisons. A crossover trial with a washout period could clarify the reasons for, and effects of, the greater discontinuation rate with liraglutide. + Second,dosingdifferencesmeant participantsknew which active treatment they could potentially receive. The potential biasinthetreatment comparisonswasmitigatedbythematched double-blind placebo controls, but this could have been further improved with a double-dummy approach. This, however,wouldhavenecessitated a greaternumber of injections for participants (8 per week) and so was not chosen for this trial. + Third, missing data were handled through multiple imputation, which can potentially introduce bias because theremay be differences between the participants for whom data are imputed and thoseused for the imputation. However, retention in this trial was high, so the number of participants with missing data that needed to be imputed was low. Furthermore, the sensitivity analyses confirmed the primary analysis was robust. + + Conflict of Interest Disclosures: Dr Rubino reported being a clinical investigator for Boehringer Ingelheim, AstraZeneca, and Novo Nordisk; receiving honoraria from WebMD, speaker fees, consulting fees, scientific advisory fees, and honoraria from Novo Nordisk, grants from SARL, and personal fees from Medscape, PeerView, and the Endocrine Society; and being a shareholder in Novo Nordisk. Dr Greenway reported receiving grants from Novo Nordisk, Pennington Biomedical Research Center, and NuSirt to his institution during the conduct of the study and personal fees from Pfizer, NovMeta Pharma, Melior Discoveries, Jenny Craig, Basic Research, Gedeon Richter Pharma, Jazz Pharmaceuticals, General Nutrition Corp, Dr Reddy’s Lab, and Regeneron and stock ownership in Academic Technology Ventures, Energesis, Ketogenic Health Systems, MetaSYn Therapeutics, Plensat, Slim Health Nutrition, UR Labs, and Rejuvenate Bio. In addition, Dr Greenway has a patent issued for orlistat and a patent pending for pramlintide/albuterol. Also, Dr Greenway served on the Novo Nordisk advisory board for the development of liraglutide that is now approved and was a comparator drug in the trial described in the present article. Dr Khalid reported being an employee of Novo Nordisk. Dr O’Neil reported receiving grants from Novo Nordisk during the conduct of the study and grants from WW International, Eli Lilly, and Epitomee Medical and personal fees from Pfizer, Robard Corporation, Novo Nordisk, WebMD, and Gedeon Richter outside the submitted work. Dr Rosenstock reported receiving scientific advisory board fees, honoraria, consulting fees, and grants/research support from Novo Nordisk (during the conduct of the study and outside the submitted work), Applied Therapeutics, Boehringer Ingelheim, Eli Lilly, Intarcia, Oramed, + Hanmi, and Sanofi; honoraria or consulting fees from Zealand; and grants/research support from Genentech, Novartis, Pfizer, REMD Biotherapeutics, vTv Therapeutics, Metacrine, Merck, and Janssen outside the submitted work. Dr Sørrig reported being a full-time employee and shareholder of Novo Nordisk. Dr Wadden reported receiving grants from Novo Nordisk on behalf of the University of Pennsylvania and scientific advisory board fees from Novo Nordisk and WW (formerly Weight Watchers). Dr Wizert reported being a full-time employee and shareholder of Novo Nordisk. Dr Garvey reported receiving grants from Novo Nordisk; serving as site principal investigator for the clinical trial, which was sponsored by his university during the conduct of the study; receiving grants from Lexicon, Pfizer, Eli Lilly, and Epitomee outside the submitted work; and serving as an ad hoc consultant on advisory committees for Jazz Pharmaceuticals, Boehringer Ingelheim, Novo Nordisk, and Pfizer. In each instance, he received no financial compensation, nor was there a financial relationship. + + Funding/Support: This trial was funded by Novo Nordisk A/S. + + Role of the Funders/Sponsor: Representatives of the sponsor (Novo Nordisk A/S) were involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, and approval of the manuscript. Data were gathered by the site investigators, and the sponsor performed study site oversight, data collation, and analysis. A medical writer (Sophie Walton, MSc, of Axis, a division of Spirit Medical Communications Group Limited, funded by the sponsor) assisted with drafting the manuscript, under the direction of the authors. The sponsor did not have the right to veto publication or to control the decision regarding to which journal the manuscript was submitted. These decisions resided with the authors. + + Group Information: A complete list of investigators for the Semaglutide Treatment Effect in People With Obesity (STEP) 8 trial appears in Supplement 4.",JAMA,1,1,1,1,1,1,1,1,1,9 +6,Effect of Antiplatelet Therapy on Survival and Organ Support–Free Days in Critically Ill Patients With COVID-19 A Randomized Clinical Trial,"Supplemental content: https://jamanetwork.com/journals/jama/fullarticle/10.1001/jama.2022.2910?utm_campaign=articlePDF%26utm_medium=articlePDFlink%26utm_source=articlePDF%26utm_content=jama.2022.2910 + + Data Sharing Statement: See Supplement 4. + + [HIDDEN LINKS]",Trial registration clinicaltrials.gov identifier: nct02735707,JAMA,"Trial Design and Oversight + REMAP-CAP is an international, adaptive platform trial designed to iteratively determine best treatment strategies for patients with severe pneumonia in both pandemic and nonpandemic settings, and has reported on corticosteroids, anticoagulants, antivirals, interleukin 6 receptor antagonists, and convalescentplasmainpatientswith COVID-19. Patients eligible for the platform are assessed for eligibility and potentially randomized to 1 ormore interventions acrossmultipledomains. Domains encompass therapeutic areas and contain 2 or more interventions (including control). Details of the trial design have been reported previously and are available in the trial protocol and statistical analysis plan (Supplement 1). The trial was approved by relevant regional ethics committees and conducted in accordance with Good Clinical Practice guidelines and the principles of the Declaration of Helsinki. Written or oral informed consent, in accordance with regional legislation, was obtained from all patients or their surrogates. To account for the observed racial and ethnicdifferences in outcomesduringthepandemic,thistrialcollected self-reported race and ethnicity data from either the participants or their surrogates via fixed categories appropriate to their region. + + Interventions + All antiplatelet interventions were administered enterally until study day 14 or hospital discharge, whichever occurred first. + After 14 days, decisions regarding antiplatelet therapy were at + the discretion of treating clinicians. Antiplatelet dosing was as + follows:aspirin,75 to 100mgoncedaily; clopidogrel,75mgonce + daily without a loadingdose; ticagrelor,60mg twicedaily without a loading dose; prasugrel, a 60-mg loading dose followed + by 10mgdaily(ifaged<75yearsandweight≥60kg)or5mgdaily + (if aged ≥75 years or weight <60 kg). Gastric acid suppression + was recommended for patients receiving antiplatelet therapy + through co-administration of either proton pump inhibitor or + H2 receptor antagonist. Antiplatelet therapy could be discontinued if there was an adverse event or commenced in the control group if clinically warranted for a standard indication other + than COVID-19. Patients received concurrent anticoagulation + thromboprophylaxis according to standard care if not randomized in the anticoagulation domain of the trial. + + Outcome Measures + The primary outcome was respiratory and cardiovascular organ support–free days to day 21. In this composite ordinal outcome, all deaths occurring during the index hospitalization were assigned the worst possible outcome (–1). Among survivors, respiratory and cardiovascular organ support–free days were calculated up to day 21 (survivors with no organ support were assigned a score of 22). Secondary outcomes were survival to day 90, progression to invasive mechanical ventilation, extracorporeal membrane oxygenation or death among those not receiving that support at baseline, vasopressor-/inotrope-free days, respiratory support–free days, duration of ICU stay, duration of hospital stay, serious adverse events, World Health Organization ordinal score for clinical improvement (ranging from 0 [no evidence of infection] to 8 [death]), major bleeding up to day 14 defined according to International Society of Hemostasis and Thrombosis criteria (see eAppendix 1 in Supplement 2 for details) including fatal and intracranial bleeding, venous thromboembolism (deep vein thrombosis, pulmonary embolism, and other venous thromboembolism), arterial thrombosis (cerebrovascular event, myocardial infarction, and other arterial thrombotic event), as well as a composite of thrombosis or death. Individual components of the above mentioned composite outcomes were also prespecified as secondary outcomes but are not analyzed individually in this report. Thrombotic outcomes and major bleeding events were centrally adjudicated in a blinded manner.","Participants + Patients admitted to the hospital, aged 18 years or older, with clinically suspected or microbiologically confirmed COVID-19 were eligible for enrollment. Patients admitted to an intensive care unit (ICU) and receiving respiratory or cardiovascular organ support were classified as critically ill and all others + as non–critically ill. Respiratory organ support was defined as invasive or noninvasive mechanical ventilation including via high-flow nasal cannula if the flow rate was at least 30 L/min and the fraction of inspired oxygen was at least 0.4. Cardiovascular organ support was defined as receipt of vasopressors or inotropes. Exclusion criteria included presumption that death was imminent with lack of commitment to full support, clinical or laboratory-based bleeding risk sufficient to contraindicate antiplatelet therapy, creatinine clearance less than 30 mL/min or receipt of kidney replacement therapy, enrollment in an external trial of anticoagulation or antiplatelet therapy, or enrollment in the anticoagulation domain of the trial platform for participants older than 75 years. Patients were also excludedif theywere already receiving antiplatelet therapy or nonsteroidal anti-inflammatory drugs (NSAIDs), if a clinicaldecisionhad beenmade to commence antiplatelet orNSAID therapy, or if a treating clinician believed that participation in the domain would not be in the best interests of a patient. Critically ill patients had to be enrolled within 48 hours of admission to an ICU. Patients were enrolled from 105 sites in 8 countries (Canada, France, Germany, India, Italy, Nepal, the Netherlands, and the United Kingdom). Additional platform and antiplatelet domain–specific exclusion criteria are listed in eAppendix 1 in Supplement 2.","Treatment Allocation + The antiplatelet domain included 3 groups to which patients could be assigned: aspirin, P2Y12 inhibitor, and no antiplatelet therapy(control).Each site’s clinical investigator team chose a priori at least 2 intervention groups, one of which had to be control, towhichpatients couldbe randomized.Sites that chose the P2Y12 inhibitor intervention further selected which P2Y12 inhibitor would be administered at their site (clopidogrel, prasugrel, or ticagrelor) according to availability and local preference. Patients were randomized via centralized computer program with allocation ratios dependent on the number of interventions at each site. Patients were initially randomized equally across the interventions available at each site. The domain alsopermitted variationin allocation ratiosbasedon regular adaptive analysis. Randomization started on October 30, 2020. Response-adaptive randomization was applied on April 21, 2021 (see eFigure 1 in Supplement 2 for recruitment rates over time). Patients could be randomized to additional interventions within other domains, depending on domains active at the site, patient eligibility, and consent (see http:// www.remapcap.org). Other aspects of care were provided per each site’s standard care. + + Sample Size Calculation + The trial was designed with no maximum sample size given + the uncertainty of the pandemic. Sample size calculations + for theprimaryoutcomewereperformedusing trial simulations + of the adaptivedesign rules(seeeFigure2in Supplement2).The + domainhadatleast90%power todemonstrate superiorityofan + antiplatelet therapy tono antiplatelet therapywith900patients + enrolled assuming an odds ratio effect size of 1.5. The cumulative type I error rate up to 3000 patients was less than 5%. + + Enrollment and Participant Characteristics + The first patient was enrolled into the antiplatelet domain on October 30, 2020. On March 22, 2021, the prespecified equivalence trigger for the aspirin and P2Y12 inhibitor groups (compared with each other) was reached in critically ill patients with 1016 patients enrolled with complete data (P2Y12 inhibitor to aspirin odds ratio, 1.00 [95% CrI, 0.80- 1.23]; 90.1% posterior probability of equivalence). These groups continued to enroll separately but were subsequently statistically pooled into a combined antiplatelet group for all further adaptive analyses. On June 24, 2021, enrollment was discontinued after an adaptive analysis demonstrated that the prespecified stopping criterion for futility had been reached in critically ill patients, and patient follow-up continued until July 26, 2021. At that time, 1557 critically ill and 267 non–critically ill patients had been enrolled and randomized (Figure 1). Of these, 8 critically ill patients and 1 non–critically ill patient withdrew consent, and outcome data were not available for 17 critically ill and 3 non–critically ill patients. For non–critically ill patients, based on slow enrollment rates and external data,22 the international trial steering committee decided to simultaneously stop enrollment. Results for non–critically ill patients are shown in eAppendix 2 and eTables 2-4 in Supplement 2. Baseline characteristics were comparable between the intervention groups (Table 1; eTable 2 in Supplement 2). The median duration of antiplatelet therapy for critically ill patients randomized to receive aspirin was 12 (IQR, 7-14) days (data available for 560/565), and for those receiving a P2Y12 inhibitor the median duration was 11 (IQR, 6-14) days (data available for 433/455). Among 455 participants allocated to receive a P2Y12 inhibitor, 403 (88.5%) received clopidogrel, 6 (1.3%) received ticagrelor, 6 (1.3%) received prasugrel, and in 40 (8.8%) the P2Y12 inhibitor administered was unknown (for these remaining patients, site choice was clopidogrel for 13, ticagrelor for 17, prasugrel for 4, and unknown for 6). All patients with data available (n = 1419) received concurrent thromboprophylaxis according to usual care at the site or were concomitantly enrolled in the platform anticoagulation study. The most frequent concurrent anticoagulant at baseline was low-molecular-weight heparin (97.7%), and the most frequent dose was an intermediate dose (59%) (see eTable 1 in Supplement 2 for anticoagulation dose classification.","Statistical Analysis + The primary analysis was a bayesian cumulative logisticmodel, which calculated posterior probability distributions of organ support–free days (primary outcome) based on evidence accumulated in the trial and prior information. Prior distributions for treatment effects in critically and non–critically ill patients were nested in a hierarchical prior distribution centered on an overall intervention effect estimated with a neutral prior assuming no treatment effect (standard normal prior on the log odds ratio; see eFigure 2 in Supplement 2). The primary model estimated treatment effects for each intervention within each domain and prespecified treatment-by-treatment interactions. The primary model also adjusted for location (site nested within country), age (categorized into 6 groups), sex, and time period (2-week epochs). The model was fit using a Markov chain Monte Carlo algorithm that calculated the posterior distribution of the proportional odds ratios, including medians and 95% credible intervals (CrIs). The predefined statistical triggers for trial conclusions were (1) a superiority conclusion if there was greater than 99% posterior probability that an intervention was optimal compared with all other interventions; (2) an inferiority conclusion if there was less than 1% posterior probability that an intervention was optimal; (3) intervention efficacy if there was greater than 99% posterior probability that the odds ratio was greater than 1 compared with control; (4) intervention futility if there was greater than 95% posterior probability that the odds ratio was less than 1.2 compared with control; or (5) intervention equivalence if there was greater than 90% probability that the odds ratio (compared with each other) was between 1/1.2 and 1.2 for 2 noncontrol interventions. + On March 22, 2021, the equivalence trigger was reached for the primary outcome in critically ill patients for the aspirin and P2Y12 inhibitor groups. Randomization continued for these 2 antiplatelet groups, but for critically ill patients, the groups were statistically pooled and a single treatment effect relative to control was estimated for subsequent primary analysis. The 2 antiplatelet groups were not pooled for non– critically ill patients as no equivalence threshold had been reached. A prespecified interaction was modeled between antiplatelet therapy and therapeutic-dose heparin in the anticoagulation domain of the trial. + The primary analysis was conducted by an independent statistical analysis committee including all patients with COVID-19 randomized to any domain up to June 23, 2021 (and with complete follow-up for the primary outcome). Patients were analyzed in the groups to which they were originally randomized. There was no imputation of missing data for primary or secondary outcomes. Recruitment of non–critically ill patients was stopped due to slow recruitment and external evidence even though no statistical threshold for the primary outcome had been reached. The analysis of the results for non– critically ill patients is presented in eTables 2-4 in Supplement 2 for completeness. + Not all patients enrolled in the platform were eligible for all domains or interventions (dependent on active domains/ interventions at the site, eligibility criteria, and patient/ surrogate consent). Therefore, the analytical model included covariate terms reflecting randomization to each domain and the site, so that treatment effects were estimated only from patients who were concurrently randomized within the domain and directly comparing specific interventions available at each site. Patients enrolled outside the antiplatelet domain did not contribute to estimates of antiplatelet treatment effect but did contribute to the estimates of the covariate effects, providing the most robust estimation of covariate effects. + Sensitivity and secondary analyses were performed by investigators blinded to ongoing interventions, so these analyses were restricted to data from patients enrolled in domains that were unblinded at the time of analysis with no adjustment for assignment in the ongoing domains. Treatment effects were also analyzed for aspirin and P2Y12 inhibitors compared with control separately. Prespecified sensitivity analyses included removing time and site effects from the model, as well as independent priors for the 2 antiplatelet treatments and alternative priors for interactions with other interventions. Secondary dichotomous outcomes were analyzed with bayesian logistic regression models. The secondary time-to-event outcomes (mortality and length of stay) were analyzed using a piecewise exponential bayesian model to estimate hazard ratio effects. No formal hypothesis tests were performed on secondary outcomes, and summaries of the posterior distributions and probabilities are provided for descriptive purposes only. Prespecified subgroup analyses included baseline mechanical ventilation status, age category (<50, 50-70, or ≥70 years), and baseline anticoagulation dose (defined in eTable 1 in Supplement 2). In a post hoc analysis, the baseline anticoagulation categories were collapsed into 2 categories, therapeutic dose and less than therapeutic dose. If the dose was not recorded, it was included in an unknown-dose category. Further details of all analyses are provided in eAppendix 1 in Supplement 2 and in the statistical analysis plan (Supplement 1). Data management and summaries were created using R version 3.6.0; the primary analysis was computed in R version 4.0.0 using the rstan package version 2.21.1. Additional data management and analyses were performed in SQL 2016, SPSS version 26, and Stata version 14.2","Limitations + The trial has several limitations. First, it used an open-label design, although the primary outcome of survival and need for organ support was selected to minimize bias. Second, the use of a composite outcome has the potential to identify different effects of treatment on each component. Although each component is reported separately, there is limitedpower to give definitive answers about the effect of treatment on each component. Third, although there was an estimated effect of the combination of antiplatelet therapy with therapeutic-dose anticoagulation, the limited numbers of patients randomized simultaneously to both treatment domains and the wide 95% CrIs limit definitive conclusions. Fourth, results from 4 antiplatelet agents were pooled in the analyses (although very few patients received ticagrelor or prasugrel), and there was also substantial underlying heterogeneity in anticoagulation regimens used, limiting ability to draw firm conclusions for any given combination. + + Conflict of Interest Disclosures: Dr Bradbury reported receipt of personal fees from Lilly,BMS-Pfizer, Bayer, Amgen, Novartis, Janssen, Portola, Ablynx, and Grifols. Dr Lawler reported receipt of personal fees from Novartis, CorEvitas, and Brigham and Women’s Hospital and royalties from McGraw-Hill Publishing. Dr McVerry reported receipt of grants from the National Heart, Lung, and Blood Institute and Bayer Pharmaceuticals and personal fees from Boehringer Ingelheim. + Dr L. Berry reported being an employee of Berry Consultants; Berry Consultants receives payments for the statistical analysis and design of + REMAP-CAP. Dr Lorenzi reported being an employee of Berry Consultants; Berry Consultants receives payments for the statistical analysis and design of REMAP-CAP. Dr Zarychanski reported receipt of grants from the Canadian Institutes of Health Research, LifeArc, Research Manitoba, the CancerCare Manitoba Foundation, Peter Munk Cardiac Centre, and the Thistledown Foundation and research operating support as the Lyonel G. Israels Research Chair in Hematology. Dr Bonten reported membership in international study steering committees, advisory boards, and independent data safety and monitoring committees funded by Janssen Vaccines, Merck Sharp & Dohme, AstraZeneca, Pfizer, and Sanofi Pasteur (all reimbursements to UMC Utrecht). Dr Brunkhorst reported receipt of grants from Jena University Hospital. Dr Buxton reported receipt of a gift from the Breast Cancer Research Foundation and contracts with Amgen and Eisai. Dr Carrier reported receipt of grants from BMS-Pfizer and personal fees from Bayer, Sanofi, Servier, Leo Phama, and BMS-Pfizer to his institution. Dr Cove reported receipt of grants from the National Medical Research Council and personal fees from Baxter and Medtronic. Dr Estcourt reported receipt of grants from the UK National Institute for Health Research (NIHR) and the European Union Horizon 2020 Research and Innovation Programme. Dr Haniffa reported receipt of grants from the UK Research and Innovation/Medical Research Council African Critical Care Registry Network. Dr Horvat reported receipt of grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Institute of Neurological Disorders and Stroke. Dr Ichihara reported being affiliated with the Department of Healthcare Quality Assessment, University of Tokyo, which is a social collaboration supported by the National Clinical Database, Johnson & Johnson, and Nipro Corporation. Dr Marshall reported receipt of personal fees from AM Pharma and Critical Care Medicine. Dr McAuley reported receipt of personal fees from Bayer, GlaxoSmithKline, Boehringer Ingelheim, Novartis, Lilly, Vir Biotechnology, Faron Pharmaceutical, and SOBI and grants from the NIHR, the Wellcome Trust, Innovate UK, the UK Medical Research Council, and the Northern Ireland Health and Social Care Research and Development Division; in addition, Dr McAuley had a Queen’s University Belfast patent for novel treatment for inflammatory disease (US8962032), was co-director of research at the Intensive Care Society until June 2021, and was director of the Efficacy and Mechanisms Evaluation Program for the UK Medical Research Council/NIHR. Dr Middeldorp reported receipt of personal fees from Daiichi Sankyo, Bayer, Pfizer, Boehringer Ingelheim, Portola/Alexion, AbbVie, BMS-Pfizer, Sanofi, and Viatris, all paid to his institution, and grants from Daiichi Sankyo, Bayer, Pfizer, and Boehringer Ingelheim. Dr Neal reported equity in Haima Therapeutics, receipt of personal fees from Janssen Pharma and Haemonetics, and receipt of grants from Instrumentation Laboratory, the National Institutes of Health, and the Department of Defense. Dr Nichol reported receipt of personal fees from AM Pharma, paid to his university, and grants from Baxter. Dr Parke reported receipt of grants from Fisher and Paykel Healthcare NZ. Dr Serpa-Neto reported receipt of personal fees from Drager and Endpoint Health. Dr Seymour reported receipt of grants from the Gordon and Betty Moore Foundation and the National Institutes of Health/National Institute of General Medical Sciences. Dr Lewis reported being senior medical scientist at Berry Consultants; Berry Consultants receives payments for the statistical analysis and design of REMAP-CAP. Dr S. Berry reported being an employee with an ownership role at Berry Consultants; Berry Consultants receives payments for the statistical analysis and design of REMAP-CAP. Dr Derde reported being a coordinating committee member for the European Clinical Research Alliance on Infectious Diseases, a member of the Dutch Intensivists Task Force on Acute Infectious Threats, a member of the International Scientific Advisory Board for Sepsis Canada, and a member of the Dutch Academy of Sciences’ Pandemic Preparedness Plan committee. Dr Gordon reported receipt of personal fees from 30 Respiratory, paid to his institution. No other disclosures were reported. + + Funding/Support: This study was funded by the following: the Platform for European Preparedness Against (Re-)Emerging Epidemics (PREPARE) consortium of the European Union, FP7-HEALTH-2013-INNOVATION-1 (grant 602525), the Rapid European COVID-19 Emergency Research Response (RECOVER) consortium of the European Union’s Horizon 2020 Research and Innovation Programme (grant 101003589), the Australian National Health and Medical Research Council (grant APP1101719), the Health Research Council of New Zealand (grant 16/631), the Canadian Institute of Health Research Strategy for Patient-Oriented Research Innovative Clinical Trials Program (grant 158584), the NIHR and the NIHR Imperial Biomedical Research Centre, the Health Research Board of Ireland (grant CTN 2014-012), the University of Pittsburgh Medical Center (UPMC) Learning While Doing Program, the Translational Breast Cancer Research Consortium, the French Ministry of Health (grant PHRC-20-0147), the Minderoo Foundation, and the Wellcome Trust Innovations Project (grant 215522). Dr Shankar-Hari is funded by an NIHR clinician scientist fellowship (grant CS-2016-16-011) and Dr Gordon is funded by an NIHR research professorship (grant RP-2015-06-18). + + Role of the Funder/Sponsor: The study funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The platform trial has 4 regional nonprofit sponsors: Monash University, Melbourne, Victoria, Australia (Australasian sponsor); Utrecht Medical Center, Utrecht, the Netherlands (European sponsor); St Michael’s Hospital, Toronto, Ontario, Canada (Canadian sponsor); and the Global Coalition for Adaptive Research, San Francisco, California (US sponsor). Several authors are employees of these organizations. However, beyond the declared author contributions, the sponsors had no additional role.",JAMA,1,1,1,1,1,1,1,1,1,9 +7,"Safety, tolerability, and anti-fibrotic efficacy of the CBP/β-catenin inhibitor PRI-724 in patients with hepatitis C and B virus-induced liver cirrhosis: An investigator-initiated, open-label, non-randomised, multicentre, phase 1/2a study","Supplementary materials + Supplementary material associated with this article can be found in the online version at doi:10.1016/j.ebiom.2022.104069. + + A complete list of inclusion and exclusion criteria is provided in Supplementary material. + + Figure 2a and Supplementary Table 1","This study was registered at ClinicalTrials.gov (no. NCT 03620474). + + The registration of this trial after enrolment of the first patient was slightly delayed owing to the COVID-19 pandemic.","The Lancet + + Trial profile (Phase 1/2a). Consort diagram.","Methods This multicentre, open-label, non-randomised, non-placebo-controlled phase 1/2a trial was conducted at three hospitals in Japan. Between July 27, 2018, and July 13, 2021, we enrolled patients with HCV- and HBV-induced cirrhosis classified as ChildPugh (CP) class A or B. In phase 1, 15 patients received intravenous infusions of PRI-724 at escalating doses of 140, 280, and 380 mg/m2/4 h twice weekly for 12 weeks. In phase 2a, 12 patients received the recommended PRI-724 dose. The primary endpoints of phases 1 and 2a were the frequency and severity of adverse events and efficacy in treating cirrhosis based on liver biopsy. + + Methods + Study design and patients + In this multicentre, open-label, non-randomised, non-placebo-controlled phase 1/2a dose-escalation trial, we sequentially enrolled patients with HBV and HCV liver cirrhosis treated at the Cancer and Infectious Diseases Center of Tokyo Metropolitan Komagome Hospital (Tokyo, Japan), Kohnodai Hospital, the National Center for Global Health and Medicine (Chiba, Japan), and Kyushu University Hospital (Fukuoka, Japan). PRI-724 (PubChem database CID: 71509318) and the related information were provided by Prism Biolab (Kanagawa, Japan) and Ohara Pharmaceutical Co., Ltd. (Tokyo, Japan). + + Patients were enrolled into three cohorts and administered 140, 280, or 380 mg/m2 PRI-724 for 4 h in phase 1 and 280 mg/m2 in phase 2a, which was the recommended dose determined in phase 1. PRI-724 was administered for 12 cycles, with each cycle comprising two doses administered each week. A single dose was administered on Day-7 (tolerance: -7 days) before the start of administration in the first cycle. The starting dose was designated as level 1 (140 mg/m2). After confirming tolerability at Level 1, the dose was escalated to Level 2 (280 mg/m2) then Level 3 (380 mg/m2). Three patients were enrolled at each level. A minimum of six patients were enrolled at the dosage level regarded as the recommended dose. Safety and pharmacokinetic evaluations were conducted at this dose level.","Blood samples were drawn pre-dose and at 30 min as well as 1, 2, and 4 h after dosing and again at 1, 5, and 20 h after administration. We measured plasma concentrations of PRI-724 and C-82 (an active metabolite of PRI-724) in blood samples obtained from patients during phase 1. Three dose levels (140 mg/m2/4 h [starting dose], 280 mg/m2/4 h, and 380 mg/m2/4 h) were administered to three patients according to the guidelines for determining whether a patient proceeded to the next dose level. Fifteen patients received the recommended dose in phase 2a, during which PRI-724 efficacy and safety were assessed. + + Three patients in phase 1 who received 280 mg/m2 PRI-724 and underwent post-treatment biopsy with written informed consent were evaluated to obtain efficacy and safety data in phase 2a. Each patient was monitored for 28 days after the last day of administration. We recorded adverse events (AEs) and clinical laboratory results throughout the study and graded the AEs according to the Common Terminology Criteria for Adverse Events version 4.0. Investigators regularly assessed safety and tolerability, including serious adverse events (SAEs) and those associated with treatment discontinuation. + + Liver biopsy samples taken at screening were used as baseline data. Samples were also taken within 2 weeks + of the final treatment. Three independent pathologists examined all biopsy slides at baseline and 12 weeks in a blinded manner. Biopsy slides were evaluated using the Knodell scoring system, and fibrosis was staged according to the Ishak-modified histology activity index (HAI) grading scale. To evaluate whether PRI-724 exhibited an anti-fibrotic effect, we measured fibrosis in hepatic lobules using standardised computer-assisted image analysis. An independent pathologist blindly selected 10 Sirius Red-stained parenchyma spots in all biopsy samples and automatically calculated the positively stained areas using HistoQuant software (3DHISTECH, Budapest, Hungary). + + Data handling procedure. To guarantee the reliability and treatment of all study-related data, the Data Management Officer and staff shall implement quality control at every level of data handling based on the Procedures for Data Management Operations. The Data Management Officer and staff shall carry out the procedures up to database locking, including EDC system (DATATRAK ONE)construction, case reports, and data inspection, on the basis of materials including the Data Management Plan for this study. When data management operations have been completed, they shall produce a Data Management Report.","Key inclusion criteria were as follows: age of 20- 74 years and diagnosis with HCV- or HBV-induced liver cirrhosis that meets condition I or II presented below while also meeting condition III (I. Serum HCV-RNA positive or HCV-antibody positive [irrespective of viral load or treatment]; II. Serum HBV-DNA positive or HBs-antibody positive [irrespective of viral load or treatment]; III. Diagnosis of liver cirrhosis confirmed by a liver biopsy performed during the screening period [modified HAI fibrosis score of 5 or 6 or Metavir score of F4]). A complete list of inclusion and exclusion criteria is provided in Supplementary material. + + We enrolled 27 participants (15 in phase 1 and 12 in phase 2a). + + Sample size calculation. The rationale for enrolling patients in phase 2a was based on the results of a previous study on PRI-724-1101 and the results of a study by D’Ambrosio et al. who observed the natural course of + patients with SVR. In the PRI-724-1101 study, the fibrotic area ratio (%) of five patients (CP class A: 2 and CP class B: 3) was 4¢28§1¢72% before administration and 2¢21 § 1¢96% after administration. The amount of change was 2¢06§1¢95% (mean § SD, respectively). In contrast, D’Ambrosio et al. reported the use of data extraction tool WebPlot Digitizer Version 4¢0 to extract the original data from the graph summarising the natural history of patients with SVR. The fibrotic area ratio of 35 patients was 9¢86§4¢50% before SVR but improved to 3¢59§3¢03% five years after SVR, and the amount of change was 6¢26§4¢88%. Thirty-eight patients were included in the original paper, but three of them were excluded since their data could not be extracted. Assuming a constant rate of decrease in the fibrotic area, the amount of change due to a natural course of three months after SVR can be calculated as 0¢31 § 0¢24%, and the bilateral 95% confidence interval can be calculated as [0¢40%, 0¢23%]. Therefore, the amount of change due to drug administration can be expected to be at least 2¢06% minus the lower limit of the confidence interval of 0¢40% of the amount of change due to natural course, which is about 1¢66%. Since this clinical trial was based on a small number of studies, the number of patients enrolled was 15 as the amount of change of this study was conservatively assumed to be 1¢60%, the standard deviation to be 2¢00%, the significance level to be 5% on both sides, and the power to be 80%. Considering the dropout, 16 patients were considered necessary for evaluating the efficacy of phase 2a.","Analyses of primary and secondary endpoints + All patients were included in the analyses of PRI-724 safety, tolerability, and anti-fibrotic effect. All statistical analyses were descriptive and calculated for each treatment group. Data are expressed as the mean§standard deviation. Differences between groups were analysed using a two-tailed Student’s t-test, with a P<0.05 considered statistically significant. Clinical safety and pharmacokinetic data were included in safety analyses. The primary endpoint of phase 2a was analysed using a mixed model for repeated measures (MMRM), which permitted the analysis of continued treatment results even if some data were missing. We chose to use an MMRM since the subjects enrolled in the study were stable and their rapid deterioration was unlikely, indicating that missing data will likely be due to other reasons, including subjects’ social engagements. Since these are independent of the treatment effect of the investigational product, the use of an MMRM will not result in an overestimation. There was no further allowance for missing data. In addition, values outside the permissible range of the evaluation implementation time were treated as missing values and were not included with other evaluation time data. PK analyses were conducted in patients with evaluable PK concentrations using non-compartmental methods with Microsoft Office Excel and WinNonlin v6.1 (Pharsight Corporation, St. Louis, MO, USA). We performed pre-specified analyses of changes in LSM, CP score, and MELD score from baseline to 12 weeks post-treatment. We also performed a pre-specified secondary analysis of change from baseline in histological scores, which focused on patients with biopsy samples from baseline and 12 weeks after PRI-724 treatment. All analyses were performed using SAS software (v9.4; SAS Institute, Cary, NC, USA).","Although the number of treated patients was small, the protocol ensured patient safety, and liver biopsy results from some patients indicated PRI-724-mediated anti-fibrotic effects. However, a limitation of the current treatment protocol is the requirement for continuous administration for 1 week, whereas our experience suggests that infusion for 4 h twice weekly would be optimal. + + LSM obtained using FibroScan is a simple and widely used method; however, limitations have been identified. In particular, it may be difficult to measure the accuracy of numerical values in cases of hepatitis or cholestasis, patients with a narrow intercostal wall, patients with a thick abdominal wall, or areas with accumulated ascites. However, numerous reports have identified a correlation between fibrosis and liver stiffness, suggesting the utility of LSM for this evaluation. + + This study has some limitations. First, the sample size used for the analyses was small. This study did not include a placebo control group; therefore, the accuracy of the therapeutic effect remains questionable. In the next phase of trials, these points will be addressed, and a company-led clinical trial will be planned. + + Declaration of interests. There are no conflicts of interest. + + Funding AMED, Ohara Pharmaceutica + + Role of the funders The funder of the study was involved in study design but had no role in writing the report or data collection, analysis, or interpretation. The corresponding author had full access to all data in the study and the final responsibility for the decision to submit the study for publication. Japan Agency for Medical Research and Development was responsible for funding the study. Study drug and financial support were provided by Ohara Pharmaceutical. + + Contributors + KK was the coordinating principal investigator and led the clinical conduct at the Komagome Hospital, TK was the principal investigator at Kohnodai Hospital, SS was the principal investigator at Kyushu University Hospital. JI, MK and KN were study sub-investigators at Komagome Hospital, and EO at Kyushu University Hospital. KK consider concept of clinical trial, acquired funding, interpret the clinical data and wrote an original draft. TK, SS, EO, II, JK, KT, and TK collected, analysed, and interpreted the data. TK, SS, and EO review and edit the manuscript. MK, KN, and JI investigated and interpreted clinical data. KH, MS, and YI analysed and interpreted the histological data. TO, KI, and TI interpreted the clinical data and organised the safety of the study. JK led the work for the statistical analysis. II contributed to PK analysis. All authors read and approved the final version of the manuscript. + + This investigator-initiated study was supported by a grant “Development the Translational Research Network Program (JP20lm0203057h0003)” from the Japan Agency for Medical Research and Development (AMED). None of the funders played any role in the study design or data analysis and interpretation. We thank Editage (www.editage.jp) for English language editing.",the lancet,1,1,1,1,1,1,1,1,1,9 +8,Response prediction and risk stratification of patients with rectal cancer after neoadjuvant therapy through an analysis of circulating tumour DNA,"Supplementary materials + Supplementary material associated with this article can be found in the online version at doi:10.1016/j. ebiom.2022.103945. + + Data sharing + All relevant data are within the paper and its supplementary files. The raw data used and/or analysed during the study are available in the Genome Sequence Archive for Human repository [HRA001933 in https://bigd.big.ac.cn/gsa-human/].","This study was registered and the inclusion criteria for patients were presented on ClinicalTrials.gov with the number NCT02533271, STELLAR. The primary endpoint was 3-year relapse-free survival, defined as the time from the date of randomization to the first occurrence of local-regional failure or distant metastasis. The secondary objectives were 3-year local relapse-free survival, distant metastasis-free survival, and overall survival.",The Lancet,"Methods Sixty patients with LARC from a multicentre, phase II/III randomized trial were included, with tissue and blood samples collected. For each cfDNA sample, we profiled MRD using 3 approaches: personalized assay targeting tumour-informed mutations, universal panel of genes frequently mutated in colorectal cancer (CRC), and low depth sequencing for copy number alterations (CNAs). + + Patients enrolled were randomly assigned in a 1:1 ratio + to short-course preoperative radiotherapy (SCPRT, 5 Gy + x 5 alone) with neoadjuvant chemotherapy (NCT) (4 + cycles of capecitabine plus oxaliplatin regimen) and preoperative long-course chemoradiotherapy (2 Gy x 25 + with capecitabine). The treatment strategies in these + two groups were described in detail in STELLAR registration file. + + For each patient, we selected up to 22 somatic mutations from the tumour tissue. We designed customized + primers targeting the mutations and used the primers to profile the matched cfDNA with Mutation Capsule + technology as previously described. Briefly, the cfDNA was ligated to a customized adaptor and amplified to + produce a whole genome library that was subsequently used as a template and amplified with customized primers. Multiplex PCR primer pairs for the two rounds of nested amplification were designed using Oligo software (v7.53) and their uniqueness were verified in the human genome (http://genome.ucsc.edu/) to ensure amplification efficiency. In the first round of amplification, the whole genome library was amplified in 9 cycles of PCR using a target-specific primer and a primer matching the adapter sequence. A second round of 14 cycles of amplification was performed with one pair of nested primers matching the adapter and the target region to further enrich the target region and add the Illumina adapter sequences to the construct. The final libraries were sequenced using the Illumina NovaSeq 6000 platform at a median depth of 6835£ after removing duplicate molecules. The median on-target ratio of reads mapped to the target region was 80%. The clean reads were mapped to the human reference hg19 genome using 'BWA (v0.7.15) mem' with the default parameters. Samtools mpileup was used to identify somatic mutations, including SNVs and INDELs, across the targeted regions of interest. Each uniquely labelled template was amplified, resulting in a certain number of daughter molecules with the same sequence (defined as a UID family). If a mutation is pre-existing in the template molecule (original cfDNA) used for amplification, the mutation should be present in each daughter molecule containing the UID (barring any subsequent replication or sequencing errors). A UID family in which at least 80% of the family members have the same mutation is called the EUID family, indicating that it harbours a mutation that should be true instead of a false-positive mutation due to amplification or sequencing error. The mutant allelic fraction was calculated by dividing the number of alternative EUID families by the sum of alternative and reference families. Tissue-specific mutations with at least one distinct paired duplex EUID family or four distinct EUID families were subsequently manually checked in IGV and verified using a cross-validation method. The candidate mutations were annotated with Ensemble Variant Effect Predictor (VEP).","The tumour tissues were collected at the diagnostic stage by biopsy sampling, and peripheral blood was collected in EDTA Vacutainer tubes (BD Diagnostics; Franklin Lakes, NJ, USA) and centrifuged within 2 h of collection at 4000 £ g for 10 min to separate plasma and blood cells. Plasma was centrifuged a second time at 12,000 £ g for 10 min at 4°C to remove any remaining cellular debris and stored at -80°C. + + Clinical serum levels of the biomarkers carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9) were monitored at baseline, before surgery and after surgery. CEA and CA19-9 levels were measured with immunoelectrochemiluminescence, with CEA concentrations of < 5.0 ng/mL and CA19-9 concentrations of < 27.0 U/mL considered within the reference range. Chest/abdominal/pelvic CT scans were performed every 3 months during the first two years and then every 6 months for a total of 5 years. Clinicians were blinded to the ctDNA results during the courses of neoadjuvant therapy. + + Genomic DNA (gDNA) was extracted from fresh frozen tumour biopsies and WBCs with the QIAamp DNA Mini Kit (Qiagen; Germantown, MD, USA), and cfDNA was extracted from 1.5-4.5 mL of plasma with the Apostle MiniMax cfDNA isolation kit (C40605, Apostle; San Jose, CA, USA). Targeted sequencing of a panel of 509 genes or exomes was performed using genomic DNA obtained from tumour tissue and WBCs as previously described. + + Briefly, the raw data (FASTQ file) were aligned to the UCSC human reference genome hg19 using BurrowsWheeler aligner software (BWA, v0.7.15). Basic processing, marking duplicates, local realignments and score recalibration were performed using The Genome Analysis Toolkit (GATK, v3.6), Picard (v2.7.1) and Samtools (v1.3.1). Candidate somatic mutations were detected by comparing sequencing data from tumour tissue samples with MuTect1 and Strelka. All selected mutations were further validated by performing a manual inspection using Integrated Genome Viewer (IGV). + + The raw sequencing data were treated as described above, and the next segmentation analysis was performed using QDNASeq (v1.14.0). The resulting output files were summarized using R software (v4.0.3). Overlap analysis was performed using bedtools (v2.17.0) and plotted with UpSetR (v1.4.0) within the R package (v4.0.3). Chromosome arm-level alterations show cancer-specific patterns. For example, a hierarchical clustering analysis of mean arm-level calls performed across 3,000 TCGA samples revealed that gastrointestinal tumours clustered with gains of chromosomes 8q, 13q, and 20. Some of these CNAs, including gains of chromosomes 1q, 8q, 7,12q, 13q, and 20q and loss of chromosomes 1p, 20p, and 22q, were also recurrently identified in our cohort as hot CNAs (34 baseline plasma samples from patients with LARC compared with 70 plasma samples from healthy controls). Therefore, we defined the CNA number as the sum of hot chromosome arms altered (|Z| > 2) to represent the level of copy number variation.","Patient characteristics and tissue mutation identification + Patients with locally advanced rectal cancer (n = 82; cT3- 4N0 or cTanyN1-2) were enrolled in the trial from December 30, 2016, to October 8, 2018. Twenty-two patients were excluded due to the lack of plasma samples obtained after NAT (Figure 1a). Thirty-one patients were treated with long-course neoadjuvant chemoradiotherapy (LCRT), and 29 patients were treated with short-course neoadjuvant radiotherapy (SCPRT) with neoadjuvant chemotherapy (Table 1). The median follow-up period was 33.25 months (range, 9.6342.43 months). Seventeen (28.33%) patients were diagnosed with local relapse or metastasis during follow-up, including 5/17 (29.41%) with local relapse, 6/17 (35.29%) with liver metastasis and 6/17 (35.29%) with lung metastasis (Table S1). + One hundred ninety-six blood samples were available during the treatment process, including baseline (collected before NAT, n = 42), in-process (collected during NAT, n = 35), post-NAT (collected 2 weeks after SCPRT or LCRT, n = 60) and pre-TME (collected before surgery, n = 59) samples (Figure 1a). We performed targeted sequencing with a panel of 509 genes or exome sequencing on the genomic DNA isolated from the tumour tissue and matched WBCs, and then identified a median of 51 (range, 3-177) somatic mutations in each tumour (Table S2). The mutational landscape of the top 15 most significantly mutated genes in the cohort was shown in Figure 1b. Customized primers were designed to profile up to 22 somatic mutations in the matched cfDNA with Mutation Capsule technology (Table S3) as previously described. + + Thirty-five patients with a positive ctDNA fraction at baseline were analysed (35/42 patients) to explore the performance of the ctDNA fraction in monitoring the NAT response. With ctDNA clearance defined as ratio of post-NAT ctDNA fraction to baseline ctDNA fraction below 2% (median value of the ratio), 19 (54.29%) patients showed no clearance at the post-NAT time point relative to baseline ctDNA fraction values (Figures 5, S3b). For patients with or without ctDNA clearance, there were 9/16 (56.25%) and 18/19 (94.74%) exhibited nonpCR/cCR (clinical complete response), respectively.","Statistics + In this clinical cohort-based investigative study, the primary aim was to test the hypothesis that changes in the ctDNA fraction during treatment dynamically reflect minimal residual disease. Correlation analysis between input and estimated ctDNA in ctDNA fraction model and analysis of variance for the assessment of longitudinal plasma samples were the exploratory studies. Method for hypothesis testing and survival analysis was commonly used by previous researchers. Specifically, correlation analysis used Spearman’s correlation analysis. For continuous variables, differences in ctDNA fractions between recurrence and non-recurrence groups were assessed with MannWhitney (rank sum) test, ctDNA fractions across treatment courses of NAT were assessed by Kruskal-Wallis test and post hoc using Dunn's multiple comparisons test, and the ctDNA fraction was assessed for patients with paired baseline and post-NAT data using Wilcoxon matched-pairs signed rank test. Differences in clinical characteristics between patients with positive and negative ctDNA fractions were evaluated with Fisher’s exact test for categorical variables. These statistical analyses were performed with Prism 8 software (v8.4.3). Relapse-free survival (RFS) was measured from the date of randomization to the first occurrence of local-regional failure or distant metastasis. The univariate analysis was conducted using the KaplanMeier method with the log-rank test. HR values were calculated using univariate Cox proportional hazard models. The multivariate analysis was based on the Cox proportional hazard model in which the common important factors, such as age, sex, and clinical risk (according to the ESMO guidelines) were included. The survival model was evaluated with the C-index. The KaplanMeier curves were verified by performing a time-dependent receiver operating characteristic (ROC) curve analysis, and the area under the curve (AUC) was calculated to evaluate the prognostic performance. These analyses were performed using R software (v4.0.3). P values < 0.05 from a 2-sided test were considered statistically significant in all analyses. A sample of fifty patients was needed to achieve the power of 0.8 in this study as previously described. + + We next checked longitudinal status of the ctDNA fraction and its possible association with the disease course, therapeutic effect and survival status of all 60 patients (Figure 4a). Compared with baseline and in-process samples, a clear trend of a reduced post-NAT ctDNA fraction was observed in both the recurrence and nonrecurrence groups (Figure 4b), which highlighted the significant therapeutic effect of NAT. We noticed a more substantial reduction in the ctDNA fraction during baseline, in-process and post-NAT stages within the nonrecurrence group (Dunn’s multiple comparison test, baseline vs. in-process: P = 0.0130; baseline vs. postNAT: P < 0.0001; in-process vs. post-NAT: P = 0.0009) compared to the recurrence group (Dunn’s multiple comparison test, baseline vs. in-process: P > 0.9999; baseline vs. post-NAT: P = 0.1819; in-process vs. post-NAT: P = 0.4114) (KruskalWallis test, nonrecurrence group, P < 0.0001; recurrence group, P = 0.113) (Figure 4b). Moreover, the post-NAT ctDNA fraction status exhibited the strongest association with RFS, followed by the status at the in-process (HR = 3.61; 95% CI, 0.73-17.91; log-rank P = 0.093) and baseline stages (HR = 1.58; 95% CI, 0.20-12.67; log-rank P = 0.66). For the 17 patients experiencing recurrence, the median lead time between the detection of positive post-NAT ctDNA fraction and finding of radiological recurrence was 10.2 months (range, 0.1-33.2 months) (Wilcoxon matched-pairs signed rank test, P = 0.0001) (Figure S3a). We explored whether ctDNA fraction dynamics were linked to RFS by specifically focusing on the 42 patients with both baseline and post-NAT samples and observed a decreased ctDNA fraction in most patients (85.71%, 36/42). For the 9 patients experiencing recurrence, the ctDNA fraction after NAT increased in 4 (44.44%) patients and decreased but was still positive in 4 (44.44%) patients. In the nonrecurrence group (n = 33), the ctDNA fraction decreased to undetectable levels in 30 patients (90.90%) (Figure 4c). These data showed better predictive value of the post-NAT ctDNA fraction status than the ctDNA fraction dynamics (HR = 7.40; 95% CI: 1.97-27.82; log-rank P = 0.00053; sensitivity of 44.44% and specificity of 93.94%) for RFS estimation. The ctDNA fraction (post-NAT) in MRD-positive samples varied significantly from 0.05% to 12.74%. We divided the post-NAT samples into two groups to test if the ctDNA fraction values were correlated with the recurrence status: highly positive ctDNA fraction ( 1%) and moderately positive ctDNA fraction (0.05%-1%). The RFS of the 3 patients with highly positive post-NAT ctDNA fractions was shorter (< 200 days) than that of the moderately positive group (Figure 4d). In patient FL126 with two post-NAT plasma samples, the ctDNA fraction in plasma was moderately positive (0.16%) at 20 days after NAT and highly positive (3.50%) at 141 days, and lung metastases appeared in this patient only 43 days after the second time point (Figure 4e). In patient FL199 with a moderately positive ctDNA fraction (0.23%), local relapse occurred 306 days later (Figure 4e). The dynamic ctDNA fraction in the remaining samples was shown in Figure S4. + + The association between ctDNA fraction clearance and response to neoadjuvant therapy was significant (Fisher's exact test, P = 0.013).","This study had several limitations. First, the sample size was modest, and a limited number of patients were included in each subgroup, such as longitudinal plasma samples or patients who accepted LCRT/SCPRT. Second, intervention studies are required to explore the potential clinical utility of ctDNA to guide therapeutic decision-making and to determine whether the administration of neoadjuvant chemotherapy under ctDNA guidance may exert a positive effect on survival. + + Declaration of interests + YCJ is one of the cofounders, has owner interest in Genetron Holdings, and receives royalties from Genetron. The other authors have declared that no competing interest exists. + + Role of the funding source + The sponsors did not have any role in the study design, data collection, data analyses, interpretation, or writing of the manuscript. + + Funding + The National Key R&D Program of China, Beijing Municipal Science & Technology Commission, National Natural Science Foundation of China, and CAMS Innovation Fund for Medical Sciences. + + Acknowledgements + The authors would like to thank Ying Zhang for the assistance with sample collection and Pei Wang for the primary technical assistance. This work was supported by financial support were as follows: the National Key R&D Program of China [2021YFC2500900], Beijing Municipal Science & Technology Commission [Z181100001718136], National Natural Science Foundation of China [82073352], and CAMS Innovation Fund for Medical Sciences [2017-I2M-1-006 and 2021-I2M-1- 067]. The sponsors had no role in study design, data collection, data analyses, interpretation, and writing of the manuscript. + + Funding The Beijing Municipal Science & Technology Commission, National Natural Science Foundation of China, and CAMS Innovation Fund for Medical Sciences",the lancet,1,1,1,1,1,1,1,1,1,9 +9,"Human mesenchymal stem cell therapy in severe COVID-19 patients: 2-year follow-up results of a randomized, double-blind, placebo-controlled trial","Appendix A. Supplementary data + Supplementary data related to this article can be found at https://doi. org/10.1016/j.ebiom.2023.104600. + + Data sharing statement + After approval from the Human Genetic Resources Administration of China, this trial data can be shared with qualifying researchers who submit a proposal with a valuable research question. A contract should be signed.","The aim of this study was to evaluate the safety and efficacy of a MSC treatment administered to severe COVID-19 patients enrolled in our previous randomized, double-blind, placebo-controlled clinical trial (NCT 04288102). + + The aim of this study was to evaluate the safety and efficacy of a MSC treatment administered to severe COVID-19 patients enrolled in our previous randomized, double-blind, placebo-controlled clinical trial (NCT 04288102). + + (NCT04288102)",the lancet,"As previously described, allogeneic MSCs derived from human umbilical cord were supported by VCANBIO Cell & Gene Engineering Corp (Tianjin, China). MSC (or placebo) was infused intravenously three times at 3-day intervals, with (or without) each dose of 4.0 × 107 cells in a volume of 100 ml/bag. Standard of care was provided according to the 7th edition of guidelines for the diagnosis and treatment of COVID-19 issued by the Chinese National Health Commission. During follow-up visits, patients were physically examined by trained physicians and completed SF-36, NRS, and symptom (e.g., appetite, sleep difficulties, pain or discomfort, fatigue or muscle weakness, anxiety or depression, and usual activity) questionnaires. In addition, a high-resolution CT (HRCT) of the chest, a standardized 6-MWD test, routine blood and biochemical tests, tumor markers, and SARS-CoV-2 NAb assays were performed. + The 6-MWD test was conducted according to practical guidelines of the American Thoracic Society. The results are expressed as distance walked in 6-min. LLN was additionally calculated by subtracting 153 m from the predicted value for men, and by subtracting 139 m for women. Lung lesions were evaluated based on HRCT images and imaging interpretations provided by three independent radiologists evaluating the outcome of lung damage. All radiologists were blinded to the treatment allocation during analysis, and final outcomes were determined by consensus. CT findings were assessed based on distribution, density, morphology, internal structure of the lesions, and mediastinum. TSS was used to quantify anatomic involvement (Appendix 1). Levels of SARS-CoV-2 NAb were detected according to the manufacturer’s instructions at month 24 (Appendix 2). Through the follow-up period, AEs were defined as abnormal symptoms, signs, laboratory tests, and tumorigenesis among the patients with severe COVID-19 or comorbidities after receiving treatment. + + Methods A total of 100 patients experiencing severe COVID-19 received either MSC treatment (n = 65, 4 × 107 cells per infusion) or a placebo (n = 35) combined with standard of care on days 0, 3, and 6. Patients were subsequently evaluated 18 and 24 months after treatment to evaluate the long-term safety and efficacy of the MSC treatment. Outcomes measured included: 6-min walking distance (6-MWD), lung imaging, quality of life according to the Short Form 36 questionnaire (SF-36), COVID-19-related symptoms, titers of SARS-CoV-2 neutralizing antibodies, tumor markers, and MSC-related adverse events (AEs).","The outcomes evaluated in this study included: (1) distance walked in 6-min (6-MWD) and the proportion of patients with a 6-MWD below the lower limit of the normal range (LLN); (2) lung imaging according to the percentages of normal CT images and total severity score (TSS); In our previous report, lung lesions were measured by centralized imaging interpretation based on both lung radiologist analyses and Lung Imaging Artificial intelligence system software (LIAIS). After 1 year, LIAIS was not sensitive enough to segment the lesion area and distinguish injured area from normal lung tissue along with lung repair. Herein, we evaluated the lung lesions only by radiologist analyses at the 18- and 24-month follow-ups. (3) quality of life according to the Short Form 36 (SF-36) questionnaire; (4) COVID-19-related symptoms measured based on symptom questionnaires and numerical rating scales (NRS); (5) titers of SARS-CoV-2 neutralizing antibody (NAb); and (6) MSC-related adverse events (AEs) and tumor markers.","In our previous phase 2 double-blind, randomized, placebo-controlled trial of MSC treatment for severe COVID-19 patients (NCT04288102), a total of 101 patients were enrolled between March 6, 2020 and March 20, 2020. A total of 100 patients finally received either MSC (n = 65) or placebo (n = 35) combined with standard of care on days 0, 3, and 6. Key inclusion criteria were: hospitalized patients with severe COVID- 19 confirmed by real-time reverse transcription PCR assay, either man or woman, aged 18–75 years old, and pneumonia combined with lung damage confirmed by chest computed tomography (CT). Major exclusion criteria were: shock, organ failures, invasive ventilation, malignant tumor, pregnancy, lactation, or co-infection with other pathogens. Severe COVID-19 was defined as any of the following conditions: dyspnea with respiratory rate ≥30/min; oxygen saturation ≤93% on room air; arterial oxygen partial pressure (PaO2)/fraction of inspired oxygen ≤300 mmHg; or lung lesion on CT progressed >50% in 24–48 h. Sex information was collected from the Hospital Information System, which was recorded according to the participant’s identity card. Follow-up was conducted at day 28, month 3, month 6, month 9, and month 12, results been reported previously. After the 28-day follow-up for the primary endpoint, the trial was unblinded on June 23, 2020. For the present study, data from additional follow-up visits conducted at month 18 and month 24 (between September 4, 2021, and May 31, 2022) at the outpatient clinic of General Hospital of Central Theater Command (Wuhan, Hubei, China) were collected to evaluate the long-term safety and efficacy of MSC treatment. Written informed consent was obtained from all of the participants. This study was approved by the Ethics Committee of the Fifth Medical Center, Chinese PLA General Hospital (2020-013-D).","Statistics + This study had no predefined hypotheses. Thus, statistical tests, confidence intervals (CIs), and p values were used for description rather than inference. Continuous variables were reported as median [interquartile range (IQR)] or mean [standard deviation (SD)] values and were compared across groups using the Wilcoxon rank sum test or Student’s t-test. The Hodges-Lehmann estimation was used to determine the 95% CI of the median differences for the non-normally distributed variables. Categorical variables were reported as n/N (%) and compared across groups using the Chi-square test, the continuity-adjusted Chi-square test or Fisher’s exact test. A logistic regression model was used to estimate odds ratios (ORs). Additionally, a post-hoc subgroup analysis was performed according to age (<65 y vs. ≥ 65 y) and body mass index (BMI) (≤24 kg/m2 vs. > 24 kg/m2) to explore heterogeneity of the therapeutic benefits of MSC. No adjustment for multiple testing was applied. The modified intention-to treat population was used as the analysis population. Missing values were not included. Statistical analyses were performed using SAS software (version 9.4; Cary, NC, USA). Figures were generated using GraphPad Prism software (version 8.0, San Diego, CA, USA).","There were several limitations associated with the present study. First, despite being one of the largest randomized controlled trials of MSC treatment, future clinical trials with larger sample sizes are needed to validate these preliminary findings. Second, given the large number of tests performed, the drawbacks of multiple comparisons must be fully appreciated. Third, a longer follow-up period inevitably involves the challenge of retaining all of the randomized patients in a cohort. Loss to follow-up can reduce statistical power and bias results, thereby leading to treatment safety or efficacy being overestimated. Therefore, the preliminary findings of the present study need to be interpreted carefully, and exact conclusions remain to be verified in prospectively designed studies with adequate statistical power. + + Funding The National Key Research and Development Program of China (2022YFA1105604, 2020YFC0860900, 2022YFC2304401), the specific research fund of The Innovation Platform for Academicians of Hainan Province (YSPTZX202216) and the Fund of National Clinical Center for Infectious Diseases, PLA General Hospital (NCRCID202105,413FZT6). + + Role of the funding source + The funder of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. + + Declaration of interests + HF, WQY, YZ and RDB are current employees of Wuhan Optics Valley Zhongyuan Pharmaceutical Co.,Ltd. TYD and LLZ are current employees of Wuhan Optics Valley Vcanbio Cell & Gene Technology Co., Ltd. All authors declare no other conflicts of interest. + + This study was supported by the National Key Research and Development Program of China (2022YFA1105604, 2020YFC0860900, 2022YFC2304401), the specific research fund of The Innovation Platform for Academicians of Hainan Province (YSPTZX202216) and the Fund of National Clinical Center for Infectious Diseases, PLA General Hospital (NCRC-ID202105,413FZT6).",the lancet,1,1,1,1,1,1,1,1,1,9 +10,Framing Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults,"Reproducible Research Statement: Study protocol: Available from Dr. Patel (e-mail, mpatel@upenn.edu). Statistical code and data set: Not available.","Design: Randomized, controlled trial. (ClinicalTrials.gov: NCT 02030119)",Annals of internal medicine,"Intervention: 13-week intervention. Participants had a goal of 7000 steps per day and were randomly assigned to a control group with daily feedback or 1 of 3 financial incentive programs + with daily feedback: a gain incentive ($1.40 given each day the goal was achieved), lottery incentive (daily eligibility [expected value approximately $1.40] if goal was achieved), or loss incentive ($42 allocated monthly upfront and $1.40 removed each day the goal was not achieved). Participants were followed for another 13 weeks with daily performance feedback but no incentives. + + Setting: University of Pennsylvania. + + METHODS + Design Overview + We conducted a 26-week randomized, controlled trial between 6 March and 6 September 2014, consisting of 13-week intervention and follow-up periods. A total of 281 participants gave their informed consent and were randomly assigned to a control group or to 1 of 3 groups with different financial incentive designs, each with the same expected economic value. All participants were given a goal of achieving at least 7000 steps per day, and this target reflects several deliberate design elements. First, this level of physical activity is endorsed by the American College of Sports Medicine to be approximately equivalent to meeting the federal guidelines for the minimum recommended levels of physical activity needed to achieve health benefits (25, 26). Second, this level is 40% higher than the average daily step count of 5000 among U.S. adults (27, 28). Prior studies using an even higher goal of 10 000 steps have found that more sedentary persons may be less likely to participate, and it was a priority in this study to engage as many persons as possible (12). Third, instead of simply asking participants to increase steps, a minimum threshold puts greater emphasis on encouraging more sedentary persons to be physically active and less emphasis on getting highly active persons to be even more active. + + Participants were electronically randomly assigned to the control group or to 1 of 3 intervention groups with an equivalent expected economic value of $1.40, which is a value used in prior work (34). For 26 weeks, participants in all 4 groups received daily feedback on whether they had achieved the 7000-step goal in the prior day. The control group received no other intervention aside from daily feedback. For the 13-week intervention, the intervention groups included a gain incentive in which participants received $1.40 for each day they met the goal, a loss incentive in which $1.40 was taken away from a monthly incentive ($42 allocated upfront) each time the daily goal was not met, or a daily lottery incentive. Persons in the lottery-incentive group selected a 2-digit number between 00 and 99. One winning number was randomly selected daily during the intervention period. If a participant's number had a single-digit match (an 18% chance), he or she won $5. If the participant's number had a 2-digit match (a 1% chance), he or she won $50. Participants were eligible to collect the reward only if the 7000-step goal was achieved on the prior day. Ineligible participants were informed what they would have won if they had achieved the goal, drawing on evidence that the desire to avoid regret can be motivating (23, 24, 35, 36). Incentives were offered only during the 13-week intervention, but daily performance feedback was delivered for the entire 26 weeks. + + Neither the participants nor the study coordinator could be blinded to the group assignment. All investigators, statisticians, and data analysts were blinded to group assignments until the 26-week study ended.","Measurements: Primary outcome was the mean proportion of participant-days that the 7000-step goal was achieved during the intervention. Secondary outcomes included the mean proportion of participant-days achieving the goal during follow-up and the mean daily steps during intervention and follow-up. + + Step counts were tracked using the Moves smartphone application (ProtoGeo Oy), which uses accelerometers within the phone and has been shown by our + prior work to be accurate (29). Each participant was + given a unique personal identification number to enter + into the smartphone application and verify permission + that the study team could access step-count data. Once + the application was installed on the phone, the participant never had to reopen it, although they could as + often as they wished. Instead, participants had to allow + the application to run passively on the phone, have the + phone powered on, and carry it with them (for example, in a pocket or on a belt clip or arm band) while they + were active.","Participants: 281 adult employees (body mass index ≥27 kg/m2). + + Setting and Participants + Eligible participants were employees of the University of Pennsylvania in Philadelphia, Pennsylvania, were aged 18 years or older, and had a body mass index (BMI) of at least 27 kg/m2 (estimated from self-reported height and weight). We chose this BMI threshold to help ensure that our sample represented overweight or obese persons. Participants were recruited by e-mail from February to March 2014 and excluded if they were already participating in another physical activity study, were not able or willing to carry an iPhone (Apple) or Android (Google) smartphone with the mobile application installed, were pregnant or lactating, intended to become pregnant within 6 months, or stated that they could not complete the study. E-mails were sent to all University of Pennsylvania staff employees (approximately 10 000 persons). All eligible participants provided electronic informed consent, completed a sociodemographic questionnaire, self-reported measures of height and weight, and reported recent physical activity using the long form of the International Physical Activity Questionnaire (30). + + Participants enrolled online using Way to Health, an automated technology platform based at the University of Pennsylvania that integrates wireless devices, conducts clinical trial randomization and enrollment processes, delivers messaging (text message or e-mail) and surveys, automates transfers of financial incentives, and securely captures data for research purposes (31).","Statistical Analysis + One participant randomly assigned to the gain incentive group was later found to be ineligible because of enrolment in another physical activity study. One participant randomly assigned to the lottery incentive group switched to a phone that was not eligible for use before the study began and therefore did not receive the intervention. Both of these participants were excluded from the analysis. All other randomly assigned participants were included in the intention-to treat analysis. + For each participant on each day of the study (participant-day level), we obtained the number of steps achieved as a continuous variable. Data could be missing for any day if a participant turned off the smartphone or the application, disabled the study team's permission before data were accessed, or did not carry the smartphone at all. For the main analysis, we used only collected data (a step-count value was received). This approach is based on the assumption that missing data occur at random and do not bias outcomes for groups with differing levels of missing data. Using the continuous steps data, we estimated the mean daily steps among participants in each group during the intervention and follow-up. We dichotomized the data at the participant-day level to create a binary variable indicating that the participant achieved the 7000-step goal (value, 1) or did not achieve it (value, 0). Using this binary variable, we estimated the mean proportion of participant-days achieving the goal for the group of participants in each group during the intervention and follow-up and for each week during the study. + For adjusted analyses, we used PROC GLIMMIX in SAS, version 9.4 (SAS Institute), to fit a generalized linear model with participant random effects, a random intercept, time-fixed effects (at the weekly level), and treatment-fixed effects (by study group) (37–40). We assumed a normal distribution for models using the continuous outcome and obtained the difference in steps among groups using the least-squares means (LSMEANS) command. We assumed a binomial distribution with logit link for models using the binary outcome to estimate adjusted difference in the proportion of participant-days achieving the goal and used the bootstrap procedure, resampling participants, to obtain 95% confidence intervals and P values (41, 42). We used a pseudolikelihood method (38) but also performed a sensitivity analysis for the main models using the quadrature approximation with 12 nodes specified (43). + Several sensitivity analyses were conducted to assess the robustness of our findings. For the primary and secondary outcomes using the binary and continuous variables, respectively, the main model was further adjusted by using device-fixed effects for smartphone type (iPhone or Android). The model was also evaluated by using all data and coding missing data (when a step value was not received) as “not achieving the goal” (in contrast to using only collected data), which is a method used in prior work (33). Further, evidence suggests that step-count values less than 1000 are unlikely to represent accurate data capture of actual activity (27, 44, 45). Therefore, to avoid these observations from downward biasing mean daily step outcomes, we did a sensitivity analysis using the model with values less than 1000 excluded from the sample. + A priori, we estimated that a sample of at least 260 participants (65 per group) would ensure 80% power to detect a 0.20 difference between each intervention group and the control group. We used a conservative Bonferroni adjustment of the type I error rate with a 2-sided a value of 0.017. This calculation assumed that the mean proportion of participant-days achieving the goal in the control group would be 0.40. We increased the participant enrolment target to 280 to account for a potential 8% dropout rate.","Limitation: Single employer. + + Primary Funding Source: National Institute on Aging. + + Role of the Funding Source + This work was funded by the National Institute on Aging. Support was also provided by the U.S. Department of Veterans Affairs and the Robert Wood Johnson Foundation. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. + + Our study has several limitations. First, participants were from a single employer in Philadelphia, which may limit generalizability because physical activity is harder in some regions with different climate, outdoor space, and culture. Second, participants needed a smartphone, which potentially makes participation less likely for those without such a device. Third, participants' physical activity was not tracked when they were not carrying their smartphones; thus, the captured physical activity levels may be lower than their actual activity. At the end of the intervention, however, about 93% of respondents stated that they carried their smartphone most or all of the time. Fourth, we did not obtain data on baseline step counts, but randomization resulted in well-balanced study groups. Therefore, outcomes among groups may reflect the differential effectiveness of interventions. In addition, self-reported physical activity did not differ among groups; however, these data seem to reflect overestimates of baseline activity because step-count data indicate that our population may be less physically active than they initially reported. Finally, our study was not well-powered to detect smaller differences or do comparisons among the intervention groups. In addition, the continuous outcome measure had a wider distribution than anticipated and we did not have enough statistical power to adequately detect differences among study groups + + Grant Support: By the National Institute on Aging (grant RC4 AG039114; Drs. Asch and Volpp) and in part by the Department of Veteran Affairs (Drs. Patel, Asch, and Volpp) and Robert Wood Johnson Foundation (Drs. Patel and Asch). + + Disclosures: Dr. Asch reports grant support from the National Institutes of Health during the conduct of the study; further, he is a principal and part owner of the behavioral economics consulting firm VAL Health. Ms. Hilbert reports grant support from the National Institute of Aging during the conduct of the study. Dr. Volpp reports grant support from the National Institutes of Health during the conduct of the study. Further, he reports consulting income from CVS Health and VAL Health (principal and part owner) and grants (or grants pending) from CVS Health, Humana, Merck, Weight Watchers, Discovery (South Africa), and Hawaii Medical Services Association; and stock in VAL Health, all outside of the study. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje /ConflictOfInterestForms.do?msNum=M15-1635",Annals of internal medicine,1,1,1,1,1,1,1,1,1,9 +11,β blockers and mortality after myocardial infarction in patients without heart failure: multicentre prospective cohort study,"Data sharing: The authors commit to making the relevant anonymised patient level data available on reasonable request + + Additional material is published online only. To view please visit the journal online.","trial registratiOn + Clinical trials NCT00673036.",BMJ,"Design + Multicentre prospective cohort study. + setting + Nationwide French registry of Acute ST- and non-STelevation Myocardial Infarction (FAST-MI) (at 223 centres) at the end of 2005. + + Main OutCOMe Measures + Mortality was assessed at 30 days in relation to early use of β blockers (≤48 hours of admission), at one year in relation to discharge prescription, and at five years in relation to one year use. + + Methods study design + The population and methods of the FAST-MI registry have been described in detail elsewhere.10 11 Briefly, the objective of the study was to collect comprehensive data on the management and outcome of consecutive patients admitted to intensive care units for definite acute myocardial infarction over a one month period in France, irrespective of the type of institution to which the patients were admitted (university hospitals, public hospitals, or private clinics, with or without on-site catheterisation facilities). Of the 374 centres that treated patients with acute myocardial infarction at that time, 223 (60%) participated in the study. + All consecutive adult (≥18 years) patients admitted to the participating centres during a one month period beginning on 1 October 2005, with a one month extension for patients with diabetes, were included in the registry if they had elevated serum markers of myocardial necrosis higher than twice the upper limit of normal for creatine kinase, creatine kinase-MB, or elevated troponins; had symptoms compatible with acute myocardial infarction and/or electrocardiographic changes on at least two contiguous leads with pathological Q waves and/or persisting ST elevation or depression greater than 0.1 mV; and consented to participate in the study. The time from the onset of symptoms to admission to the intensive care unit had to be less than 48 hours. Patients with iatrogenic myocardial infarction, defined as occurring within 48 hours of a therapeutic procedure, and those in whom diagnosis of acute myocardial infarction was invalidated in favour of another diagnosis were excluded from the survey. Patients were not involved in the registry organisation. The patients had to give their informed consent for participation in the study.","Data collection + Specially trained research technicians who visited each centre at least once a week prospectively recorded all data on computerised case record forms. Cardiovascular history, drug treatment at the time of admission, risk factors, and in-hospital clinical course, including maximal Killip class, as well as initial diagnostic and therapeutic management, were recorded for each patient. Discharge drugs, including type and dose of β blockers, were recorded. We considered doses at or above 50 mg/day for atenolol, 100 mg/day for metoprolol, 200 mg/day for acebutolol, or 5 mg/day for bisoprolol to be moderate to high doses. + Follow-up was centralised at the French Society of Cardiology, and dedicated research technicians contacted both the physicians and the patients themselves or their families, after checking the patients’ vital status in municipal registers. Information on cardiovascular and non-cardiovascular hospital admissions and drug prescriptions during follow-up was sought; drug use was self reported by the patients and in many instances supported by copies of the medical prescription. + When the patients or their families or physicians reported events that had led to hospital admission, hospital discharge letters and supportive documents were retrieved whenever possible. All events reported + were reviewed by at least one member of a three member critical events committee (ND, TS, and Pascal Guéret); the committee reviewed all cases that seemed debatable. Cause of death was assessed in the same way and additionally cross linked with the national database of causes of deaths. For the analysis presented here, we used the following classification: cardiovascular cause, non-cardiovascular cause, cause undetermined; in addition, we categorised mode of death into sudden or non-sudden. + The rates of patients lost to follow-up for vital status were 0.3% at one year and 4.1% at five years. The outcome variables used for this study were all cause mortality at 30 days, one year, and five years.","Participants + 2679 consecutive patients with acute myocardial + infarction and + + Populations studied + A first analysis focused on the association between early use of β blockers (within 48 hours of admission) and 30 day mortality in patients without previous history of heart failure and without signs of heart failure on admission (Killip class I) (population 1; fig 1). We then analysed the relation between β blockers at discharge and one year mortality in the population without history of heart failure and with no sign of heart failure (Killip class I) throughout the hospital stay and without documentation of an ejection fraction of 40% or below before hospital discharge (using echocardiography, contrast left ventricular angiography, or radionuclide assessment of left ventricular function) (population 2; fig 1 ). We did a third analysis in the subset of population 2 who had received β blockers at discharge and were alive at one year, to determine five year outcome according to persistence of β blockers at one year (population 3; fig 1). Finally, we did an analysis of five year mortality according to persistence of statin treatment at one year in population 3 patients who were discharged taking statins. We used this analysis to determine whether its results would be concordant with those of the randomised trials of statins after acute myocardial infarction, which, unlike β blocker trials, were conducted in the contemporary era of reperfusion therapy and invasive strategies for patients with acute coronary syndromes. + + Patient involvement + No patients were involved in setting the research question, nor were they involved in developing plans for recruitment, design, or implementation of the study. No patients were asked to advise on interpretation or writing up of results. Patients were contacted personally during follow-up, and we sent them a newsletter on the course of the study and its main findings + + Of the 3670 patients included in the registry, 991 had a history of heart failure before the current episode or had Killip class II or higher at admission.","statistical analysis + All continuous variables are described as their mean values with standard deviation or as median and interquartile range. All categorical variables are described using absolute and relative frequency distributions. Comparisons between groups used unpaired t tests or non-parametric Mann-Whitney tests for continuous variables and χ2 tests for discrete variables. We generated survival curves by using the Kaplan and Meier method and used log rank tests to compare them. Patients lost to follow-up were kept in the analyses and censored at the time they were last known to be alive. We used backwards Cox multivariable analyses for assessing the association between β blockers and mortality. We used a P value of 0.05 for inclusion and 0.10 for exclusion. We calculated the cumulative hazard functions for each covariate to assess proportionality and verified collinearity by calculating variance inflation factors. + We did several analyses using different sets of covariates for the three populations studied. We selected covariates ad hoc, on the basis of their physiological relevance and potential to be associated with short term or long term mortality. A detailed description of the variables used is provided in appendix 1 of the supplementary material. + In addition, we used non-parsimonious logistic regression analysis to calculate propensity scores for getting β blockers at each time point (first 48 hours, discharge, one year), leading to one propensity score for each population. Within each population, we matched one patient not receiving β blockers with a given propensity score with one (populations 1 and 2) or three (population 3) patients receiving β blockers and having a similar propensity score, by using a greedy procedure based on the Mahalanobis distance within propensity score callipers set at a 0.2*sigma. A first propensity score was calculated in population 1, and two cohorts were matched with a 1:1 ratio (502 patients each); a second propensity score was calculated in population 2, with a 1:1 matching procedure (383 patients each); finally, a third propensity score was calculated in population 3, with a 3:1 matching procedure (95 patients who discontinued β blockers and 277 with prolonged β blocker treatment). Model fits were satisfactory: Hosmer-Lemeshow P value 0.41, C statistic 0.75 for the model in population 1; Hosmer-Lemeshow P value 0.83, C statistic 0.83 for population 2; and Hosmer-Lemeshow P value 0.45, C statistic 0.72 for population 3. We also used propensity score matching (3:1 matching) to compare patients with continued versus discontinued statin treatment at one year in the population who had received both statins and β blockers at discharge. Model fit for continuation of statins at one year: Hosmer-Lemeshow P value 0.63, C statistic 0.80. + We used the IBM-SPSS version 20.0 and NCSS 9 software for all analyses. For all tests, we considered a P value of less than 0.05 (two sided) to be significant.","limitations of study + As in all observational studies, this analysis has limitations. At the acute stage, the most severely ill patients less often receive β blockers, and statistical techniques may not be sufficient to adjust completely for these confounders, thereby increasing the measured favourable association between early β blocker treatment and mortality. Conversely, because only a minority of patients did not receive β blockers at discharge and a smaller minority still discontinued β blockers during the first year, we cannot exclude the possibility that unusual, and therefore unmeasured, confounders explaining the absence of prescription or discontinuation of treatment existed. However, FAST-MI provided very detailed characterisation of the patients, making it unlikely that major confounders were not recorded. In addition, unrecorded confounders would probably have been similar for statins and β blockers. + Also, we did not do a formal sample size calculation for our analysis, and the limited size of our population increases the risk of a type B error and of an underestimation of the potential benefit of β blockers, especially during the first year. Therefore, the lack of statistical significance for β blocker prescription at discharge cannot be considered proof of its lack of effect. Likewise, subgroup analyses or analyses according to type or dose of β blockers should be interpreted with caution. + More importantly, most observational data have shown that patients who adhere to preventive drugs are more “health conscious” than those who do not adhere,22-24 with a less severe profile, including their socioeconomic status, and an overall better prognosis, thus leading to a “healthy user” bias (in other words, adherence to any drug in itself is associated with higher survival). In this regard, the striking difference between mortality in patients who stopped β blockers and those who stopped statins (granting that patients stopping β blockers were also more likely to stop other recommended drugs such as statins) suggests that the lack of prognostic significance of β blocker discontinuation at one year is unlikely to have been affected by such a bias. + + Funding: FAST-MI is a registry of the French Society of Cardiology, supported by unrestricted grants from Pfizer and Servier. Additional support was obtained from a research grant from the French Caisse Nationale d'Assurance Maladie. + + Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: EP has received speaker, board membership, and consulting fees from Amgen, AstraZeneca, Bayer, Daiichi Sankyo, Lilly, MSD, and Sanofi-Aventis; SC has received grants from AstraZeneca, Boehringer Ingelheim, Boston Scientific, Medtronic, and Servier; GS has received institutional research grant support from NYU School of Medicine, Sanofi-Aventis, and Servier and consulting/advisory board fees from Ablynx, Amarin, Astellas, AstraZeneca, Bayer, BoehringerIngelheim, BMS, Daiichi-Sankyo-Lilly, GSK, Medtronic, MSD, Novartis, Otsuka, Pfizer, Roche, Sanofi-Aventis, Servier, and The Medicines Company and is a stockholder and co-founder of Aterovax; FS has received grant support to his institution and travel support for scientific meetings from AstraZeneca, Boehringer-Ingelheim, Daiichi-Sankyo, Lilly, Medtronic, Pfizer; Sanofi-Aventis, Servier, and Takeda; JF has received grants and speaker fees from AstraZeneca, Genzyme, Merck, Novartis, and Servier. TS has received research grants from Astra-Zeneca, DaiichiSankyo, Eli-Lilly, Glaxo-Smith-Kline, MSD, Novartis, Pfizer, Sanofi-Aventis, and Servier and speaker and consulting fees from AstraZeneca, Bayer-Schering, Eli-Lilly, and Sanofi-Aventis; ND has received research grants from AstraZeneca, Daiichi-Sankyo, Eli-Lilly, Glaxo-Smith-Kline, MSD, Novartis, Pfizer, Sanofi-Aventis, Servier, and The Medicines Company and advisory panel or lecture fees from AstraZeneca, Boehringer-Ingelheim, Bristol-Myers Squibb, Eli-Lilly, Menarini, Merck-Serono, Novo-Nordisk, Servier, and Sanofi-Aventis; no other relationships or activities that could appear to have influenced the submitted work.",BMJ,1,1,1,1,1,1,1,1,1,9 +12,One year outcomes in patients with acute lung injury randomised to initial trophic or full enteral feeding: prospective follow-up of EDEN randomised trial,"Extra material supplied by the author (see http://www.bmj.com/content/346/bmj.f1532?tab=related#webextra) + + Data sharing: No additional data available + + Appendix",Trial Registration NCT No 00719446,BMJ,"Design Prospective longitudinal follow-up evaluation of the NHLBI ARDS Clinical Trials Network’s EDEN trial + Setting 41hospitals in the United States. + + Interventions Randomised assignment to trophic or full feeding for up to six days; thereafter, all patients still receiving mechanical ventilation received full feeding. + + We undertook a prospective longitudinal evaluation of patient outcomes at six and 12 months after acute lung injury in participants from the EDEN study. We assessed patients’ physical function, quality of life, functional activities, fatigue, psychological symptoms, cognition, and employment status at six and 12 months after acute lung injury and evaluated the effect of initial trophic compared with full enteral feeding on physical function and secondary outcome measures. + + Methods + This study, the ARDS Network Long Term Outcomes Study (ALTOS), was designed to prospectively follow patients enrolled in several ARDS Network trials, including the EDEN trial. Three of the 44 hospitals included in the EDEN study did not participate in this follow-up study. Consenting patients from the 41 participating hospitals were eligible for enrolment into this prospective longitudinal study, with follow-up from April 2008 to April 2012.","Measurements Blinded assessment of the age and sex adjusted physical function domain of the SF-36 instrument at 12 months after acute lung injury. + + Study procedures + Trained research staff, blinded to treatment allocation, telephoned patients three months after the onset of acute lung injury to provide a reminder about the follow-up study and to obtain updated contact information for the patient and designated proxies. They completed the study assessments at six and 12 months. Published methods were used to minimise loss to follow-up.27-32 When patients could not complete the assessments by telephone, study assessments were completed by mail (5% of all assessments) and/or by designated proxies (only for the + functional performance inventory and the employment secondary outcome measures, representing 9% of these assessments).","Participants 525 patients with acute lung injury. + + Patients + Details of the EDEN eligibility criteria and study intervention have been reported previously (see appendix).8 Over the first six days of the EDEN trial, the trophic feeding group received, on average, 1672 kJ/day (25% of caloric goal), while the full feeding group received 5434 kJ/day (80% of caloric goal).8 We excluded patients from the EDEN trial if they met any of the following criteria, based on their status before admission to hospital for acute lung injury: cognitive impairment (evaluated from the medical record and interview with the patient and/or proxy), non-English speaking, homelessness, or aged under 18. The first 272 of 1000 patients enrolled in EDEN were simultaneously randomised to a separate blinded trial (the OMEGA study) that examined a nutritional supplement containing omega 3 fatty acids and antioxidants compared with an isoenergetic isovolemic control in a 2×2 factorial design.24 All EDEN patients were managed with simplified versions of lung protective ventilation25 and fluid conservative haemodynamic management26 protocols, with blood glucose control accomplished with institution specific protocols for insulin targeting about 4-8 mmol/L, with tighter control permitted + + Eligibility criteria for EDEN trial","Statistical analyses + All analyses were by intention to treat and performed with SAS version 9.2 (SAS Institute, Cary, NC). A two sided P<0.05 was considered significant. Statistical analyses were conducted according to an a priori written statistical analysis plan. A Kaplan-Meier curve was used to display survival during the follow-up period, with a comparison of trophic versus full feeding groups with the log rank test. To evaluate change over time (12 v six months) for the entire study population, we compared continuous and binary outcome measures, ignoring treatment assignment, using linear and binomial (identity link) regression models, respectively, with generalised estimating equations44 and an exchangeable correlation model. To quantify the treatment effect for the continuous and binary outcome measures assessed at six and 12 months, we created linear and logistic regression models, using generalised estimating equations with an exchangeable correlation model and an indicator for treatment group (trophic v full feeding), follow-up time (12 v six months), and the interaction of treatment group and time. In a secondary analysis for the primary outcome variable we extended the above model to test for a statistical interaction between OMEGA randomised assignment and EDEN treatment group (trophic v full feeding). We performed additional secondary analyses for the primary outcome variable for a priori patient subgroups at baseline (body mass index (BMI) <25, 25 to <30, ≥30), acute lung injury subgroup (Pa02/Fi02 ≤200 v Pa02/Fi02 >200), shock (present v absent), and a priori statistical interactions (age and APACHE III score as continuous variables). Missing data were excluded from statistical analyses as only 1-6% of each outcome instrument evaluated had any missing data.","Limitations + The study has several strengths, including detailed prospective longitudinal assessment of about 500 patients recruited from 41 hospitals. In addition, at six and 12 month follow-up, only 2% and <5% of consenting patients missed their visits. This study also has potential limitations. Firstly, the EDEN trial primarily evaluated relatively young, well nourished, overweight patients with acute lung injury with pneumonia or + non-pulmonary sepsis. The study’s findings might not therefore be generalisable to critically ill patients who are older, malnourished, and without infection. Secondly, the study evaluated only patient/proxy reported outcomes obtained by phone or mail, without any performance based assessments (such as the six minute walk test) from direct evaluation. Thirdly, the open label design of the EDEN trial has the potential to introduce bias. In our study, however, the patient outcomes assessors and investigators were blinded to randomised group assignment, and the written statistical analysis plan and study data were finalised before unblinding the treatment allocation. Finally, as functional outcome measures can be assessed only in survivors, mortality after randomisation could introduce bias in understanding the effect of a randomised treatment on functional outcomes.59 This issue is of less importance in this study, however, because the randomised treatment allocation did not differentially affect mortality. + + Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. + + Funding: National Heart, Lung and Blood Institute funded this follow-up study (N01HR56170, R01HL091760 and 3R01HL091760-02S1) and the EDEN trial (contracts HHSN268200536165C to HHSN268200536176C and HHSN268200536179C). All researchers are independent of the funding bodies. The funding bodies had no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the manuscript for publication.",BMJ,1,1,1,1,1,1,1,1,1,9 +13,Glasgow supported self-management trial GSuST) for patients with moderate to severe COPD: randomised controlled trial,"Data sharing: The dataset is still subject to further analyses but will continue to be held by the Robertson Centre for Biostatistics; contact the corresponding author for further information. + + Extra material supplied by the author (see http://www.bmj.com/content/344/bmj.e1060?tab=related#webextra) + + Appendix A Appendices B-D",Trial registration Clinical trials NCT 00706303.,BMJ,"Design Randomised controlled trial. + + Setting Community based intervention in the west of Scotland. + + Intervention Participants in the intervention group were trained to detect and treat exacerbations promptly, with ongoing support for 12 months. + + Study protocol + All participants had their long term treatment optimised and inhaler technique checked and were offered appropriate smoking cessation advice and pulmonary rehabilitation if this had not been done within the previous two years. + + Participants in the intervention group received supported self management. Study nurses’ training was based on self regulation theory (box 2; further details available from corresponding author).14 The intervention aimed to empower patients to manage their COPD independently by improving their understanding of disease and monitoring of symptoms and by developing their confidence to carry out appropriate actions, such as altering treatment early in the evolution of an exacerbation or initiating contact with their usual medical attendant. Self management materials based on the Living Well with COPD programme and previously adapted for the UK population and healthcare setting by an iterative process, were used (Sue Mason, personal communication).15 Web appendix A shows an example. Participants received four 40 minute individual training sessions at home from a study nurse, fortnightly over a two month period, with further home visits at least every six weeks (but more frequently on request) thereafter for a total of 12 months. Nurses showed patients how to use their symptom diary cards to recognise deteriorating symptoms and activate their self management plan. Follow-up visits were patient centred, based on individual needs as well as reviewing and reinforcing basic self management messages on the basis of diary card content. We used Anthonisen’s criteria for characterisation of acute exacerbations of COPD,16 defining an exacerbation as a 2 point change from the participant’s normal level of breathlessness and sputum colour and quantity or the development of new upper airway symptoms for two consecutive days. We defined the end of an exacerbation as a return of respiratory symptoms to baseline for three days. Participants were trained to identify and treat exacerbations associated with a 2 point deterioration in sputum colour with antibiotic (amoxicillin 500 mg three times daily or oxytetracycline 500 mg four times daily for seven days) and those associated with increased breathlessness, mucoid sputum, or upper airway symptoms with prednisolone 25 mg for five days. This dose was a compromise between the convenience of the 25 mg tablet and the higher doses used for established exacerbations,12 together with the use of treatment earlier in an exacerbation, taking account of the possibility that participants would overuse treatment with its associated side effects. + The control group continued to be managed by their general practitioner, hospital based specialists, or both (including the use of emergency out of hours services and the NHS 24 hour helpline)","Participants received monthly telephone calls from an independent researcher, blinded to the patients’ randomisation status, to collect information on health service usage and exacerbations. They were asked to complete daily diary cards and the questionnaires described below at six and 12 months and reminded to complete these at the time of the appropriate monthly telephone call and return them by prepaid postage. Diary cards were based on those of Woolhouse et al (box 1).","Participants Patients admitted to hospital with acute exacerbation of COPD. + + Participant recruitment and randomisation + Eligible patients were those with COPD who had been admitted to hospital with an acute exacerbation of COPD. We defined COPD as chronic irreversible airflow limitation with forced expiratory volume in one second (FEV1) less than 70% predicted and a FEV 1/forced vital capacity ratio of less than 70%. Forced vital capacity is defined as the total amount of air that can be expelled from the chest by a forced expiratory manoeuvre. We excluded patients with a history of asthma or left ventricular failure, which might cause confusion about the cause of breathlessness; evidence of active malignant disease, which could influence mortality; or any evidence of confusion/poor memory, assessed with the abbreviated mental test (scores of 9/10 or 10/10 required).10 We identified potentially eligible patients during or shortly after their hospital admission in all six acute Glasgow hospitals and contributing Lanarkshire hospitals to which eligible patients with a Glasgow postcode were admitted. We augmented this by reviewing patients attending pulmonary rehabilitation and crosschecking for evidence of hospital admission. + We gave or sent potentially eligible patients a study information leaflet and then contacted them, usually by telephone, to establish their interest in participation. We made a home visit to check eligibility and to enrol and subsequently randomise the patient, if appropriate. + We used a minimisation technique to stratify randomisation of participants by demographic factors (deprivation category of area of residence,11 age and sex, FEV1 per cent predicted at the time of randomisation, smoking status, participation in pulmonary rehabilitation within two years, and number of previous admissions) to control for key aspects of disease severity and predictors of readmission. We constructed a computer generated sequence by using the method of randomised permuted blocks of length four, with two allocations being made at random and two by minimisation. Treatment group allocations were obtained by telephone, after baseline assessments had been made. This registered the participant on the system, and a researcher entered the characteristics necessary for the minimisation algorithm by using an interactive voice response system. The researcher did not know whether a participant was being allocated at random or by minimisation and could therefore not determine the next treatment allocation before enrolling each participant. + + Study protocol + All participants had their long term treatment optimised and inhaler technique checked and were offered appropriate smoking cessation advice and pulmonary rehabilitation if this had not been done within the previous two years.","Statistical analysis, study numbers, and power calculation + To achieve 90% power to detect a reduction in the composite end point of COPD related readmission or death rate from 40% to 25%, we needed 216 patients per group on the basis of a continuity corrected χ2 test for association. We aimed to recruit 250 patients per group, to allow for 13.5% attrition. + Data for the primary outcome (time to first acute COPD hospital admission or death) were available for all patients and analysed with a Cox proportional hazards model adjusting for the stratification variables. We present results as hazard ratios (intervention:control) with corresponding 95% confidence intervals and P values. We considered P values less than 0.05 to be statistically significant. We produced Kaplan-Meier plots to compare the unadjusted survival rates between the groups. We used analysis of covariance models to analyse the secondary outcomes (change from baseline in questionnaire scores at 6 and 12 months), adjusting the models for the baseline score and stratification variables. We present results as estimated differences (intervention minus control) with 95% confidence intervals and P values. + We used Cox proportional hazards models to investigate differences in the effect of the intervention between subgroups as determined by the stratification variables by including a “intervention by subgroup” interaction term in the model. We present the hazard ratios and 95% confidence intervals for the intervention effects within each of the subgroups, along with the P values for the intervention by subgroup interaction. We identified predictors of successful self management initially from univariate logistic regression models. We then investigated multivariately those variables identified as significant at the univariate level. A backwards stepwise selection method identified those variables that were independently associated with successful self management. Within the intervention arm of the study, we compared successful and unsuccessful self managers in terms of the study outcomes, using the methods detailed above.","Strengths and weaknesses of study + The robust study design, the large cohort that allowed subgroup analyses, and the use of record linked data from all hospital admissions in Scotland for all randomised cases are important positive features of this study. The low participation rate (47%) theoretically limits the generalisability of the findings. However, given the commitment needed from patients to actively monitor their condition and adjust treatment within the study, patients not agreeing to participate in a trial of this design would probably not be more likely to benefit than those studied. Web appendix C shows the limited comparison possible on demographic data of patients who participated and those who declined, showing that participants were slightly younger on average (mean age 69 v 70 years; P=0.07) and were less likely to be living in the most highly deprived areas of residence; despite this, 61% of the study population came from the most deprived areas (61% in deprivation categories 6 and 7, compared with 69% of non-participants; P=0.02). Nevertheless, given that the primary analysis was negative and none of the pre-planned subgroup analyses found any evidence of benefit, + non-participation is unlikely to have biased this result. Our recruitment rate, at 47% of eligible patients, was similar to that reported in previous studies (for example, 41% in Bourbeau et al,15 49% in Rice et al21), so that this problem applies to the entire literature, an aspect of methodology not covered in the recent Cochrane review.2 The findings of our study in terms of participation rates and lack of effect on important outcomes highlight the fact that this practice cannot be recommended for the generality of COPD cases of this level of severity in the UK healthcare setting. + Completion rates for study questionnaires were also disappointing and were lower in the control arm of the study. Consequently, the apparent improvements in the intervention arm (impacts subscale of St George’s respiratory questionnaire, hospital anxiety and depression scale anxiety) could be biased, and these results cannot be taken as convincing evidence in favour of the intervention. + + Funding: In addition to funding from the Chief Scientist Office, Scottish Health Department (CZH/4/246), this study was supported by educational grants from Boehringer Ingelheim, GlaxoSmithKline, and Astra Zeneca. The commercial sponsors played no part in the design, implementation, or analysis of results from this trial or in the preparation of this paper. + + Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: in addition to the Chief Scientist Office grant (CZH/4/246), CEB’s institution received financial support for the employment of a research fellow from Boehringer Ingelheim, GlaxoSmithKline, and Astra Zeneca, and JC holds other grants; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work",BMJ,1,1,1,1,1,1,1,1,1,9 +14,Surgery with disc prosthesis versus rehabilitation in patients with low back pain and degenerative disc: two year follow-up of randomised study,"Data sharing: Dataset available from the corresponding author at christian.hellum@medisin.uio.no. + + Details of further inclusion and exclusion criteria, compliance with randomisation, and drop-outs are listed in the appendix 1 on bmj.com. + + See appendix 2 on bmj.com for detailed description of the rehabilitation intervention. + + See table A in appendix 3 on bmj.com.",Trial registration www.clinicaltrial.gov NCT 00394732.,BMJ,"Design A prospective randomised multicentre study. + + Setting Five university hospitals in Norway. + + Interventions Surgery with disc prosthesis or outpatient multidisciplinary rehabilitation for 12-15 days. + + Study interventions + Rehabilitation—The rehabilitation was based on the treatment model described by Brox et al4 and consisted of a cognitive approach and supervised physical exercise. A team of physiotherapists and specialists in physical medicine and rehabilitation directed the multidisciplinary treatment. Other specialists, such as psychologists, nurses, social workers, etc, could complete the team. The intervention was standardised through three seminars and videos and lecture sessions for the treatment providers before the study. The intervention was organised as an outpatient treatment in groups at the involved university hospitals and lasted for about 60 hours over three to five weeks. The treatment consisted of lectures and individual discussions focusing on relevant topics (such as anatomy and the physiological aspects of the back, diagnostics, imaging, pain medicine, normal reactions, coping strategies, family and social life, and working conditions), daily workouts for increased physical capacity (endurance, strength, coordination, and specific training of the abdominal muscles and the lumbar multifidus muscles), and challenging patients’ thoughts about, and participation in, physical activities previously labelled as not recommended (such as lifting, jumping, vacuum cleaning, dancing, and ball games). Follow-up consultations were conducted at six weeks, three months, six months, and one year after the intervention. + + Surgery—The surgical intervention consisted of replacement of the degenerative intervertebral lumbar disc with an artificial lumbar disc (ProDisc II, Synthes Spine). The ProDisc consists of three pieces: two metal endplates of cobalt chromium molybdenum alloy and a core (made from ultrahigh molecular weight polyethylene) fixed to the inferior endplate after insertion. Surgeons used a Pfannenstiel or a para-median incision with a retroperitoneal approach. A nearly complete discectomy was performed with removal of the cartilaginous endplates and a sufficient release of the posterior longitudinal ligament to ensure disc space mobilisation. A fluoroscope was used to ensure that the prosthesis was placed in the midline and sufficiently towards the posterior edge of the vertebrae. All hospitals participating in the study used the same artificial lumbar disc device. One surgeon at each centre had main responsibility for the operation (five centres and five surgeons). Surgeons were required to have inserted at least six disc prostheses before performing surgery in the study. There were no major postoperative restrictions. Patients were not referred for postoperative physiotherapy, but at six weeks’ follow-up they could be referred for physiotherapy if required, emphasising general mobilisation and non-specific exercises.","Main outcome measures The primary outcome measure was the score on the Oswestry disability index after two years. Secondary outcome measures were low back pain, satisfaction with life (SF-36 and EuroQol EQ-5D), Hopkins symptom check list (HSCL-25), fear avoidance beliefs (FABQ), self efficacy beliefs for pain, work status, and patients’ satisfaction and drug use. A blinded independent observer evaluated scores on the back performance scale and Prolo scale at two year follow-up. + + Independent observers collected and entered data. Storage of data was allowed by the Norwegian data inspectorate. + + Outcome measures + The primary outcome measure was pain and disability measured with version 2.0 of the Oswestry disability index, translated into Norwegian and tested for psychometric properties by Grotle et al. (Scores range from 0 to 100, with lower score indicating less severe pain and disability.) Secondary outcomes included low back pain (measured with a visual analogue scale, ranging from 0 (no pain) to 100 (worst pain imaginable)) and general health status assessed with SF-36 (scores range from 0 to 100, higher scores correspond to better health status) and EQ-5D (scores range from -0.59 to 1 (1 equals perfect health)). For psychological variables we included emotional distress (Hopkins symptom check list (HSCL-25), scores range from 1 to 4, with lower scores indicating less severe symptoms) and the fear avoidance belief questionnaire (FABQ) for work and physical activity (scores range from 0 to 42 (work) and from 0 to 24 (physical), with lower scores indicating less severe symptoms). Self efficacy beliefs for pain were registered by a subscale of the arthritis self efficacy scale (scores range from 1 to 10 and are summarised and divided by 5; lower scores indicate uncertainty in managing the pain) + + We calculated a net back to work rate, subtracting patients who went back to work from patients who stopped working, satisfaction with the result of the treatment on a seven point Likert scale, and satisfaction with care on a five point Likert scale. Further daily consumption of drugs was registered. Patients attended for follow-up visits at six weeks, three and six months, and one and two years (the main end point of follow-up was at two years). At two years we sent a questionnaire including the most important outcome measures to 29 of the 34 patients who were lost to follow-up (see table B in appendix 3 on bmj.com). At the two year follow-up, two independent observers blinded to treatment evaluated patients using the back performance scale (consists of five tests with a score ranging from 0 to 15, worst possible) and the Prolo scale (consists of functional and economic parts, which are summed to a worst score of 2 and a best score of 10). Patients were informed before this session not to reveal the treatment received, and had tape placed on their abdominal wall to hide the scarring from the operation. We also carried out a full health economic analysis, which will be reported elsewhere.","Participants 173 patients with a history of low back pain for at least one year, Oswestry disability index of at least 30 points, and degenerative changes in one or two lower lumbar spine levels (86 patients randomised to surgery). Patients were treated from April 2004 to September 2007. + + METHODS + Study design + A multicentre study conducted at five university hospitals in Norway included patients with low back pain and degenerative discs. Patients were included in the period between April 2004 and May 2007 and were treated within three months after randomisation. They were randomised in blocks with a website hosted by the medical faculty. Allocation was concealed for all people involved in the trial. A coordinating secretary not involved in the treatment could access randomisation details on the internet. The patient and the treating unit were informed about the allocation shortly after randomisation. Randomisation was stratified by centre (the five university hospitals) and whether the patient had had previous surgery (microsurgical decompression) or not. + + Participants + Patients were referred from all health regions in Norway. They were recruited from local hospitals or primary care to their nearest university hospital as usual without any supplemental recruitment attempt. An orthopaedic surgeon and a specialist in physical medicine and rehabilitation examined the patients before enrolment. All patients were informed about the procedures and told that neither of the treatment methods was documented as superior to the other. Eligible patients were aged 25-55 and had low back pain as the main symptom for at least a year, structured physiotherapy or chiropractic treatment for at least six months without sufficient effect, a score of at least 30 on the Oswestry disability index, and degenerative intervertebral disc changes in L4/L5 or L5/S1, or both. Degeneration had to be restricted to the two lower levels. We evaluated the following degenerative changes: at least 40% reduction of disc height,14 Modic changes type I or II, or both,15 high intensity zone in the disc,16 and morphological changes classified as changes in signal intensity in the disc of grade 3 or 4.17 The disc was classified as degenerative if the first criterion alone or at least two changes were found on magnetic resonance imaging. The discs were independently classified by two observers (orthopaedic surgeon/radiologist). When there was disagreement, a third observer classified the images and the outcome was decided by simple majority. + Degeneration of the facet joints was not an exclusion criterion, but symptoms of nerve root involvement + were. + + Patients’ characteristics + Most baseline characteristics were similar in the two treatment groups (table 1). Low back pain score and SF-36 mental health subscores, however, were significantly worse in the rehabilitation group than in the surgery group.","Statistical considerations + The trial was designed to have 80% power to detect a significant difference of at least 10 points in change in the mean Oswestry disability index score between the intervention groups at two year follow-up. Baseline standard deviation was estimated at 18. Considering these assumptions and adding 25% for a multicentre study design and 30% for possible drop-outs, we estimated we required 180 patients. + + Planned analyses + The main statistical analysis was in the intention to treat population at one and two year follow-up. According to our protocol the analysis was performed with the assumption that patients who dropped out had no improvement after drop-out (last value carried forward). We also determined if different centres had different outcomes. We used χ2 test or Fisher’s exact test to analyse categorical variables and independent two sided t test or analysis of variance to analyse continuous variables. A significance level of 5% was used throughout. All statistical analyses were performed with SPSS version 16.0. We did not adjust for significantly different baseline scores. + + Unplanned analyses (analyses not recorded in the original protocol) + We conducted a per protocol analysis for the primary outcome variable (score on Oswestry disability index). Consistent with criteria from the Food and Drug Administration, we considered an individual change in score of at least 15 points from baseline to two year follow-up as a minimal important change. A deterioration of 6 points in the score was considered a “change for the worse.” We calculated the number needed to treat with confidence intervals. A mixed model analysis was used to evaluate the effect of each efficacy variable over time and between groups. In the mixed model patients were not excluded from the analysis of an efficacy variable if the variable was missing at some, but not all, time points after baseline. In the additional analysis (categorical or ordinal data at two year followup), missing data were not replaced. Significantly different baseline scores were not adjusted for in the longitudinal model. Each outcome variable was adjusted for the baseline values of the variable.","Strengths and limitations + Our study has several strengths. It was randomised and had few patients who crossed over to the other treatment regimen. In addition, an independent research assistant collected the data, the observers at the two year evaluation were blinded, the interventions were standardised, and the financing of the study was public. Choosing magnetic resonance imaging criteria for inclusion could be a strength or limitation. To our knowledge, there are no specific criteria to determine which degenerative changes should be operated on. When designing the study we wanted the inclusion of patients across centres to be as unanimous as possible, treating the same population, although this possibly would lead to less external validity of the study. It could also possibly lead to inclusion of more severe degenerated discs in our study compared with other studies. + One limitation of our study is the lack of a placebo or sham group. The regression to the mean and the natural resolution of chronic low back pain must also be considered in both groups. When balancing a nonoperative regimen with an operative treatment, there is probably a difference in placebo effect that is difficult to untangle from the treatment effect. The placebo effect might be higher in the surgical group, although the possible placebo effect of rehabilitation over several weeks with personal contact with a therapist should not be underestimated. Furthermore, it could be argued that the patients included in the study wanted surgery, but the number of patients not wanting the rehabilitation programme was similar to the number of patients not wanting surgery (see figure and appendix 1 on bmj.com). Brox et al found no difference in treatment effect between patients who did and did not “believe” in surgery, and a recent study found no significant relation between baseline expectations and follow-up scores. On the other hand, “expectation being fulfilled” might be a predictor of global outcome. During the inclusion process, we emphasised the advantages and disadvantages of the two treatment options and that none of the treatments are documented as superior to another. It is still possible, however, that patients in the rehabilitation group found themselves faced with “more of the same.” The lack of routine rehabilitation in the surgical arm could be another limitation in the study. We wanted to avoid the postoperative treatment containing elements from the rehabilitation programme. Hence, patients received only general advice when they were discharged from the hospital and received no rehabilitation in the first weeks after surgery. At six weeks, however, patients could be referred if required to a physiotherapist at their home for functional mobilisation and general muscle training. Furthermore, some surgical patients underwent a second operation but repeat rehabilitation was not considered. Patients did not request a second chance for rehabilitation, though they were advised during follow-up consultations. Another weakness in our study is the difference in compliance between groups and the high drop-out rate. This difference in adherence to the protocol probably leads to an underestimate of the true effect of surgery, especially in the intention to treat analysis. In similar studies comparing surgery with rehabilitation, the drop-out rates were similar to ours. The patients we included in our study were highly selected, with one or two level degenerative changes and good general health. Thus, our results are valid only in similar patients. Furthermore, we examined several secondary outcome variables that could lead to the detection of differences by chance. Although we conducted several unplanned analyses (not recorded in the original protocol), in common with similar studies, we consider it as an important asset to our data. Lately, similar studies have applied repeated measurements by using mixed models. Using unplanned analysis could be considered a weakness, but our findings in these analyses support our main analyses and strengthen our conclusion. Nevertheless, caution should be used in interpreting the results of non-prespecified analyses. + + Funding: The study was funded by the South Eastern Norway Regional Health Authority and EXTRA funds from the Norwegian Foundation for Health and Rehabilitation, through the Norwegian Back Pain Association. + + Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.",BMJ,1,1,1,1,1,1,1,1,1,9 +15,Tailored Immunotherapy Approach With Nivolumab in Advanced Transitional Cell Carcinoma,"Appendix + + Data Sharing Statement + + DATA SHARING STATEMENT + The data set used and analyzed during the current study is available from the corresponding author on reasonable request. For more information, visit https://ascopubs.org/doi/pdf/10.1200/JCO.21.02631.","CLINICAL TRIAL INFORMATION + NCT03219775 (TITAN-TCC)","FIG 1. (A) Study design and (B) CONSORT diagram. + + Journal of Clinical Oncology + + For a CONSORT diagram, see Figure 1B","METHODS After four doses of nivolumab induction, responders continued with nivolumab maintenance therapy. Patients with stable/progressive disease received nivolumab 3 mg/kg plus ipilimumab 1 mg/kg once every 3 weeks for 2 doses followed by nivolumab 1 mg/kg plus ipilimumab 3 mg/kg once every 3 weeks for 2 doses, if not responding to the initial boost. Responders to boosts continued with nivolumab maintenance. + + Study Design + TITAN-TCC is a multicenter, single-arm, open-label phase II adaptive trial (Fig 1A). Patients were enrolled at 22 sites in Germany and Austria. All patients, irrespective of the therapy line, received induction nivolumab 240 mg monotherapy once every 2 weeks for 4 doses. TAs were performed by computed tomography or magnetic resonance imaging at baseline and at week 8 after first dose. On the basis of response as per RECIST v1.1, (1) patients with partial (PR) or complete response (CR) continued with maintenance nivolumab until disease progression or immune-related adverse events requiring discontinuation and (2) patients with stable (SD) or progressive disease (PD) at week 8 received a boost with nivo3 1 ipi1 once every 3 weeks for 2 doses and, if SD or PD was still present, another boost with nivo1 1 ipi3 once every 3 weeks for 2 doses was applied. If responding to the first (CR/PR) or second (CR/PR/SD) two boost doses, patients entered maintenance nivolumab monotherapy. + + Patients developing PD during nivolumab maintenance were also boosted using the schedule mentioned above. This applied to patients without prior boosts and to patients who had experienced SD, PR, and/or CR for (in total) 3 or more months of nivolumab maintenance after their last boost combination dose and not more than two prior boost phases (of up to four doses). + + + Patients with PD after four consecutive nivolumab/ ipilimumab boost doses were considered immunotherapyresistant. Tailored treatment was administered until immunotherapy resistance, unacceptable toxicity, or patient’s withdrawal of consent. After discontinuation, patients completed two follow-up visits and were subsequently monitored for survival on a 3-monthly basis with a minimum follow-up of 24 months. + + Treatment Exposure + In the overall population, the median follow-up time was 7.7 months. The median number of nivolumab induction doses received was 4 (range, 1-4) in the overall population, in 1L and 2/3L. Of all patients, 60% (n 5 52) received at least one boost dose—48% (n 5 41) after week 8 and 13% (n 5 11) for later progression. This corresponds to 57% (n 5 24) of 1L patients being boosted at least once (17 of 24 [71%] after week 8) and 64% (n 5 28) of 2/3L patients (24 of 28 [86%] after week 8). At data cutoff, 63 patients had discontinued treatment, in which 29 and 34 patients were in 1L and 2/3L, respectively. On the basis of investigator assessment, the most common reasons for discontinuation were AE/intercurrent illness/rapid progression, indicating continuous participation not to be in the best interest of the patient (n 5 23); death (n 5 22); and immune-related adverse events (n 5 10), with multiple reasons for discontinuation being possible per patient.","We report a response-based approach starting treatment with nivolumab monotherapy with nivolumab/ipilimumab as immunotherapeutic boost. + + A Karnofsky Performance Score (KPS) $ 70 and measurable disease as per RECIST v1.1 were required. A tumor sample was mandatory for central pathology assessment of PD-L1 expression. + + On the basis of response as per RECIST v1.1, (1) patients with partial (PR) or complete response (CR) continued with maintenance nivolumab until disease progression or immune-related adverse events requiring discontinuation and (2) patients with stable (SD) or progressive disease (PD) at week 8 received a boost with nivo3 1 ipi1 once every 3 weeks for 2 doses and, if SD or PD was still present, another boost with nivo1 1 ipi3 once every 3 weeks for 2 doses was applied. If responding to the first (CR/PR) or second (CR/PR/SD) two boost doses, patients entered maintenance nivolumab monothera. + + While on nivolumab maintenance therapy, patients received a confirmatory TA at week 6 after first maintenance doses and further TAs every 12 weeks. During nivolumab/ ipilimumab boosts, TAs were performed 6 weeks after the first two boost doses. + + Every 12 weeks, patients who were off treatment received TAs until documented PD. AEs were recorded until 100 days after the last dose. + + Outcome Parameters + The primary end point was investigator-assessed ORR according to RECIST v1.1 among all treated, 1L, and 2/3L patients, designating the rate of patients with a best overall response (BOR) of CR or PR. Key secondary end points included progression-free survival (PFS) and OS in the overall cohort, 1L, and 2/3L patients. In addition, safety and tolerability were assessed. Efficacy by tumor PD-L1 expression was an exploratory end point. Tumor PD-L1 expression was centrally assessed using anti–PD-L1 immunohistochemistry antibody 28-8 (Abcam, Cambridge, United Kingdom) and an OptiView DAB IHC detection Kit (Roche Diagnostics, Basel, Switzerland). PD-L1 expression was considered positive (PDL11) at the cutoff of $ 1% of tumor cells.","Between July 2017 and April 2019, 86 patients were enrolled. + + The median age was 68 years. + + Patient Population + Adults with histologically confirmed advanced UC (surgically unresectable) or mUC of the bladder, urethra, ureter, or renal pelvis were eligible. Patients were either untreated (1L) or had progressed during or after platinum-based 1L therapy and up to one further treatment line (2/third-line [3L]). Patients who received (neo-)adjuvant chemotherapy were eligible and considered 1L if progression occurred . 12 months from the last therapy (surgery and chemotherapy). A Karnofsky Performance Score (KPS) $ 70 and measurable disease as per RECIST v1.1 were required. A tumor sample was mandatory for central pathology assessment of PD-L1 expression. + The following key exclusion criteria were applied: history of or current brain metastases; former treatment with any antibody or drug specifically targeting T-cell costimulation or checkpoint pathways; autoimmune disease or conditions requiring systemic corticosteroid treatment (. 10 mg per day prednisone equivalents) or other immunosuppressive medications; prior malignancies active within the previous 3 years except for locally curable and apparently cured cancers; and patients in active surveillance for prostate cancer, human immunodeficiency virus infection or known acquired immunodeficiency syndrome, and acute or chronic hepatitis B or C. + + Baseline Characteristics + Eighty-six patients were enrolled between July 2017 and April 2019. Of the patients, 42, 39, and five were 1L, 2L, and 3L, respectively. Seventy-one percent (n 5 61) were male, and 79% (n 5 68) showed metastatic disease, with the primary tumor being located in the bladder (Table 1). A KPS of 70% was noted in 7 (17%) and 4 (9%) of 1L and 2/3L patients, respectively. Of the 2/3L patients, 93% (n 5 41) had received the gemcitabine/cisplatin regimen as 1L chemotherapy. Almost half of the patients (n 5 41, 48%) had PD-L11 tumors.","Statistical Design + On the basis of data of the phase II, single-arm CheckMate 275 study for single-agent activity of PD-(L)1 ICI, separate assumptions were made in the 1L and 2/3L cohort, respectively.3 The study was conducted in a Fleming singlestage phase II design with a sample size of 108 patients with 90% power to, in 1L, reject the null hypothesis of a true ORR of # 24% if the true ORR was $ 37% with a one-sided target error rate of 5%. Similarly, in 2/3L, 99 patients would be required to test a true ORR of # 20 against a one-sided alternative hypothesis of $ 33% in 2/3L. + Following the European Medicines Agency restriction of PD-(L)1 ICIs in the 1L treatment of mUC to PD-L11 patients and safety concerns by the data monitoring committee, recruitment of the 1L cohort was discontinued in January 2019. After analysis of efficacy results up to 8 weeks after the first dose and on the basis of more mature data from CM032, the Protocol was adapted and restricted to 2/3L patients (protocol v4.0). Herein, we report the primary end point of ORR of 30 weeks after first treatment of the last patient enrolled (data cutoff November 1, 2019) treated according to protocol v3.0 with escalating boosts. + Demographics and baseline characteristics were summarized using descriptive statistics. ORR was summarized by binomial response rates and corresponding two-sided 95% exact CIs using the Clopper-Pearson method. Time-toevent distribution was estimated using Kaplan-Meier methodology for PFS and OS, with medians and 95% CIs constructed on the basis of a log-log transformed CI for the survivor function. + Descriptive statistics of safety were tabulated using the worst-grade criterion by the system organ class and preferred term according to the National Cancer Institute Common Terminology Criteria for Adverse Events v4.0.","AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST + Disclosures provided by the authors are available with this article at DOI https://doi.org/10.1200/JCO.21.02631. + + SUPPORT + Funded by Bristol Myers Squibb. + + AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST + Tailored Immunotherapy Approach With Nivolumab in Advanced Transitional Cell Carcinoma + The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I 5 Immediate Family Member, Inst 5 My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center. + + Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments). + + No other potential conflicts of interest were reported. + + Honoraria: Bayer, Merck, AstraZeneca/MedImmune, Janssen Oncology, Pfizer Consulting or Advisory Role: MSD Oncology, AstraZeneca, Bayer, Bristol Myers Squibb/Pfizer, Ipsen, EDAP TMS, Sanofi, Janssen Oncology, Astellas Pharma Research Funding: Bristol Myers Squibb Foundation (Inst), AstraZeneca (Inst), Ipsen (Inst), MSD Oncology (Inst), Janssen Oncology (Inst), Sanofi (Inst), Bayer (Inst) + Travel, Accommodations, Expenses: AstraZeneca, MSD Oncology, Bristol Myers Squibb/Pfizer, Sanofi, Merck, EDAP TMS, Pfizer, Bayer",Journal of Clinical Oncology,1,1,1,1,1,1,1,1,1,9 +16,Mutations in BRCA1/2 and Other Panel Genes in Patients With Metastatic Breast Cancer - Association With Patient and Disease Characteristics and Effect on Prognosis,"ASSOCIATED CONTENT + Data Supplement + + Data Supplement [online only])","PRAEGNANT (ClinicalTrials.gov identifier: NCT02338167; Data Supplement [online only])17 is an ongoing, prospective, multicentric BC registry in hospitals and practices across Germany.",Journal of Clinical Oncology,"The frequencies of mutations in known BC predisposition genes were compared with results from a prospective registry of patients with nonmetastatic BC sequenced using the same QIAseq method and with public reference controls. Associations between mutation status and tumor characteristics, progression-free survival, and overall survival were assessed. + + Comparison With Mayo Clinic Breast Cancer Study + To determine whether mutations in specific genes were + enriched in patients with mBC compared with a non-mBC + population, gene-specific mutation frequencies in known + BC predisposition genes from the present study were + compared with frequencies among primary (non-mBC) + invasive BC cases in Mayo Clinic Breast Cancer Study + (MCBCS)21 that were identified using the same QIAseq + panel. The MCBCS is a clinic-based prospective registry of + consecutive patients with BC, unselected for age at diagnosis or family history, seen at the Mayo Clinic between + 2000 and 2016 (Data Supplement).","Patient and disease data are collected at study entry and at follow-up visits (Data Supplement). All patients provided informed consent at enrollment. + + Ascertainment of Clinical and Histopathologic Data Definitions of hormone receptor (HR) status, HER2 status, and grade have been described previously. Briefly, estrogen receptor status, progesterone receptor status, HER2 status, and tumor grade were requested from all available biopsies (primary BC and mBC). If biomarker assessment of a metastatic site was available, these assessments were used. Otherwise, the latest biomarker results from the primary tumor were used. All patients treated with endocrine therapy up to the study inclusion were assumed to be HR-positive (HR1), and all patients treated with an antiHER2 therapy were assumed to be HER21. There was no central review of biomarkers. Estrogen receptor and progesterone receptor were considered positive if $ 1% of tumor cells were stained. A positive HER2 status required an IHC score of 31 or a positive fluorescence in situ hybridization or chromogenic in situ hybridization. Tumors were classified into mutually exclusive groups as luminal A– like (HR1 and grade 1/2), luminal B–like (HR1 and grade 3), triple-negative breast cancer (TNBC), or HER21. The site of metastasis was classified into four discrete categories in the following hierarchical order—brain (additional locations allowed), visceral (additional locations except brain allowed), bone only, and other—on the basis of the presence or absence of tumors at these locations. The site of metastasis, body mass index, and family history were used from the documentation at study entry. + + Germline Genetic Testing, Bioinformatics Analysis, and Classification of Variants + Germline genetic testing and bioinformatics analysis for 37 cancer predisposition genes were performed using a custom amplicon-based QIAseq panel (QIAGEN, Hilden, Germany) as previously described (Data Supplement). Annotation of mutations was conducted using the American College of Medical Genetics and the Association for Molecular Pathology guidelines. Low-penetrance missense variants in CHEK2 were excluded from analyses.","PATIENTS AND METHODS Germline DNA from 2,595 patients with mBC enrolled in the prospective PRAEGNANT registry was evaluated for mutations in cancer predisposition genes. + + Patients are eligible at any time point of their disease. Data are documented in electronic case report forms17 and monitored using plausibility checks and on-site monitoring. + + A total of 2,647 patients with mBC were registered between July 2014 and March 2018. Of these, 2,595 patients yielded high-quality germline sequencing data and were included in the correlative analyses. Among these, 1,516 had complete information on molecular subtype, line of therapy at enrollment, and follow-up duration and were included in survival analyses (Fig 1). + + Patient and Tumor Characteristics According to Mutation Status + Patient characteristics according to the mutually exclusive mutation groups are shown in Table 1. In the total cohort, the mean age of BC metastasis diagnosis was 57.8 years, and 41.4% of patients were enrolled while receiving the first line of therapy. Of those with available tumor pathology information, 11.1% (n 5 254) were TNBC, 27.6% (n 5 632) HER21, and 61.3% (n 5 1,401) HER22/HR1. Visceral metastases were seen in 50.9% of patients, 17.8% had bone-only metastases, and 14.3% had brain metastases","Statistical Considerations + Patient and tumor characteristics of patients in PRAEGNANT and MCBCS are shown as counts and frequencies. + For each patient, PFS was only considered for the earliest line of therapy during which the patient entered the study. PFS was defined as the time from the date of initiation of therapy to the earliest date of disease progression or death from any cause. Observation time was left-truncated for the time at which the patient entered the study if study entry was later than the start of treatment. Overall survival (OS) was defined similarly. For PFS and OS ascertainment, see the Data Supplement. A multivariable Cox regression model was fitted with PFS as outcome and the following predictors: age at study entry, HR status (positive or negative), HER2 status (positive or negative), tumor grade, selected therapy line, ECOG status, metastasis pattern, and number of concomitant diseases and mutation status (no mutation, gBRCA1/2 mutation, HRD mutation, DNA repair gene mutation, and other). + Similar analyses were performed for OS. Unadjusted survival rates were estimated using the Kaplan-Meier product-limit method. Two sensitivity analyses were done. First, survival analyses were repeated for patients included in PRAEGNANT at the time of first therapy line and second, survival analyses were repeated excluding patients with left-truncated survival information. Missing predictor values were imputed. The proportional hazards assumptions were checked using the method of Grambsch and Therneau. All the tests were two-sided, and a P value , .05 was regarded as statistically significant. Statistical analyses were performed using the R software (v3.4.0).","There are some limitations to this study. Despite the large sample size, the numbers of mutations in some genes were low. Therefore, we were not able to generate conclusive evidence about the effect of mutations in several genes on prognosis or associations with clinical characteristics. Additionally, a mutation that was already clinically known to the treating physicians could have altered both chosen therapies and the course of the disease. Allowing late entry into the study and handling the survival data by left truncation could potentially introduce a bias into the survival analysis; however, we addressed this by performing a sensitivity analysis, which yielded similar survival estimates. In addition, the inherent differences in the patient population and ascertainment between PRAEGNANT and MCBCS cohorts must be acknowledged, which could potentially affect the comparison of mutation frequencies. For example, in PRAEGNANT, only 63 patients were not of White European descent. In addition, the young mean age at diagnosis (52.8 years) could point to a possible selection bias. However, because young patients have a worse prognosis when diagnosed with early BC, an enrichment of young patients is expected in an mBC population. In addition, a French mBC registry with more than 22,000 patients reported a similar mean age at diagnosis of 54.0 years. + + DISCLAIMER + The supporters did not have any involvement in the study design; collection, analysis, or interpretation of data, writing of the report, or decision to submit this article. + + SUPPORT + The PRAEGNANT network is supported by grants from Novartis, Celgene, and Pfizer. MCBCS was supported by the National Institutes of Health (NIH) Specialized Program of Research Excellence (SPORE) in Breast Cancer to Mayo Clinic (P50 CA116201), NIH grant R01CA225662, R01CA192393, R35CA253187, and the Breast Cancer Research Foundation. + + AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST + Disclosures provided by the authors are available with this article at DOI https://doi.org/10.1200/JCO.20.01200. + + AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST + Mutations in BRCA1/2 and Other Panel Genes in Patients With Metastatic Breast Cancer—Association With Patient and Disease Characteristics and Effect on Prognosis + The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I 5 Immediate Family Member, Inst 5 My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center. + + Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments). + + Peter A. Fasching + Honoraria: Roche, Novartis, Pfizer, ClinSol GmbH, Daiichi Sankyo, Eisai, Merck Sharp & Dohme, AstraZeneca, Hexal, Lilly, Cepheid, BionTech, Pierre Fabre Consulting or Advisory Role: Amgen, Teva, Celgene, Novartis, Pfizer, Roche, Puma Biotechnology, Daiichi Sankyo, Eisai, Merck Sharp & Dohme, AstraZeneca, Hexal, Myelo Therapeutics GmbH, Macrogenics + Research Funding: Novartis, BioNTech AG, Cepheid Eric C. Polley + Research Funding: GRAIL Hans Tesch + Honoraria: Novartis, Roche Pharma AG, Pfizer, Amgen GmbH, AstraZeneca, Vifor Pharma, Lilly, Eisai, MSD Oncology, Grunethal, Bristol Myers Squibb, ¨ Mundipharma, ClinSol GmbH + Travel, Accommodations, Expenses: Roche Pharma AG, Pfizer, Novartis, Amgen, AstraZeneca, Vifor Pharma, Lilly, Eisai Europe, MSD Oncology",Journal of Clinical Oncology,1,1,1,1,1,1,1,1,1,9 +17,Lithium preserves peritoneal membrane integrity by suppressing mesothelial cell αB-crystallin,"SUPPLEMENTARY MATERIALS + stm.sciencemag.org/cgi/content/full/13/608/eaaz9705/DC1 Materials and Methods + Fig. S1 to S14 Tables S1 to S9 Data file S1 References (87–98) + View/request a protocol for this paper from Bio-protocol. + + Data and materials availability: All mass spectrometry data have been deposited into the ProteomeXchange Consortium (http://proteomecentral. proteomexchange.org) via the PRIDE partner repository with dataset identifiers PXD011938 and 10.6019/PXD011938. All transcriptomics array data have been deposited into ArrayExpress with dataset identifiers E-MTAB-7485 and E-MTAB-7793. All other data associated with this study are present in the paper or the Supplementary Materials + + Further details of applied protocols and techniques and the animal models are described in Supplementary Materials and Methods.",The study was performed according to the Declaration of Helsinki and registered at www.clinicaltrials.gov (NCT01893710). The study was part of the International Pediatric Dialysis Network (www.pedpd.org).,,"To investigate mechanisms of acute cellular damage by PDF, we chose an in vitro model with direct exposure to PDF followed by short-term or extended recovery for detection of short-term and long-term changes in transcriptome, proteome, and cell injury (Fig. 1A). We cultured primary human peritoneal mesothelial cells (HPMC) from omental biopsies of nondialyzed patients. Confluent HPMC were exposed for the indicated times (Fig. 1A) to a PDF in clinical use [40 mM lactate (pH 5.5) containing 7.5% icodextrin and glucose degradation products] with and without LiCl. After 16 hours of recovery, HPMC exposed to unsupplemented PDF showed morphological changes and cell detachment (Fig. 1B) as well as decreased cell membrane integrity and decreased viability assessed by intracellular esterase activity (Fig. 1C). LiCl addition reversed these effects in a dose-dependent manner. Lactate dehydrogenase (LDH) release increased to 247% (±151%) (P < 0.0001) after PDF exposure compared to control but decreased to 174% (±72%) (P = 0.037) with 2.5 mM LiCl and to 149% (±69%) (P = 0.001) with 10 mM LiCl. + + Study design + In this study, we used primary human omental mesothelial cells, peritoneal effluents from patients on PD, or patients with heart failure and peritoneal biopsies from pediatric patients on PD or with CDK5 or healthy controls. Experiments with primary cells were performed in at least duplicates per donor, and all experimental settings were performed with cultures from at least three different donors. Written informed consent was obtained from parents and from patients as appropriate. The use of patients’ material was approved by the local ethics committees and was performed according to the Declaration of Helsinki + + For in vivo experiments, mice were randomly assigned to experimental groups on the day of surgery. Measurements of histology, immunofluorescence, and immunohistochemical detections were performed in a blinded manner.","Preparation of PD effluent cells from PD patients + Human peritoneal cells from ascites (n = 4) or PD effluents (n = 7) were obtained from 11 patients at the Vienna General Hospital. PD effluents were collected from dwells of at least 4 hours from stable pediatric and adult patients on PD. Ascites samples were collected from patients with congestive heart failure and refractory ascites. The fluid of the whole bag was centrifuged, cells were counted, and slides (20,000 cells per slide) were prepared with a cytocentrifuge. The use of material obtained from patients on PD and patients with ascites for the current study was approved by the Ethics Committee of the Medical University of Vienna (EK2035/2015). Cells were fixed and permeabilized with the Leucoperm Kit (Bio-Rad) and then incubated overnight at 4°C with anti-CD45 [allophycocyanin (APC); 1:100; Miltenyi Biotec, Bergisch Gladbach, Germany], anti– Pan-Keratin (Alexa Fluor 488; 1:100; Cell Signaling Technology, Danvers, MA), and anti–aB-crystallin (ab76467; 1:200; Abcam). These were detected by Alexa Fluor 568–labeled secondary antibody (1:1000; Abcam) in 1% bovine albumin serum in phosphate-buffered saline with Tween 20 (0.1%) (PBS-T). Nuclei were stained with 4′,6-diamidino-2-phenylindole (DAPI) (NucBlue). Slides were mounted, the whole cell area was imaged with an automated fluorescence microscope (TissueFAXS, TissueGnostics, Vienna Austria), and fluorescence intensity was then quantified using Fiji (82) + + aB-crystallin abundance in PD effluent and human plasma proteomics datasets + Proteomics data from PD effluent was obtained from a recent study identifying 2506 proteins in PD effluent (39). Human plasma proteome analyses were obtained from two publicly available datasets [dataset I: https://pax-db.org (H.sapiens-Plasma, year: 2017, file: “9606-PLASMA-integrated”) and dataset II: (83)]. A total of 2436 proteins in PD effluent, 4492 plasma proteins in dataset I, and 1700 in plasma proteins in dataset II with abundances were used for analyses.","Primary human cells + Cultures of primary HPMC were derived from specimens of human omentum resected from consenting, nonuremic patients without known cancer, undergoing elective abdominal surgery at the Department of Surgery of Vienna General Hospital. + + Mesothelial cells were isolated from 3 to 5 cm3 specimens of omentum by enzymatic digestion [trypsin/EDTA, 0.05%/0.02% (w/v); Merck Biochrom, Darmstadt, Germany] and characterized as previously described (80). Isolated mesothelial cells were cultured in medium 199 supplemented with l-glutamine (0.1 g/liter), penicillin (50 U/ml), streptomycin (50 mg/ml), sodium bicarbonate (2.2 g/liter), Hepes (5.96 g/liter), and 10% fetal calf serum at 5% CO2 and 37°C in a humidified atmosphere. Media were changed every day until cells reached confluence. Only cultures with cobblestone-like morphology were used (see fig. S14). All experiments were performed with second passage cells. Primary human umbilical vein endothelial cells (Lonza, Basel, Switzerland) were cultured under standard conditions and used from passages 2 to 5 as previously described (for details, see Supplementary Materials and Methods) (81). + + Human samples + Forty-one peritoneal biopsies from the pediatric biopsy biobank (obtained from 23 boys and 18 girls with mean age of 7.5 years) were included in this study. Eleven were patients on PD, representing all patients in the biobank treated with icodextrin-containing PDF in their PD prescription (the glucose-based PDFs in the prescription were pH neutral with low GDP concentrations). Age-matched controls (n = 9) with normal renal function undergoing elective surgery and patients with CKD5 (n = 11) at time of PD catheter insertion were also included and a control group treated only with pH-neutral, low-GDP PDFs (n = 10). Patients on PD were treated with different PDF regimens but without use of amino acid–based PDF (mean PD vintage, 24 months; see fig. S9 for patient characteristics). In patients on PD, the sampling site was at least 5 cm away from the PD catheter entry site. Written informed consent was obtained from parents, and from patients as appropriate. + + Patients with a body mass index of >35 kg/m2 and with chronic inflammatory diseases were excluded. Underlying diseases in patients with CKD5 and PD were congenital anomalies of the kidney and the urinary tract (n = 13), juvenile nephronophthisis (n = 6), congenital nephrotic syndrome (n = 7), focal segmental glomerulosclerosis (n = 1), neonatal asphyxia and shock (n = 1), membranoproliferative glomerulonephritis (n = 1), and diffuse mesangial sclerosis (n = 1).","The isolated effects of PDF exposure without [F = 57.98 (P < 0.0001)] or with added LiCl [F = 7.32 (P = 0.001)] were significant but not the effect modulation (interaction) [F = 2.42 (P = 0.093); all by two-way analysis of variance (ANOVA)] (Fig. 1D). + + Statistical analysis and data visualization + Statistical analyses and graphical representations of results were performed using Statistical Package for the Social Sciences 17 (SPSS Inc., Chicago, IL), R (v3.5.1; http://www.r-project.org/), Prism 7 and 8 (GraphPad, La Jolla, CA, USA), and Venn Diagram Plotter (version 1.5.5228.29250). Values from different groups were compared using one-way or two-way ANOVA with Tukey’s post hoc test, with mixed-model analysis with Geisser-Greenhouse’s correction for sets with single missing values or with paired t test for protein spot abundance on two-dimensional (2D) gels. P < 0.05 was considered significant. Correction for multiple testing was performed as individually indicated by BH or Bonferroni correction. Results of animal experiments were analyzed by two-sided Mann-Whitney test or t test (two-sided, paired, or unpaired as indicated in the figure legends). Normal distributions were tested by Shapiro-Wilk test. Results are given as means ± SEM or, for non-normal distributions, as medians with IQR. Statistical overrepresentation tests of unique candidate genes or proteins were performed using the PANTHER Classification System and implemented GO database (version 13.1; www.pantherdb.org) with Fisher’s exact test and corrected for multiple testing, with an FDR <0.05 considered significant. Cytoscape [v3.5.1, (84)] plug-in ClueGO [v2.5.1, (85)] was used to summarize and visualize functionally grouped terms of significantly enriched biological processes of significantly regulated unique genes with the following settings: database, Homo sapiens-GO_BiologicalProcess-EBI-UniProt-GOA; GO term fusion; on, only nonredundant terms and significantly enriched pathways (P < 0.05) are shown; and statistical test, two-sided hypergeometric test with Bonferroni step-down as multiple testing correction. GO terms are shown as nodes with links based on k score (≥0.4), with at least three genes per term. The node size represents the term significance (smallest node: P < 0.05). In Fig. 7, estimation statistics were performed. Effect size is presented as a bootstrap 95% confidence interval on an aligned axis, where the effect size is displayed to the right of the raw data and the median of the test group is aligned with the effect size. A total of 5000 bootstrap samples were taken; the confidence interval is bias corrected and accelerated (86).","Funding: R.H. was supported by a research fellowship of the European Renal Association and European Dialysis and Transplant Association. K.B., M.B., C.P.S., M.L.-C., C.A., and K. Kratochwill were supported by the European Training and Research in Peritoneal Dialysis (EuTRiPD) program, a project funded by the European Union within the Marie Skłodowska-Curie Innovative Training Networks scheme (grant no. 287813). This work has been funded by IMPROVE-PD, a project from European Union’s Horizon 2020 program under the Marie Skłodowska-Curie Innovative Training Networks scheme (grant no. 812699) (to R.H., J.M.S., C.P.S., M.L.-C., C.A., and K. Kratochwill). M.B. is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project no. 419826430). This work was supported by grant (PID2019- 110132RB-I00/AEI/10.13039/501100011033) from the Spanish Ministry of Science and Innovation/Fondo Europeo de Desarrollo Regional (MICINN/FEDER) to M.L.-C. and Zytoprotec GmbH. + + Competing interests: C.A. is cofounder of Zytoprotec GmbH, a spin-off of the Medical University of Vienna that holds the patent “Carbohydrate-based peritoneal dialysis fluid comprising glutamine residue” (International Publication Number: WO 2008/106702 A1) and the use patent “Peritoneal dialysis fluid comprising a GSK-3 inhibitor.” R.H., K.B., A.W., M.U., I.J.S., J.M.S., and K. Kratochwill are former employees, PhD students, or consultants of Zytoprotec GmbH. A.V. has received honoraria and travel grants from Baxter and Fresenius Medical Care (manufacturers of dialysis solutions) and Fresenius Kabi unrelated to this study. C.P.S. obtained research funding from Baxter and Fresenius Medical Care unrelated to this study. S.L.A. was a consultant to the Medical University of Vienna and received research funding from Quest Diagnostics unrelated to this study. All other authors declare that they have no competing interests.","Science Translational Medicine + + Sci. Transl. Med.",1,1,0,1,1,1,1,1,1,8 +18,"Persistence of Contradicted Claims + in the Literature",,,JAMA,"Citation Curves. We downloaded annual citation counts from Thomson Scientific ISI Web of Knowledge for each of the 2 highly cited epidemiological studies between 1993 and 2006 and also assessed the number articles citing at least 1 of the 2 studies. For reference standard, we examined the total annual citation curves for all the articles published in the same year (1993) and in the same journal as the 2 highly cited epidemiological studies.","A randomized trial of 2002 patients (CHAOS) published in 1996 also found a 47% relative risk reduction for cardiovascular events. However, many randomized trials subsequently found no cardiovascular benefit. The most-cited contradicting trial (HOPE) was published in January 2000 and found an RR of 1.05 (95% CI, 0.95-1.16) for cardiovascular events,8 an effect entirely incompatible with estimates of the epidemiological studies. A meta-analysis published in late 2004 concluded that at high doses, vitamin E significantly increased the risk of death (RR, 1.04; 95% CI, 1.01- + 1.07).","Selection of the Citing Articles. We sampled citations to the 2 highly cited epidemiological studies at 3 different and equidistant years: 1997, 2001, and 2005. The first selected year (1997) represents the peak of annual citations and may be perceived to be the time when the evidence was the strongest in favor of vitamin E (shortly after the additional support offered by the CHAOS + trial published in 1996).7 The second selected year (2001) corresponds with an early period after major refutation (1-2 years after the HOPE results).8 The + third selected year (2005) corresponds with a late period after major refutation; meta-analysis had even + shown increased harm with vitamin E.","Quantitative analyses were performed using SPSS version 13.0 (SPSS Inc, Chicago, Illinois) and StatXact (Cytel Corp, Boston, Massachusetts). P values were 2-tailed, and a P value of less than .05 + was considered statistically significant","Biases + Selection bias: meta-analysis did not put its results in perspective by reviewing the context of research on vitamin E including the many positive observational and interventional studies28 + + Information bias: mortality estimates from CHAOSa came from a research letter, not a peer-reviewed study, and included data after the study was officially ended, and thus subject to information bias28 + + Funding/Support: None.","©2007 American Medical Association. All rights reserved + + Facciamo riferimento alla rivista, come acronimo o per esteso, quindi JAMA e Journal of the Americal Medical Association",0,0,1,1,1,1,1,1,1,7 +19,Effect of More vs Less Frequent Follow-up Testing on Overall and Colorectal Cancer–Specific Mortality in Patients With Stage II or III Colorectal Cancer,The study protocol and statistical analysis plan appear in Supplement 1.,TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00225641,JAMA,"Intervention Patients randomized to the high-frequency group were re quired to have follow-up testing with multislice contrast enhanced CT of the thorax and abdomen and CEA at 6, 12, 18, 24, and 36 months after surgery. Patients randomized to the low-frequency group were required to have follow-up testing with multislice contrast-enhanced CT of the thorax and ab domen and CEA at 12 and 36months after surgery. Testing with a pelvic CT was not required. Participating patients were ran domized in block sizes of 10 by computer allocation to 1 of the 2 follow-up regimens. Endoscopy and examination for pelvic recurrence were al lowed in both groups at the discretion of the treating physi cian. Although permitted in the study, no department used magnetic resonance imaging or chest radiography as part of its surveillance program. An external consultant (Lennart Blomquist, PhD, Karolinska Hospital, Stockholm, Sweden)with extensive experience in abdominal CT certified the quality of the CT scans at each recruitment center (Supplement 1). After verification of study enrollment criteria, baseline in formation for each participant (sex, comorbidity, and life style factors such as smoking and alcohol consumption, pre operative diagnosis and staging, type of surgery performed, pathological staging after surgery, postoperative complica tions, blood transfusions, and adjuvant chemotherapy or ra diation therapy) was recorded. At each follow-up surveil lance examination, datawere collected on symptoms, CT scans, and CEA test results per the trial protocol, and additional ex aminations were performed for suspected recurrence. In ac cordance with the study’s pragmatic approach, up to 3months’ variability in follow-up intervals was allowed to accommo date local needs for prioritization and patient preferences. Symptoms leading to interval examinations also were re corded. If a recurrence was not detected during an interval follow-up examination, the patient was allowed to continue in the study. If a recurrencewas suspected during any follow-up examination, the case was discussed at a meeting of the local multidisciplinary team and further diagnostic assessment (eg, positron emission tomography or CT) and treatment was un dertaken as recommended (eg, surgery for liver or other me tastases, referral for chemotherapy or radiation therapy, or both surgery and therapy). Each center had to follow-up all study participants with surveillance examinations until 3 years after surgery accord ing to the protocol and to report outcomes to the study’s co ordinating center until 5 years after surgery. Clinically diag nosed recurrences and deaths were reported at the time of the event. All patients were tracked throughout the study bymoni toring their inpatient and outpatient records and through link age with national population and cancer registries (except in Uruguay because only hospital data were available).14,15 Patients known to have emigrated or whose medical rec ordswere discontinuedwere deemed lost to follow-up and cen sored on the date of their last identifiable data point. Follow-up ended on December 31, 2015. All data were submitted elec tronically from the recruitment centers to the study’s coordi nating center in Denmark.","Intervention Patients randomized to the high-frequency group were re quired to have follow-up testing with multislice contrast enhanced CT of the thorax and abdomen and CEA at 6, 12, 18, 24, and 36 months after surgery. Patients randomized to the low-frequency group were required to have follow-up testing with multislice contrast-enhanced CT of the thorax and ab domen and CEA at 12 and 36months after surgery. Testing with a pelvic CT was not required. Participating patients were ran domized in block sizes of 10 by computer allocation to 1 of the 2 follow-up regimens. Endoscopy and examination for pelvic recurrence were al lowed in both groups at the discretion of the treating physi cian. Although permitted in the study, no department used magnetic resonance imaging or chest radiography as part of its surveillance program. An external consultant (Lennart Blomquist, PhD, Karolinska Hospital, Stockholm, Sweden)with extensive experience in abdominal CT certified the quality of the CT scans at each recruitment center (Supplement 1). After verification of study enrollment criteria, baseline in formation for each participant (sex, comorbidity, and life style factors such as smoking and alcohol consumption, pre operative diagnosis and staging, type of surgery performed, pathological staging after surgery, postoperative complica tions, blood transfusions, and adjuvant chemotherapy or ra diation therapy) was recorded. At each follow-up surveil lance examination, datawere collected on symptoms, CT scans, and CEA test results per the trial protocol, and additional ex aminations were performed for suspected recurrence. In ac cordance with the study’s pragmatic approach, up to 3months’ variability in follow-up intervals was allowed to accommo date local needs for prioritization and patient preferences. Symptoms leading to interval examinations also were re corded. If a recurrence was not detected during an interval follow-up examination, the patient was allowed to continue in the study. If a recurrencewas suspected during any follow-up examination, the case was discussed at a meeting of the local multidisciplinary team and further diagnostic assessment (eg, positron emission tomography or CT) and treatment was un dertaken as recommended (eg, surgery for liver or other me tastases, referral for chemotherapy or radiation therapy, or both surgery and therapy). Each center had to follow-up all study participants with surveillance examinations until 3 years after surgery accord ing to the protocol and to report outcomes to the study’s co ordinating center until 5 years after surgery. Clinically diag nosed recurrences and deaths were reported at the time of the event. All patients were tracked throughout the study bymoni toring their inpatient and outpatient records and through link age with national population and cancer registries (except in Uruguay because only hospital data were available).14,15 Patients known to have emigrated or whose medical rec ordswere discontinuedwere deemed lost to follow-up and cen sored on the date of their last identifiable data point. Follow-up ended on December 31, 2015. All data were submitted elec tronically from the recruitment centers to the study’s coordi nating center in Denmark.","Participants Inclusion criteria were surgical resection with curative intent for colorectal adenocarcinoma (with or without adjuvant treat ment), age of 75 years or younger, provision of written in formed consent for participation, a colon and rectum free of neoplasia verified by perioperative barium enema or a colo noscopy within 3 months after surgery, and tumor stage II or III (T3-T4, N0, M0, any N1-N2, M0). Exclusion criteria were a clinical diagnosis of hereditary nonpolyposis colorectal cancer or familial adenomatous pol yposis, local resection of colorectal cancer (eg, transanal en doscopicmicrosurgery procedure), life expectancy of less than 2 years due to comorbid conditions (eg, cardiac disease, ad vancedmultiple sclerosis with systemic complications, or liver cirrhosis), inability or refusal to provide informed consent, in ability to comply with study requirements, inability to toler ate surgery for recurrence, other or previous malignancies (except for nonmelanoma skin cancer), or participation in an other clinical trial that was incompatible with this study’s follow-up regimen. Participants were required to have at least 1 imaging pro cedure (ultrasonography, magnetic resonance imaging, or CT) of the liver and CT or radiography of the lungs prior to sur gery. Patients also were required to have testing with CEA at 1 month after surgery. Patients with an elevated CEA level were enrolled only after a completely negative diagnostic workup. Written informed consent for participation was obtained at least 30 days after surgical resection of the primary colorectal cancer. + + Main Statistical Analysis Participants were characterized by randomization group and by sex, age, clinical variables, comorbidities, and the lifestyle factors of smoking and alcohol consumption. Pri mary and secondary outcomes data were analyzed using the Kaplan-Meier method and the log-rank test was used for between-group comparisons. In the time-to-recurrence analysis, patients were censored at the time of death. In the intention-to-treat analyses, trial participants were followed up from the date of radical surgery for colorectal cancer until the analyzed study outcome, date of dropout, date when lost to follow-up, or at 5-year follow-up, whichever came first. In addition, risk differences in the 5-year mortality rate and in the recurrence probabilities were calculated with 95% CIs. The cumulative incidence curves were computed using Kaplan-Meier estimates minus 1. Study results were evalu ated on an intention-to-treat basis and on an as-treated per protocol basis. There were missing data for some key vari ables for 11 patients (5 in the high-frequency group and 6 in the low-frequency group). Patients who withdrew informed consent or switched to another follow-up regimen remained in their randomized group for the intention-to-treat analysis, but were excluded from the per-protocol analysis.","Primary and secondary outcomes data were analyzed using the Kaplan-Meier method and the log-rank test was used for between-group comparisons + + In addition, risk differences in the 5-year mortality rate and in the recurrence probabilities were calculated with 95% CIs. The cumulative incidence curves were computed using Kaplan-Meier estimates minus 1. + + Post Hoc Subgroup Analysis Post hoc analyses were stratified by cancer stage (stage II or III) and were repeated for patients with rectal cancer who had or did not have preoperative radiotherapy. Moreover, a potential statistical cancer stage × frequency of follow-up testing interaction was assessed by inclusion of these interaction terms in a Cox regression model + + Post Hoc Sensitivity Analysis To test the robustness of the risk estimates, 3 additional sensitivity analyses were performed. First, Cox proportional hazard regression was used to compute hazard ratios (HRs) with 95% CIs for overall mortality rate, colorectal cancer– specific mortality rate, and colorectal cancer–specific recurrence rate. + + In the intention-to-treat analysis,no significant associations with the primary outcomes were found in a Cox regression analysis controlling for covariates when patients in the high-intensity group were compared with patients in the low-intensity group for the 5-year overallmortality rate (adjusted HR, 0.90; 95% CI, 0.73-1.12) or the colorectal cancer–specific mortality rate (adjusted HR, 0.92; 95% CI, 0.72-1.17)","Funding/Support: This study was funded by unrestricted grants from the Nordic Cancer Union, A. P. Møller Foundation, Beckett Foundation, Grosserer Chr. Andersen og hustru bursary, Sigvald og Edith Rasmussens Memorial Fund, Martha Margrethe og Christian Hermansens Fund, the Danish Medical Association, the Danish Cancer Society, the Danish Council for Independent Research/Medical Sciences (all awarded to Dr Wille-Jørgensen), and by unrestricted grant CAN 2013/553 from the Swedish Cancer Foundation (awarded to Dr Påhlman). + Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.",JAMA,1,1,1,1,1,1,1,1,1,9 +20,Outcomes of acute leukemia patients transplanted with naive T cell–depleted stem cell grafts,"The full clinical trial protocol is available in the Supplemental Methods. + + (See Supplemental Methods for a list of reagents). + + (Supplemental Table 1; supplemental material available online with this article; doi:10.1172/ JCI81229DS1","TRIAL REGISTRATION. ClinicalTrials.gov (NCT 00914940). + + The clinical trial is registered at ClinicalTrials.gov (NCT 00914940).","Figure 1. Consort diagram of phase II nonrandomized clinical trial. + + The Journal of Clinical Investigation","METHODS. In a single-arm clinical trial, we transplanted 35 patients with high-risk leukemia with TN-depleted PBSC grafts following conditioning with total body irradiation, thiotepa, and fludarabine. GVHD prophylactic management was with tacrolimus immunosuppression alone. Subjects received CD34-selected PBSCs and a defined dose of TM purged of CD45RA+ TN. Primary and secondary objectives included engraftment, acute and chronic GVHD, and immune reconstitution. + + Graft engineering. The rationale and methodology for depleting TN using anti-CD45RA mAb-conjugated beads have been published previously (29). To allow precise T cell dosing and because a minor subset of CD34+ stem/progenitor cells express CD45RA, we used a 2-step immunomagnetic selection procedure involving positive selection of CD34+ progenitor cells, followed by depletion of CD45RA+ cells from the CD34-negative fraction (29). In brief, CD34+ selections were performed using the CliniMACS CD34 reagent system (Miltenyi Biotec) (33, 64), followed by depletion of CD45RA+ cells from the CD34– fraction using anti-CD45RA immunomagnetic beads (Miltenyi Biotec) (see Supplemental Methods for a list of reagents). The CD34-enriched and the CD45RA-depleted cell populations were each formulated in 100 ml Normosol-R (Hospira) with 1% human serum albumin prior to infusion. + + Following the completion of conditioning, patients received a graft composed of CD34-selected PBSCs (≥5 × 106/kg) and CD45RA-depleted PBSCs containing a target dose of 107 CD3+ T cells/kg and ≤7.5 × 104 TN/kg. The cells were infused into the patient the same day as cell selection over 1 to 4 hours, with infusion of the CD34+-enriched cells followed immediately by infusion of the CD45RA-depleted cells. All patients received GVHD prophylaxis, with tacrolimus titrated to a serum level of 5 to 15 ng/ml and tapered after day 50 in the absence of GVHD or subsequently after GVHD resolution. We chose to use tacrolimus monotherapy, rather than a more intensive GVHD prophylaxis regimen, such as a combination of a calcineurin inhibitor with methotrexate or mycophenolate mofetil, because our intent was to evaluate TN depletion as an alternative rather than additional form of GVHD prophylaxis. GVHD was treated according to institutional standard practice with systemic and/or topical corticosteroid administration and continuation of tacrolimus. Additional second-line GVHD therapies were permitted for the management of corticosteroid-resistant GVHD if necessary. The duration of full-dose systemic corticosteroids (0.5–2 mg/kg/d prednisone) and subsequent taper schedule were determined by the treating physician within the scope of institutional practice. Antimicrobial prophylaxis, infection definitions, monitoring and preemptive management, chimerism testing, and minimal residual disease evaluation are described in the Supplemental Methods. + + Clinical trial patients and the comparison cohort received the same supportive care according to standard practice guidelines at FHCRC. Evaluations of clinical aGVHD and cGVHD were performed for TN-depleted clinical trial patients and the comparison cohort by the same expert evaluators who were not associated with the study. Histopathology of endoscopic GI and skin biopsies was assessed and graded by an expert GVHD pathologist in-house who was blinded to the transplant protocol","Lymphocyte enumeration. Lymphocyte enumerations were performed by the Hematopathology Laboratory at the University of Washington using multicolor flow cytometry. Briefly, 100 μl of whole lood was labeled with mAbs, red blood cells were lysed (TQ-Prep; Beckman Coulter), and 10,000 mature lymphocyte events were acquired on an FC500 flow cytometer. TruCount beads (Becton Dickinson) were included and used to generate absolute counts for each population. The lymphocyte subsets were defined as follows using CXP software (Beckman Coulter): CD8+ T cells (CD8+CD3+), CD4+ T cells (CD4+CD3+), B cells (CD19+), and NK cells (CD3–CD56+ and/or CD16+). A separate 100-μl aliquot of sample was labeled with appropriately titered antibodies, red blood cells were lysed using NH 4Cl containing 0.25% ultra-pure formaldehyde (Polysciences) and washed once with PBS-BSA, and up to 200,000 total events were acquired on a LSRII flow cytometer (Becton Dickinson). The additional lymphocyte subsets investigated using WoodList software were as follows: CD8+ T N (CD8+CD3+CD45RA+CD45RO–CD62L+), CD4+ T N CD4+CD3+CD45RA+CD45RO–CD62L+), and Tregs (CD4+ CD3+CD25+CD127–). CD127 expression has been demonstrated to correlate inversely with FOXP3 expression on CD4+CD25+ cells, and the CD4+CD25+CD127– phenotype is considered to be an acceptable surrogate marker for human Tregs and a practical alternative to intracellular staining for FOXP3 (65, 66). Antibodies were obtained from Beckman Coulter or Becton Dickinson. + + TREC analysis. TREC analysis was performed in the FHCRC Immune Monitoring Shared Resource Facility. Signal-joint TRECs were evaluated in peripheral blood samples obtained on days 28, 56, 80, 180, and 360 after HCT. Primers and probes for TCR δ locus signal-joint TRECs were synthesized according to the methods described by Douek et al. (67). DNA was extracted from PBMCs and used as a template for real-time qPCR. To generate standard curves, plasmid DNA containing TREC and β-actin DNA segments was made into serial dilutions containing 102–106 copies per PCR reaction. Triplicate PCR reactions were run for each sample on the StepOnePlus real-time PCR system (Applied Biosystems). + + Spectratyping. TCR spectratyping was performed in the FHCRC Immune Monitoring Shared Resource Facility. To assess TCR Vβ repertoire diversity in peripheral blood samples obtained at 6 and 12 months after HCT from T N-depleted HCT recipients, we used a multiplex PCR spectratyping method that amplifies 46 functional genes, comparing 23 TCRβV families in 5 reactions in which each reaction contains 4 to 7 specific primers, together with a single fluorescence-tagged TCR β constant region primer (68) + + Antigen-specific T cell evaluation. MHC-tetramer analysis for CMV pp65 NLVPMVATV–specific (pp65NLV-specific) T cells was performed by flow cytometry using iTag MHC tetramers (Beckman Coulter) and mAbs specific for CD3, CD8, CD28, CD27, IFN-γ, and IL-2 (Becton Dickinson) (see Supplemental Methods for a list of reagents). Dead cell exclusion was performed using DAPI (Sigma-Aldrich) or Live/ Dead Fixable Violet (Molecular Probes). PBMCs were surface labeled with antibodies and tetramers for 30 minutes at 4°C and evaluated on a LSRII flow cytometer. Analysis was performed using FlowJo software (Treestar). To assess function, aliquots of PBMCs were stimulated with pp65NLV peptide in the presence of anti-CD28 and anti-CD49a costimulatory mAbs (5 μl/ml; BD Biosciences). Brefeldin A (1 μl/ml Goligplug; BD Biosciences) was added 1.5 hours into the stimulation. After 6 hours, cells were stained with Live/Dead Fixable Violet, fixed, and permeabilized (Cytofix/Cytoperm, BD Biosciences) and then stained with fluorescent protein-conjugated mAbs against IFN-γ, IL-2, CD4, and CD8 (BD Biosciences) (see Supplemental Methods for a list of reagents) in Perm/Wash buffer (BD Biosciences), before washing and analysis on the flow cytometer.","Patient characteristics and graft engineering. The patient characteristics are listed in Table 1. Of 108 patients aged 14 to 55 years with an HLA-MRD (>13 years old) who were evaluated for HCT for the treatment of acute leukemia or advanced MDS during the study period (December 2009 to May 2014), 35 were allocated to HCT in the T N depletion clinical trial and treated accordingly (Figure 1). The major reasons that other patients were not allocated to the trial included allocation to a non-TBI–containing myeloablative HCT at the discretion of the transplant attending physician (in most cases, patients with AML or MDS with better-risk disease and/or comorbidities); allocation to a nonmyeloablative regimen; or allocation to transplantation on a standard myeloablative treatment plan with cyclophosphamide and TBI conditioning. Patients allocated to cyclophosphamide and TBI included patients that lacked insurance coverage for a clinical trial, were unwilling to consent to the trial of T N depletion, or were precluded for participating for logistical reasons or because they did not meet eligibility criteria for the trial. + + Patients and treatment. Thirty-five patients, aged 19 to 55 years, with AML, ALL, or refractory anemia with excess blasts, who were candidates for myeloablative HCT and had a MRD, were enrolled on the phase II clinical trial at FHCRC (n = 33) or YUSM (n = 2) between December 2009 and July 2014. Eligible patients were considered by their referring physicians to require allogeneic HCT because they were judged to be at high risk of leukemic relapse following chemotherapy alone. Inclusion and exclusion criteria are detailed in the clinical trial protocol (Supplemental Methods). Patients at a very high risk of relapse after HCT due to a history of previous relapses or detectable disease immediately prior to HCT were designated “poor risk,” and those who had leukemia with high-risk cytogenetic or molecular characteristics but no prior history of relapse or detectable disease at the time of HCT were designated “better risk.” The conditioning regimen was composed of fludarabine (125 mg/m2), thiotepa (10 mg/kg), and TBI (1,320 cGy) (30). + + Contemporary comparison cohort. A cohort of patients that underwent HCT at FHCRC on a standard treatment plan during the same time period served as a comparison group for analysis of GVHD. This cohort represented all other patients aged 14 to 55 years who received TBI-containing myeloablative T cell–replete PBSC HCT from a HLAMRD for the treatment of ALL, AML, or refractory anemia with excess blasts at FHCRC on a standard HCT treatment plan between April 2008 and March 2014. These patients received a standard conditioning regimen consisting of TBI (12 Gy) followed by cyclophosphamide (120 mg/kg) and GVHD prophylaxis, consisting of short-course methotrexate (15 mg/m2 day 1, 10 mg/m2 days 3, 6, and 11) and either tacrolimus (n = 28) or cyclosporine (n = 5). For inclusion in the comparison cohort, the patients had to meet the same age, disease status, and organ function eligibility criteria as patients treated in the TNdepleted PBSC clinical trial. The comparison group consisted primarily of patients who were unwilling or lacked insurance company approval to participate in an experimental clinical trial.","Statistics. Data were analyzed as of December 2014. The protocol was designed with engraftment and grades II–IV aGVHD as the primary endpoints. We reviewed the FHCRC clinical research databases and derived estimates of the incidence of grade II–IV (60%) and III–IV (19%) aGVHD in patients undergoing HLA-MRD myeloablative HCT. Thirty-five patients provided 92% power to observe a statistically significant (1-sided significance level of 0.05) reduced probability of GVHD relative to the fixed rate of 60%, under the assumption that the true probability of grades II–IV GVHD is 35%. A 1-sided binomial test was performed in order to test the null hypothesis that the true rate of grade II–IV aGVHD is equal to the fixed rate of 60%. A P value of less than or equal to 0.05 was considered significant. Stopping rules were created such that the trial would stop prior to the accrual of 35 patients if the true probability of graft failure exceeded 5%. cGVHD was a predetermined secondary endpoint of the study. Probabilities of overall survival and DFS were estimated with the Kaplan-Meier method. Probabilities of death not preceded by relapse, recurrent malignancy, and GVHD were summarized with the use of cumulative incidence estimates, with recurrent malignancy viewed as a competing risk for death not preceded by relapse, with death not preceded by relapse viewed as a competing risk for recurrent malignancy, and with death without GVHD viewed as a competing risk for GVHD. Probabilities of discontinuation of systemic corticosteroids and of discontinuation of all system immune suppression were also summarized with cumulative incidence estimates, with death while still on corticosteroids or on any systemic immunosuppression viewed as a competing risk for discontinuation of corticosteroids or any systemic immune suppression, respectively. Statistical analyses of clinical outcomes were conducted using SAS 9.3 for Windows (SAS Institute).","Within the limitations of a single-arm trial of this size, the reduction in cGVHD did not come with apparent decrements in other important clinical outcomes. The 2-year DFS rate of 70% in T N-depleted HCT recipients compares favorably to DFS rates of 50% to 65% after TCD or T cell–replete MRD HCT for acute leukemia (7, 33, 56, 57). Potentially fatal EBV reactivation and PTLD did not occur in T N-depleted recipients, and other serious infections were rare. Additionally, relapse was uncommon. In particular, the relapse rate of 28% observed among patients that received HCT with residual leukemia or a history of previous relapses compares favorably with the expected relapse rates of 37% to 60% with T cell–replete or TCD MRD HCT for this subset of patients, implying that the GVL effect may not be abrogated by TN depletion and/or that relapse is suppressed due to an earlier withdrawal of immunosuppressive drugs (7, 33, 57, 58) + + Conflict of interest: The authors have declared that no conflict of interest exists. + + FUNDING. NIH, Burroughs Wellcome Fund, Leukemia and Lymphoma Society, Damon Runyon Cancer Research Foundation, and Richard Lumsden Foundation.","The Journal of Clinical Investigation + + jci",1,1,1,1,1,1,1,1,1,9 +21,Genomics of lethal prostate cancer at diagnosis and castration resistance,"(Supplemental Figures 1 and 2 in the Supplemental Materia) + + Supplemental material available online with this article; https://doi.org/10.1172/JCI132031DS1).","Study approval. The study included all patients with mCRPC who, between March 2015 and December 2017, provided written consent to participate in 1 of 2 IRB-approved molecular characterization programs for prostate cancer: an internal molecular characterization study at The Royal Marsden Hospital and/or a tumor NGS prescreening study at 17 hospitals (Supplemental Material) for the TOPARP-B study, an investigator-initiated clinical trial of the PARP inhibitor olaparib in mCPRC (42) (CR-UK 11/029, NCT 01682772).","The Journal of Clinical Investigation + + jcm","We profiled 470 treatment-naive prostate cancer diagnostic biopsies and, for 61 cases, mCRPC biopsies, using targeted and low-pass whole-genome sequencing (n = 52). Descriptive statistics were used to summarize mutation and copy number profile + + Methods + Study design. This analysis included all consecutive patients who gave consent between March 2015 and December 2017 for molecular characterization of prostate cancer biopsies at The Institute of Cancer Research (London, United Kingdom). These studies involved either prostate tumor samples and/or newly acquired metastatic biopsies. We report here on all patients for whom a treatment-naive primary prostate tumor sample was successfully sequenced. Primary tumor samples were retrieved from referring hospitals. In most cases, only one sample was made available for the study; if more than one sample from the primary tumor was available, the highest Gleason lesion was used. Additionally, metastatic biopsies in castrate-resistant conditions were pursued in consenting patients.","Genomic profile of lethal primary prostate tumors. Recurrent aberrations in genes and pathways related to lethal prostate cancer were identified, the commonest being mutations and homozygous loss of TP53 (27%) (Figure 1 and Supplemental Figure 3). Deleterious mutations and/or homozygous deletions in genes involved in DDR pathways were identified in 23% of primary tumors. BRCA2 was the DDR gene most commonly altered (7%). Alterations in mismatch repair genes were detected in 11 of 470 (2%) cases. + Activating mutations in PIK3CA and AKT1 were detected in 5% of tumors, with PTEN loss-of-function mutations or deep deletions in 12% of tumors. Deep deletions of RB1 were uncommon in the primary tumors (5%), although shallow deletions in RB1 were frequent. Genes in the WNT pathway (loss of APC or activating mutations in CTNNB1) were altered in 7% of cases (8, 9). SPOP mutations were identified in 7% cases (10, 11). Surprisingly, low-allele frequency AR T878A or R630Q mutations (always with low mutation allele frequency, range 0.06–0.18) were detected in 1% of treatment-naive samples (12). + Our cohort 1 of primary tumors, without detectable metastases at diagnosis, was enriched for alterations in TP53 (25% vs 8%; P < 0.001), BRCA2 (8% vs 3%; P = 0.015), and CDK12 (6% vs 2%; P = 0.04) when compared with the TCGA series (Table 2). Conversely, SPOP mutations were less common in our population than in the better prognosis TCGA series (3% vs 11%; P = 0.001). No relevant differences in prevalence of other mutations were observed when comparing cohort 1 and cohort 2. After adjusting for Gleason score, CDK12 mutations were enriched in Gleason 8 or higher cases (1 of 105 cases in Gleason 6–7 vs 21 of 353 in Gleason ≥8) + + We pursued NGS of mCRPC biopsies acquired from 61 patients participating in this study to further investigate if certain gene aberrations were detected more often in biopsies after progression on ADT and subsequent lines of therapy. Overall, we performed targeted NGS on 61 mCRPC biopsies (using the same panel as for the primary treatment-naive samples). Copy-number profiles for both primary and mCRPC samples were compared using lowpass + whole-genome sequencing (WGS) in 52 cases with sufficient DNA in both samples. Copy number estimation was adjusted for ploidy and tumor purity, since mCRPC biopsies had higher tumor content overall than the primary prostate biopsies (Supplemental Figures 5 and 6). + + Sample acquisition and processing. All prostate cancer treatmentnaive and metastatic biopsy samples were centrally reviewed by a pathologist. DNA was extracted from formalin-fixed and paraffin-embedded (FFPE) tumor blocks (average, 6 sections of 10 μm each per sample) using the FFPE Tissue DNA kit (Qiagen). DNA was quantified with the Quant-iT high-sensitivity PicoGreen double-stranded DNA Assay Kit (Invitrogen). The Illumina FFPE QC kit (WG-321-1001) was used for DNA quality control tests according to the manufacturer’s protocol as previously described (34). In brief, quantitative PCR (qPCR) was performed using 4 ng of sample or control DNA, and the average Cq (quantification cycle) was determined. The average Cq value for the control DNA was subtracted from the average Cq value of the samples to obtain a ΔCq. DNA samples with a ΔCq less than 4 were selected for sequencing. A double amount of DNA was used for cases with ΔCq between 2–4","We profiled 470 treatment-naive prostate cancer diagnostic biopsies. + + Table 1. Population characteristics and sample disposition for the overall study population (n = 470) + + Patient and sample disposition. Between March 2015 and December 2017, 652 primary tumor samples from consenting patients were received; 87 cases (13%) were discarded due to either low DNA yield or excessive DNA degradation. Hence, targeted next-generation sequencing (NGS) was successfully performed on 565 prostate cancer diagnostic biopsies. Fifty-four cases were excluded due to either the biopsy not being collected before ADT, or diagnosis being based on a metastatic biopsy. We analyzed the NGS of the remaining 511 samples; of those, 41 (8%) cases did not meet quality control criteria for copy-number calling (7) and were discarded, so the final analysis evaluated 470 cases. Two cohorts were defined for the planned analyses based on disease extent at the time of original diagnosis: cohort 1 was composed of 175 cases with locoregional prostate cancer at diagnosis (69.5% confined to the prostate, 30.5% with pelvic nodal extension); cohort 2 included 292 primary tumors from patients with metastatic disease at diagnosis. The clinical records of 3 subjects were unobtainable (Table 1)","Prevalence was compared using Fisher’s exact test. Survival correlations were studied using log-rank test. + + Clinical outcome based on primary tumor genomics. Median time to ADT progression and start of first mCRPC therapy was 1.17 years (95% CI: 1.08–1.26 years) among the subset (n = 210) of patients with clinical data available. Median overall survival from first evidence of metastatic disease was 4.28 years (95% CI: 3.72–4.84 years) + + Patients with RB1 alterations in the primary tumor had a significantly shorter overall survival (OS) (median OS from metastatic disease 2.32 years; 95% CI: 1.82–3.84; P = 0.006) (Table 3 and Supplemental Figure 4). + + The median time between the 2 same-patient biopsies was 45.2 months (range 12–211 months). All mCRPC samples were obtained after progression on ADT, and in 50 of 61 (82%) cases after progression on at least 2 further lines of therapy for mCRPC (80% after at least 1 taxane and 90% after abiraterone acetate and/or enzalutamide) (Table 4) + + Sequencing and bioinformatic analyses. Libraries for next-generation targeted sequencing were constructed using a customized panel (GeneRead DNAseq Mix-n-Match Panel v2; Qiagen) covering 6025 amplicons (398702 bp) across 113 genes used in Pritchard et al. (Supplemental Table 2) (35). Libraries were run using the MiSeq Sequencer (Illumina). FASTQ files were generated using the Illumina MiSeq Reporter v2.5.1.3. Sequence alignment and mutation calling were performed using the Qiagen GeneRead Targeted Exon Enrichment Panel Data Analysis Portal (https:// ngsdataanalysis.qiagen.com). Mutation calls were reviewed manually in Integrative Genomics Viewer (https://software. broadinstitute.org/software/igv) according to the standard operating procedure for somatic variant refinement of tumor sequencing data, following principles previously described (36). This manual review included assessing read strand quality, base quality, read balance, and sequencing artifacts (high discrepancy regions, adjacent indels, multiple mismatches, start or end of amplicons). Mutation annotation was based on data from publically available databases (ClinVar, COSMIC, Human Genome Mutation Database, IARC TP53 Database), published literature, and in silico prediction tools. Only deleterious mutations were included in the analysis. + Copy number variations (CNVs) in prostatic biopsies were assessed using the CNVkit (v0.3.5, https://github.com/etal/ cnvkit) (37), which we previously validated in an independent cohort of prostate cancer samples (7). The read depths of tumor samples were normalized and individually compared with a reference consisting of nonmatched male germline DNA. The circular binary segmentation (CBS) algorithm was used to infer copy number segments. Quality estimation of the CNV was based on distribution of bin-level copy ratios within segments. Cases were excluded from the analysis if any of the following criteria were met: IQR greater than 1, total reads fewer than 500,000, fewer than 99.9% of reads on target, fewer than 95% paired reads, or single reads greater than 0. Manual review of copy number calls for selected oncogenes and tumor suppressors was pursued, accounting for tumor content. Oncoprints and heatmaps representing mutations and copy number calls were generated using R and cBioportal OncoPrinter (38–40). + Low-pass WGS was performed on the mCRPC, and same-patient, treatment-naive, diagnostic, paired samples for copy-number profiling. Libraries were constructed using the NEBNext Ultra FS II DNA kit (New England Biolabs) according to the manufacturer’s protocol. Samples were pooled and run on the NextSeq (Illumina) at ×0.5 mean coverage, using the 300 cycles High Output v2.5 kit (Illumina). BCL files were converted to FASTQ files using BCL2FASTQ v2.17. Sequence alignments were performed using Burrows-Wheeler Aligner (BWA-MEM v0.7.12) to the hg19 human genome build. Copy number analysis was performed using IchorCNA (41). In short, hg19 genomes (filtered centromeres) were divided into 500-kb nonoverlapping bins, and the abundance of the mapped reads was counted by HMMcopy Suite in each bin and predicted segments of CNAs. GC and mappability bias were corrected by loess regression and based on a panel of germline DNA sequencing from healthy donors. The maximum CNA detection was set to 20 copies. + Raw sequencing data have been deposited at the European Nucleotide Archive with accession number PRJEB32038. VCF files with mutation calls and CN values for the targeted sequencing data are available in the Supplemental Material + + Statistics. Descriptive statistics were used to summarize patient and sample characteristic data as well as mutation frequency. The prevalence of mutations was compared between cohorts using Fisher’s exact test. The statistical analysis plan and the gene list to be analyzed was designed before data collection. A Bonferroni’s correction was applied; P values of less than 0.01 were considered statistically significant. All tests were 2-sided unless otherwise specified. + Additionally, exploratory associations between the preselected list of gene alterations and patient outcomes were tested in a subset of the study population (n = 210) with available consent for clinical data collection (all at The Royal Marsden Hospital, London, United Kingdom). Clinical data were captured retrospectively from electronic patient records. Time to ADT progression was defined from the date of starting ADT to start of first mCRPC therapy. Overall survival was defined as time from the date of diagnosis, date of metastatic disease, and the date of CRPC to the date of death or last follow-up. To account for variability among patients who were diagnosed with de novo metastatic versus localized disease, survival data are presented from the first evidence of metastatic disease. Patients alive at the time of last follow-up were censored. Association of genomic aberrations with survival are presented using Kaplan-Meier curves and log-rank test. All calculations were performed using STATA v15.1 (Stata Corp).","Conflict of interest: JM has served as a consultant for AstraZeneca, Roche, Janssen, Clovis, and Amgen. TE has received educational grants from Janssen. RJ has received fees from or acted in an advisory role for Astellas, AstraZeneca, Bristol-Myers Squibb, Bayer, Exelixis, Janssen, Ipsen, Merck Serono, Novartis, Pfizer, Roche, Sanofi, and EUSA Pharma. CR has received research grants from Oncolytics and Tusk Therapeutics, honoraria from Bristol-Myers Squibb, and support for travel from Roche, GlaxoSmithKline, Viralytics, Janssen, Novartis, Pfizer, and Ipsen. SJ has received fees from or acted in an advisory role for Astellas, Janssen, Bayer, Boston Scientific, and Almac Diagnostics. JSDB has served as a consultant for Astellas, AstraZeneca, Bayer, Daiichi, Genentech, GlaxoSmithKline, Janssen, Merck Serono, Merck Sharp & Dome, Orion, Pfizer Oncology, Sanofi-Aventis, Silicon Biosystems, and Taiho. + + Acknowledgments + We would like to acknowledge funding support from the Prostate Cancer Foundation, Prostate Cancer UK, Movember, Cancer Research UK (Centre Programme grant), Experimental Cancer Medicine Centre grant funding from Cancer Research UK and the Department of Health, and Biomedical Research Centre funding to The Royal Marsden. TOPARP is an investigator-initiated study supported by Cancer Research UK (CRUK/11/029, C12540 A12829, C12540/A13230, and C12540/A20447) and conducted with support from the Investigator-Sponsored Study Collaboration between AstraZeneca and the National Institutes for Health Research Cancer Research Network. JSDB is a senior investigator at NIHR. The views expressed in this article are those of the author(s) and not necessarily those of the UK National Health Service. JM was supported by a Prostate Cancer Foundation Young Investigator Award (PCF16YOUN11) and research funding from Fundacio LaCaixa (LCF/PR/PR17/51120011), FERO Foundation, Cellex Foundation, and Instituto de Salud Carlos III (PI18/01384). GS was supported by a Prostate Cancer UK PhD Studentship. We acknowledge the patient recruitment contributions from all investigators involved in the TOPARP trial and the staff at the ICR Clinical Trials and Statistics Unit. A full list of clinical investigators involved in this work is presented in Supplemental Table 1. + + However, the limited number of cases with DDR gene alterations in the cohort of matched primarymetastatic biopsies, including only 4 cases with BRCA2 mutations, prevents us from making broad conclusions with regard to the genomic evolution of these tumors. Indeed, we and others have reported subclonal homozygous deletions of DDR genes (20, 21). Detecting these subclonal deletions is technically challenging with targeted NGS assays used for patient stratification in clinical practice or in clinical trials, particularly when studying primary tumor samples with low tumor content and degraded DNA + + Another key limitation is the inability to pursue subclonality assessments using our clinically oriented targeted sequencing assay. Hence, we cannot prove if some of the gene aberrations detected in the mCRPC biopsies but not in the treatment-naive samples were already present at a subclonal level at the time of diagnosis. Regardless of whether these events emerge de novo or as a result of expansion of a subclone, the observed enrichment for certain alterations (such as TP53 or RB1) in the posttreatment resistance samples supports the clinical relevance of such alterations. + + The main limitation of our study comes from having only one biopsy core available per time point and patient; we therefore could not assess spatial tumor heterogeneity. Primary prostate cancers can be multifocal, and previous studies have reported on interfoci genomic heterogeneity (30, 31). We cannot rule out that in some cases the primary tumor sample may not represent the dominant tumor clone in the primary biopsy. Hence, it is possible that some of the differences we observe in paired mCRPC biopsies may have not resulted from treatment-selective pressure but from other areas of these primary tumors. However, genomic testing in clinical practice is largely based on the analyses of single biopsy cores. With the advent of novel imaging modalities, genomic stratification of prostate cancer could be improved by better identifying aggressive areas of prostate cancer in clinical diagnostic pathways (32, 33) + + C and mappability bias were corrected by loess regression and based on a panel of germline DNA sequencing from healthy donors. The maximum CNA detection was set to 20 copies.","The Journal of Clinical Investigation + + jci",1,1,1,1,1,1,1,1,1,9 +22,"Assessment of transparency indicators across + the biomedical literature: How open is open?","Citation: Serghiou S, Contopoulos-Ioannidis DG, Boyack KW, Riedel N, Wallach JD, Ioannidis JPA (2021) Assessment of transparency indicators across the biomedical literature: How open is open? PLoS Biol 19(3): e3001107. https://doi.org/ 10.1371/journal.pbio.3001107 + + Data Availability Statement: Data are available on Open Science Framework at http://www.doi.org/10. 17605/OSF.IO/E58WS. + + Information about concordance is available as a Supporting information (S10 Table). All extracted data were harmonized into a unified database, which can be accessed on OSF at https://doi.org/10.17605/OSF.IO/E58WS. + + Data sharing All data are available on the OSF and may be accessed, shared, or adapted under the Creative Commons Attribution 4.0 International License at the following link: https://doi.org/10. 17605/OSF.IO/E58WS. + + Code sharing All code is available on GitHub at https://github.com/serghiou/transparency-indicators/, and our algorithms are available under a GNU-3 license as an R package called rtransparent on GitHub at https://github.com/serghiou/rtransparent.",,This manuscript was prepared using guidance from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines [33] for observational studies and the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines for reporting prediction models [34].,"First, we randomly assembled a retrospective cohort of 520 records made available on PubMed between 2015 and 2018. PubMed is maintained by the United States NLM and provides citations to 30,732,929 references of the biomedical and life sciences literature (as of March 2020), 4,552,825 of which were published between 2015 and 2018 + + PMC is a free full-text archive for a subset of the publications available on PubMed. It was set up in 2000 and includes publications from journals that have agreed to either share all of their publications, NIH-funded publications, or a select subset of their publications [35]. Out of 5,747,776 publications made available on PubMed between 2015 and 2019 (in terms of Entrez Date), 2,497,046 (43.4%) were also made available on PMC. We randomly identified and downloaded the PDF of 6,017 of these records. + + As of February 29, 2020, out of 6,016,911 records ever made available on PMC (1795 to 2020), 2,754,689 are part of the PMCOA [36]; not all articles on PMC are part of PMCOA. These articles are made available under a Creative Commons or similar license, and their full text (but not their supplements) may be downloaded in bulk (as XML files) and used for research; these are the publications that were used to estimate the open access–wide biomedical literature degree of transparency. + + Extraction of indicators of transparency and reproducibility. Two reviewers (S.S. and D.G.C.I.) used a previously published protocol from Wallach and colleagues [40] to extract appropriate information from eligible articles","We extracted all metadata related to the articles of interest provided by PubMed and PMC (e.g., journal of publication, publisher, authors, affiliations, etc.). For all manually assessed articles, we extracted all social media–related data from Altmetric on May 30, 2019. Altmetric captures and tracks the use and sharing of articles across social media. For all manually assessed articles, we extracted citation counts from Crossref on May 30, 2019; for automatically assessed articles, we extracted citation counts from the NIH OCC (iCite 2.0) [37] on April 17, 2020. + + Extraction of article characteristics. For each article, we gathered the following information: PMID, PMCID, title, authors, year of publication, journal, first author country of affiliation, field of study (as provided by WOS; more information in our protocol [40]), and type of publication (e.g., research article, review article, case series, etc.) as detailed in our protocol + + We first extracted any mention of a COI or funding disclosures from all abstracts and full text articles in English. Then, for all English records with empirical data (henceforth referred to as “research articles”), we further extracted whether (a) the abstract and/or full-text of each eligible record mentions any protocol registration (whether for the whole study or part of the study), data sharing, or code sharing; and whether (b) the abstract and/or introduction of each eligible record implies any novelty (e.g., “our study is the first to identify this new protein,” etc.) or that at least part of this study represents a replication of previous work (e.g., “our study replicates previously reported results in a new population,” etc.). We further extracted whether (a) COI disclosures mentioned any conflict or not; (b) disclosures of funding mentioned any of public or private funds; and (c) whether websites included within data sharing statements were indeed accessible. In addition to the data extracted on the basis of the aforementioned protocol, for each one of the extracted indicators, we also extracted the text in which the information was identified to facilitate our work on automated extraction of these indicators. We only considered clear statements of these indicators, did not attempt to identify whether these statements were complete (e.g., did the authors report all of their conflicts of interest?) or truthful (e.g., has this finding truly never been published before?), and did not consider statements that were not included in the PubMed site or full text. Note that as per the Wallach and colleagues protocol and in a deviation from Iqbal and colleagues, which counted all studies with Supporting information as potentially containing a partial/complete protocol, in this study, we downloaded and examined all Supporting information to verify whether they indeed contain any of data, code, or protocol registration. + + Note also that we found the Novelty and Replication indicators particularly ambiguous, for which reason we have created a document with further specifications of nontrivial cases (S1 Text). After compiling this document, we proceeded to have both main reviewers (S.S. and D. G.C.I.) reassess and cross-check all of their articles, to reduce variability in labeling due to systematic reviewer differences. Information about 40 randomly identified articles was extracted by 3 reviewers (S.S., D.G. C.I., and J.D.W.). Upon studying discrepancies and clarifying aspects of the protocol, 2 reviewers (S.S. and D.G.C.I.) extracted relevant information, each from 240 articles","All English articles published between 2015 and 2018 were eligible for analysis. + + We also used OCC to extract whether an article is considered a research article or not—this is based on definitions by PubMed and considers articles such as those labeled by PubMed as journal articles, randomized controlled trials, or observational studies as research articles and articles such as those labeled as reviews, editorials, news, or comments as non-research [38]—it should be noted that in our work we identified that PubMed annotations do not always agree with PMC and that 47,631 articles labeled by PMC as “research articles” were classified as a non-research type by PubMed (and thus, iCite)—in these cases, we maintained the definition of research by iCite to remain internally consistent. We used 2018 journal impact factors made available by InCites Journal Citation Reports of WOS (the latest available at the time). We used the categorizations of PMC articles across fields of science provided by the galaxy of science developed by SciTech (author: K.W.B.) [39]. Briefly, this approach clusters similar articles together and allocates each cluster to the field of the dominant journal within that cluster. Note that using this approach, it may happen that, for example, articles from medical journals are labeled as “Chemistry” if they end up in a cluster dominated by articles from chemistry journals. Also note that this galaxy of science is based on PubMed, for which reason articles found on PMC but not on PubMed have not been given a field allocation—this also applies to OCC + + Given differences in languages between fields, it should be noted that by protocol registration, we refer to active preregistration and public availability of a study protocol, such as those found for clinical trials on ClinicalTrials.gov. + + Protocol registration statements. Briefly, we recognize registration statements using regular expressions developed to identify the following: (a) mentions of registration on ClinicalTrials.gov and other clinical trial registries (e.g., “This study was registered on ClinicalTrials.gov (NCT12345678),” etc.); (b) mentions of registration on PROSPERO (e.g., “This study was registered on PROSPERO (CRD42015023210),” etc.); (c) mentions of registration of a protocol or a study regardless of registry (e.g., “Our protocol was registered on the Chinese Clinical Trials Register (ChiCTR-IOR-12345678),” etc.); (d) mentions of research being available on a specific register regardless of registry (e.g., “Our research protocol is available on the ClinicalTrials.gov registry (NCT12345678),” etc.); (e) titles commonly associated with registration regardless of registry (e.g., “Registration Number,” “Trial registration: NCT12345678,” etc.); (f) previously published protocols of studies (e.g., “Our study protocol was previously published (Serghiou et al. 2018),” etc.); and (g) registration statements within funding disclosures (e.g., “Funded by the NIH. SPECS trial (NCT12345678),” etc.). This algorithm was developed to specifically avoid mentions of registry or registration that were not relevant (e.g., “This study enrolled patients in our hospital registry.,” etc.) or registrations with no open protocol availability (e.g., “Our protocol was approved by the IRS (registration no. 123456)”).","We adjusted a previously reported algorithm developed by N.R. [29] to identify data and code sharing and developed algorithms to identify COI disclosures, funding disclosures, and proto col registration statements. All algorithms were constructed to take a PDF file of a typical article available on PubMed and output (a) whether it has identified a statement of relevance; (b) why it is of relevance; and (c) what the exact phrase of relevance is. This flexibility was built in (a) to help integrate these algorithms into the researcher workflow by combining manual and automated inspection; (b) to allow for different definitions of the indicators by different investigators (e.g., consider only COI disclosures that were specifically included as a stand-alone statement, rather than within acknowledgments); and (c) to ease adjudication of their performance. All algorithms, including those for data and code sharing, were further adopted to work with XML files from PMC (i.e., using the NLM XML structure). Before using any of the algorithms, we preprocessed the text to fix problems with text extraction from PDF files (e.g., inappropriately broken lines, non-UTF8 symbols, etc.), remove non-informative punctuation (e.g., commas, full stops that do not represent the end of a phrase [e.g., “no. 123”], etc.), and remove potentially misleading text (e.g., references, etc.). For COI disclosures, Funding disclosures, and Protocol registration, text was not converted to lower or uppercase, we did not use stemming (e.g., we did not convert “processing” into “pro cess”), and we did not remove stop words (e.g., “and,” “or,” etc.)—even though these are frequent preprocessing steps in natural language processing, we found these nuances informative and exploitable. Text was tokenized into phrases for data and code sharing and tokenized into paragraphs for all other algorithms; for the algorithms we developed from scratch, we used a custom-made tokenizer because already available tokenizers were not found to be accurate or flexible enough. Even though we also considered using machine learning approaches to extract these indicators, we found that the current approach performed well and afforded a level of interpretability and flexibility in definitions that is not easily achievable by alternative methods. + All programming was done in R [41] and particularly depended on the packages tidyverse [42], stringr [43], and xml2 [43,44]. The programs were structured into several different kinds of functions. Helper functions (n = 7) were developed to help in creating complex regular expressions more easily and in dealing with XML files. Preprocessing functions (n = 9) were developed to correct mistakes introduced by the conversion from PDF to text and turn the text into as conducive a document to text mining as possible. Masking functions (n = 7) were developed to mask words or phrases that may induce mislabeling (e.g., in searching for funding disclosures, we are masking mentions of finances within COI disclosures to avoid mislabeling those statements as funding dis closures). Labeling functions (n = 81; 20 for COI, 39 for Funding, and 22 for Registration) used regular expressions to identify phrases of interest (described below). The regular expressions of these labeling functions also take into account transformations of the text to improve performance (e.g., labeling functions can capture both “we report conflicts of interest” and “conflicts of interest are reported”). Localization functions (n = 3) were developed to identify specific locations within the text (e.g., acknowledgments). Labeling functions that were more sensitive were only applied within small localized sections of the text to reduce mislabeling. Negation functions (n = 7) were developed to negate potentially false labels by the labeling functions. XML functions (n = 17) were developed to preprocess and take advantage of the NLM XML structure. A dictionary was constructed with all phrases and synonyms used by the regular expressions (n = 637). + + Statistical information Homogeneity between the 2 reviewers as well as with the previous reviewer (J.W.) was assessed by quantifying the frequency of identification of each feature by each reviewer. These frequencies were statistically compared using Fisher exact test of independence and calculating a 2-sided p-value—we did not use common measures of inter-rater reliability because each reviewer assessed a different random batch of articles. Validation of the automated feature extraction algorithms was evaluated using accuracy, sensitivity (= recall), specificity, PPV and NPV (PPV = precision), prevalence of the indicator, and error between estimated and true prevalence (in terms of absolute difference) (for a detailed explanation of definitions and procedures, see S4 Text). The 95% confidence interval around the diagnostic metrics was built using the nonparametric bootstrap with 5,000 iterations and taking the 2.5th and 97.5th quantiles—in building this confidence interval, we considered the variability introduced by all sampling steps (i.e., sampling 6,017 from PMC and sampling 225 from those predicted positive or negative). For the whole PMCOA, we produced univariable frequency statistics for all variables and frequency statistics of each indicator variable across years, journal, publisher, country, and field of science. The estimate of indicator prevalence was adjusted by considering the observed PPV and NPV in the test set, such that for an observed prevalence p, the adjusted prevalence was p×PPV+(1−p)×(1−NPV). p-Values were produced using nonparametric tests (Kruskal– Wallis test for continuous data and Fisher exact test for discrete). Correlation coefficients were calculated using the Spearman correlation coefficient.","Funding: This work was primarily funded by the National Institutes of Health award HHSN271201800033C to SciTech (K.B.) and METRICS (J.P.A.I). METRICS has also been supported by grants from the Laura and John Arnold Foundation. S.S. has been funded by the Department of Epidemiology and Population Health at Stanford University and as a Scholar of the Stanford Data Science Initiative. In the past 36 months, J.D.W. received research support through the Collaboration for Research Integrity and Transparency from the Laura and John Arnold Foundation and through the Center for Excellence in Regulatory Science and Innovation (CERSI) at Yale University and the Mayo Clinic (U01FD005938). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. + + Competing interests: The authors have declared that no competing interests exist. + + Any uncertainties were discussed between all 3 reviewers to maintain a homogeneous approach. Discrepancies were identified in adjudication of novelty and replication, for which reason these indicators were re-extracted for each article, and all unclear articles were discussed between reviewers. + + Conflict of interest disclosures. Briefly, our approach recognizes COI disclosures using regular expressions to identify whether a publication mentions (a) phrases commonly associated with a COI disclosure (e.g., “conflicts of interest,” “competing interests,” etc.); (b) titles of sections associated with a COI disclosure (e.g., “Conflicts of Interests,” “Competing Interests,” etc.); (c) phrases associated with COI disclosures (e.g., “S.S. received commercial benefits from GSK,” “S.S. maintains a financial relationship with GSK,” etc.); (d) phrases associated with declaration of no COI (e.g., “Nothing to disclose.,” “No competing interests.,” etc.); and (e) acknowledgment sections containing phrases with words associated with COI disclosures (e.g., “fees,” “speaker bureau,” “advisory board,” etc.). + + Funding disclosures. Briefly, our approach recognizes funding disclosures using regular expressions to identify whether a publication mentions (a) phrases commonly associated with a funding disclosure (e.g., “This study was financially supported by . . .,” “We acknowledge financial support by . . .,” etc.); (b) titles of sections associated with a funding disclosure (e.g., “Funding,” “Financial Support,” etc.); (c) phrases commonly associated with support by a foundation (e.g., “S.S. received financial support by the NIH,” etc.); (d) references to authors (e.g., “This author has received no financial support for this research.,” etc.); (e) thank you statements (e.g., “We thank the NIH for its financial support.,” etc.); (f) mentions of awards or grants (e.g., “This work was supported by Grant no. 12345,” etc.); (g) mentions of no funding (e.g., “No funding was received for this research”); and (h) acknowledgment sections containing phrases with relevant words (e.g., “funded by NIH,” etc.). This algorithm was also designed to avoid mentions of funding related to COI disclosures (e.g., “S.S. has financial relationships with GSK,” etc.).","Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pbio.3001107",1,0,1,1,1,1,1,1,1,8 +23,Synaptic pathology and therapeutic repair in adult retinoschisis mouse by AAV-RS1 transfer,supplemental material available online with this article; doi:10.1172/JCI81380DS1,"This is the therapeutic vector we expect to use in the human clinical trial (ClinicalTrials.gov NCT 02317887). + + We are mounting a human trial with the same AAV8- RS1 vector used in this murine study to probe synaptic plasticity in XLRS patients (ClinicalTrials.gov NCT02317887).","The Journal of Clinical Investigation + + jcm","AAV8-RS1 gene vector and intravitreal injections. AAV8-scRS/IRBPhRS1 delivered a self-complimentary vector genome that contained human RS1 gene-specific promoter, an IRBP enhancer, an intact human RS1 cDNA with a truncated first intron located in its authentic position between exon 1 and 2 sequences and a human β-globin 3′ UTR and polyadenylation site. A dose of 2.5 × 109 viral vector genomes per eye was administered into the right eyes of 6 Rs1-KO mice by intravitreal injection at P30. The contralateral left eye served as the control and remained untouched. After anesthetizing animals with intraperitoneal ketamine (80 mg kg–1)/xylazine (15 mg kg–1), both eyes of each mouse were dilated with 2.5% phenylephrine hydrochloride (Bausch & Lomb Inc.) and 0.5% tropicamide (Alcon Laboratories Inc.). Intravitreal injection was performed using a 5-μl Hamilton syringe with 33-gauge beveled-tip needle (Hamilton) inserted through the sclera just posterior to the limbus in the temporal side of the eye. Retinal morphology and functions were analyzed 2 months after injection. Untreated contralateral XLRS eyes served as controls. + + Immunohistochemistry. The retinas from WT and Rs1-KO mice were dissected, fixed in 4% PFA for 20 minutes, and either cut into smaller pieces for whole-mount staining or processed for either vibratome or cryosectioning by standard methods. Briefly, a high Triton X-100 (0.4%) containing PBS was used for permeating the retina pieces and a low Triton X-100 (0.1%) containing PBS (PBST) was used for retinal sections. Nonspecific binding sites in the tissue were blocked with 4% normal serum in PBST from the same host species as the labeled secondary antibody. Then primary antibodies with appropriate dilution in the serumcontaining PBST buffer were added (antibodies and their dilutions used for immunohistochemistry are given in Supplemental Table 2). Wholemount retinal tissues were incubated for 4 to 7 days, and retinal sections were incubated overnight. Subsequently, the retinal tissues or sections were washed with PBST at least 5 times for 20 minutes each time. Fluorescent secondary antibodies (Jackson ImmunoResearch Laboratories) were diluted 1:1000 in PBST and added to retinal whole-mount tissues or sections overnight or for 1 hour, respectively. Then the tissues or sections were washed in PBST and mounted. The sections were imaged on a Confocal Laser Scanning Module LSM 510 Microscope System (ZEISS). Images shown are representative of images obtained from retinas from at least 3 to 4 different animals for each genotype. + + Western blotting. Retinas from WT or RS1-KO mice were lysed in RIPA buffer, pH 7.4 (50 mM Tris-HCl, 1% NP-40, 0.25% sodium deoxycholate, 150 mM NaCl, and 1 mM EGTA supplemented with Halt protease inhibitor cocktail; Thermo Fisher Scientific). Total protein was determined based on the bicinchoninic acid (BCA) method using the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). Retinal lysates (30 μg protein) were resolved on 10% Bis-Tris gels (Thermo Fisher Scientific) followed by blotting onto PVDF membranes by wet transfer. The membranes were blocked in blocking buffer (LI-COR Biosciences) and later incubated overnight with one of the indicated primary antibodies diluted in PBS containing 0.1% Tween 20 (PBST), pH 7.5, at 4°C. Antibodies and their dilutions used for Western blot are given in Supplemental Table 2. After overnight incubation, the membranes were rinsed 3 times in PBST and incubated with one of the following appropriate IRDye-conjugated secondary antibodies: IRDye 800CW-conjugated goat (polyclonal) anti-rabbit IgG or IRDye 800CW-conjugated donkey (polyclonal) anti-goat IgG (LI-COR Biosciences); or Alexa Fluor 680–conjugated goat anti-mouse IgG (Thermo Fisher Scientific).","Electroretinography. Retinal function was evaluated by recording the full-field scotopic ERG. Mice were dark adapted overnight and prepared under red dim light. They were anesthetized with intraperitoneal ketamine (80 mg/kg) and xylazine (10 mg/kg). Pupils were dilated with topical 0.5% tropicamide and 0.5% phenylephrine HCl. Body temperature was maintained at 37°C with a heating pad. ERGs were recorded from both eyes simultaneously. Gold wire recording loops were placed on the center of the cornea with a drop of methylcellulose for corneal hydration. A gold wire attached to the mouth was used as the reference electrode, and the common electrode was placed subcutaneously in the upper back. Scotopic responses were elicited using single flashes from -4.9 to +0.6 log cd•s/m2 in 0.5-log steps (Espion E2 System, Diagnosys LLC). Responses were computer averaged, with stimulus intervals of 3 to 60 seconds depending on stimulus intensity. The a-wave amplitude was measured from prestimulus baseline to the initial trough, and b-wave amplitude was measured from the a-wave trough. Separate measurements were made on 4 animals. ERG waveforms of a representative WT and Rs1-KO mice are shown. + + Intracellular free [Ca2+]i measurement. We measured intracellular free [Ca2+]i in synaptic terminals of WT and Rs1-KO retinas. These experiments were performed under dim background illumination (mesopic range), in which calcium channels were likely to be submaximally activated. Buffers used in calcium-imaging assays are listed in Supplemental Table 1. Mouse retinae were dissected, sliced, and incubated in Hibernate-A/B27 medium (Life Technologies) with 2.5 μM Fluo-4-AM dye (Life Technologies) at room temperature for 45 minutes. Excess dye was rinsed by 5% CO2/95% O2–saturated buffer containing 3 mM Ca2+, and time-lapse [Ca2+]i imaging was performed and recorded on LSM510 confocal microscopy (ZEISS) with continuous irrigation. Rod photoreceptor synaptic terminals in-focus were identified and imaged before switching to 0 mM Ca2+ buffer containing 5 μM ionomycin (Sigma-Aldrich). After the fluorescent signals gradually decreased and stabilized, the buffer was switched to 20 mM Ca2+ with 5 μM ionomycin until the fluorescent signals reached maximum. The average intensities of fluorescence at 3 mM, 0 mM, and 20 mM Ca2+buffer (F3mM, F0mM, and F20mM) were obtained. The [Ca2+]i (nM) was calculated as follows: [Ca2+]i = Kd × F3mM – F0mM)/(F20mM – F 0mM). The average [Ca2+]i in Rs1-KO was normalized to that of WT. + + Whole-cell recordings from BCs in retinal slice. All chemicals and reagents used in this study were obtained from Sigma-Aldrich except tetrodotoxin (TTX) (Abcam). During recording, dissected retina slices were perfused with bicarbonate-buffered Ame’s media bubbled with 95% O 2 + 5% CO2 at 32°C to 34°C. Picrotoxin (50 μM), (1,2,5,6-tetrahydropyridin-4-yl) methylphosphinic acid (TPMPA) (50 μM), strychnine (0.5 μM), and TTX (500 nM) were added to the Ames’ media to block γ-amino butyric acid (GABAAR, GABACR), glycine receptors (GlyR), and voltage-gated Na+ channel–mediated currents, respectively. The pipette solution contained the following: 108 mM potassium gluconate, 32 mM KCl, 0.5 mM MgCl2, 10 mM HEPES, 2.5 mM K-EGTA, 3 mM ATP, and 1 mM GTP. The pH of the media was adjusted to 7.4 with KOH. Recordings were obtained with Axopatch 200B amplifiers (Molecular Devices). Data were digitized at 10 kHz using an ITC-18 interface (HEKA) controlled by a Dell computer running IgorPro 6.0 (WaveMetrics Inc.). MPs were recorded in whole-cell current clamp configuration immediately after break-in. Data were analyzed with custom-made software (IgorPro 6.0). + + Blots were scanned on an LI-COR Odyssey Infrared Imaging System (Model 9120, LI-COR Biosciences) and analyzed using Odyssey software. Protein levels were normalized to β-actin signal.","Animals. Male Rs1-KO mice and littermate WT controls were studied on P21–P22, P30–P32, and P90–P94. Animals were born and raised in our laboratory and derived from founders described by Zeng et al. (17). The Rs1-KO mice have been backcrossed onto C57BL/6J for more than 20 generations. They were raised in 20 lux lighting on a 12-hour light/12-hour dark cycle, with food and water available ad libitum. Animals were weaned at 3 weeks of age. All Rs1-KO mice in the study were genotyped from tail DNA to verify that they carried the Rs1-KO construct.",Statistics. Data were statistically analyzed using Prism 5 (Graph Pad). Groups’ differences were calculated by 2-tailed Student’s t test or by 1-sample t test. Results are presented as mean ± SEM. P values of less than 0.05 were considered significant.,Conflict of interest: The authors have declared that no conflict of interest exists.,"The Journal of Clinical Investigation + + jcm",1,1,1,1,1,1,1,1,1,9 +24,Comparison Between 5-Azacytidine Treatment and Allogeneic Stem-Cell Transplantation in Elderly Patients With Advanced MDS According to Donor Availability (VidazaAllo Study),ASSOCIATED CONTENT See accompanying editorial on page 3311 Protocol,CLINICAL TRIAL INFORMATION The study was registered under ClinicalTrials.gov (identifier: NCT01404741); EudraCT: 2010-018467-42.,Journal of Clinical Oncology,"METHODS Study Design and Patients In this prospective multicenter open-label phase II study, patients received initial therapy consisting of 5-aza 75 mg/m2 once a day on days 1-7 (every 28 days) for four cycles. Donor search was initiated immediately after the patient had been included. After four cycles of 5-aza, all patients with response or stable disease (SD) were treated in arm A (continued 5- aza) until disease progression or unacceptable toxicity if no HLA-compatible (10 of 10 alleles) donor had been found, or in arm B (HSCT after a reduced-intensity conditioning regimen) if an HLA-compatible donor had been identified (10 of 10 alleles). Patients assigned to HSCT could receive up to six cycles of 5-aza if transplantation could not be performed immediately. Most patients received HSCT after cycle four of 5-aza (58%), 12% after cycle 5, 6% after cycle 6, 13% after cycle 3, 6% after cycle 2, and 1% after cycle 1. The RIC regimen consisted of either busulfan (3.2 mg/kg intravenously once a day on days –7 and –6) plus fludarabine (30 mg/m2 once a day on days –7 through –3), or a sequential regimen including amsacrine (100 mg/m2 once a day), cytosinearabinoside (1,000 mg/m2 once a day), and fludarabine (30 mg/m2 once a day) on days –11 through –8 followed after a rest of 3 days by busulfan (3.2 mg/kg intravenously once a day) and fludarabine (30 mg/m2 once a day) on days –4 and –3 (FLAMSA regimen).","Populations The population of patients targeted by the clinical question of interest, that is, the primary objective, was taken to be the principal stratum in which the intercurrent events progress or death during the induction phase would not occur. That is, the clinical question of interest relates to the treatment effect of HSCT only within the principal stratum, resulting in those 108 patients being eligible for allocation to HSCT (n 5 81) or continuation of 5-aza (n 5 27; see ICH E9 (R1) addendum on estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials). The following three analysis populations were defined: (1) The safety analysis set included all patients who were included into the trial and received any 5-aza. (2) The full analysis set comprised all patients who were included into the trial and were assigned to one of the two treatment groups. This analysis population was used for the confirmatory part of the analysis. (3) The per-protocol analysis set included all patients who received the assigned treatment and completed the trial without relevant protocol violations.","Sample Size Calculation The sample size estimation was based on the percentage of patients who survived 3 years 1112 days (representing the 5- aza therapy). According to the findings of previous trials, we expected a 3-year OS rate of 50% for patients receiving an allogeneic transplantation and 30% for 5-aza treatment alone. Furthermore, it was anticipated that about 60% of the included patients would receive an allogeneic transplantation, whereas 40% of the patients would receive only 5-aza treatment. Assuming a standard deviation of 0.35, a difference of 20% in the OS rates at 3 years between the two treatment arms can be detected with a power of more than 80% and a two sided significance level of a .05. The total sample size was 110 patients assigned to one of the two treatment groups (details are given in the Protocol [online only]).","For the analysis of time-dependent exposure in time-to-event data, the two most common approaches are time-dependent Cox regression (Mantel-Byar approach) and landmarking. + + Even so there is no association between prognosis and availability of the donor expected for the 108 patients, the traditional Kaplan-Meier estimates could be criticized because HSCT did not happen at the same point in time for each patient. Therefore, even if not prespecified in the Protocol, a time-varying covariate analysis (Mantel-Byar approach) was performed for all included patients as sensitivity analysis and results can be found in event-free survival and overall survival. + + The primary end point OS at 3 years between both treat ment arms was analyzed with a two-sided Z test on the basis of the Kaplan-Meier (KM) rates by using Greenwood’s formula. + + The secondary effectiveness analyses were comparison of OS and EFS between treatment arms illustrated with KM estimates of survivor functions and testing using the unstratified log-rank test. Second, the response and relapse rates were reported for each treatment arm with two-sided Clopper-Pearson confidence intervals and were tested for difference using the chi-squared test. Gray’s test and cause-specific cumulative incidence functions for treatment-related mortality between two groups after accounting for competing risk event (non-treatment-related death) were performed. Using a Cox, HSCT was evaluated as time-dependent covariate Z(t) defined to be equal to 1 if the patient has already had an HSCT at time t; otherwise, Z(t) is equal to 0. Thus, a patient had a value Z(t) 5 0 when first eligible (ie, when included into the study) until the time HSCT was received, after which time point, the covariate Z(t) 5 1.","AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST Disclosures provided by the authors are available with this article at DOI https://doi.org/10.1200/JCO.20.02724. + + AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST Comparison Between 5-Azacytidine Treatment and Allogeneic Stem-Cell Transplantation in Elderly Patients With Advanced MDS According to Donor Availability (VidazaAllo Study) The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I 5 Immediate Family Member, Inst 5 My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center. Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).",Journal of Clinical Oncology,1,1,1,1,1,1,1,1,1,9 +25,CD19 CAR T cell product and disease attributes predict leukemia remission durability,(Supplemental Figure 1; supplemental material available online with this article; https://doi.org/10.1172/JCI125423DS1),"(ClinicalTrials.gov, NCT02028455) + + TRIAL REGISTRATION. ClinicalTrials.gov, NCT02028455. + + We have previously reported the results from a phase I safety study of the CD19 CAR T cell product to treat pediatric ALL (ClinicalTrials.gov, NCT02028455) (9). + + The study (PLAT-02) is registered at http://www.clinicaltrials.gov as NCT NCT02028455 and the main results of the study have recently been reported (9)","The Journal of Clinical Investigation + + jcm","Experimental design. Samples from the study were taken from subjects enrolled in a phase I, open-label, nonrandomized study (9)","Peripheral blood was collected from subjects following CD19 CAR T cell infusion. Mononuclear cells were isolated from peripheral blood using Ficoll-Pacque (GE Healthcare) density gradient centrifugation or CPT tube (BD Biosciences) gelbarrier centrifugation. Samples were cryopreserved in CryoStor (MilliporeSigma) until further analysis. + + Cell lines. A cell line expressing membrane-tethered CD3 epsilon– specific scFv was produced from an EBV-transformed parental lymphoblastoid cell line (TM-LCL, Pelloquin 1986) and an OKT3 mAB. K562 cells derived from human erythroleukemia cells were obtained from the European Collection of Cell Cultures through Sigma-Aldrich. CD19t-expressing K562s were provided by the lab of Stanley Riddell at Fred Hutchinson Cancer Research Center. All cell lines were authenticated by STR Profiling to set baseline on October 12, 2015, by University of Arizona Genetics Core.",We analyzed 43 pediatric and young adult subjects participating in a phase I trial of defined composition CD19 CAR T cells.,"Statistics. Statistical analyses were performed using Prism (GraphPad), R or SAS software. Cox regression and survival curves were adjusted for multiparameter analyses. Results with a P value less than 0.05 were evaluated as statistically significant. Medians between groups were compared using a Mann-Whitney test. A Welch 2-sample t test was performed when comparing differences in mean of SM phenotype to FP phenotype. A pairwise Spearman correlation test was used to calculate the Spearman’s rho and P values comparing SM to FP phenotype. Odds ratios and their confidence intervals were calculated in using the Baptista-Pike method in Prism and a Fisher’s exact test was used to compute the significance of the difference in odds. To evaluate zero values in the contingency tables, 0.5 was added to all quadrants of the table","FUNDING. Partial funding for this study was provided by a Stand Up to Cancer and St. Baldrick’s Pediatric Dream Team Translational Research Grant (SU2C-AACR-DT1113), R01 CA136551-05, an Alex Lemonade Stand Phase I/II Infrastructure Grant, a Conquer Cancer Foundation Career Development Award, the Washington State Life Sciences Discovery Fund, the Ben Towne Foundation, the William Lawrence & Blanche Hughes Foundation, and Juno Therapeutics Inc., a Celgene Company. + + Conflict of interest: DL is an employee of, and has an equity interest in, Juno Therapeutics Inc. MCJ has received consulting fees and grants from and is an inventor of patents licensed to Juno Therapeutics Inc., in which he has an equity interest. Seattle Children’s Hospital received funds from Juno Therapeutics Inc + + Acknowledgments + Partial funding for this study was provided by a Stand Up to Cancer and St. Baldrick’s Pediatric Dream Team Translational Research Grant (SU2C-AACR-DT1113), R01 CA136551-05, an Alex Lemonade Stand Phase I/II Infrastructure Grant, a Conquer Cancer Foundation Career Development Award, the Washington State Life Sciences Discovery Fund, the Ben Towne Foundation, the William Lawrence and Blanche Hughes Foundation, and Juno Therapeutics Inc., a Celgene Company.","The Journal of Clinical Investigation + + jcm",1,1,1,1,1,1,1,1,1,9 +26,Systematic evaluation of environmental factors: persistent pollutants and nutrients correlated with serum lipid levels,"Supplementary Data Supplementary data are available at IJE online. + + More details can be found in the Supplementary Data (available at IJE online)",,,"We used linear regression to correlate each environmental chemical factor to triglycerides, LDL-C and HDL-C adjusting for age, age2 , sex, ethnicity, socio-economic status and body mass index. Final estimates were adjusted for waist circumference, diabetes status, blood pressure and survey. Multiple comparisons were controlled for by estimating the false discovery rate and significant findings were tentatively validated in an independent survey. + + Using a categorization provided by NHANES, we binned these factors into 26 ‘classes’ of related factors (Figure 1A, Supplementary Table 1, available as Supplementary Data at IJE online).","We downloaded all available NHANES laboratory and questionnaire data for 1999–2000, 2001–02, 2003–04 and 2005–06 surveys. Laboratory data included serum and urine measures of environmental factors and clinical measures including lipid levels. + + We analysed factors that were a direct measurement of an extrinsic environmental factor (e.g. amount of pesticide or heavy metal in urine or blood). We did not consider intrinsic physiological measures (e.g. red blood cell count or albumin) or responses to questionnaires except for sensitivity analyses. We used three of the four surveys (1999–2000, 2001– 02, 2005–06) for testing for multiple environmental factors in association with lipid levels and reserved one survey (2003–04) for validation testing of findings. As each survey had a different set and number of environ mental factors measured, we selected 2003–04 as the validation survey as it had the largest number of shared factors with each of the other surveys, maximizing the number of factors that could be validated. We eliminated 119 factor variables from our analyses whose majority of observations were under the National Centers for Health Statistics (NCHS) documented limit of detection or, for categorical factor variables, varied little. Specifically, we omitted continuous variables if 99% of the observations were deemed below the thresh old limit of detection. For categorical factor variables, we omitted those that had 99% of the observations belonging to one category. After the elimination of these 119 such factor variables, we were left with 169 variables from the 1999–2000 survey, 182 from 2001–02, 96 from 2005–06 and 258 from the 2003–04 (validation) survey. Next, we selected factors from each survey that were present in the validation survey. This left us with a total of 188 unique factors that could be validated, of which 126 were from the 1999–2000 survey, 157 from 2001–02 and 65 from 2005–06. + + Different environmental factors were measured in varying numbers of participants: 109–3610 (median 938), 101–3388 (median 896) and 222–7485 (median 1958) individuals for triglyceride, LDL-C and HDL-C levels, respectively (Figure 1B). + + Serum triglyceride levels were measured in the morning after 48.5 h of fasting. LDL-C levels were derived from total cholesterol and direct HDL-C measurements were derived from the Friedewald calculation.","Each survey is an independent, non-overlapping sampling of participants representative of the general US population + + Individuals are selected randomly based on their demographic characteristics for the complex, stratified survey.","Correlation between factors We computed the pair-wise partial Pearson correlation coefficient between each environmental factors using the test and validation surveys separately, adjusting for age and BMI in addition to creatinine levels for urinary measures. Since we had 188 environmental factors, the total number of possible pairs of factors (and correlations) equals 17 578 (188 187/2); however, 4455 (25%) of all possible pairs of factors were not measured in the same overlapping individuals and, as a result, their correlations could not be computed. We assessed correlations between factors in the test and validation cohorts separately and compared their relative strength by estimating percentiles of the entire distribution of correlations. We also compared correlations within classes (or ‘intra-class’ correlation) and between classes (‘inter-class’) correlations. For factors measured in more than one of the test surveys, their coefficient was combined using a meta-analytic random effects method.","Funding The National Library of Medicine (grant numbers T15 LM 007033 and R01 LM009719); National Institute of General Medical Sciences (grant number R01 GM079719); National Institutes of Health Clinical and Translational Science Award (UL1 RR025744); Lucile Packard Foundation for Children’s Health, Howard Hughes Medical Institute. + + Conflict of interest: None declared.",International Journal of Epidemiology,1,0,0,1,1,1,1,1,1,7 +27,Meta-analyses in environmental and occupational health,The association between mobile phones and cancer has been assessed in 12 meta-analyses published between 2006 and 2014 (references in the online supplementary appendix).,,,"The search was tailored to capture >98% of the 53 meta-analysis articles ever published by Occupational and Environmental Medicine. The search string: (Meta-analysis [sb]) OR meta-analysis [ti] AND (work [ti] OR worker* [ti] OR working [ti] OR occupation* [ti] OR pesticide* [ti] OR dust [ti] OR hydrocarbon [ti] OR chromium [ti] OR cement [ti] OR employment [ti] OR job [ti] OR trichloroethylene [ti] OR solvent* [ti] OR pilots [ti] OR phone [ti] OR phones [ti] OR telephones [ti] OR particulate [ti] OR DDT [ti] OR professional [ti] OR by-product* [ti] OR benzene [ti] OR exposure [ti] OR electric [ti] OR industry [ti] OR voltage [ti] OR pollut* [ti] OR hairdresser* [ti] OR ‘passive smoking’ [ti] OR ‘environmental tobacco’ [ti]) captured 52 meta-analyses. It did not capture one Occupational and Environmental Medicine meta-analysis on effects of exercise on low-back pain recurrences, but ‘exercise’ was excluded because the vast majority of exercise meta-analyses would not be relevant to occupational and environmental medicine. Some additional search terms were included for specific exposures of high interest to the field that did not happen to be included among the 53 index meta-analyses: OR cadmium [ti] OR arsenic [ti] OR copper [ti] OR lead [ti] OR ‘heavy metal’ [ti] OR dioxin* [ti] OR biphenyl [ti] OR chlorpyrifos [ti] OR toluene [ti] OR herbicide [ti]. These additional terms increased the yield of retrieved papers by only 9%. Therefore, it is likely that adding more exposure-specific terms would only yield few additional meta-analyses. From the PubMed (inception in January 1996 to 2 February 2017), all articles that had an abstract were screened further. Papers that included any quantitative syntheses and were pertinent to environmental and occupational medicine or health were eligible. Pooled analyses were also eligible. Any environ mental or occupational risks, interventions and outcomes were eligible. Meta-synthesis of qualitative data, and studies on diet, infectious and lifestyle exposures (eg, exercise, active smoking) were excluded unless they had an occupational focus. Eligible meta-analyses with final publication dates in 2015 were also examined in more depth. Information was extracted on country of origin (first listed affiliation, when multiple countries were listed), whether they considered randomised (intervention) trials, whether they included individual-level data and whether any industry authors or authors from consultancy firms were included. Finally, to probe an example of overlapping meta-analyses on the same topic, all meta-analyses retrieved on the association between mobile phones and cancer were assessed and compared regarding their year, number of studies, eligibility criteria and conclusions. This topic was chosen because it has substantial public health impact and, furthermore, it has attracted large public attention.","Results The PubMed search yielded 1777 items that had an abstract. Of those, 1311 were considered possibly eligible based on screening the title and, of those, 1251 were considered eligible after perusing the abstract and, whenever necessary, the full text. Overall, 163 eligible meta-analyses had been published in 2015 (vs 16 in 1995). Among the 163 eligible meta-analyses published in 2015, the most common country primary affiliation was China (n=49), followed at a distance by the USA (n=19), Australia (n=12), the UK (n=10), Canada (n=7) and Finland (n=7). Only 16/163 (9.8%) meta-analyses included randomised trials on interventions (15/16 on humans). Overall, 13/163 (8.0%) papers used individual-level data, including 3 papers from the ESCAPE group investigating long-term effects on human health of exposure to air pollution in Europe, 2 from the individual-participant data meta-analysis in working populations consortium, 3 meta-analyses that used published group data but had also collected and analysed some individual-level data and 5 other pooled analyses combining different observational data sets. Only 1 of the 163 papers (0.6%) was authored by industry authors and none of the 150 papers had authors from consultancy firms. + + These are summarised in table 1. With different eligibility criteria (eg, what tumours are included, design/quality criteria, minimum required follow-up for latency) and timing of their literature searches, they included anywhere between 2 and 47 studies. The meta-analyses also differ in their conclusions and emphasis. While some differences would be expected over time, as new studies become available, in this example some show increased risk, in particular with long-term use (≥10 years) and especially in ipsilateral gliomas, while others focus mostly on interpreting the results as consistent with null effect. The largest effect sizes come from two meta-analyses from the academic authors who originally proposed a causal link in their primary studies and in a meta-analysis from China (relative risk 2.27, 95%CI 1.81 to 2.85 for low-grade glioma and long-term use). Further investigation of the differences found is beyond the scope of this paper.",,,"Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. + + Competing interests None declared.","Provenance and peer review Commissioned; internally peer reviewed. + + OEM",1,0,0,1,1,0,0,1,1,5 +28,"Safety of Adalimumab in Pediatric Patients with Polyarticular Juvenile Idiopathic Arthritis, Enthesitis-Related Arthritis, Psoriasis, and Crohn's Disease",Methods and results from these studies are published (briefly summarized in Table I),"Safety findings from 7 AbbVie-sponsored, global clinical trials of adalimumab (subcutaneous injection; 40 mg/0.8-mL or 20 mg/0.4-mL formulation) in pediatric patients were included in this analysis: 4 studies of rheumatic disease, including pJIA (National Clinical Trial [NCT] no. 00048542, NCT00775437, NCT00690573) and ERA (NCT01166282); 1 study of pediatric psoriasis (NCT01251614); and 1 study of pediatric CD (NCT00409682), including its ongoing openlabel extension (NCT00686374).","Jpeds + + the journal of pediatrics","Study design This analysis included data from 7 global, randomized, and open-label AbbVie-sponsored clinical trials of adalimumab and their open-label extensions conducted between September 2002 and December 31, 2015 (cutoff date for ongoing studies). Patients who received ≥1 dose of adalimumab subcutaneously were included. Adverse events that occurred after the first dose of adalimumab and up to 70 days (5 half-lives) after the last dose were reported and events per 100 patient-years were calculated. + + Growth/height analyses were performed in 2 patient populations. In the pJIA study,3 patients were pooled and divided into 2 groups based on their baseline height percentile (<33 or >33) on the Centers for Disease Control and Prevention growth chart.17 Height and body mass index and improvement of pJIA signs and symptoms were evaluated. In the CD study,6 height velocity z scores based on bone age were calculated using reference standard height velocity tables according to the following equation: (observed height velocity – median height velocity for age and sex)/SD of the median. Patients with height velocity z score ≤–1.0 were considered to have growth delay at baseline.18 Change from baseline in height velocity z score was evaluated in patients with and without growth delay at baseline.","This analysis included all AEs that occurred after the first dose of adalimumab and up to 70 days (5 half-lives) after the last dose (ie, all treatment-emergent AEs); data are presented through December 31, 2015. An analysis of infections by concomitant corticosteroid use also was conducted.AEs were coded using the Medical Dictionary for Regulatory Activities, version 18.1. AEs of special interest included infections and serious infections, opportunistic infections (due to bacterial, mycobacterial, invasive fungal, viral, parasitic, or other opportunistic pathogens),16 malignancies, and hypersensitivity reactions.Serious adverse events (SAEs) were defined as events that were fatal or immediately life-threatening; required inpatient or prolonged hospitalization; resulted in persistent or significant disability/incapacity, congenital anomaly, or spontaneous or elective abortion; or required medical or surgical intervention to prevent a serious outcome.","This analysis included 577 pediatric patients (Figure 1; available at www.jpeds.com), representing 1440.7 PY of exposure (Table II). A total of 274 patients with JIA (806.9 PY), including 228 patients representing 662.3 PY in 3 pJIA studies and 46 patients representing 144.5 PY in the pediatric ERA study, 111 patients with pediatric psoriasis (121.5 PY), and 192 patients with pediatric CD (512.3 PY), were included in the analysis. Baseline characteristics for these pediatric populations are summarized in Table II.","AEs are presented as the number and proportion of patients experiencing each event and as the number of events and rate of events per 100 patient-years (PY). A Kaplan–Meier analysis was used to evaluate the time to first serious infectious event for each indication. Height and growth analyses were reported as observed data. For the CD growth analyses, the Wilcoxon rank sum test was used to compare change from baseline (2-sided, 5% level of significance).","Funded by Abbvie. Abbvie contributed to the design and was involved in the collection, analysis, and interpretation of the data and in the writing, review, and approval of this article. G.H. has received grants from AbbVie, Chugai, Novartis, Pfizer, and Roche. M.S. has received grants from/was involved in clinical trials from AbbVie, Almirall, Astellas, Leo Pharma, and Pfizer; has served as a consultant for AbbVie, Almirall, Boehringer Ingelheim, Lilly, and Pfizer; gave lectures for AbbVie and Pfizer; and traveled with AbbVie, Pfizer, and Leo Pharma to meetings (fees were paid directly to the institution for these activities). D.A., J.K., J.A., A.L., D.W., and R.T-P. are employees of AbbVie and may own AbbVie stock and stock options. C.W. was an employee of AbbVie and may own AbbVie stock and stock options. J.H. serves on advisory boards for Janssen, AbbVie, and UCB and is a consultant for Takeda, Boehringer Ingelheim, Lilly, Celgene, Receptos, Merck, Roche, and AstraZeneca. + + The safety analysis also is limited by the paucity of placebo-controlled studies, in part due to the withdrawal design of several studies,3,4 and that non–AbbViesponsored clinical trials were not included, such as the controlled SYCAMORE trial.","Jpeds + the journal of pediatrics",1,1,1,1,1,1,1,1,1,9 +29,"Data sharing and reanalysis of randomized controlled trials in + leading biomedical journals with a full data sharing policy: survey + of studies published in The BMJ and PLOS Medicine","Additional material is published online only. To view please visit the journal online. + + Data sharing: The code is shared on the Open Science Framework (https://osf.io/jgsw3/). All datasets that were used are retrievable following the instruction of the original papers. + + Supplementary information: e-Table 1: results of reanalyses for three ineligible studies published in The BMJ after the policy but submitted before","TRIAL REGISTRATION Open Science Framework osf.io/c4zke. + + Methods The methods were specified in advance. They were documented in a protocol submitted for review on 12 November 2016 and subsequently registered with the Open Science Framework on 15 November 2016 (https:// osf.io/u6hcv/register/565fb3678c5e4a66b5582f67).",BMJ,"DESIGN Survey of published RCTs + + SETTING PubMed/Medline. + + Reproducibility When data were available, a single researcher (FN) carried out a reanalysis of the trial. For each study, analyses were repeated exactly as described in the published report of the study. Whenever insufficient details about the analysis was provided in the study report, we sought clarifications from the trial investigators. We considered only analyses concerning the primary outcome (or outcomes, if multiple primary outcomes existed) of each trial. Any discrepancy between results obtained in the reanalysis and those reported in the publication was examined in consultation with a statistician (CS). This examination aimed to determine if, based on both quantitative (effect size, P values) and qualitative (clinical judgment) consideration, the discrepant results of the reanalysis entailed a different conclusion from the one reported in the original publication. Any disagreement or uncertainty over such conclusions was resolved by consulting a third coauthor with expertise in both clinical medicine and statistical methodology (JPAI). If, after this assessment process, it was determined that the results (and eventually conclusions) were still not reproduced, CS independently reanalyzed the data to confirm such a conclusion. Once the “not reproduced” status of a publication was confirmed, FN contacted the authors of the study to discuss the source of the discrepancy. After this assessment procedure, we classified studies into four categories: fully reproduced, not fully reproduced but same conclusion, not reproduced and different conclusion, and not reproduced (or partially reproduced) because of missing information.","Data extraction and datasets retrieval A data extraction sheet was developed. For each included study we extracted information on study characteristics (country of corresponding author, design, sample size, medical specialty and disease, and funding), type of intervention (drug, device, other), and procedure to gather the data. Two authors (FN and PJ) independently extracted the data from the included studies. + + One reviewer (FN) was in charge of retrieving the IPD for all included studies by following the instructions found in the data sharing statement of the included studies. More specifically, when data were available on request, we sent a standardized email (https://osf.io/h9cas/). Initial emails were sent from a professional email address (fnaudet@stanford.edu), and three additional reminders were sent to each author two or three weeks apart, in case of non-response.","RCTs that had been submitted and published by The BMJ and PLOS Medicine subsequent to the adoption of data sharing policies by these journals. + + 37 RCTs (21 from The BMJ and 16 from PLOS Medicine) published between 2013 and 2016 met the eligibility criteria. 17/37 (46%, 95% confidence interval 30% to 62%) satisfied the definition of data availability and 14 of the 17 (82%, 59% to 94%) were fully reproduced on all their primary outcomes. Of the remaining RCTs, errors were identified in two but reached similar conclusions and one paper did not provide enough information in the Methods section to reproduce the analyses. + + Eligibility criteria We surveyed publications of RCTs, including cluster trials and crossover studies, non-inferiority designs, and superiority designs, that had been submitted and published by The BMJ and PLOS Medicine subsequent to the adoption of data sharing policies by these journals. + + Search strategy and study selection We identified eligible studies from PubMed/Medline. For The BMJ we used the search strategy: “BMJ”[jour] AND (“2013/01/01”[PDAT]: “2017/01/01”[PDAT]) AND Randomized Controlled Trial[ptyp]. For PLOS Medicine we used: “PLoS Med”[jour]) AND (“2014/03/01”[PDAT]: “2017/01/01”[PDAT]) AND Randomized Controlled Trial[ptyp]. Two reviewers (FN and PJ) performed the eligibility assessment independently + + More specifically, the eligibility assessment was based on the date of submission, not on the date of publication. When these dates were not available we contacted the journal editors for them.","Statistical analyses We computed percentages of data sharing or reproducibility with 95% confidence intervals based on binomial approximation or on Wilson score method without continuity correction if necessary.14 For the purposes of registration, we hypothesized that if these data sharing policies were effective they would lead to more than 80% of studies sharing their data (ie, the lower boundary of the confidence interval had to be more than 80%). High rates of data sharing resulting from full data sharing policies should be expected. On the basis of experience of explicit data sharing policies in Psychological Science, 15 however, we knew that a rate of 100% was not realistic and judged that an 80% rate could be a desirable outcome. When data were available, one researcher (FN) performed reanalyses using the open source statistical software R (R Development Core Team), and the senior statistician (CS) used SAS (SAS Institute). In addition, when authors shared their codes (in R, SAS, STATA (StataCorp 2017) or other), these were checked and used. Estimates of effect sizes, 95% confidence intervals, and P values were obtained for each reanalysis.","Difficulties identified included problems in contacting corresponding authors and lack of resources on their behalf in preparing the datasets. In addition, there was a range of different data sharing practices across study groups. + + Disagreements were resolved by consensus or in consultation with a third reviewer (JPAI or DM). + + Disagreements were resolved by consensus or in consultation with a third reviewer (JPAI). + + Difficulties in getting and using data or code and performing reanalyses We noted whether the sharing of data or analytical code, or both, required clarifications for which on 5 January 2024 by guest. Protected by copyright. http://www.bmj.com/ BMJ: first published as 10.1136/bmj.k400 on 13 February 2018. Downloaded from RESEARCH the bmj | BMJ 2018;360:k400 | doi: 10.1136/bmj.k400 3 additional queries had to be presented to the authors to obtain the relevant information, clarify labels or use, or both, and reproduce the original analysis of the primary outcomes. A catalogue of these queries was created and we grouped similar clarifications for descriptive purposes to generate a list of some common challenges and to help tackle these challenges pre-emptively in future published trials + + Patient involvement We had no established contacts with specific patient groups who might be involved in this project. No patients were involved in setting the research question or the outcome measures, nor were they involved in the design and implementation of the study. There are no plans to involve patients in the dissemination of results, nor will we disseminate results directly to patients. + + Competing interests: All authors have completed the ICMJE uniform disclosure form at http://www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare that (1) No authors have support from any company for the submitted work; (2) FN has relationships (travel/accommodations expenses covered/ reimbursed) with Servier, BMS, Lundbeck, and Janssen who might have an interest in the work submitted in the previous three years. In the past three years PJ received a fellowship/grant from GSK for her PhD as part of a public-private collaboration. CS, IC, DF, DM, and JPAI have no relationship with any company that might have an interest in the work submitted; (3) no author’s spouse, partner, or children have any financial relationships that could be relevant to the submitted work; and (4) none of the authors has any non-financial interests that could be relevant to the submitted work. + + Funding: METRICS has been fundedby Laura and John Arnold Foundation but there was no direct funding for this study. FN received grants from La Fondation Pierre Deniker, Rennes University Hospital, France (CORECT: COmité de la Recherche Clinique et Translationelle) and Agence Nationale de la Recherche (ANR), PJ is supported by a postdoctoral fellowship from the Laura and John Arnold Foundation, IC was supported by the Laura and John Arnold Foundation and the Romanian National Authority for Scientific Research and Innovation, CNCS–UEFISCDI, project number PN-II-RU-TE-2014-4-1316 (awarded to IC), and the work of JI is supported by an unrestricted gift from Sue and Bob O’Donnell. The sponsors had no role concerning preparation, review, or approval of the manuscript.",BMJ,1,1,1,1,1,1,1,1,1,9 +30,Effects of a Preschool Intervention on Physical Activity and Body Composition,,Trial registration ISRCTN: ISRCTN94022291.,"Jpeds + + the journal of pediatrics + + ISRCTN","The protocol for the ABC trial, including further details on the design, sample size, methods, and intervention specifics, has been published previously. + This single site, 3-arm, cluster-randomized controlled trial performed in Ottawa, Canada, evaluated the efficacy of the ABC intervention to increase physical activity with childcare centers as the unit of measurement (clusters; Figure 1; available at www.jpeds.com) + + Eighteen childcare centers (clusters) were randomly assigned to 1 of 3 groups: (1) CC (n = 6), (2) CC + HOME (n = 6), or (3) COM group (n = 6). + To take into account possible seasonal variation and its effects on physical activity, the trial was stratified by season: 8 sites were randomized in the spring of 2013 (3 CC, 3 CC + HOME, and 2 COM), 7 in the fall of 2013 (2 CC, 2 CC + HOME, and 3 COM), and 3 in the fall of 2014 (1 CC, 1 CC + HOME, and 1 COM). To ensure adequate allocation concealment, the computer-generated randomization sequence was kept centrally by a data manager not affiliated with this trial. Given the nature of the study, center staff were not blinded; however, the preschoolers were likely unaware of their center’s allocation. All outcomes were measured objectively and the investigators and analyst were blinded to center assignment. + + The ABC intervention, focusing on the childcare center as the unit of randomization (cluster) and children as unit of analysis, was designed to be delivered by the center-specific providers. The study design took into account the socioecological conceptual model of health promotion, acknowledging the powerful influence of the setting and place on behavior and that children’s social and physical environments influence their activity levels. The intent was to meet the age-related, Canadian physical activity guidelines recommendations by facilitating at least 180 minutes of total physical activity per day at any intensity for 3- and 4-year-old children, and to progress to at least 60 minutes per day of moderate-tovigorous intensity physical activity (ie, activities that increase heart rate and breathing) for children 5 years of age. In addition, the intervention aimed to reduce sedentary time as recommended. Briefly, the childcare-specific intervention, which was based on an evidence-based train-the-trainer approach used with Healthy Opportunities for Preschoolers, consisted of multiple components. + + Bimonthly support or “booster” sessions took place during regular hours within intervention centers. These included (1) in-center, ABC trainer-guided, structured physical activity sessions engaging both preschoolers and providers, (2) goal setting and iterative action planning regarding intervention delivery, and (3) performance monitoring and feedback related to implementation successes and where relevant overcoming barriers, troubleshooting, and problem solving. + + Study design For this cluster randomized controlled trial, 18 childcare centers were randomly allocated in equal numbers to the typical curriculum comparison group, childcare intervention alone (CC), or childcare intervention with parental involvement.","At baseline, a questionnaire was used to gather information on sociodemographics and trial assessments were conducted by trained staff (Figure 2; available at www.jpeds.com). + Both physical activity and sedentary time were measured using omnidirectional Actical accelerometers (Mini Mitter Co., Inc, Bend, Oregon). These devices capture all movement intensities (light, moderate, vigorous) as well as step counts and counts per minute. According to ABC trial-based standard operating procedures, these activity monitors were worn during all waking hours (except when engaged in water-based activities) for 7 days at each measurement time point. Time spent at various intensities of movement (eg, sedentary, light, moderate to vigorous) were derived using a 15-second epoch and the cut points by Adolph et al. for preschool-aged children as recommended. Physical activity and sedentary time was reported separately for total hours (childcare hours + outside childcare hours), childcare center only hours, and outside center hours. Weekdays with at least 4 hours of accelerometer wear time during childcare center hours (from 8:30 a.m. to 4:30 p.m.) and at least 1 hour of weartime during outside childcare hours were included. Weekend days with at least 5 hours of wear time were included. The 5 hours of accelerometer wear time per day follows the accepted standards within this population. To make days with different amounts of wear time more comparable, physical activity and sedentary time data are reported per hour of wear time. Children with at least 3 days of valid data were included in the analysis. The mean of valid days was reported. Height was measured with a portable stadiometer (Seca GmBH & Co Kg, Hamburg, Germany) and weight with a portable digital scale (ProFit Precision Personal Health Scale, UC- 321, A&D Medical, San Jose, California). Body mass index was calculated as weight (in kilograms) divided by height (in meters squared). Body composition (fat free mass and body fat percentage) was assessed using a validated bioelectrical impedance analyzer (RJL Quantum IV, RJL Systems, Clinton Township, Michigan). + + Accelerometers were used to asses physical activity and sedentary time, and body composition was measured by bioelectrical impedance.","As outlined in our protocol, all licensed childcare centers enrolling ≥20 children between 3 and 5 years of age were eligible. A letter of invitation was mailed to all qualified childcare directors with follow-up by phone. The first 18 centers that expressed an interest and met all eligibility criteria were randomized. + All 3- to 5-year-old children enrolled in participating centers with English- or French-speaking parents who reported planning to stay at their respective childcare centers for at least 6 months, were contacted for recruitment + + 18 childcare centers","Statistical Analyses + As previously published, sample size calculations were based on calculations that 6 centers with 15 preschoolers per group is required to achieve power of 80%, to detect a 15-minute difference in moderate-to-vigorous physical activity between the groups with the 5% probability of a type 1 error. Baseline characteristics were analyzed with c2 test (categorical) or linear regression model with prespecified analysis of variance style contrast (continuous).Actical data were processed using a combination of SAS (Version 9.2; Cary, North Carolina) and Stata/ SE 13.1 (StataCorp LP, College Station, Texas). Data reduction procedures were performed in accordance with previous work. To evaluate the effects of the intervention on our primary outcome measures, we followed the intention-totreat principle. To account for the cluster randomized design, a linear mixed effects model with a random effect for center was used to compare change in primary and secondary outcomes from baseline to 6 months. Furthermore, we performed a sensitivity analysis to investigate the influence of dropouts or missing data on primary outcomes. Our sensitivity analysis included a sample where all children with at least 1 hour of physical activity data from at least 1 day were included (n = 128). All mixed models were based on complete cases, adjusted for baseline value, and robust standard errors were reported. P < .05 was considered statistically significant. All tests were performed with Stata/SE 13.1 (StataCorp LP). + + Results Linear mixed model regression analyses showed no differences between the CC, the childcare intervention with parental involvement, and the comparison groups in changes from baseline to 6 months in total physical activity (P for time × group interaction = .665) or moderate-to-vigorous physical activity (P for time × group interaction = .164)","There are some limitations to our study that should be considered. We may not have had sufficient power to detect a significant difference in primary outcomes. Our final analyses included fewer than our planned sample of 15 preschoolers per center, because the province of Ontario adopted full day junior kindergarten after the recruitment of our first cohort of 6 centers. Subsequently, a number of children moved on to elementary school before study completion. Additionally, to compare the CC and CC + HOME arms, we needed to capture the time within and outside of the childcare environment. Subsequently, we selected the period between 8:30 a.m. and 4:30 p.m. to represent childcare hours, because this coincided with the timeframe when the majority of the children were in attendance. It is possible that there were a few children for whom this window captured slightly more or slightly less time in the childcare center than in reality. Moreover, as mentioned, the robustness of the engagement and adherence to the intervention (childcare providers and parents) is disputable and a common predicament in “real-world” settings. Although we offered additional training for new or replacement childcare providers, staff attrition may have also contributed to the suboptimal provision of the intervention. Children in our study were already quite active at baseline (98% of 3- and 4-year-olds were meeting physical activity guidelines), which could have created a ceiling effect in their daily physical activity. High baseline total physical activity could also indicate that more active children and childcare centers were more likely to participate in this study. Finally, there was a significant time effect, where all groups increased their physical activity and thus the Hawthorne effect (reactivity) and typical increases in fundamental movement skills are also possibilities, which may have contributed to the null findings. Our 6-month preschool intervention program delivered by childcare providers in licensed childcare settings, with or without the addition of a parent-facilitated home physical activity promotion, seemed to have no significant impact on daily physical activity, sedentary time, or adiposity. + + Funded by the Canadian Institutes of Health Research (CIHR – MOP 123326). The authors declare no conflicts of interest.","Jpeds + + the journal of pediatrics",0,1,1,1,1,1,1,1,1,8 +31,"Evolution of Reporting P Values in the Biomedical Literature, + 1990-2015","Supplemental content at jama.com + + See the Appendix in the Supplement for further details of the structure of the generated datasets of Pvalues, the process followed to homogenize Pvalue expressions, and technical issues and validation of the results yielded by the automated text mining vs in-depth manual extraction of information.","Full Dataset: The full records of P values extracted from PubMed and PMC, with their metadata (doi:10 .7910/DVN/6FMTT3), are available at https: //dataverse.harvard.edu/dataset.xhtml ?persistentId=doi:10.7910/DVN/6FMTT3.",JAMA,"Automated text-mining analysis was performed to extract data on P values reported in 12 821 790 MEDLINE abstracts and in 843 884 abstracts and full-text articles in PubMed Central (PMC) from 1990 to 2015. + + A random sample of 1000 MEDLINE abstracts was manually assessed for reporting of P values and other types of statistical information; of those abstracts reporting empirical data, 100 articles were also assessed in full text. + + Automated text-mining analysis was performed on the entire MEDLINE database since 1990 and on a random sample of the PubMed Central (PMC) database. Both databases are freely accessible to the public. MEDLINE is the free bibliographic data base of life sciences and biomedical information compiled by the US National Library of Medicine. PMC is a free repository of publicly accessible full-text scholarly articles from biomedical and life sciences journals. + + Of those 796, 100 were randomly selected and examined to determine whether the full text of the articles clearly specified the primary outcome(s) of interest and reported any P values, effect sizes, CIs, Bayesian methods or statistics, false-discovery rates (q-statistics),or sample size/ power calculations.","For the MEDLINE text mining, all P value data were extracted from the MEDLINE archives from January 1, 1990, to June 4, 2015, for all items with article meta-data that have an abstract. The same methodology was applied to a random sample of the PMC database (downloadedMarch 20, 2015) consisting of full-text articles with an abstract. + + Data were manually extracted in duplicate from a random sample of 1000 abstracts drawn from MEDLINE articles with abstracts. Two reviewers (J.D.W., A.H.T.L.) extracted data independently and then compared data extractions;","Reporting of P values in 151 English-language core clinical journals and specific article types as classified by PubMed also was evaluated + + RESULTS Text mining identified 4 572 043 P values in 1 608 736 MEDLINE abstracts and 3 438 299 P values in 385 393 PMC full-text articles. + + Besides the analysis including all MEDLINE abstracts and PMC articles with an abstract, specific predetermined categories of articles that may be most important for clinical medicine were examined separately. These categories were the subset of the Abridged Index Medicus journals (a list of 151 English-language core clinical journals [https://www.nlm.nih.gov/bsd/aim.html]) as well as the articles included in the categories clinical trial, randomized controlled trial, meta-analysis, and review that were classified as such by PubMed. The “core clinical journals” category includes articles of various study designs that are all published in these journals. To avoid overlap in the results, data in the clinical trials category exclude randomized clinical trials, and data in the reviews category exclude meta-analyses. + + Of the 1000 abstracts, 796 were from articles reporting empirical data and, based on the abstract, reviewers felt that reporting of Pvalues of effects in the full text could not be excluded; the others were from expert reviews or case reports where such reporting could reasonably be excluded","Reporting of P values in abstracts increased from 7.3% in 1990 to 15.6% in 2014. In 2014, P values were reported in 33.0% of abstracts from the 151 core clinical journals (n = 29 725 abstracts), 35.7% of meta-analyses (n = 5620), 38.9% of clinical trials (n = 4624), 54.8% of randomized controlled trials (n = 13 544), and 2.4% of reviews (n = 71 529). The distribution of reported P values in abstracts and in full text showed strong clustering at P values of .05 and of .001 or smaller. Over time, the “best” (most statistically significant) reported P values were modestly smaller and the “worst” (least statistically significant) reported P values became modestly less significant. Among the MEDLINE abstracts and PMC full-text articles with P values, 96% reported at least 1 P value of .05 or lower, with the proportion remaining steady over time in PMC full-text articles. In 1000 abstracts that were manually reviewed, 796 were from articles reporting empirical data; P values were reported in 15.7% (125/796 [95% CI, 13.2%-18.4%]) of abstracts, confidence intervals in 2.3% (18/796 [95% CI, 1.3%-3.6%]), Bayes factors in 0% (0/796 [95% CI, 0%-0.5%]), effect sizes in 13.9% (111/796 [95% CI, 11.6%-16.5%]), other information that could lead to estimation of P values in 12.4% (99/796 [95% CI, 10.2%-14.9%]), and qualitative statements about significance in 18.1% (181/1000 [95% CI, 15.8%-20.6%]); only 1.8% (14/796 [95% CI, 1.0%-2.9%]) of abstracts reported at least 1 effect size and at least 1 confidence interval. Among 99 manually extracted full-text articles with data, 55 reported P values, 4 presented confidence intervals for all reported effect sizes, none used Bayesian methods, 1 used false-discovery rates, 3 used sample size/power calculations, and 5 specified the primary outcome. + + We defined a Pvalue report as astringstartingwith either “p,” “P,”“p-value(s),”“P-value(s),”“Pvalue(s),”or“pvalue(s),” followed by an equality or inequality expression (any combination of =, , ≤, ≥, “less than,” or “of<” and then by a value, which could include also exponential notation (for example, 10-4, 10(-4), E-4, (-4), or e-4). + + The following characteristics of P value were evaluated: (1) the proportion of abstracts and full texts of articles that include P values and whether this is increasing over time; (2) the distribution of the reported Pvalues, focusing in particular on the extent of reporting of very small Pvalues (≤.001)vs the conventional P value of .05 (long considered a threshold of formal statistical significance); (3) the evolution of the minimal (best, most statistically significant) and maximal (worst, least statistically significant) reported Pvalues across abstracts and full-text articles; and (4) the number and proportion of abstracts and full-text articles that included at least 1 P value ≤.05. + + In each of these abstracts, we assessed reporting of any Bayes statistics, any P values (and, if so, how many), any statistically significant P values (<.05), any CI, any effect sizes (and, if so, what type, eg, odds ratio, hazards ratio), and any other information that would allow the calculation of effect sizes (eg, a comparison of proportions). The number of abstracts that had at least 1 effect size reported along with at least 1 corresponding Pvalue or CI also was recorded. In addition, the frequency of qualitative statements about significance without reporting at least 1 corresponding Pvalue, whether these statements were positive (eg, “was statistically significant”) or negative (eg, “was nonsignificant”), and whether there was any qualification of what type of significance was alluded to (statistical, clinical, biological, other) were recorded.","persisting discrepancies were resolved through discussion with a third reviewer (J.P.A.I.). + + Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. + + Funding/Support: The Meta-Research Innovation Center at Stanford (METRICS) is supported by a grant by the Laura and John Arnold Foundation. The work of Dr Chavalarias is supported by the Complex Systems Institutes of Paris Ile-de-France (ISC-PIF), the Région Ile-de-France and a grant from the CNRS Mastodons program. Mr Li was supported by a Canadian Institute for Health Research Doctoral Scholarship with a Michael Smith Foreign Study Supplement. The work of Dr Ioannidis is supported by an unrestricted gift by Sue and Bob O’Donnell to Stanford Prevention Research Center. + + Role of the Funders/Sponsors: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.",JAMA,1,1,1,1,1,1,1,1,1,9 +32,Stability of Developmental Problems after School Entry of Moderately-Late Preterm and Early Preterm-Born Children,,"This study was part of the Longitudinal Preterm Outcome Project (LOLLIPOP) cohort study, which has its main focus on the growth and development of moderately-late pretermborn children compared with both early preterm and full termborn children (controlled-trials.com ISRCTN 80622320).","Jpeds + + the journal of pediatrics + + ISRCTN","From the combinations of normal and abnormal ASQ-4 and ASQ-5 scores we constructed 4 categories: consistently normal, emerging, resolving, and persistent problems. + + Procedure + One month before the children’s well-child visit at age 43-49 months, parents received information about the LOLLIPOP study, an informed consent form, the ASQ-4, and a questionnaire about family and perinatal characteristics. These were returned by the parents at their child’s scheduled well-child visit. Following parental informed consent, we retrospectively recorded perinatal characteristics from discharge letters of mother and child, well-child care records, and information from linked national birth registers. Approximately 4-6 weeks before the child’s fifth birthday, parents received the ASQ-5. The ASQ-5 was returned by mail + + The ASQ-4 and ASQ-5 were completed within the determined time windows (43-49 months and 57-63 months after birth, respectively) for 1467 children, including 376 early preterm, 688 moderately-late preterm, and 403 full termborn children (Figure 1). The children with only an ASQ-4 (within the time window) but not an ASQ-5 (no ASQ-5 n = 484, outside time window n = 25) had more frequently an abnormal ASQ-4 total score than the children with completed ASQ’s at both ages (11.1% vs 8.1%, P = .048), and their parents had more frequently a low education (28.6% vs 14.2% P < .001). Similar rates of preterm and full term-born children were lost to follow-up (25.8% vs 25.8%, P = .988).","Developmental problems were assessed by the total score and the 5 domain scores of the Ages and Stages Questionnaire at ages 4 (ASQ-4) and 5 (ASQ-5). + + Developmental Problems: Ages and Stages Questionnaire (ASQ). Developmental problems were measured with the ASQ, which is, worldwide, the most commonly used parentcompleted developmental screener. We used the validated Dutch versions appropriate for ages 4 (ASQ-4) and 5 years (ASQ-5). The ASQ contains 5 domains: communication, gross motor, fine motor, problem solving, and personalsocial skills. Each domain is assessed by the use of 6 questions about reaching milestones. The response format is “yes” (10 points), “sometimes” (5 points), or “not yet” (0 points). The scores of the questions were summed into a score for each domain separately and overall, the ASQ total score. Subsequently, these scores were categorized into normal and abnormal scores, defined as abnormal if the score was more than 2 SDs below the mean of the Dutch reference population. We combined the dichotomous ASQ-4 and ASQ-5 outcomes on the 5 ASQ domains and the ASQ total score to form 4 stability categories for each ASQ outcome: stable normal, emerging problems, resolving problems, and persistent problems. The stable normal group had normal scores at both ages, the emerging problems group had a normal ASQ-4 score and an abnormal ASQ-5 score, the resolving problems group had an abnormal ASQ-4 and a normal ASQ-5, and the persistent problems group had 2 abnormal scores.","We included 376 early preterm, 688 born moderately-late preterm, and 403 full term-born children from the Longitudinal Preterm Outcome Project (LOLLIPOP) cohort study. + + The LOLLIPOP cohort is a community-based sample of early preterm and moderately-late preterm-born children and a random sample of full term-born children, born in 2002 and 2003 in the Netherlands. This community-based sample came from 13 preventive child health centers. These centers monitored a sample representative of 25% of the children born in 2002 and 2003 in The Netherlands. Children were included before their regular well-child visit at the age of 43-49 months. All children born before 36 weeks’ GA without major congenital malformations, congenital infections, or syndromes were sampled. After each second preterm-born child which was sampled, the next full term-born child (38-41 weeks’ GA), without the aforementioned exclusion criteria, was drawn from the same files to serve as a control. In addition, the early preterm-born sample was enriched with a sample of early preterm-born children, born in 2003, taken from 5 of the 10 neonatal intensive care units in The Netherlands. A detailed description of this study cohort can be found elsewhere. + + Gestational Age. The children in the preterm-born group were split into an early preterm-born category (250/7-316/7 weeks’ GA) and an moderately-late preterm-born category (320/7-356/7 weeks’ GA). GA was determined in completed weeks and was based on early ultrasound measurements in >95% of the cases. For the remaining cases, only clinical estimates based on last menstrual date were available; these were checked against clinical estimates of GA after birth.","Statistical Analyses + First, we compared characteristics between the GA groups (early preterm, moderately-late preterm, and full term). Second, we determined the overall stability per GA group by comparing rates of abnormal scores on the ASQ-4 and ASQ-5. Third, we assessed individual stability within the GA groups in 2 ways: by calculating the predictive values and by comparing prevalence rates of the 4 stability categories (consistently normal, resolving problems, emerging problems, persistent problems). The “predictive value of a normal ASQ-4” was defined as the proportion of children with a normal ASQ-5 out of the children with a normal ASQ-4, and the “predictive value of an abnormal ASQ-4” was defined as the proportion of children with an abnormal ASQ-5 out of the children with an abnormal ASQ-4. We performed the analyses on the 4 stability categories, both crude and adjusted for perinatal and family characteristics (sex, small for GA, being part of a multiple birth, low education level of the parents, non-Dutch birth country of parent or children, and single-parent family). All tests performed were 2-tailed and considered as significant when P < .05","Supported by the research foundation of Beatrix Children’s Hospital, the Cornelia Foundation for the Handicapped Child, the A. Bulk Preventive Child Health Care Research Fund, the Dutch Brain Foundation (15F07(2).59), and an unrestricted research grant from Friesland Campina, Friso Infant Nutrition, AbbVie, and Pfizer Europe (672394 and WI206819). The authors declare no conflicts of interest.","Jpeds + + the journal of pediatrics",0,1,1,1,1,1,1,1,1,8 +33,"Assessing scientists for hiring, promotion, and + tenure","Citation: Moher D, Naudet F, Cristea IA, Miedema F, Ioannidis JPA, Goodman SN (2018) Assessing scientists for hiring, promotion, and tenure. PLoS Biol 16(3): e2004089. https://doi.org/10.1371/ journal.pbio.2004089 + + Supporting information S1 Table. Name, portfolio, and affiliation of workshop organisers and participants. (DOCX)",,,"we convened a 22-member expert panel workshop in Washington, DC, in January 2017. + + As background for the meeting, we completed a selective literature review of 22 key documents critiquing the current incentive system. + + To help address this goal, we convened a 1-day expert panel workshop in Washington, DC, in January 2017. Pre-existing commentaries and proposals to assess scientists were identified with snowball techniques [16] (i.e., an iterative process of selecting articles; the process is often started with a small number of articles that meet inclusion criteria; see below) to examine the literature to ascertain what other groups are writing, proposing, or implementing in terms of how to assess scientists. We also searched the Meta-Research Innovation Center at Stanford (METRICS) research digest and reached out to content experts. Formal searching proved difficult (e.g., exp Reward/(7408); reward.ti,kw (9708), incentiv.ti,kw. (5078)) and resulted in a very large number of records with low sensitivity and recall. We did not set out to conduct a formal systematic review of every article on the topic.","From each document, we extracted how the authors perceived the problems of assessing science and scientists, the unintended consequences of maintaining the status quo for assessing scientists, and details of their proposed solutions. + + From each included article we extracted the following information: authors, name of article/report and its geographic location, the authors’ stated perspective of the problem assessing research and scientists, the authors’ description of the unintended consequences of maintaining the current assessment scheme, the article’s proposed solutions, and our interpretation of the potential limitations of the proposal. + + This was followed by discussions of possible solutions to the problems, new approaches for promotion and tenure committees, and implementation strategies. All discussions were recorded, transcribed, and read by five coauthors. For this, six general principles were derived. This summary was then shared with all meeting participants for additional input.","Twenty-two academic leaders, funders, and scientists participated in the meeting + + Broad criteria were used for article inclusion (the article focus had to be either bibliometrics, research evaluation, and/or management of scientists and it had to be reported in English). Two of us selected the potential papers and at least three of us reviewed and discussed each selection for its inclusion. + + We invited 23 academic leaders: deans of medicine (e.g., Oxford), public and foundation funders (e.g., National Institutes of Health [NIH]), health policy organisations (e.g., Science Policy, European Commission; Belgium), and individual scientists from several countries. They were selected based on contributions to the literature on the topic and representation of important interests and constituencies. Twenty-two were able to participate (see S1 Table for a complete list of participants and their affiliations). Prior to the meeting, all participants were sent the results of a selected review of the literature distilled into a table (see Table 1) and several selected readings. + Table 1 served as the basis for an initial discussion about the problems of assessing scientists.","We included a list of 21 documents + + An almost equal number of documents originated from the US and Europe (one also jointly from Canada). We divided the documents into four categories: large group efforts (e.g., the Leiden Manifesto [20]), smaller group or individual efforts (e.g., Ioannidis and Khoury’s Productive, high-Quality, Reproducible, Shareable, and Translatable [PQRST] proposal [29]); journal activities (e.g., Nature [32]); and newer quantitative metric proposals (e.g., journal citation distributions [34]). + We interpreted all of the documents to describe the problems of assessing science and scientists in a similar manner","Funding: The authors received no specific funding for this work. + + Competing interests: The authors have declared that no competing interests exist","PLOS Biology + + Provenance: Not commissioned; externally peer reviewed",1,0,0,1,1,1,1,1,1,7 +34,"Tobacco smoking and somatic mutations in + human bronchial epithelium","Online content Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-020-1961-1. + + Reporting summary Further information on research design is available in the Nature Research Reporting Summary linked to this paper. + + Data availability Sequencing data have been deposited at the European Genome-phenome Archive (http://www.ebi.ac.uk/ega/) under the accession number EGAD00001005193. Somatic-mutation calls, including single-base substitutions, indels and structural variants, from all 632 samples have been deposited on Mendeley Data with the identifier: https:// doi.org/10.17632/b53h2kwpyy.2. + + Code availability Detailed method and custom R scripts for the analysis of mutational burden in bronchial epithelium are available in Supplementary Code. Other packages used in the analysis are as follows: R v.3.5.1; BWA-MEM v.0.7.17-r1188 (https://sourceforge.net/projects/bio-bwa/); CaVEMan v.1.11.2 (https://github.com/cancerit/CaVEMan); Pindel v.2.2.5 (https:// github.com/cancerit/cgpPindel); Brass v.6.1.2 (https://github.com/ cancerit/BRASS); ASCAT NGS v. 4.1.2 (https://github.com/cancerit/ ascatNgs); Xenome (https://github.com/data61/gossamer/blob/ master/docs/xenome.md); deepSNV v.1.28.0 (https://bioconductor. org/packages/release/bioc/html/deepSNV.html); ANNOVAR (http:// wannovar.wglab.org/); IGV (http://software.broadinstitute.org/soft ware/igv/); JBrowse (https://jbrowse.org/); cgpVAF (https://github. com/cancerit/vafCorrect); RPhylip v.0.1.23 (http://www.phytools.org/ Rphylip/); hdp v.0.1.5 (https://github.com/nicolaroberts/hdp); MutationalPatterns v.1.8.0 (https://bioconductor.org/packages/release/ bioc/html/MutationalPatterns.html); dNdScv v.0.0.1 (https://github. com/im3sanger/dndscv); and Telomerecat v.3.1.2 (https://github.com/ jhrf/telomerecat). + + Additional information Supplementary information is available for this paper at https://doi.org/10.1038/s41586-020- 1961-1.",,NATURE,"Here we sequenced whole genomes of 632 colonies derived from single bronchial epithelial cells across 16 subjects. + + Data reporting No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment.","Single-cell-derived colonies Endobronchial biopsies were dissociated using 16 U/ml dispase in RPMI for 20 min at room temperature. The epithelium was dissected away from the underlying stroma and fetal bovine serum (FBS) was added to a final concentration of 10%. Both the epithelium and stroma were combined and digested in 0.1% trypsin/EDTA at 37 °C for 30 min. The solution was neutralized with FBS to a final concentration of 10% and added to the neutralized dispase solution36. Cells were passed through a 100-μm cell strainer and stained in sorting buffer (1× PBS, 1% FBS, 25 mM HEPES and 1 mM EDTA) with anti-CD45-PE (BD Pharminogen 555483, 1:200), anti-CD31-PE (BD Pharminogen 555446, 1:200), anti EPCAM-APC (Biolegend 324208, 1:50) antibodies and DAPI (1 μg/ml). For endobronchial brushings, no dissociation was carried out and the cell suspension was passed through a 100-μm cell strainer before staining. Cells were single-cell sorted on the basis of their expression of CD45, CD31 and EpCAM, using a BD FACSAria Fusion. Each DAPI− CD45− CD31− EpCAM+ cell was sorted into 1 well of a 96-well plate, pre-coated with collagen I and mitotically inactivated 3T3-J2 feeder cells. Feeder cells were authenticated by whole-genome sequencing, and were screened for mycoplasma contamination by PCR. Cells were grown in fresh epithelial growth medium37 (Dulbecco’s modified Eagle medium (DMEM):F12 at a 3:1 ratio with penicillin–streptomycin, 5% FBS, 5 μM Y-27632, 5 μg/ml insulin, 25 ng/ml hydrocortisone, 0.125 ng/ml epidermal growth factor, 0.1 nM cholera toxin, 250 ng/ml amphotericin B and 10 μg/ml gentamicin), which was supplemented for the first week of culture with epithelial growth medium that had been conditioned on growing epithelial cells and a final concentration of 10 μM Y-27632. Epithelial cells were grown in 96-well plates for 2 weeks before being passaged into 24-well plates and then into T25 flasks. Epithelial cells were in culture for a total of about 25 days at 37 °C and 5% CO2 with 3 changes of medium per week. When cells reached 70–80% confluence in T25 flasks, they were differentially trypsinized (making use of the greater sensitivity of feeder cells to trypsin compared with epithelial cells), generating a mostly pure population of epithelial cells. DNA was then extracted using the PureLink Genomic DNA Mini Kit (Invitrogen). + + Whole-genome sequencing Paired-end sequencing reads (150 bp) were generated using the Illumina Hiseq X-Ten platform for 662 samples from 16 patients. The target coverage was 15× per sample, except for 30× for 26 pilot samples that were derived from the first patient (PD26988). For ten patients, blood DNA samples were also sequenced as germline controls. For three patients, samples of bulk squamous cell carcinoma or carcinoma in situ, which were collected at the same or close time points (around four months after), were sequenced, including two samples of carcinoma in situ that were used in a previous study38 (PD38326a and PD38327a, which are carcinomas in situ that were derived from PD30160 and PD34210, respectively). We also sequenced the whole genome of the pure mouse feeder cell layer. + + Discrimination of human and mouse sequences Bronchial epithelium samples were cultured on J2 mouse embryonic feeder fibroblast cells, which caused various degrees of contamination of mouse DNA in the samples from bronchial cell colonies. To remove mouse-derived sequencing reads, we used the Xenome algorithm39 with default setting (k-mer size = 25). The Xenome algorithm classifies fastq files into five categories: graft (human), host (mouse), ambiguous, both and neither. We confirmed that most of the sequencing reads of a sample of pure human DNA were classified as human (98%) and those of a sample of DNA derived from mouse feeder cells were rarely (2.8%) classified as human (Extended Data Fig. 2a). In addition, we mapped sequencing reads of a DNA sample from mouse feeder fibroblasts to the human reference genome, and confirmed that most of the mouse derived mutations had been successfully removed using Xenome for selected samples with mouse contamination (Extended Data Fig. 2b). Although all samples were negative for mycoplasma using standard laboratory PCR testing, Xenome identified sequencing reads derived from the mycoplasma genome in a subset of samples, and assigned them to the ‘neither’ classification. With testing complete, we ran Xenome for all bronchial epithelium samples, and aligned only reads that were classified as human to the human reference genome (NCBI build 37d5) using the BWA-MEM algorithm. The metrics of sequencing coverage and proportion of human derived reads are listed in Supplementary Table 2, and 20 samples with an average sequencing depth of less than 8× were excluded from further analysis owing to lower estimated sensitivity, as described later (Extended Data Fig. 2e). + + Extraction of SBS signatures To analyse mutational signatures for single-base substitutions, those assigned to each branch of the phylogenetic trees were categorized into 288 subtypes, consisting of 6 mutation classes by 16 5′- and 3′-base contexts on the transcribed strand, non-transcribed strand or intergenic region. Mutational signatures were extracted using the HDP package50, relying on the hierarchical Bayesian Dirichlet process (https://github.com/nicolaroberts/hdp). Owing to the lack of reference signatures categorized into 288 subtypes, we conducted a de novo signature extraction. We included somatic mutations from squamous cell lung carcinomas sequenced by The Cancer Genome Atlas (TCGA) and from in vitro single-cell culture controls as separate samples to maintain comparability with signatures that have already been established in previous studies. For identified SBS signatures, signatures with ≥0.90 cosine similarity with reported signatures, in terms of distribution to 96 or 192 subtypes24, were considered as the same signatures, including SBS-1, SBS-4, SBS-5, SBS-16 and SBS-18. For the remaining new signatures, the expectation-maximization algorithm was used to deconvolute these signatures into the five signatures above and other known signatures in lung cancers (SBS-2, SBS-8 and SBS-13), because it is difficult to separate signatures that are strongly correlated across samples. If a signature reconstituted from the components that expectation maximization extracted (only including signatures that accounted for at least 10% of mutations in each sample to avoid overfitting) had a ≥0.90 cosine similarity to the original HDP signature, the signature was presented as its expectation maximization deconvolution. Two HDP signatures met these criteria: one new signature was deconvoluted into a mixture of SBS-4 and SBS 5, and another new signature was deconvoluted in SBS-2 and SBS-13. After these analyses, seven known and two new SBS signatures were identified. To validate these signatures that were identified using the HDP, we also analysed SBS signatures using the MutationalPatterns package20, which relies on non-negative matrix factorization. The optimal factorization rank (7) was determined on the basis of the slope of the cophenetic correlation coefficient. MutationalPatterns identified similar signatures to SBS-5 (Signature A), SBS-4 (Signature B), Sig-B (Signature D), SBS-18 (Signature E), SBS-1 (Signature F), SBS-2 and SBS-13 (Signature G) (Extended Data Fig. 5a, b). + + Extraction of indel and DBS signatures For indels and double-base substitutions, each type of genetic alteration that was assigned to each branch of the phylogenetic trees was categorized into 83 and 78 subtypes, as previously reported24. First, the algorithm was conditioned on the set of mutational signatures that have been detected in lung cancers (ID-1, ID-2, ID-3, ID-5, ID-6, ID-8, ID-9, DBS-2, DBS-4, DBS-5, DBS-6, DBS-11). This allows simultaneous discovery of known and new signatures. For known signatures, signatures identified by HDP with a cosine similarity ≥0.90 with corresponding reported signatures were accepted as known signatures. Deconvolution of new signatures to the above known signatures was also performed, and one new indel signature was deconvoluted in ID-5 and ID-8. Finally, ten known signatures and one new signature were identified.","Subjects Subjects were recruited at University College London Hospitals (UCLH) or Great Ormond Street Hospital (GOSH) and gave written informed consent with approval of the Research Ethics Committee (REC reference 06/Q0505/12 and 11/LO/152, respectively). Details of the patients studied are listed in Supplementary Table 1. All patients underwent bronchoscopy as part of their clinical care. In adults, the bronchoscopy procedure was performed for diagnostic or surveillance indications; in children, it was undertaken for investigational procedures on con genital tracheal abnormalities. For five patients with squamous cell carcinomas or carcinoma in situ, biopsy of normal bronchial tissue was taken from a site distant from the tumour.","Analysis of A>G transcriptional strand bias First, we measured the distance from mutations to the nearest transcription start sites (TSSs) of all the expressed genes in the lung; expressed genes were defined as those with a median of one or more transcripts per million in lung samples in the GTEx database (https://gtexportal. org/home/). Mutations in regions of bidirectional transcription were excluded from further analysis. We tiled 10 kb up and downstream of the TSSs into 1-kb bins, and counted the number of A>G mutations on transcribed and untranscribed regions in each tile. This number was further divided by the average number of bins in intergenic regions. + + Analysis of driver variants To systematically identify genes under positive selection in normal bronchial epithelium, we used the dN/dS method12. We performed exome-wide dN/dS analysis and also analysed global dN/dS ratios for driver genes (n = 86) reported in lung cancer12,13,18,26 or normal skin or oesophagus tissues27–29 using dNdScv (Supplementary Table 3). Genes with q value ≤ 0.05 were reported as driver genes (Supplementary Tables 4, 5). Finally, hot-spot mutations reported in COSMIC for four or more patients were also considered as driver mutations, in addition to those in the seven driver genes identified by dNdScv (Fig. 3b). The proportion of shared mutations (found in more than one colony) and private mutations (found in a single colony) was calculated for patients other than PD30160 (who had a low number of sequenced samples (n = 13)). For known lung cancer driver genes, the distributions of mutations were compared between bronchial cells and lung squamous cell carcinoma13 (Extended Data Fig. 9b). To estimate the effect of smoking status on the number of driver mutations, a generalized LME model was fitted using the lme4 package in R (Supplementary Code). Patient was modelled as a random effect, and the fixed effects of age, smoking status and total mutational burden were fitted into the model. + + Estimation of telomere length The average telomere lengths of bronchial epithelium cells were estimated from the whole-genome sequencing data using Telomerecat51. Considering the similarity of telomere sequences between human and mouse, we aligned all sequencing reads to the human reference genome using BWA-MEM without using Xenome, and then ran Telomerecat on the bam files. Samples with reported mouse contamination of more than 10% were excluded from further analysis to prevent a possible effect of mouse cells on telomere length. The average telomere length for the mouse fibroblast feeder samples was estimated at 1,745 bp, which is within the range of estimates of human telomere length, so a low level of mouse contamination will not substantially affect the estimates. An LME model was then fitted to estimate the effect of telomere length on the number of single-base substitutions using the lme4 package in R (Supplementary Code). Patient was modelled as a random effect, and the fixed effects of telomere length and its interaction with smoking status, as well as the fixed effects of age and smoking status, were fitted into the model.",Competing interests The authors declare no competing interests.,"NATURE + + Peer review information Nature thanks Gerd P. Pfeifer, Roman Thomas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.",1,0,1,1,1,1,1,1,1,8 +35,Effect of Manual Acupuncture Stimulation at “Bai-Hui” (GV 20) or “Yinta´ng” (Ex-HN3) on Depressed Rats,,,,"We maintained the animals in an environment at room temperature (22 3C) with 60% humidity and a 12-hour light/ dark cycle. The rats were given free access to animal feed (CE-2; CLEA Japan, Inc.) and water. Rats were acclimatized to handling for 1 week after purchase. Thirty-five rats were randomly divided into two groups with 10 rats in the nondepression group and 25 rats in the mild depression group. The rats in the nondepression group were maintained under the conditions described above. For the rats in the mild depression groups, mild depression was created using water-immersion stress according to Tanahashi et al [11]. The night water-immersion stress was continued from 22:00 to 10:00 of the next day for 1 week. The floor of the cage was flooded with water at 25 2C to a depth equivalent to ankle height on the rat. The degree of mild depression created in the rats by using water-immersion stress was evaluated by using the forced swimming test described by Porsolt et al [13]. + To avoid disruptions in the rats’ sleep cycle, which may produce or contribute to the depressive symptomology, and disruptions in the rats’ circadian rhythm, which are associated with stress, anxiety, and depression, we performed water immersion during the time described above because rats are nocturnal and are usually awake and active at night. The weight of each rat and its food intake were measured every week. + The 10 rats in the nondepression group were randomly divided into two groups with five rats in each group: Group 1 [water-immersion stress () þ immobilization ()] and Group 2 [water-immersion stress () þ immobilization (þ)]. In addition, the 25 mildly depressed rats were randomly divided in five groups with five rats in each group: Group 3 [water-immersion stress (þ) þ immobilization ()], Group 4 [water-immersion stress (þ) þ immobilization (þ)], Group 5 [water-immersion stress (þ) þ acupuncture at “Yinta´ng” (Ex-HN3)], Group 6 [water-immersion stress (þ) þ acupuncture at “Bai-Hui” (GV 20)], and Group 7 [waterimmersion stress (þ) þ imipramine] (Table 1). + Mild depression was induced in the rats by using water immersion (from 22:00 to 10:00 of the next day) for 1 week [11]. Thereafter, rats exhibiting symptoms suggestive of mild depression underwent either stimulation by acupuncture or administration of imipramine as an antidepressant for 3 weeks. Body weights and food intakes were measured every week. To clarify the effects of acupuncture stimulation and pharmacotherapy on rats exhibiting symptoms suggestive of mild depression, we randomly divided the rats into seven groups with five rats per groups, as has already been described (Table 1). + Acupuncture stimulation was continued for 20 minutes by inserting a stainless-steel needle (diameter, 0.25 mm; length, 15 mm; Acupuncture Needle D-Type; SEIRIN Co. Ltd., Shizuoka, Japan), without any spinning, flicking, moving up and down, or application of electrical current, to a depth of 5 mm into the GV 20 or the Ex-HN3 acupoint. This procedure was performed 5 days a week for 3 weeks [11]. Groups that did not receive acupuncture stimulation, except Group 1 and Group 3, were immobilized for a similar length of time in a plastic bag in which a hole had been made to allow the rats to breathe. The rats in Group 1 and Group 3 were not immobilized for comparison with other groups to study the effects of the immobilization. + The antidepressant imipramine (10 mg/kg body weight) was dissolved in saline and administered intraperitoneally 5 days a week for 3 weeks [14,15]. Groups not receiving antidepressants, including Group 1 [water-immersion () þ immobilization ()], were intraperitoneally administered with saline, instead of antidepressants, without immobilization. + The forced swimming test was performed using the method described by Porsolt et al [13]. Rats were placed in an open cylindrical container with a diameter of 25 cm and a height of 50 cm containing fresh water at 25 2C to a depth of body height þ 5 cm for 13 minutes. The actions of the rats were recorded with a video camera. The immobile time for the 10 minutes after the first 3 minutes of the 13- minute recording had been excluded was measured, the first 3 minutes being regarded as the acclimation time. The immobile state was defined as the state in which the rat stopped most movements and only performed the smalllimb movements necessary to maintain balance. The immobile time was defined as the time during which that state continued.",The anxiety state was evaluated by measuring the number of head dips and the number of times the rat looked into a hole.,"We purchased 4-week-old male Wister rats (body weight, 100e120 g) from CLEA Japan, Inc. (Tokyo, Japan).","Data are presented as means standard errors of the mean and were analyzed at first by using Excel Statistics 2012 (Society Information Service) and were then reanalyzed using IBM SPSS Statistics 22. The presence of significant differences was assessed using the one-way analysis of variance and a multiple comparison assay (TukeyeKramer), except for the analysis for Figure 1. The analysis for Figure 1 was done using a single comparison assay (ManneWhitney). A p value < 0.05 were considered statistically significant.","Discussions of the results using animal models have a serious limitation. In rats experiencing trauma in the form of water-immersion stress, immobilization, and intraperitoneal injection, as well as acupuncture, the normal stressreducing and pain-attenuating mechanisms activated in all of these animals in response to their environment may have been sufficiently large to override the ability to detect differences in the effect of acupuncture among the groups. This needs to be addressed in future research.",,0,0,0,1,1,1,1,1,0,5 +36,"Academic criteria for promotion and tenure in biomedical + sciences faculties: cross sectional analysis of international + sample of universities","Additional material is published online only. To view please visit the journal online. + + Data sharing: The code is shared on the Open Science Framework (https://osf.io/jgsw3/). All datasets that were used are retrievable following the instruction of the original papers. + + Supplementary information: e-Table 1: results of reanalyses for three ineligible studies published in The BMJ after the policy but submitted before + + Data sharing: All data associated with this study are posted on the open science framework (https://osf.io/26ucp/?view_ only=b80d2bc7416543639f577c1b8f756e44). The study protocol, data extraction forms, and data are also available at this link. + + Web appendix: Appendix 1-4","Study registration Open Science Framework (https://osf.io/26ucp/?view_ only=b80d2bc7416543639f577c1b8f756e44). + + The protocol for this study was registered within the Open Science Framework database (https://osf.io/26ucp/?view_only=b80d2bc74165436 39f577c1b8f756e44) before the study’s data collection.","We used the STROBE checklist for cross sectional studies to ensure that methods and findings are clearly reported (see appendix 1). + + BMJ","Design Cross sectional study. + + Approach to selecting university institutions We used the Centre for Science and Technology Studies (CSTS) Leiden ranking of world universities from 2017 (https://www.leidenranking.com/ranking/2017/ list) to select institutions for inclusion in the study. We selected a random sample of 20% (170/854) of institutions from the Leiden ranking list by using online random sampling software (https://www. randomizer.org/). We selected the CSTS ranking list for the field of “Biomedical and Health Sciences,” which represents the field to which publications from universities are assigned. We planned to include all randomly selected institutions on this list, regardless of the faculties present at each university. We used the default settings on the CSTS website. The default indicator settings include type of indicator (‘impact’) and indicators (“P, P(top 10%), PP(top 10%)”). This indicator represents the number and proportion of a university’s publications that, compared with other publications in the same field and in the same year, are among the top 10% of most frequently cited publications. We ordered the list by publications and selected the calculation of impact indicators by using fractional counting option. A minimum publication output was set at the default value of 100.","Data collection For each eligible institution, we extracted the following information: university name, faculty name, country, and human development index rating of country. We reviewed guidelines used by faculties of biomedical sciences or institutions for the evaluation of professors, where available, to determine whether each of the 12 items from our list of criteria for promotion and tenure of faculty were present. We recorded the relevant mentions for each criterion, regardless of exactly how the criterion was considered or operationalised. We did not intend to arbitrate whether the proposed version of the criterion was appropriate and technically sophisticated; however, we collected information about whether guidelines applied thresholds for each criterion. When promotion and tenure guidelines were available, we first reviewed the table of contents and located the section on criteria for promotion and tenure and reviewed this section of the document, including any sections that the document referred to for context. If a table of contents was not provided, we reviewed the document in its entirety. We then reviewed and extracted the presence of criteria and the relevant statement for each level of promotion criteria published for universities, including promotions to assistant professor, associate professor, and full professor and the granting of tenure, as well as whether a criterion was mentioned for at least one of these levels. We considered these levels of promotion on the basis of a North American framework of career advancement. Where institutions applied different labels to ranks/positions (for example, researcher level A), we sought documentation for the appropriate equivalent categorisation of the promotion levels. If documentation describing the position was not available, we consulted with professors from the institution’s country to equate positions with those being applied in our study. If no equivalent position was available, we did not include the institution in our sample (n=3 institutions). We extracted this information for tenure track positions rather than nontenure track positions. We did not extract promotion and tenure criteria for aspects of career advancement related to teaching or clinical duties or for positions that comprised more educational or clinical activities than research activities. We also extracted the level of the promotion criteria available (that is, faculty level criteria, departmental level criteria), the year that the promotion guideline was published, the associated URL of the criteria, and the date that the website was searched. Two reviewers (DBR, HR) independently extracted all data, and results were compared for consistency. Where consensus was not achieved between reviewers after discussion, a third team member (DM) was consulted to resolve discrepancies in the interpretation of criteria. For guidelines published in languages other than English or French, translation of the relevant documents was conducted by one person and verified by a second reviewer (DBR) using Google Translate. A Hungarian translator was not available for one guideline. For this guideline, one reviewer (DBR) used Google Translate to extract data. We used a standardised electronic data collection form in Distiller Systematic Reviewer (Evidence Partners, Ottawa, Canada) for data collection.","Setting International sample of universities. + + Participants 170 randomly selected universities from the Leiden ranking of world universities list.","Approach to synthesis We summarised institutions’ characteristics and promotion and tenure criteria in table format to facilitate inspection and discussion of findings. We compared the percentage of criteria that were included in promotion and tenure guidelines with a paired sample t test. We present categorical variables as percentages and counts and continuous variables as means and standard deviations or medians and interquartile ranges. We compared institutions that had criteria available with institutions that did not have criteria available by using independent samples t test, χ2 tests, or non-parametric tests. We did exploratory analyses for the full professor position, as this had the most data available. We conducted two multiple linear regressions to assess the associations between institutions’ characteristics (independent variables: level of criteria, continent, human development index, and Leiden ranking) and the number of criteria present for traditional and non-traditional items for guidelines for professors (dependent variable), as most institutions had guidelines for this promotion level. We did logistic regressions for each criterion present among 10% to 90% of institutions at the rank of full professor to assess the associations between institutional characteristics (independent variables) and the presence of each criterion (dependent variable). We selected institutional characteristics as covariates given their availability and the potential relevance to the type of criteria applied (for example, regional differences in career advancement procedures). If an independent variable did not have at least one institution with and one without the item criteria, we removed that variable from the logistic regression. Before doing regression analyses, we did preliminary tests to confirm that no violations of multiple regression assumptions existed. We used Microsoft Excel for summing study results and SPSS version 21.0 for statistical tests. All statistical analyses were two tailed with P<0.005 significance level to adhere to recent recommendations for a lowered threshold of statistical significance.","Limitations of study Some limitations should be considered when interpreting our study results. Direct involvement of patients and the public was absent from this review. Incorporating the perspectives of patients and the public in future research of promotion and tenure criteria can incentivise research practices that better align with the needs and expectations of society. This could also allow for international differences to be highlighted by speaking with stakeholder groups in various regions. Next, although we searched websites and contacted institutions, not all institutions use pre-specified criteria for assessing promotion, and in some instances we did not find documents. This resulted in only a subset of the intended sample being available for review and included in our analyses. South America and Africa were underrepresented in our sample, so we can draw few conclusions about the criteria of institutions in these regions. An additional limitation is that incentives for professors can occur through other pathways, such as financial bonuses, which may not be publicly available or included in the documents reviewed. Obtaining a more complete understanding of the criteria used for providing financial and reputational incentives in medical faculties may require review of internal documentation on bonuses and awards or recognitions in addition to formal promotions. Furthermore, medical faculties often take into account clinical work and teaching, which we did not include. + Finally, we should acknowledge that for both traditional and non-traditional criteria, the exact way they are proposed and operationalised can make a difference to whether they might have a positive or negative effect on research quality. With a plethora of metrics being developed for non-traditional criteria, some of them may be much better than others. For example, although citations may be a more accurate representation of one’s research impact than journal impact factor, considering the number of citations in isolation from the field of research may not motivate those who work in otherwise important research fields that have low citation density (for example, because few other scientists work in them). + + Funding: No funding was received for this work. DBR is funded through a Canadian Institutes of Health Research Vanier graduate scholarship. DM is funded by a university research chair. METRICS is funded by a grant from the Laura and John Arnold Foundation. Funding sources did not have any role in the design and conduct of the study, data collection and analysis, interpretation of study findings, or the decision to publish. + + Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.",BMJ,1,1,1,1,1,1,1,1,1,9 +37,"Populating the Data Ark: An attempt to + retrieve, preserve, and liberate data from the + most highly-cited psychology and psychiatry + articles","Citation: Hardwicke TE, Ioannidis JPA (2018) Populating the Data Ark: An attempt to retrieve, preserve, and liberate data from the most highly cited psychology and psychiatry articles. PLoS ONE 13(8): e0201856. https://doi.org/10.1371/ journal.pone.0201856 + + Data Availability Statement: All data, materials, and analysis code pertaining to this study have been made publicly available on the Open Science Framework (https://osf.io/64qvb/). + + Open practices statement All data exclusions and measures conducted during this study are reported. All data, materials, and analysis code pertaining to this study have been made publicly available on the Open Science Framework (https://osf.io/64qvb/). To facilitate reproducibility this manuscript was writ ten by interleaving regular prose and analysis code (https://osf.io/7syrt/) using knitr and papaja, and is available in a Code Ocean container (https://doi.org/10.24433/CO.241ffbb1- 5b81-44bd-94f4-d066b62c5f7f.v2) which re-creates the software environment in which the original analyses were performed.",,,"Web of Science Essential Science Indicators was used to identify the top 200 most highly-cited articles in the research category “psychology/psychiatry” between 2006 and 2016 (date of search: 31st May, 2017). From these 200 we selected only research articles that would in principle have recorded individual-participant level data, leaving 48 eligible (24 from psychology and 24 from psychiatry). As none of these articles were published after 2011 they may be unrepresentative of recent data sharing trends [3]. To address this, we conducted an additional focused search to identify the top 200 most highly articles published during the 2014–2016 time period. Applying the same eligibility criteria, we identified 63 eligible studies (17 from psychology and 46 from psychiatry).","Procedure The 111 corresponding authors of eligible articles were contacted on 23rd June 2017 using the e-mail address provided in the published article. Two reminder e-mails were sent to nonrespondents at 2 weeks intervals as required. If e-mails bounced, and before sending any reminders, we performed an Internet search to obtain the most up-to-date contact details for the corresponding author. If we could not identify an active e-mail address, we attempted to contact a different member of the research team. The initial contact e-mail (full version available here: https://osf.io/e8gxq/) outlined our goal to promote the availability and usability of raw data from the most influential investigations in psychology and psychiatry by uploading data to an online repository that would ensure their persistence and accessibility. We specifically requested raw, participant-level data that supports all findings [reported in their article] and mentioned that it would be highly desirable if additional documentation and/or analysis scripts were also be made available. We stressed that contributing researchers could specify access restrictions for the data if they desired. We also highlighted that we were aware that data sharing may not be feasible in all cases and asked that if this were the case, researchers send us their reasons for not sharing. The e-mail concluded by asking researchers to send us their data files (if applicable) and specify their desired level of sharing from one of four options: (1) Online data repository, completely open access; (2) Online data repository, controlled access (please state what prerequisites, criteria and processes you might consider for deciding whether to share the data with others); (3) Sharing with the METRICS team only, not to be shared with anyone else; (4) Cannot share data (please state the key reason(s)).","Combining the two groups of studies resulted in a total sample size of 111 articles, 70 of which were from psychiatry and 41 of which were from psychology. + + Therefore, our sample includes papers in the top 0.11% and top 0.16% of citations for 2006–2011 and 2014–2016, respectively. The median number of citations for eligible articles was 64 in psychiatry (range: 45–1390) and 470 in psychology (range: 48–1768). Based on examination of article titles and abstracts, the types of eligible studies included field experiments or surveys (n = 26), epidemiological surveys (n = 23), randomized clinical trials (n = 23), case-control studies (n = 16), laboratory experiments (n = 13), and development of stimuli, surveys, or diagnostic screening instruments (n = 10). A data file containing all 400 sampled studies is available here: https://osf.io/84cm5/",,"Funding: METRICS is supported by a general support grant from the Laura and John Arnold Foundation. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. + + Competing interests: The authors have declared that no competing interests exist.",PLOS,1,0,0,1,1,1,0,1,1,6 +38,"Reproducible Research Practices and + Transparency across the Biomedical + Literature",Data Availability Statement: All relevant data are within the paper and its Supporting Information files. All authors had full access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and accuracy of the data analysis.,,,"PMID numbers ranging from 10,000,000 to 25,000,000 were inputted into OpenEpi (version 3.02) random number generator to select a random sample of 750 PMID numbers. Beginning from the first number generated, each number was verified for eligibility in sequence until 500 eligible PMID numbers were chosen. Of the original 750 numbers, 742 were checked, with 242 being ineligible (54 did not have an article assigned, 100 were from before the year 2000, 35 were not in English, and 53 were not in English and before the year 2000). The selected article distribution of PMID numbers (by year) was compared to the overall distribution of PMID numbers by year for English articles. + + Two investigators independently characterized and then cross-compared all extractions in groups of 50 articles at a time. Any uncertainties were first discussed in detail, and a third reviewer (JPAI) reassessed articles with arbitration discrepancies.","The sample was characterized into seven study categories: (1) no research (items with no data such as editorials, commentaries, news, comments and non-systematic expert reviews), (2) models/modeling or software or script or methods without empirical data (other than simulations), (3) case report or series (humans only, with or without review of the literature), (4) randomized clinical trials (humans only), (5) systematic reviews and/or meta-analyses (humans only), (6) cost effectiveness or decision analysis (humans only), and (7) other (empirical data that includes uncontrolled study [human], controlled non-randomized study [human], or basic science studies). InCites Essential Science Indicators (ESI) was used to determine the main scientific field of each article. The journal for each index paper was searched in ESI in order to find the scientific field to which its Highly Cited Papers are ascribed. If a journal had articles ascribed to more than one scientific field, we examined the first five cited journals referenced by the index article. The journal names for these articles were then searched in ESI. If the majority belonged to the same field, this field was used for the index paper. If there was no majority, a field was selected based on the best judgment of the reviewers (JPAI, SAI, and JDW). If a specific journal was not found on ESI, we searched Journal Citation Reports (JCR) and identified the scientific field to which the highest-cited journal in the same JCR category had been ascribed to in ESI. Publications in scientific fields not directly related to biomedical research (chemistry, physics, computer science, economics and business, engineering, geosciences, material science, mathematics, physics, and space science) were further excluded from analysis. Even though these fields may sometimes have repercussions for biomedicine, their transparency practices may differ systematically, and their evaluation would require a separate, focused effort. Thus, 59/500 articles were excluded. JCR was used to determine 2013 journal impact factor. No information was recorded for journals without an impact factor for 2013. Availability of free access in PubMed Central was based on assignment of a PCMID (yes/no).","In this survey, we assessed the current status of reproducibility and transparency addressing these indicators in a random sample of 441 biomedical journal articles published in 2000–2014. + + A sample of 500 English-language journal articles published between 2000 and 2014 was chosen randomly based on PubMed identification (PMID) numbers. + + The sample was found to be representative of the overall distribution (χ2 (df = 14), p > 0.05). This sample size was chosen because given 500 articles and assuming that about half of them might have empirical data, if no article is found to fulfill the criterion for a transparency indicator, then the 95% confidence interval around that 0% estimate does not exceed 1%.",,"Funding: The authors received no specific funding for this work. The Meta-Research Innovation Center at Stanford (METRICS) is supported by a grant from the Laura and John Arnold Foundation. + + Competing Interests: The authors have declared that no competing interests exist. + + Limitations Our evaluation is limited to published biomedical research information. In theory, sometimes one may be able to obtain additional raw data and protocols, and clarifications on conflicts or funding by communicating with the authors or sponsors. However, the yield would be uncertain, and personal communications should not replace the lack of transparency in the published scientific record. Furthermore, the fact that we only used the published records means that we could not correct any inaccuracies in the claims of the original authors. This may be particularly prominent in the case of claims for novelty, in which some authors may have tried to sell their paper as being more novel than it really is, so as to make it more attractive for publication. Although the two investigators (SAI and JDW) used their best judgment and discussed all eligible papers before agreeing upon a final classification, certain decisions may have been subjective. In particular, when determining study novelty and replication for articles from diverse biomedical fields, difficulty arose assessing whether study results were truly ground breaking or being fully replicated. In order to account for these limitations, all ambiguous articles were discussed with a third reviewer (JPAI).",PLOS,1,0,0,1,1,1,0,1,1,6 +39,"Reproducible research practices, + transparency, and open access data in the + biomedical literature, 2015–2017","Data Availability Statement: All data and code files are publicly available at https://osf.io/3ypdn/. + + We based the design of this study on a previously published manuscript, which includes a study protocol in “Supporting information” [7]. The definitions of captured indicators in the previous evaluation have been carried forward in the current work.",,,"We used a sampling process to generate a new random sample of 155 articles published between 2015 and 2017 and indexed in PubMed. We did not perform any sample size calculations since our study evaluated multiple indicators that were all equally important, and they varied substantially in the proportion to which they were satisfied already by the articles in the 2000–2014 sample. + + Articles classified as a “Journal Article” in PubMed were considered and then ordered randomly. Articles in scientific fields not directly related to biomedical research (defined as Biology/Biotechnology, Medicine, Infectious Disease, Health Sciences, and Brain Sciences) [39] were excluded. Even though these fields may sometimes have repercussions for biomedicine, their transparency practices may differ systematically, and separate evaluation efforts would be necessary [7]. All non-English language articles were then excluded and one investigator (JDW) independently characterized the new sample into seven study categories, as previously described (Box 1) [7]. + + Both sets were chosen randomly based on PubMed identification (PMID) numbers. Although both samples were limited to articles considered to be in biomedical fields, in the current analyses, we used an enhanced field classification process based on article-level classification [40], which allowed for a better categorization of both the 155 new articles and the 441 previous articles.","In order to determine whether there are different reporting practices among free full text articles, we identified the subset of articles made available through PubMed Central (PMC), a digital repository that archives publicly accessible full text biomedical and life science journal articles. Availability of free access in PMC was based on assignment of a PMC identifier (i.e., PMCID versus non-PMCID articles). We also classified articles based on whether there was a publicly available XML version of the full text of the article in the open access subset of PMC (i.e., PMCOA versus non-PMCOA articles). The XML of the full text of roughly 1.7 million PMCOA articles is available in bulk, which allows for algorithmic analyses of the data at scale, as opposed to one at a time. Since 2015, PMCOA comprises roughly half of PMC articles and over 20% of all PubMed articles [41]. We aimed to compare the key indicators of reproducibility across the different article types. In order to maintain consistency with our previous evaluation [7], we determined the 2013 impact factor of each publication’s journal. The journal name for the eligible article was searched in InCites Journal Citation Reports. No information was recorded for journals without a 2013 impact factor.","Here, we surveyed a random sample of 149 biomedical articles published between 2015 and 2017 + + Description of assessed sample of articles, 2015–2017 Among the 155 randomly selected articles published between 2015 and 2017, we excluded 6 non-English language articles. Of the remaining 149, 68 (45.6% [95% confidence interval, 37.5% to 54.0%]) were publications in the research field of Medicine, with smaller numbers in the fields of Health Sciences (n = 28), Biology (n = 13), Infectious Disease (n = 16), and Brain Sciences (n = 24). Among 120 articles that were published in a journal with a 2013 impact factor, the median impact factor was 3.1 (interquartile range, 2.0–4.7). The majority of publications had some form of empirical data (118 of 149 [79.2% (95% confidence interval, 71.6% to 85.2%)]—n = 104 excluding case studies and case series, in which protocol and raw data sharing may not be pertinent, and n = 97 excluding also systematic reviews, meta-analyses and cost-effectiveness analyses in which replication in studies with different data would not be pertinent). Among the 149 eligible articles, there was one (0.7% [0.0% to 4.2%]) cost-effectiveness or decision analysis, 14 (9.4% [5.4% to 15.6%]) case studies or case series, four (2.7% [0.9% to 7.2%]) randomized clinical trials, six (4.0% [1.6% to 8.9%]) systematic reviews and/or meta-analyses, and 92 (61.7% [53.4% to 69.5%]) “other” articles with empirical data (including cross-sectional, case-control, cohort, and various other uncontrolled human or animal studies). Approximately one-fifth (20.8% [14.8% to 28.4%]) of the sample was classified as research without empirical data or models/modeling studies. There were 64 (43.0% [35.0% to 51.3%]) with a PubMed Central reference number (PMCID), of which 37 were also PubMed Central Open Access (PMCOA). + + Our sample of 155 articles ensured that 2015–2017 would be as well represented as previous years, accounting for the fact that the number of annual published biomedical articles increases approximately 5% per year (Table 4). The sample of 155 articles for the years 2015–2017 was at least 1.5 times that for any other 3-year period from 2000–2014. + + We also considered a previous sample of 441 English language journal articles published between 2000 and 2014 [7] for a comparison against the newer articles and for combined analyses of indicators in terms of open source data. Sampling for the recent set (2015–2017) of papers was done in a manner to produce a set that, given data availability, was as similar as possible to the original set (2000–2014) to enable comparison. + + Furthermore, the recent sample was limited to “articles” only. While this information was not in place for the original set, only 19 of the 441 articles in the original set were designated as “letters” in PubMed rather than articles [7].","Statistical analysis Using descriptive statistics, we characterized the indicators of transparency for the period 2015–2017. A priori established Fisher’s exact tests were used to examine differences between the 2000–2014 and 2015–2017 samples, PMCOA and non-PMCOA articles, and PMCID and non-PMCID articles; all statistical tests were two-tailed. As suggested during peer review of our work, we also analyzed potential changes over time for certain indicators of reproducibility and transparency. In particular, we plotted 3-year moving proportions for indicators with an adequate number of events against time. For instance, for the year 2013, we calculated the pro portion of articles with a data sharing statement between 2012 and 2014. These analyses can explore more gradual changes that could have occurred. Analyses were performed using R (Version, 3.2.3: The R Project for Statistical Computing). We used the P < 0.005 threshold for statistical significance [2, 42], calling results with P values 0.05 to 0.005 suggestive.","Funding: National Institute on Drug Abuse, National Institutes of Health https://projectreporter. nih.gov/project_info_description.cfm?aid= 9583616&icde=41489254 (grant number HHSN271201700041C). Received by KWB and JPAI. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Laura and John Arnold Foundation. Received by the Meta-Research Innovation Center at Stanford (METRICS). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. + + Competing interests: The authors have declared that no competing interests exist. + + Limitations Our study has certain limitations. Our evaluation relied on published biomedical research information. Therefore, it is possible that additional protocols, raw data, and clarifications on conflicts or funding could be established by contacting authors, journals, or sponsors. Second, our study relied on published records. This means that we based our determination of novelty on the information reported by investigators. For instance, it is possible that authors may have tried to spin their manuscript as being more novel than it really is in order to ensure publication. Although we used our best judgment to classify articles and two authors discussed uncertainties before agreeing upon a final classification, certain decisions were more subjective [7]. Moreover, since only one author conducted the data abstractions, we were unable to calculate any inter-rater reliability metrics. However, the primary abstractor for these data was the coprimary abstractor in a previous study evaluating the same indicators of transparency and reproducibility in articles published in the biomedical literature [7]. Therefore, the primary abstractor of the current evaluation has had extensive experience analyzing these indicators and had an already streamlined process to do so. Nevertheless, when determining study novelty and replication for articles from diverse biomedical fields, difficulty arose assessing whether study results were actually groundbreaking, full or partial replication efforts, or being fully replicated by subsequent studies. In order to account for these limitations, all uncertain ties were discussed by two investigators (JDW and JPAI). Third, we did not perform any sample size calculations. Our study evaluated multiple indicators that were all equally important, and they varied substantially in the proportion to which they were satisfied already by the articles in the 2000–2014 sample. The number of annual published biomedical articles increases at approximately 5% per year, and our sample ensured that 2015–2017 would be as well represented as previous years, accounting also for an increase in the volume of published literature over time. Fourth, we acknowledge that the sampling method for the recent set of articles was not identical to the sampling method for the original set of articles. However, when we applied the new enhanced field-classification method based on article-level classification to the original set of 441 articles, we found that 421 were in common between the original and new classifications. With approximately 95% overlap in biomedical definitions between the two samples, we are confident that our population of articles from which the sample was drawn and the sampling methods are comparable. Fifth, our analyses were based on a random sample of 149 biomedical articles published between 2015 and 2017. Therefore, we were unable to account for potential differences in reporting practices across various fields and subdisciplines. Future evaluations should assess these indicators within specific fields. Improvements over time may reflect improvements within specific fields, across many/all fields, and/or an increased representation of the most transparent fields in the more recent literature. Sixth, it is worth noting that we focused on key indicators of reproducibility and transparency that have been proposed as important to monitor. In particular, these indicators were established based on a series of five papers about research published in the Lancet [5]. However, these indicators serve as a proxy for transparency and reproducibility and do not capture all potential areas where open science advances may have been made. Finally, an additional limitation is that this study required manual examination of publications and coding of data. We are hopeful that algorithmic means to extract similar information from full text sources (such as PMCOA) can be developed to enable larger scale analyses in the future. + + As previously reported in our survey of biomedical research published between 2000 and 2014 [7], full articles with data and analyses were examined for statements of conflicts of interest, funding disclosures, and publicly available full protocols and data sets. In particular, we reviewed the final versions of the articles available online. For published articles without data and analyses, only statements of conflict and funding were investigated, since protocols, data sets, and reproducibility were not relevant [7]. These indicators, which were assessed in a previous evaluation of articles published in the biomedical literature between 2000 and 2014 [7], have been proposed as being important to monitor in relation to transparency and reproducibility. According to “Increasing value and reducing waste in research design, conduct, and analysis” [5], one of five papers on “Research: Increasing value, reducing waste” published in the Lancet, there are several key issues necessary to improve the research process. Under the recommendations section, the authors note that it is necessary to monitor the proportion of research studies “with publicly available (ideally preregistered) protocol and analysis plans, and proportion with raw data. . .,” “without conflicts of interests, as attested by declaration statements and then checked by reviewers,” and “undergoing rigorous independent replication and reproducibility checks” [5]. As suggested during peer review, we also determined the proportion of articles with (1) statements related to the sharing of script/code by searching the full text of the articles for the words “supporting,” “supplement,” “appendix,” “code,” and “script,” respectively, and (2) any supplemental materials.",PLOS,1,0,0,1,1,1,1,1,1,7 +40,"Is everything we eat associated with cancer? A systematic + cookbook review","We selected ingredients from random recipes included in The Boston Cooking-School Cook Book, available online at http://archive.org/details/bostoncookingsch00farmrich + + (see Supplementary Table 1 under “Supplemental data” in the online issue)",,,"Design: We selected 50 common ingredients from random recipes in a cookbook. PubMed queries identified recent studies that evaluated the relation of each ingredient to cancer risk. + + We selected ingredients from random recipes included in The Boston Cooking-School Cook Book + + A copy of the book was obtained in portable document format and viewed by using Skim version 1.3.17 (http://skim-app.sourceforge.net). The recipes (see Supplementary Table 1 under “Supplemental data” in the online issue) were selected at random by generating random numbers corresponding to cookbook page numbers using Microsoft Excel (Microsoft Corporation). The first recipe on each page selected was used; the page was passed over if there was no recipe. All unique ingredients within selected recipes were chosen for analysis. This process was repeated until 50 unique ingredients were selected. + + Study searches We performed literature searches using PubMed (http://www. ncbi.nlm.nih.gov/pubmed/) for studies investigating the relation of the selected ingredients to cancer risk using the following search terms: “risk factors”[MeSH Terms] AND “cancer”[sb] AND the singular and/or plural forms of the selected ingredient restricted to the title or abstract. + + Whenever <10 studies were retrieved for a given article, an attempt was made to obtain additional studies by searching for ingredient synonyms (eg, mutton for lamb, thymol for thyme), using articles explicitly referred to by the previously retrieved material, and broadening the original searches (searching simply by ingredient name AND “cancer”). Searches for relevant meta-analyses were performed in the same manner as for single studies, but adding the PubMed “meta-analysis” filter.","Information regarding author conclusions and relevant effect estimates were extracted. When >10 articles were found, we focused on the 10 most recent articles. + + Data extraction From each retrieved study or meta-analysis, data were extracted from the abstract regarding the ingredient and cancer type, authors’ conclusions regarding the risk of malignancy (increased risk, decreased risk, no effect, or borderline/other effect), the respective RR estimate (typically the HR for cohort studies or OR for case-control studies), and the exposure contrast to which it pertained, its 95% CI, and P value. When available, we used P values that were explicitly reported, including P values for trends. Standard reporting of these P values did not adjust for potential multiple testing. When not available, we estimated the P values from the reported point estimates and CIs of the effects, assuming no testing for trends across multiple different exposure levels. Whenever the effect estimate and P value were not available and could not be approximated from data available in the article abstract, the full text was then retrieved and examined in an attempt to obtain this information. When multiple potentially relevant effect estimates were available from a given study, the following criteria were applied in order of priority: the estimates most specific for the ingredient, the most broadly defined definition of malignancy (eg, colorectal compared with colon or rectal cancers), the most general patient subgroup, the most adjusted estimate, and that corresponding to the most extreme reported exposure contrast (ie, highest compared with lowest level of exposure). This allowed us to better compare effect estimates across ingredients and from individual studies with meta-analyses, because it is common practice in the literature to report comparisons of extreme exposure levels (22). In the case of estimates reported for multiple malignancies or patient subgroups of similar magnitude, the estimate or conclusion referred to first in the abstract was chosen for further analysis. If no estimate or conclusion was specifically referred to in the abstract, the same criteria described above were applied to the full text. Whenever available, effect estimates limited to the analysis of prospective cohort data were also separately extracted from the retrieved meta-analyses. One author performed data extraction (JDS) and discussed any uncertainties with the other author (JPAI) for arbitration.","Titles and abstracts of retrieved articles were then reviewed to select the 10 most recently published cohort or case-control studies investigating the relation between the ingredients and cancer risk. Ingredient derivatives and components (eg, orange juice) and ingredients analyzed as part of a broader diet specifically mentioned as a component of that diet were considered. + + For each ingredient, the most recent meta-analysis investigating the relation with a particular cancer was selected for analysis. In 2 meta-analyses that separately investigated associations with more than one different type or subtype of cancer, only the first type mentioned in the abstract was considered.","We summarized and compared data from the retrieved single studies and from the meta-analyses on the conclusions of the authors and on whether these were congruent with the presence of nominal statistical significance (P , 0.05) without adjustment for potential multiple testing. We also assessed the types and consistency of exposure contrasts used. Finally, we evaluated the distribution of P values (and corresponding standardized, z scores from the normal distribution) to examine whether there were any peaks of frequently reported P values and troughs of infrequently reported P values and the distribution of RRs to examine the median and IQR of reported effect sizes, to help highlight trends in the literature and potential biases. For P values (z scores), we also examined whether the results listed in the abstract differed from those listed only in the full text using a chi-square test. P values .0.05 are considered not nominally significant, whereas P values between 0.05 and 0.001 are considered to offer weak support, as previously proposed for epidemiologic analyses (29). In Bayesian terms, such P values generally do not correspond to very strong support, regardless of prior assumptions (23, 30). The main analyses evaluated all retrieved data from single studies and from meta-analyses. Sensitivity analyses focused on comparisons of meta-analyses against single studies on the same ingredient-cancer pairs (excluding single studies on associations for which no meta-analysis had been found and meta-analyses on associations for which no single study had been among the 10 more recent captured studies) and assessment of meta-analysis data only from prospective cohort studies. JMP version 9.0 (SAS Institute) was used to generate summary statistics, calculate z scores from the normal distribution, perform chi-square analysis, and draft figures.","There was no funding for this study. + + We aimed to examine whether results and their interpretations were generally more conservative in the meta-analyses than in the single studies and whether there were any hints of biases in the overall evidence. + + we evaluated the distribution of P values (and corresponding standardized, z scores from the normal distribution) to examine whether there were any peaks of frequently reported P values and troughs of infrequently reported P values and the distribution of RRs to examine the median and IQR of reported effect sizes, to help highlight trends in the literature and potential biases. + + No conflicts of interest were reported by either author.",The American Journal of Clinical Nutrition,1,0,0,1,1,1,1,1,1,7 +41,"Systematic evaluation of environmental and + behavioural factors associated with all-cause + mortality in the United States National Health + and Nutrition Examination Survey","see Table 1 and Supplementary Table S1 (available as Supplementary data at IJE online). + + Supplementary Data Supplementary data are available at IJE online.",,,"We selected 249 factors from a set of all possible factors based on their presence in both the 1999– 2002 and 2003–04 surveys and linkage with at least 20 deceased participants. + + We downloaded NHANES laboratory, questionnaire and National Death Index (NDI) linked mortality data for 1999–00, 2001–02 and 2003–04 surveys. + + Figure 1 depicts our procedure. We assessed a total of 249 environmental and behavioural factors, see Table 1 and Supplementary Table S1 (available as Supplementary data at IJE online).","Mortality information was collected from the date of the survey participation through 31 December 2006 and ascertained via a probabilistic match between NHANES and NDI death certificate information. The NDI matches individuals on personal and demographic criteria, such as social security number and date of birth, and its performance has been described elsewhere (e.g. ref 12). Overall, 9555, 11 021, and 10 100 participants were followed in the 1999–2000, 2001–02 and 2003–04 surveys, respectively, with 611, 470 and 276 assumed death events, respectively. We used the 1999–2000 and 2001–02 surveys to scan for factors associated with all-cause mortality (‘training’ dataset) and reserved the 2003–04 survey to replicate findings from the training set. Factors such as age, sex, race/ethnicity, educational attainment, occupation and income are hypothesized to be associated with both mortality and environmental/behavioural factors and we estimated their association with mortality.13 Further, these sociodemographic factors may also confound associations of environmental/behavioural factors with death. In NHANES, race/ethnicity was coded as Non-Hispanic White (‘White’), Mexican American (‘Mexican’), Non-Hispanic Black (‘Black’), Other Hispanic and Other. We coded educational attainment as less than high school, high school equivalent and greater than high school education. We estimated socioeconomic status (SES) as the categorical quintile of income/poverty index as previously described.9,10 We estimated occupation in categories corresponding to white-collar and professional (reference group), white-collar and semi-routine (e.g. technicians), blue-collar and high-skill (e.g mechanics, construction trades and military) and blue-collar and semi-routine (e.g. personal services, farmworkers) as previously described. + + Next, from these 406, 457 and 564 factors, we identified a total of 347 that were present in all three surveys. Of these 347 factors, we found 249 that could be linked with at least 20 deceased participants in the training (1999–2000 and 2001–02 surveys) and testing (2003– 04) datasets independently (Figure 1A, B). + + The 58 self-reported food and nutrient consumption factors were determined from one in-person 24-h interview (1999–2000, 2001–02) or two 24-h (2003– 04) in-person and telephone interviews using the United States Department of Agriculture and Department of Health and Human Services food recall questionnaires.17–20 These food and nutrient consumption factors were linearly adjusted by total caloric intake and z-standardized.","These factors were either (i) information on behaviours, such as self-reported dietary intake (from a food frequency questionnaire), self-reported alcohol consumption, self-reported smoking, body mass index (BMI) from a physical examination or self-reported physical activity; or (ii) physical/chemical biomarkers of external exposures measured in serum or urine, such as blood lead concentration. Table 1 shows examples of factors and Table S1 (available as Supplementary data at IJE online) provides a listing of all factors. There were a total of 416, 467 and 574 factors in the 1999– 2000, 2001–02 and 2003–04 surveys, respectively. + + Behavioural factors included three surveying alcohol consumption, one on ‘street drug’ use, 58 factors on food and nutrient consumption, 23 on smoking-related behaviours [e.g. ‘current or past smoker? (versus never smoker)’, ‘does anyone in your household smoke (yes/no)?’)] one on physical activity and three on social support (e.g. ‘have anyone to help?’, ‘how many close friends do you have?’). We discuss these variables in the following. First, the three factors on alcohol consumption included five or more drinks per day, number of drinks per day in last month [z-standardized (divided by the population standard deviation to facilitate comparison of effects) ordinal factor] and how many total days drinking per year (z-standardized ordinal factor). The 23 smoking factors included four regarding family smoking behaviour and 19 on personal smoking behaviour. The four family smoking behaviour factors included any smokers in the household (referent group: no smokers in household), total number of cigarette smokers in the household (z-standardized ordinal factor) and the total number of cigarettes smoked at home (z-standardized ordinal factor). + + The 18 factors regarding personal behaviour included a categorical factor on current or past smoking (analyzed as a two-level categorical factor with never smoking as a referent) and four on ever-used cigars, chewing tobacco, snuff and pipes (referent group: never smoked the item). Specifically for current and past smokers, factors included the number of cigarettes smoked just before quitting (z-standardized ordinal factor), how many years smoked (z-standardized ordinal factor), number of cigarettes currently smoking (z-standardized ordinal factor), the average number of cigarettes smoked per day in the past month (z-standardized ordinal factor) and an estimated nicotine, tar and carbon monoxide content of smoked item (z-standardized ordinal factors). Other factors for current smokers included years since started smoking (z-standardized ordinal variable). Physical activity was estimated by deriving metabolic equivalents for self-reported leisure and normal-time activities15 and treated as an ordinal factor based on Health.gov physical activity guideline categories for no aerobic activity, low activity (medium intensity activity greater than baseline but fewer than 150 min/week), moderate activity (150 to 300 medium intensity min/ week) and high activity (4300 min medium intensive activity per week or4150 min high intensity per week) as previously described.10,16 + + We considered BMI as another behavioural four-level categorical factor. We divided BMI into five categories as previously described,21 including <18.5 kg/m2, 518.5 and <25 kg/m2, 525 and <30 kg/m2, 530 and <35 kg/m2, and 535 kg/m2. The 518.5 and <25 kg/m2 category was the reference group. The 156 factors were serum or urine-based measures of environmental exposure, including infectious agents, environmental chemicals and nutrients. Broadly, these included a serum marker of nicotine metabolism (cotinine), dioxins (n ¼ 7 markers), furans (n ¼ 10), heavy metals (n ¼ 15), hydrocarbons (n ¼ 21), nutrients (n ¼ 15), polychlorinated biphenyls (n ¼ 34), pesticides (n ¼ 22), phthalates (n ¼ 12), oestrogenic compounds (n ¼ 6), bacterial (n ¼ 2) and viral organisms (n ¼ 6). With the exception of assays detecting infectious agents (which were positive/negative assays), factors were continuous in scale. Continuous biomarker factors that had a rightskewed distribution were log-transformed and z-standardized as previously described.9,10 Different measures of environmental and behavioural factors had different numbers of eligible participants for mortality follow-up assessment (Figure 1B). In the training surveys (1999–2002), there were 330– 6008 eligible participants (with 26–655 death events). For the replication survey (2003–04), there were 177–3258 eligible participants (with 20–202 deaths) (Supplementary Table S1, available as Supplementary data at IJE online).","We used Cox proportional hazards regression to associate 249 factors with all-cause mortality while adjusting for sociodemographic factors on data in the 1999–2000 and 2001–02 surveys (median 5.5 follow-up years). We controlled for multiple comparisons with the false discovery rate (FDR) and validated significant findings in the 2003–04 survey (median 2.8 follow-up years). + + We evaluated the correlation pattern of validated factors + and built a multivariable model to identify their independent contribution to mortality. + + We used the R-project survival and survey library for all analyses and accounted for clusters pseudo-strata, pseudo-sampling units and participant weights to accommodate the complex sampling of the data.22,23 Estimates were verified with STATA.24 + + Systematic scan of environmental and behavioural factors associated with all-cause mortality We associated each of the 249 factors to all-cause mortality serially using proportional hazards (Cox) regression, while adjusting for sociodemographic attributes described above, including age, sex, an estimate of SES (categorical quintiles of poverty to income ratio), educational attainment, occupation and race/ ethnicity in the training surveys, the 1999–2002 NHANES (the ‘training’ step, Figure 1C). We used the FDR to correct for multiple hypotheses as described previously9–11 (Figure 1D). The FDR is the estimated proportion of the false discoveries made over the number of total discoveries made at a given significance level. We used a permutation simulation method to estimate the numerator, the number of false positives incurred at a significance threshold as documented earlier.9,11,25 Specifically, to estimate the expected number of false positives, we permuted the censorship and follow-up time variable within each stratum of the survey; in other words, participants were randomly assigned mortality status. Then, we re-ran survival analyses for each of the 249 factors. We repeated this process 100 times to attain a distribution of P-values drawn from the null distribution. The permutation method accounts for the correlation amongst factors.26 We set an FDR threshold of 5% to identify findings in the training step for validation in the testing survey. For each factor that passed the FDR threshold in the training step, we assessed violation of proportional hazards by examining inter action between the factor and follow-up time. We deemed a factor tentatively validated if it had achieved FDR < 5% in the training step, specifically bi-serial correlations between binary factors and Spearman correlations when considering quantitative factors. We visualized these pairwise correlations in a heat map and arranged the factors using a hierarchical clustering algorithm27 as previously described.11 + We computed the power for detection of factors at P-value corresponding to FDR <5% (equivalent to P ¼ 0.0003) for sample sizes corresponding to each factor tested at a range of adjusted HR of (1.1, 1.3, 1.5, 1.7 and 1.9) with the powerSurvEpi R library.28 Specifically, this library implements methods that take into account the correlation among the factor and adjustment co-variates29,30 sample size and number of death events to estimate power at a given P-value threshold and HR. We then estimated how many factors we would detect if every one of the 249 were associated with all-cause mortality for FDR <5% (P <0.0003) and each HR above by totalling the power estimations for each factor tested (Supplementary Table S2, available as Supplementary data at IJE online). At HRs of 1.1, 1.3, 1.5, 1.7 and 1.9, we estimated we would find 7 out of 249 (3%), 120/249 (49%), 194/249 (79%), 221/249 (89%) and 233/249 (94%), respectively, if all 249 factors were associated with all-cause mortality. We concluded we were adequately powered to detect modest and large associations (HR 41.3 or HR <0.8), but not weak associations with all-cause mortality.","Funding This work was supported by the National Heart, Lung, and Blood Institute [T32 HL007034] to C.J.P., and the National Institute of Diabetes and Digestive Diseases [K24 DK085446] to G.M.C. and [K23 DK089086] to J.T.L. + + Conflict of interest: None declared.",International Journal of Epidemiology,1,0,0,1,1,1,1,1,1,7 +42,"Low replicability can support robust and efficient + science","Reporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. + + Data availability MATLAB code for the simulation and all results are available at https://git.io/fhHjg. A reporting summary for this Article is available as a Supplementary Information file. + + Additional information Supplementary information is available for this paper at https://doi.org/10.1038/s41467- 019-14203-0.",,NATURE,"Here we examine potential solutions by modeling a scientific community under various different replication regimes. In one regime, all findings are replicated before publication to guard against subsequent replication failures. In an alternative regime, individual studies are published and are replicated after publication, but only if they attract the community’s interest. + + Methods Simulation. All simulations involved 1000 replications. The simulation comprised three main components. The landscape of true effects was modelded by a 10 ´ 10 grid that represented the ground truth. For discovery-oriented research, the grid was randomly initialized for each replication to 0 (H0) or 1 (H1), with PðH1Þ ¼ :09 (Fig. 3a). The two dimensions of the grid are arbitrary but can be taken to represent potential independent and dependent variables, respectively. Each grid cell therefore involves a unique combination of an experimental intervention and an outcome measure, and the ground truth in that cell (1 or 0) can be understood as presence or absence, respectively, of a difference to a presumed control condition. For theory-testing research, the same landscape was used but all effects were randomly clustered within four rows and columns centered on a randomly chosen centroid (subject to the constraint that all effects fit within the 10 ´ 10 grid; Fig. 6). The second component was a decision module to determine scientific interest. The distribution of citations for 1665 articles published in psychology in 2014 (downloaded from Scopus in April 2018) was fit by a generalized Pareto distribution (shape parameter, k ¼ 0:115; scale parameter, σ ¼ 8:71; and location parameter, θ ¼ 0; Fig. 2). For the simulations reported here, the 90th percentile of the fitted distribution (q ¼ 22:98 citations) was used as threshold in a logistic transfer function: + PðIkÞ ¼ 1 + 1 þ e ðnk qÞ=t ; + where PðIkÞ is the probability that finding k would be deemed interesting, nk represents the finding’s citation count, and t 2 f1; 5; 10g the temperature of the logistic function. (The reciprocal of the temperature is known as the gain of the function.) Each nk represented a random sample from the best-fitting Pareto distribution. Other cutoff values of q were explored, spanning the range from the 10th through the 90th percentile, which did not materially affect the results (Supplementary Figs. 1 and 2). The final component was an experimental module to run and interpret experiments. Each simulation run (that is, each of 1000 replications) involved a first round of 100 experiments. Each experiment was simulated by sampling observations from a normal distribution with mean equal to the value of the targeted cell in the grid of ground truths (0 or 1) and standard deviation σ. + + For discovery-oriented research, the targeted cell in the landscape was chosen randomly (Fig. 3b). Theory-testing research also used a 10 ´ 10 grid to represent the gound truth, but all true effects (i.e., H1) were constrained to fall within a 4 ´ 4 grid that straddled a randomly chosen centroid. For each simulated experiment, the targeted cell was chosen randomly from another 4 ´ 4 grid of predicted effects whose centroid was a prescribed distance from the centroid of true effects. The parameter ρ determined the proximity between the centroid of true effects and the centroid of the predicted effects targeted by theory-testing research (Fig. 6). When ρ ¼ 1, the centroids were identical, and for ρ < 1, the theory’s centroid was moved ð1 ρÞ ´ 9 rows and columns away from the true centroid (subject to the constraint that all cells predicted by the theory had to fit within the 10 ´ 10 grid). A perfect theory (ρ ¼ 1) thus predicted effects to be present in precisely the same area in which they actually occurred, whereas a poor theory (ρ ’ 0) would search for effects in a place where none actually occurred.","Responses were collected after each talk until a final set of 102 responses was obtained. Each item involved a quasi-continuous scale (14 cm horizontal line) with marked end points. Responses were indicated by placing a tick mark or cross along the scale. Responses were scored to a resolution of 0.5 cm (minimum 0, maximum 14, and midpoint 7). Items, scale end points, and summary of responses are shown in Table 1.","The sample size was determined by G*Power42 to achieve the desired statistical power. Power was either .5 or .8, mapping into sample sizes of n ¼ f18; 34g. For frequentist analyses, σ ¼ 2:0 and α ¼ :05 in all simulations. For Bayesian analyses, , n ¼ 34 and σ ¼ 1:5 throughout, which achieved a “power” of ~0.8 with BF10 ¼ 3. + + Expert survey. Attendees of a symposium on statistical and conceptual issues relating to replicability at the International Meeting of the Psychonomic Society in Amsterdam (May 2018) were given the opportunity to respond to a seven item single-page survey that was distributed before the symposium started.","An experiment was declared “significant” if the single-sample t-statistic exceeded the appropriate two-tailed critical value for α ¼ :05 or if BF10 > 3, Bayesian single-sample t-test as described in ref. 28. + + The first round of 100 experiments was followed by replications as determined by the applicable regime (Fig. 1). Thus, under the private regime, any significant result from the first round was replicated, whereas under the public regime, significant results were replicated with a probability proportional to their scientific interest as determined by Eq. (1). (In the simulation that also examined null effects, see Fig. 8, replication decisions were also based on Bayes Factors for the null hypothesis).","Competing interests The authors declare no competing interests. + + Acknowledgements The authors do not have funding to acknowledge","NATURE + + Peer review information Nature Communications thanks Rolf Ulrich and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.",1,0,1,1,1,1,1,1,1,8 +43,"Genome-wide CRISPR–Cas9 screening reveals + ubiquitous T cell cancer targeting via the + monomorphic MHC class I-related protein MR1","Online content Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41590- 019-0578-8. + + Reporting Summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. + + Data availability The datasets generated during the current study are available from the corresponding author upon reasonable request. + + Additional information Supplementary information is available for this paper at https://doi.org/10.1038/ s41590-019-0578-8.",,NATURE,"Here, we use genome-wide CRISPR–Cas9 screening to establish that a T cell receptor (TCR) recognized and killed most human cancer types via the monomorphic MHC class I-related protein, MR1, while remaining inert to noncancerous cells. + + Neither blinding nor randomization was performed for the in vivo studies.","Ovarian cancer ascites were sourced through the Wales Cancer Bank (ethics reference WCB14/004) from a patient with stage 3 chemotherapy resistant (50001389) carcinoma at Velindre Cancer Centre. Blood was sourced from the Welsh Blood Service. The use of human blood was approved by the School of Medicine Research Ethics Committee (reference 18/56). All human blood was procured and handled in accordance with the guidelines of Cardif University to conform to the United Kingdom Human Tissue Act 2004. All samples were taken with informed consent from participants. + + Cell lines. Cell lines were regularly tested for mycoplasma, and cultured on the basis of ATCC guidelines; breast adenocarcinomas MCF-7 (HTB-22); prostate adenocarcinoma LnCAP (CRL-1740); cervical adenocarcinomas HeLa (CCL-2) and SiHa (HTB-36); acute lymphoblastic leukemia MOLT3 (CRL-1552); chronic myeloid leukemia K562 (CRL-3344); myeloma/plasmacytoma U266 (TIB-196); osteosarcoma U-2 OS (HTB-96); immortalized embryonic kidney cell HEK293T (CRL-1573); acute monocytic leukemia THP-1 (TIB-202); lung carcinoma A549 (CCL-185); acute T cell leukemia Jurkat (TIB-152); colorectal adenocarcinoma COLO 205 (CCL-222); and ovarian carcinoma A2780 (ECACC 93112519 for culture guidelines). Melanomas FM-45, MM909.11 and MM909.24, and renal cell carcinoma RCC17 were sourced from the CCIT, and MEL 624 from in-house, with all being cultured in R10 (RPMI 1640 supplemented with 10% fetal bovine serum (FBS), 100Uml−1 penicillin, 100μgml−1 streptomycin and 2mM l-glutamine (Life Technologies) at 37 °C as adherent monolayers, passaged when 50–80% confluent using 2mM EDTA D-PBS to detach cells. C1R and lymphoblastoid cell line SAR26 were sourced or generated in-house and cultured in R10 as suspension cells. The primary epithelial ovarian cancer cell line EOC031 was generated from ascites following previous guidelines28 with the following amendments: the ascites were diluted 1:10 with R10 and centrifuged to collect the cells, which were subsequently depleted of red blood cells and debris using standard density gradient centrifugation. DMEM-F12 media (Life Technologies) was supplemented as for R10 with the addition of 5% human serum. Once cells had attached to the flasks and grown for 3d, fibroblasts were removed by incubation with trypsin/ EDTA for 1min leaving the ovarian cancer cells for assays. Primary melanoma lines MM909.11, MM909.20 and MM909.21 were sourced from the CCIT and used directly from cryopreserved samples for killing assays without prior culture. Normal/healthy cells and their proprietary culture media were obtained from Sciencell: SMC3 (colonic smooth muscle); CIL-1 (nonpigmented bronchial ciliary epithelium); HH (hepatocyte); pulmonary alveolar epithelia; melanocytes; renal epithelia; and pancreatic stellate cells. MRC5s (fibroblast) were sourced locally and cultured as described by the ATCC. Intestinal epithelia and their media were sourced from Lonza. Dendritic cells and Langerhans cells were generated from CD14+ cells purified from PBMCs using magnetic beads (Miltenyi Biotec). Briefly, both immature dendritic cells and Langerhans cells were differentiated with GM-CSF (20ngml−1 ) and IL-4 (10ngml−1 ) sourced from Miltenyi Biotec, with Langerhans cells also receiving 20ngml−1 of TGFβ (Miltenyi Biotec), for 7–10d before maturation for 48h with 20ngml−1 of tumor necrosis factor (TNF) (Miltenyi Biotec). Healthy T and B cells were purified from PBMCs using CD3 (negative purification) or CD19 magnetic beads (Miltenyi Biotec), then activated with 1μgml−1 phytohemagglutinin or 1μM of TLR9 ligand ODN 2006 (Miltenyi Biotec), respectively, for 24h. Mouse anti-human CD69 (clone FN50, BioLegend) was used to confirm activation. + + T cell clones. HLA-A*0201 restricted clone MEL5, recognizing peptides EAAGIGILTV and ELAGIGILTV (heteroclitic L at position 2) from Melan A29,30, and a canonical MAIT clone were cultured as described previously31. Clone 40E.22 was confirmed as CD1a-restricted using CRISPR–Cas9 ablation of CD1a/b/c/d (data not shown). + + M. smegmatis and S. Typhimurium. Bacterium was grown and used to load phagocytic A549 as previously described. + + MC.7.G5 isolation and cloning. PBMCs were isolated by standard density gradient centrifugation and labeled with proliferation dye carboxyfluorescein succinimidyl ester (CFSE) (eBiosciences, Thermo Fisher Scientific) and cultured for 2weeks with A549 cells in priming medium (R10 supplemented with 20 IUml−1 IL-2 (Proleukin; Prometheus), 1× MEM nonessential amino acids, 1mM sodium pyruvate and 10mM HEPES buffer (Thermo Fisher Scientific). Primed PBMCs were bulk sorted for CFSElow viable CD3+ CD4neg cells on a BD FACS Aria (BD Biosciences) and cloned by plating 0.3 cells per well in 96U-well plates. + + T cell activation assays. T cells were rested in R5 (as for R10 with 5% FBS) for 24h before assay. Typically, 3×104 T cells and 6×104 target cells were used per well in R5 and incubated overnight, with supernatants collected for an ELISA (MIP-1β or TNF), which was performed according to the manufacturer’s instructions (R&D Systems). For antibody blocking assays, target cells were preincubated with anti-MR1 clone 26.5, BioLegend), pan anti-MHC I (clone W6/32, BioLegend) or pan anti-MHC II (clone Tü39, BioLegend) before incubating with T cells. Staining for surface CD107a (ref. 32) using an anti-CD107a PE (H4A3, BD Biosciences), and intracellularly with antibodies for anti-TNF PE-Vio770 (clone cA2, Miltenyi Biotec) and anti-IFN-γ (clone 45–15, Miltenyi Biotec), was performed as described previously31, following activation for 4h at a T cell to target cell ratio of 1:1. Intracellular cytokine staining was performed according to the manufacturer’s instructions using a Cytofix/Cytoperm kit, GolgiPlug and GolgiStop (BD Biosciences). For TNF-processing inhibitor TAPI-0 (Santa Cruz Biotechnology) assays33, T cells and target cells were co-incubated for 4h with 30μM TAPI-0 and antibody directed against TNF (clone cA2, Miltenyi Biotec). CD107a antibody (clone H4A3, Miltenyi Biotec Ltd.) was also included at the start of the assay to detect activation-induced degranulation of cytotoxic T cells32. Following incubation, cells were washed and stained with Fixable Live/Dead Violet Dye and antibodies against T cell surface markers. Gating strategy and isotype antibody (as recommended by the manufacturer of the primary antibodies) control experiments for the TAPI-0 assay are shown in Supplementary Fig. 7. Ac-6-FP (Schircks Laboratories) was reconstituted in DMSO to 50mgml−1 and stored at −20 °C protected from light. For MR1 loading, Ac-6-FP was incubated overnight at 37 °C and 5% CO2 with target cells in their respective media. + + Cytotoxicity assays. For cytotoxicity assays, target cells were labeled with chromium-51 (Perkin Elmer) then co-incubated with T cells at various T cell to target ratios for 6 or 18h and specific lysis calculated, as described previously31. For flow-based killing assays 5,000–10,000 cancer or healthy cell lines were plated in 96U-well plates, and MC.7.G5 added to give the desired T cell to cell line ratio (experimental wells). The cells were cocultured in 200μl of target-cell media supplemented with 20 IU of IL-2 and 25ngml−1 of IL-15. Target cells (control wells), MC.7.G5 and CSFE CIRs were also cultured alone to aid analysis. The cells were incubated for 48h or 7d and fed (50% media change) twice for the latter. Before collection, either BD negative CompBeads (BD Biosciences) (1 drop in 100μl of PBS then 25μl per well) or 0.1×106 CFSE labeled (0.1μM) CIR cells were added to each well to allow the number of target cells that remained in experimental and control wells to quantified. The cells were washed three times with chilled D-PBS EDTA (2mM) then stained in the assay plates with Fixable Live/Dead Violet Dye (VIVID, Thermo Fisher Scientific) then CD3 PerCP (clone UCHT1, BioLegend) and/or anti-TRBV25.1 APC TCR (TRBV11 Arden nomenclature: clone C21, Beckman Coulter) to allow dead cells and T cells to be gated out, leaving viable target cells for analyses (Supplementary Fig. 7). Percentage killing was calculated using the following equation: + Percentage killing ¼ 100 - experimental target cell events|experimental bead or CFSE C1R events control target cell events|control bead or CFSE CIR events ¬ * 100 ¬ + + Flow cytometry. Cells were stained with Fixable Live/Dead Violet Dye VIVID and the following surface antibodies: pan-αβ TCR PE (clone IP26, BioLegend), pan-γδ TCR-FITC (clone REA591, Miltenyi Biotec), CD3 PerCP (clone UCHT1), CD4 APC (clone VIT4, Miltenyi Biotec), CD8 PE (clone BW135/80, Miltenyi Biotec), rat CD2 PE (clone OX-34, BioLegend) and MR1 PE (clone 26.5, BioLegend). For staining with MR1 PE, FcR Block (Miltenyi Biotec) was used according to manufacturer’s instructions and isotype antibody as described previously24. For tetramer staining, MR1 monomers were provided by J.R., and pMHC monomers produced in-house. Tetramers were assembled and used for optimized staining as described previously31. Cells were gated on lymphocytes (FSC-A versus SSC-A), single cells (FSC-A versus FSC-H), then viable cells (marker of choice versus VIVID) as shown in Supplementary Fig. 7. Data were acquired on a BD FACS Canto II (BD Biosciences) and analyzed with FlowJo software (Tree Star). + + MR1 knockout and transgene expression. MR1 single guide (sg)RNA and CRISPR–Cas9 lentivirus was produced and used as described previously24. The native MR1 transgene was cloned into the second generation pRRL.sin.cppt. pgk-gfp.wpre lentivector backbone developed by D. Trono’s laboratory (Addgene plasmid no. 12252) devoid of the human PGK promoter and GFP cDNA. The codon-optimized MR1 K43A transgene was cloned into the third generation pELNS vector (kindly provided by J. Riley, University of Pennsylvania) devoid of GFP cDNA. Lentiviral particles for native MR1 and MR1 K43A were produced by calcium chloride transfection of HEK293T cells, as described for MR1 sgRNA24. Target cells were spinfected in the presence of 8μgml−1 polybrene; 500g for 2h at 37 °C (ref. 21). Anti-MR1 PE (clone 26.5, BioLegend)-positive cells were magnetically enriched using anti-PE magnetic beads according to the manufacturer’s instructions (Miltenyi Biotec) + + TCR sequencing and transduction. MC.7.G5 TCR was sequenced in-house using the SMARTer RACE kit (Takara Bio USA) and two-step polymerase chain reaction using universal forward primers and reverse primers specific for TCR-α and TCR-β constant regions. The TCR was then synthesized with codon optimization (Genewiz), with full-length α and β TCR chains separated by a ‘self-cleaving’ T2A sequence34 and cloned into the third generation pELNS lentiviral vector containing rCD2 as a comarker (kindly provided by J. Riley, University of Pennsylvania); the TCR β-chain was separated from rCD2 by a P2A self-cleavage sequence (Supplementary Fig. 6). MC.7.G5 TCR-rCD2 pELNs was used to produce virus with envelope plasmid pMD2.G (Addgene plasmid no. 12259), and packaging plasmids pMDLg/pRRE (Addgene plasmid no. 12251) and pRSV-Rev (Addgene plasmid no. 12253) (all gifts from D. Trono). Lentiviral particles were generated by calcium chloride transfection of HEK293T cells and the supernatant 0.4-μm filtered then concentrated by ultracentrifugation (150,000g for 2h at 4 °C). The concentrated lentiviral supernatants were resuspended in T cell transduction media (as for priming media but with 20% FBS and 25ngml−1 of IL-15 (Miltenyi Biotec)), used immediately or stored at −80 °C and only defrosted once before transduction. Posttherapy PBMCs were obtained from patients (receiving tumor infiltrating therapy) MM909.11 and MM909.24 and CD8 and CD4 T cells were purified by magnetic enrichment (Miltenyi Biotec). T cells (1–1.5×106 ) were then activated by overnight incubation with CD3/CD28 beads (Dynabeads; Thermo Fisher Scientific) at a 3:1 bead to T cell ratio in 2ml of T cell transduction media in 24-well plates. The following day, 900μl of the media was removed and replaced with 500μl of MC.7.G5 TCR lentivirus supernatant in the presence of 5μgml−1 polybrene (Santa Cruz Biotechnology). Seven days later, T cells that had taken up the virus were magnetically enriched with anti-rCD2 PE conjugated antibody and anti-PE magnetic beads, according to the manufacturer’s instructions (Miltenyi Biotec). Fourteen days posttransduction, T cells were expanded as described previously31 and used for assays after 2weeks. + + Whole-genome GeCKO v.2 screening. Lentiviral particles for the GeCKO v.2 library (plasmid kindly provided by F. Zhang21 (Addgene plasmid no. 1000000048)). The GeCKO v.2 library consists of 123,411 sgRNAs targeting 19,050 protein-coding genes (six sgRNAs per gene) and 1,864 microRNAs (four sgRNAs per microRNA) and was used as lentivirus to transduce the target-cell line HEK293T. HEK293T cells (4×107 ) were transduced with a multiplicity of infection of 0.4 to provide 100× coverage of each sublibrary. Cells that had taken up the lentivirus were selected under puromycin. After 14d, half the library-containing cells were frozen as a control. MC.7.G5 was added to the remaining transduced HEK293T cells at a T cell to HEK293T ratio of 0.25:1 in 20 IU of IL-2 media. After 14d, MC.7.G5 was added again at a 0.5:1 ratio. After 7d the HEK293T cells were used for sequencing. Genomic DNA from 3×107 of the HEK293T cells (unselected control and selected with MC.7.G5) was isolated (GenElute Mammalian Genomic DNA Miniprep Kit, Sigma-Aldrich). The entirety of isolated genomic DNA (2.5μg per 50μl reaction) was used for subsequent PCR, to ensure capturing the full representation of the libraries. The two-step PCR was performed as described previously22,35, using HPLC-purified primers and NEBNext High Fidelity PCR MasterMix (New England Biolabs). The <300base pair PCR products were subsequently isolated from the agarose gel and sequenced on a HiSeq instrument (Illumina) with 80 cycles of read 1 (to determine the sequence of sgRNAs) and 8 cycles of read 2 (to identify sample-specific barcode). Analysis of enriched guides was performed using MAGeCK analysis. + + Cell stress assays. Cells were collected from culture then incubated with 100– 200μM of tBHP or H202 for 1h in R10, followed by staining with CellROX green reagent to detect ROS, according to the manufacturer’s instructions (Thermo Fisher Scientific). Cells were also stained with viability stain VIVID as above. Cesium source gamma irradiation of cells was performed using a Gamma Cell irradiator. M. smeg infection of healthy lung epithelial cells was performed as for A549 cells described above. + + Experiments were performed under United Kingdom Home Office approved projects 30/3188 and P2FB675AB conducted in compliance with the United Kingdom Home Office Guidance on the Operation of the Animals (Scientific Procedures) Act 1986. Jurkat cell expressing DsRed-Express2 were generated using pELNS vector and lentiviral particles, as described above, then cloned. Before in vivo transfer JurkatDsRed cells and MC.7.G5 were depleted of dead or dying cells by standard density gradient centrifugation. Jurkat cells (3×106 ) were engrafted first, followed by 1.5×106 MC.7.G5 cells 7d later. Cells were injected into the tail vein of mice using a 29G BD microfine syringe in 100μl of PBS. Mice that did not receive cells were injected with PBS. Each mouse (±T cells) received 5×104 IU of IL-2 and 50μg of IL-15 (details as above) via injection into the peritoneal cavity on the day of T cell transfer, and every 48h for the duration of the experiment. Bone marrow was collected from the tibia and fibula, and splenocytes prepared for staining using standard density gradient centrifugation. Cells were stained with the viable dye VIVID, followed by antibodies for human CD3 and CD8 (details as above), and anti-human CD45 APC-Cy7 (clone HI30, BioLegend) and anti-mouse/human CD11b PE-Cy7 (clone M1/70, BD Biosciences) as described previously37. The gating strategy for analyses of flow cytometry data is shown in Supplementary Fig. 8. For Jurkat cotransfer experiments, MR1−/− DsRed-Express2+ Jurkat cells were first generated as described above using the MR1 CRISPR–Cas9, followed by cloning. Wild-type and MR1−/− (DsRed-Express2+) Jurkat cells (2×106 ) were transferred to the same mouse, then MC.7.G5 T cells (3×106 ) were added 7d later to the +T cell group. Splenocytes were collected at 25d following T cell transfer, then incubated with mouse and human FcR block (Miltenyi Biotec), stained with VIVID and antibodies for CD3, CD8, CD45, as above, and also with mouse anti human pan HLA class I (clone W6/32, BioLegend). Survival of mice with Jurkat cells was assessed by monitoring body weight; mice were killed when they had lost ≥15% of their initial body weight, according to United Kingdom Home Office stipulation.","Patients with stage IV metastatic melanoma (MM909.11 and MM909.24) underwent rapid tumor-infiltrating lymphocyte therapy at the Centre for Cancer Immunotherapy (CCIT), Herlev Hospital (ethics reference EudraCT no. 2008-008141-20). + + Mouse experiments. Female JAX NOD scid gamma (NSG) were purchased from Charles Rivers at 6–7weeks of age, housed under specific pathogen-free conditions and experiments initiated within 1week of arrival. + + The number of mice used in each group is indicated in the respective figure legend.","A two-sided nonparametric two-sample Kolmogorov–Smirnov test was used for Jurkat cell burden in NSG mice. The log-rank two-sided P value and hazard ratio were calculated using the MatSurv survival analysis function in Matlab, available at https://www.github.com/aebergl/MatSurv",Competing interests Cardiff University has filed patents based on these findings.,"NATURE + + Peer review information Zoltan Fehervari was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.",1,0,1,1,1,1,1,1,1,8 +44,"Ileal-lymphoid-nodular hyperplasia, non-specific colitis, and pervasive developmental disorder in children",,,Lancet,"Children underwent + gastroenterological, neurological, and developmental + assessment and review of developmental records. + Ileocolonoscopy and biopsy sampling, magnetic-resonance + imaging (MRI), electroencephalography (EEG), and lumbar + puncture were done under sedation. Barium follow-through + radiography was done where possible. Biochemical, + haematological, and immunological profiles were + examined.","We took histories, including details of immunisations and exposure to infectious diseases, and assessed the children. In 11 cases the history was obtained by the senior clinician (JW-S). Neurological and psychiatric assessments were done by consultant staff (PH, MB) with HMS-4 criteria.1 Developmental histories included a review of prospective developmental records from parents, health visitors, and general practitioners. Four children did not undergo psychiatric assessment in hospital; all had been assessed professionally elsewhere, so these assessments were used as the basis for their behavioural diagnosis. + After bowel preparation, ileocolonoscopy was performed by SHM or MAT under sedation with midazolam and pethidine. Paired frozen and formalin-fixed mucosal biopsy samples were taken from the terminal ileum; ascending, transverse, descending, and sigmoid colons, and from the rectum. The procedure was recorded by video or still images, and were compared with images of the previous seven consecutive paediatric colonoscopies (four normal colonoscopies and three on children with ulcerative colitis), in which the physician reported normal appearances in the terminal ileum. Barium follow-through radiography was possible in some cases. + Also under sedation, cerebral magnetic-resonance imaging (MRI), electroencephalography (EEG) including visual, brain stem auditory, and sensory evoked potentials (where compliance made these possible), and lumbar puncture were done. + + Thyroid function, serum long-chain fatty acids, and cerebrospinal-fluid lactate were measured to exclude known causes of childhood neurodegenerative disease. Urinary methylmalonic acid was measured in random urine samples from eight of the 12 children and 14 age-matched and sex-matched normal controls, by a modification of a technique described previously.2 Chromatograms were scanned digitally on computer, to analyse the methylmalonic-acid zones from cases and controls. Urinary methylmalonic-acid concentrations in patients and controls were compared by a two-sample t test. Urinary creatinine was estimated by routine spectrophotometric assay Children were screened for antiendomyseal antibodies and boys were screened for fragile-X if this had not been done before. Stool samples were cultured for Campylobacter spp, Salmonella spp, and Shigella spp and assessed by microscopy for ova and parasites. Sera were screened for antibodies to Yersinia enterocolitica. + + Formalin-fixed biopsy samples of ileum and colon were assessed and reported by a pathologist (SED). Five ileocolonic biopsy series from age-matched and site-matched controls whose reports showed histologically normal mucosa were obtained for comparison. All tissues were assessed by three other clinical and experimental pathologists (APD, AA, AJW)","12 children (mean age 6 years [range 3–10], 11 + boys) were referred to a paediatric gastroenterology unit + with a history of normal development followed by loss of + acquired skills, including language, together with diarrhoea + and abdominal pain. + + All children were admitted to the ward for 1 week, accompanied by their parents",,,Lancet,0,0,1,1,1,1,0,0,1,5 +45,Longitudinal brain structure changes in Parkinson’s disease: a replication study,"Code availability We used publicly available software to facilitate reproducing our study. Pandas v. 1.5.2 was used to define the cohort from PPMI data files. FreeSurfer 7.1.1 was used for image preprocessing and vertex wise analyses. We used a containerized version of FreeSurfer managed by Boutiques 0.5.25 (doi:10.5281/zenodo.3839009). The containerized FreeSurfer analyses were executed through the Slurm batch manager on the Narval cluster (https://docs.alliancecan.ca/wiki/Narval/en) hosted at Calcul Québec and part of Digital Research Alliance of Canada. + + The code and results are publicly available at https://github.com/LivingPark-MRI/hanganu-etal-2014. Data used in the notebook were downloaded directly from the PPMI and cannot be shared publicly due to its Data Usage Agreements preventing republishing data. We developed a Python package (LivingPark utils, available at https://github.com/LivingPark-MRI/livingpark-utils) to download and manipulate PPMI data directly from the original PPMI database. As a result, our notebook can be re-executed by anyone with a PPMI account.",,,"Methods. Using 25 PD subjects and 18 healthy controls, we analyzed the rate of change of cortical thickness and of the volume of subcortical structures, and we measured the relationship between MRI structural changes and cognitive decline. We compared our findings to the results in the original study. + + The original study included 15 PD-non-MCI, 17 PD-MCI and 18 HC. In order to reconstruct this cohort, PD patients and HC were selected from PPMI to attempt to match the sample size and demographics of the groups in the original study.","Data was collected after approval of the local ethics committees of the PPMI’s participating sites. + + Image acquisition and preprocessing MRI images were taken from the PPMI which uses a standardized study protocol and the following parameters: repetition time = 2.3 s, echo time = 2.98 s, inversion time = 0.9 s, slice thickness = 1 mm, number of slices = 192, field of view = 256 mm, and matrix size = 256 × 256. However, since PPMI is a multisite project there may be slight differences in the sites’ setup. Scans were acquired using different 3T scanners (Philips Achieva n=2; Siemens Prisma fit n=8; Siemens Prisma n=4; Siemens Skyra n=2; Siemens TrioTim n=64; Siemens Verio n=6). There were scans with echo time (TE) that diverged from the standardized protocol: one image with TE = 2.52 s, one image with TE = 1.91 s, three images with TE = 2.91 s, one image with TE = 2.93 s, four images with TE = 2.95 s, four images with TE = 2.96 s, two images with TE = 3.06s. Additionally, two images had TE = 2.94 s, TR = 6.49 s, and TE = 2.91 s, TR 6.26 s. T1-weighted brain images were processed using FreeSurfer 7.1.1 [17]. The longitudinal preprocessing stream was used to calculate the change in cortical thinning and subcortical volumes [18]. FreeSurfer’s recon-all function was used for cortical reconstruction. First, all timepoints were processed cross sectionally with the default workflow, then an unbiased template from the two timepoints was created for each subject, finally data was processed longitudinally. Specifically an unbiased within-subject template space and image [19] is created using robust, inverse consistent registration [20]. Several processing steps, such as skull stripping, Talairach transforms, atlas registration as well as spherical surface maps and parcellations are then initialized with common information from the within-subject template, significantly increasing reliability and statistical power [18]. The rate of change of cortical thickness between the two timepoints was calculated for each subject. Cortical thickness was smoothed with a 10 mm FWHM kernel. The original study also reported manual correction of misclassified tissue types, which was not performed in our study since the protocol for it was insufficient to replicate.","The following criteria were used to define the PD cohorts: clinical diagnosis of PD, available T1-weighted images at two research visits, Hoehn and Yahr stage I and II (the stage was stable across the two visits for each patient), testing performed at PD OFF state, available MoCA scores, and the absence of any other neurological condition. + + All participants provided written informed consent. This study was conducted in accordance with the Declaration of Helsinki and was exempt from the Concordia University’s Research Ethics Unit. + + Patients were divided into PD-MCI and PD-non-MCI groups. In the original study, MCI was diagnosed on the basis of the presence of subjective complaints of cognitive impairment, objective impairment on two or more neuropsychological tests in one domain of cognitive function and the absence of dementia. In the PPMI dataset, patients are already classified as having MCI or not using a very similar criteria for classification, and thus the existing classification was used. Diagnosis of MCI in the PPMI is determined based on the following criteria: impairment in at least one cognitive domain, decline from pre-morbid function, and lack of significant impact of cognitive impairment on daily function. + + Ten PD-MCI (M age = 67.6; SD = 5.8), 15 PD-non-MCI (M age = 63.4; SD = 9.4), and 18 HC participants were selected (M age = 66.9; SD = 6.1). PD-non-MCI and HC group sample sizes match those of the original study but an insufficient number of PD-MCI patients were identified in the PPMI dataset that met all the original inclusion criteria, thus our sample is smaller than the original sample (n=10 vs n=17).","Descriptive statistics are reported in Table 1. + + Group differences computed with Student’s t-test for continuous variables and with χ2 test for the categorical variable. + + Statistical analyses Structural brain images and Montreal Cognitive Assessment (MoCA) scores from the initial and the follow up visits were analyzed consistently with the 4 main findings reported in the original study. (Finding 1) We tested vertex-wise differences in the change of cortical thickness between HC, PD-MCI, and PD-non-MCI groups with an ANCOVA model. (Finding 2) We tested the correlation between the change of cortical thickness and the change of MoCA scores in PD-MCI, PD-non-MCI, and PD-all (all PD patients) groups. The time between the two visits was added as a covariate in the general linear models. Cluster-wise p-value threshold was used at the p < .05 level. The rate of change of the cortical thickness was calculated with the formula: (Thickness at Time 1 – Thickness at Time 2) / (Time 2 – Time 1). Subcortical volumes were adjusted for the estimated total intracranial volume as well as the averages of the two time points using regression-based correction, in line with the original study. (Finding 3) We tested the differences in regional volume changes between the three groups using t-tests and (Finding 4) measured the correlations between the change in MoCA scores and change of the subcortical volumes and cortical thickness in each group using Pearson correlation.",Acknowledgment This work was funded by the Michael J. Fox Foundation for Parkinson's Research (MJFF-021134).,,1,0,0,1,1,1,1,1,0,6 +46,Cardiopulmonary Bypass Priming Using a High Dose of a Balanced Hydroxyethyl Starch Versus an Albumin-Based Priming Strategy,,,Anesthesia & Analgesia,"METHODS: In 50 patients undergoing coronary artery bypass grafting, the CPB circuit was prospectively and randomly primed with either 1500 mL of 6% HES 130/0.42 in a balanced electrolyte solution (Na1 140 mmol/L, Cl2 118 mmol/L, K1 4 mmol/L, Ca21 2.5 mmol/L, Mg11 1 mmol/L, acetate2 24 mmol/L, malate2 5 mmol/L) (n 5 25) or with 500 mL of 5% human albumin plus 1000 mL 0.9% saline solution (n 5 25). Inflammation (interleukins [IL]-6, -10), endothelial damage (soluble intercellular adhesion molecule-1), kidney function (kidney-specific proteins a-glutathione S-transferase, neutrophil gelatinase-associated lipocalin), coagulation (measured by thrombelastometry [ROTEMt, Pentapharm, Munich, Germany]), and platelet function (measured by whole blood aggregometry [Multiplatet analyzer, Dynabyte Medical, Munich, Germany]) were assessed after induction of anesthesia, immediately after surgery, 5 h after surgery, and on the morning of first and second postoperative days. + + The patients were prospectively randomized into one of the two groups by a computer-generated list and sealed envelopes. In group HES (n 5 25), priming of the CPB circuit consisted of 1500 mL of balanced 6% HES 130/0.42 containing Na1 140 mmol/L, Cl2 118 mmol/L, K1 4 mmol/L, Ca21 2.5 mmol/L, Mg11 1 mmol/L, acetate2 24 mmol/L, and malate22 5 mmol/L (Tetraspant, B. Braun, Melsungen, Germany). In the albumin group (n 5 25), the CPB circuit was primed with 500 mL 5% human albumin dissolved in 0.9% normal saline (Na1 154 mmol/L, Cl2 154 mmol/L) with an additional 1000 mL of normal saline. Perioperatively, IV volume was given when mean arterial blood pressure (MAP) was ,60 mm Hg and pulmonary capillary wedge pressure (PCWP) or central venous pressure (CVP) was ,10 mm Hg to a target of 12–14 mm Hg. In group HES, balanced HES and a balanced crystalloid containing Na1 140 mmol/L, Cl2 127 mmol/L, K1 4 mmol/L, Ca21 2.5 mmol/L, Mg21 1 mmol/L, acetate2 24 mmol/L, and malate22 5 mmol/L (Sterofundin Isot, B. Braun) was given in a 1:2 ratio. In the albumin group, albumin or saline solution was given in a 1:2 ratio. + Anesthesia induction and maintenance were performed with sufentanil (total dose: 5–7 mg/kg), midazolam (total dose: 0.3 mg/kg), and pancuronium bromide (total dose: 0.35–0.4 mg/kg). Desflurane was given and titrated based on clinical assessments. CPB was performed using nonpulsatile blood flow at 2.4 L z min21 z m2, a nonheparin coated circuit, and a membrane oxygenator (Terumo System 1™, Terumo, Leuven, Belgium). St. Thomas cardioplegic solution was used for myocardial preservation. The patients received tranexamic acid (2 g after anesthesia induction and then 6 mg z kg21 z h21, with 1 g added to the CPB prime). During CPB, body temperature was kept .34°C (bladder temperature). Norepinephrine was given to maintain MAP .60 mm Hg during CPB. HES or albumin was added to maintain sufficient filling of the extracorporeal circuit. Leukocyte-depleted packed red blood cells (PRBCs) were given when hemoglobin was < 7 g/dl. After termination of CPB, the blood from the CPB circuit was given to the patient without processing after sternal closure. All patients were transferred to the intensive care unit (ICU) where their lungs were mechanically ventilated. Tracheal extubation was performed when hemodynamics were stable, temperature was .36°C, and there was adequate spontaneous breathing (Pao2 .80 mm Hg with Fio2 0.3, breathing frequency ,15/min). After surgery, PRBCs were given when the hemoglobin was ,9 g/dL, and fresh frozen plasma (FFP) was given when there was excessive bleeding (.400 mL/h) in the presence of an activated partial thromboplastin time .60 s. Platelet concentrates were given when bleeding continued (.400 mL/h) despite a normal activated clotting time. Epinephrine or dobutamine was given when MAP was ,60 mm Hg and cardiac index was ,2.5 L z min21 z m2 despite administration of IV volume to reach PCWP (or CVP) .16 mm Hg (target for cardiac index: 2.5–3.0 L z min21 z m2). Norepinephrine was given when systemic vascular resistance was ,600 dyn z s21 z cm25 and MAP was ,60 mm Hg.","Measurements + Hemodynamic measurements included heart rate, MAP, pulmonary artery pressure, PCWP, CVP, and cardiac output (by pulmonary artery catheter). sCR concentrations were measured using Jaffe´ reaction (Modular, Roche, Mannheim, Germany). Urine aglutathione S-transferase (a-GST) was measured by enzyme immunoassay (Nephkit™-Alpha, Biotrin International, Sinsheim-Reihen, Germany). Normal values for this assay are 3.5 6 11.1 mg/L (mean 6 2 sd). Urine neutrophil gelatinase-associated lipocalin (NGAL) was analyzed by sandwich enzyme-linked immonosorbent assay using microwells coated with monoclonal antibody against human NGAL (Kit 0236, Antibody Shop, Grusbakken, Denmark). Normal values are 0.7–9.8 ng/mL and the lowest sensitivity is 0.5 ng/mL. Plasma interleukin-6 (IL-6) and IL-10 were measured using commercially available solid-phase twosite chemiluminescent enzyme immunometric assays (Diagnostic Product Corporation, Los Angeles, CA). Normal values for IL-6 are ,5 pg/dL and 2–24 pg/mL for IL-10. The lower limit of detection for IL-6 is 0.5 pg/dL and for IL-10 is 1 pg/dL. Plasma levels of soluble intercellular adhesion molecule-1 (sICAM-1) were measured from arterial blood samples using enzyme-linked immonosorbent assay (British Bio-technology Products, Abington, UK). Normal range for this assay is 200–300 ng/mL. A four-channel analyzer was used to measure rotational thrombelastometry (ROTEMt, Pentapharm, Munich, Germany). ROTEM analysis relies on continuous measurement of clot firmness, allowing the determination of the onset of coagulation (coagulation time [CT], standard TEGt: reaction time), kinetics of clot formation (clot formation time [CFT], standard TEG: CT), and maximum clot firmness [MCF], standard TEG: maximal amplitude). Clot formation was measured after recalcification of 300 mL of whole blood (20 mL of calcium chloride 0.2 M) and adding thromboplastin-phospholipid (20 mL) to monitor the intrinsic system (IntrinsicROTEM). The contact activator is ellagic acid. Clot formation was monitored after addition of calcium chloride to 300 mL of whole blood and addition of liquid-stable thromboplastin reagent derived from rabbit brain (i.e., tissue factor 1 phospholipids) (20 mL) for monitoring the extrinsic system (ExtrinsicROTEM). + Platelet function was assessed with a whole blood platelet function analyzer (Multiplatet, Dynabyte Medical, Munich, Germany). This test measures electrical impedance between electrodes immersed in whole blood.9 Blood is stirred using an electromagnetic stirrer at 800 rpm. The attachment of platelet aggregates on the electrodes increases impedance. The change of the impedance is transformed to arbitrary aggregation units and plotted against time. Three hundred microliters of blood was withdrawn into a tube containing hirudin and then mixed with 300 mL + of prewarmed isotonic saline solution. After incubation for 3 min, 20 mL of activating substrate was added to the blood sample. Activated platelet function was recorded for 6 min. The area under the curve of the clotting procedure of each measurement was measured and averaged. Platelet function was assessed for each sample after the addition of adenosine diphosphate (ADPTestt 2 mM/mL, Instrumentation Laboratory, Munich, Germany), thrombin-activating protein (TRAPTestt 1 mM/mL, Instrumentation Laboratory), and collagen (COLTestt 100 mg/mL, Instrumentation Laboratory). Measurements were performed in duplicate within 30 min after blood withdrawal always by the same person who was blinded to the grouping. + Hemodynamic and all laboratory measurements were made after induction of anesthesia (before any IV volume was administered), at the end of surgery, 5 h after surgery (in the ICU), and at the morning of the first and second postoperative day (POD) in the ICU. A questionnaire was sent to the patients’ primary physician to receive information on patients’ sCr, renal failure requiring renal replacement therapy, and mortality approximately 60 days after hospital discharge.","Fifty consecutive patients undergoing elective coronary artery bypass grafting were studied after approval of the IRB and after receiving individual written informed consent. Patients were excluded from study for kidney dysfunction (serum creatinine [sCR] concentration .2.0 g/dL; chronic oliguria/ anuria requiring dialysis), liver insufficiency (aspartate aminotransferase .40 U/L, alanine aminotransferase .40 U/L), or current corticosteroid treatment.","Data Analysis + Data from Tamayo et al.10 were used for power analysis. We hypothesized that the use of HES for CPB priming would reduce IL-6 levels after surgery by 30% + compared with albumin priming. Based on this assumption, 20 patients in each group would be needed to detect this difference with an a of 0.05 and a power of 80%. Data are expressed as mean and standard deviation unless otherwise indicated. x2 test was used to analyze categorical data. Normally distributed data (tested by Kolmogorov-Smirnov test) were analyzed using Student’s t-test. Two-way analysis of variance with repeated measures and post hoc Scheffe´ test were used to determine the effects of group, time, and group-time interaction. When multiple comparisons were made, Bonferroni correction was done (serially measured data, e.g., for hemodynamics, biochemical data). Mann– Whitney U-test or the Kruskal–Wallis H-test was also used when appropriate. A MedCalc 4.30 (MedCalc Software, Mariakerke, Belgium) software package was used for statistical analyses. A P value ,0.05 was considered significant.",Retracted,Anesthesia & Analgesia,0,0,1,1,1,1,1,1,1,7 +47,"Science mapping analysis characterizes 235 biases + in biomedical research","Supplementary data Supplementary data can be found, in the online version, at doi: 10.1016/j.jclinepi.2009.12.011.",,Journal of Clinical Epidemiology,"Study Design and Setting: We used advanced text-mining and clustering techniques to evaluate 17,265,924 items from PubMed (1958e2008). + + We screened electronically the PubMed database from 1958 to 2008 (17,265,924 references) for articles that included the word ‘‘bias’’ in their title, so as to focus on an enriched sample of papers where bias was a key consideration. The titles of the 6,405 retrieved abstracts were electronically text-mined to identify two-grams (two words in sequence) with ‘‘bias’’ as last word that appeared in at least three titles. Moreover, the abstracts of the 6,405 retrieved papers were also text mined to identify all n-grams with n < 3 appearing in at least 100(1/n) abstracts. Thus, we retained all words that appeared at least 100 times; all two-grams that appeared at least 10 times; and all three-grams that appeared at least 4 times. We then cleaned the terms with standard linguistic treatment. Specifically, we removed all n-grams ending with ‘‘ly,’’ ‘‘ful,’’ ‘‘ary,’’ ‘‘ory,’’ ‘‘al,’’ ‘‘able,’’ ‘‘ed,’’ or ‘‘ic’’; uninformative stop words such as ‘‘and,’’ ‘‘of,’’ ‘‘the,’’ and so forth; all two-grams and three-grams including the word ‘‘bias’’ as a first word (e.g., ‘‘bias correction’’ or ‘‘bias is significant’’); all threegrams including the word ‘‘bias’’ as middle word (e.g., ‘‘large bias is’’); and two-grams or three-grams where ‘‘bias’’ was the last word, but the preceding words were only a verb, an adjective, or adverb and that did not characterize a specific type of bias (e.g., ‘‘reducing bias,’’ ‘‘large bias,’’ ‘‘significantly bias’’). Moreover, we merged synonyms with different spelling (e.g., ‘‘meta-analysis’’ and ‘‘metaanalysis,’’ terms with English versus American spelling, and singular and plural of same word). Eventually, the final list of terms, thereafter referred as L, had 338 entries, of which 235 were bias terms. We counted the number of occurrences and pair-wise cooccurrences for all 338 entries across the entire PubMed (titles and abstracts).","Mapping: general principles The general principle of our analysis is to use automated methods to extract meaningful sets of terms related to each other and occurring together in the literature of specific themes. We define a proximity measure between terms that reflects the way terms are associated with similar themes and extract coherent sets of terms delimiting a domain. These sets of terms (clusters) are then displayed as connected nodes of a graph, where connections indicate the proximity between domains of investigation. The resulting maps highlight which types of biases tend to co-occur and may be considered together and along with what other terms. + + Pseudo-inclusion measure We choose here a variant of the paradigmatic proximity Pa proposed by Chavalarias and Cointet [4], thereafter called pseudo-inclusion measure. This measure has the advantage to convey information about the degree of specificity of a term: given two terms i and j, it conveys whether one is more specific than the other, i.e., tends to be used by a subcommunity of the community using the other. See the Appendix for the exact formula to calculate the pseudo-inclusion. Pa is asymmetric and a is a focus parameter that determines the direction and the strength of the asymmetry. For small values (!1) of a, the higher Pa(i,j) the more specific is j relative to i. Asymmetry means that Pa(i,j)5P1/a(j,i) so if j is specific to i, i is generic to j. For example, ‘‘citation bias’’ is specific to the term ‘‘publication,’’ whereas ‘‘publication’’ is generic to ‘‘citation bias.’’ Two terms that are specific to each other are used roughly by the same communities, e.g., ��‘emotional bias’’ and ‘‘affective bias.’’ Two terms in which both Pa(i,j) and Pa(j,i) are low are considered as irrelevant to each other, e.g., ‘‘accessibility bias’’ and ‘‘myocardial infarction.’’ In the presented analyses we used a 5 0.1. + + Clustering P0.1 transforms the co-occurrence matrix into a proximity matrix. This matrix defines a directed weighted graph G on the set L that can be further analyzed with clustering methods. In our context, clusters should represent domains of investigation defined by sets of strongly related terms that contextualize each other, some being more specific and others more generic. This notion fits well with the concept of cliques from graph theory. A clique is a subgraph of G such that all vertices are linked to all others in the sub graph. Because our proximity measure is asymmetric, we choose to define clusters as directed cliques [5]; this makes it possible to take into account the directionality of edges. We also pruned the graph G, keeping for each node only its 20 strongest connections. This operation makes it possible both to render the clique detection algorithms computationally tractable on large networks and avoid very common (and less informative) terms linked to many others to be over represented. + + Specificity and genericity indices The labeling of clusters is an important issue in the map ping procedure. Cluster labels should both display relevant information about the cluster’s content and provide an understandable global view when displayed all together. For this purpose we defined two indices for each term w participating in a clique C. The specificity index Is indicates the extent to which the term w is specific relative to other terms w0 in the same clique. In our case (a ! 1), Is is said to be the mean ‘‘in-proximity’’ of w. Conversely, the genericity index indicates the extent to which the term w is generic relative to other terms in C. Ig is said to be the mean ‘‘out-proximity’’ of w. Specificity and genericity indices can be profitably used to label clusters in maps by labeling a cluster with its most specific or most generic term(s). In this study, we propose maps where clusters are labeled by either their most specific or most generic term. These indices also make it possible to visualize a cluster in a two-dimensional representation where each term has coordinates (Is; Ig). The average of these two indexes defines the pseudo-inclusion index that conveys how well term i fits the cluster. The change of this index between two time periods indicates whether the term is becoming more or less relevant for this cluster over time. The pseudo-inclusion index can also be defined for a whole cluster C as the mean pseudo-inclusion index of its terms. This is a measure of the integration of a cluster. A low pseudo-inclusion index means that at least one of the terms of the cluster does not fit the cluster, i.e., the cluster does not define a mature field. This index may also prove to be useful when assessing the evolution of the structure of a cluster over time. For formal equations of these indices, see Appendix.","We considered 235 bias terms and 103 other terms that appear commonly in articles dealing with bias. + + We aimed to generate a systematic, comprehensive list of terms that include the word ‘‘bias’’ and one or two other words preceding ‘‘bias.’’ We did not consider terms that may signify biases but do not contain the word ‘‘bias’’ per se, because their identification would be subjective and potentially erratic. We also aimed to identify terms that are frequently encountered in articles that deal with bias.","Filtering cliques The main analysis used data from PubMed in the past decade (1999e2008) so as to focus on the current use of these terms and their co-occurrence patterns. We used the CFinder software [6] to extract all possible directed cliques from graph G. This yielded 1,577 cliques, with sizes varying between 3 and 11 terms; 1,526 of these cliques mentioned ‘‘bias’’ and covered 311 of the 338 words. To make maps more informative, we filtered this large number of cliques to retain those of best quality. First, we filtered cliques based on their size. Because terms contextualize each other within a clique, terms gets more precise meanings, with growing clique size. Therefore, we considered only cliques with at least 5 terms. Second, we imposed that for each selected set of terms, all its elements should appear together in the full text of at least one published article over the period considered. We chose for that assessment the Scirus.com search engine as a reference, as it includes Medline and allows full-text search. Finally, we merged cliques that were entirely included in a larger one. This reduced the number of cliques to 252, mentioning 203 terms (including 108 bias terms). These 252 clusters were then mapped to highlight their articulation. The asymmetric proximity measure can be generalized into a measure between clusters Ca and Cb [7] (for the exact equation, see Appendix). The mapping represents a directed weighted network where the clusters are the nodes. The general principle of network visualization is that strongly connected nodes should appear close on the plot. One can selectively discard some links according to their weight being under a given threshold. Here we are presenting maps where we discarded all links with strength less than 50% of the maximum value. We used the Gephi visualization tool with the Force Atlas and Label Adjust algorithms [8] to generate the layout of the graphs. + + Software We used the Words Evolution software developed by David Chavalarias and Jean-Philippe Cointet [10]. Written in Matlab, this software is interfaced with network visualization tools (Pajek [11] and GraphViz [12], Gephi [8]) and clustering software (CFinder [6])",,Journal of Clinical Epidemiology,1,0,1,1,1,1,1,0,1,7 +48,Replication validity of genetic association studies,Note: Supplementary information is available on the Nature Genetics web site (http://genetics.nature.com/supplementary_info/).,,NATURE,"We considered meta-analyses of disease association studies that had been based on human genetic markers other than HLA alleles. A Medline search (last update December 2000) used the terms ‘polymorphism(s)’ and ‘genetics’, and ‘meta-analysis’ as type of publication. Meta-analyses with discrete outcomes qualified if (i) the outcome was related to a genetic marker (ii) detailed data were available for constructing 2×2 tables for each individual study (number of disease cases with and without the marker, number of controls with and without the marker) and (iii) data had been published in at least two different years. When a published report examined several genetic markers or several clinical outcomes, we considered separately each genetic marker and outcome. We obtained qualitatively similar results in analyses selecting only one outcome (the one with the largest number of tested subjects). We considered different polymorphisms of the same gene as separate genetic markers. When there were several meta-analyses on exactly the same association, we generally retained only the most updated one, provided it had adequate data for each of the included studies. We screened in detail 51 reports of meta-analyses and excluded 25 of them (more recent similar meta-analysis available, n=19; lack of detailed data for individual studies, n=5; publication of all pertinent studies in the same year, n=1).","When the genetic marker had more than two categories (such as AA homozygosity, Aa heterozygosity, aa homozygosity), we considered the comparison of the two categories that had been proposed originally in the first study in the field. One or both of the compared categories could be combinations of different genotypes (for example, Aa heterozygosity and aa homozygosity). When it was not clear which was the most important genetic contrast and when several ‘first’ studies were published in the same year in different journals, we selected the genetic contrast proposed by the meta-analysis. If several comparisons were carried out even by the meta-analysis, we used an a priori algorithm (which selects genotype contrasts over allele frequency comparisons, and genotype contrasts based on recessive inheritance over other genotype contrasts). For data presented only in abstract form and for unpublished data, we imputed publication to occur after the meta-analysis. We always considered the first study or studies for the specific genetic association, as well as all the other subsequent studies included in the meta-analysis. In 27 cases, there was an easily identifiable first study (Web Note B); in the other 9 cases, 2–10 studies had been published close to each other in the same year in different journals, and we therefore estimated their summary odds ratio by fixed- and random-effects models.","Twenty-six meta-analysis reports were eligible (Web Notes A and B), addressing 36 genetic associations across 370 studies (Web Note C).","Modeling. We estimated between-study heterogeneity in each meta-analysis by the Q statistic; Q is traditionally considered to be significant for P<0.10 (ref. 5). Summary odds ratios calculations used the Mantel–Haenszel fixed-effects model6 and the DerSimonian and Laird random-effects model7,9. Detailed graphs for each eligible meta-analysis are provided in the Supplementary Information (Web Figs. A1–A36). Fixed-effects models assume that all studies aim at evaluating a common truth and results differ by chance alone. Random-effects models anticipate that the studies may have genuine differences in their results9; thus, they also incorporate a between-study variance in their estimates. Random-effects models are generally more conservative (that is, they provide wider confidence intervals when there is between-study heterogeneity5). Fixed-effects models may be inappropriate if there is genuine heterogeneity in the size of genetic effects across subpopulations. Random-effects models are thus preferable, but they assume a certain distribution for the effect sizes that may be difficult to validate. + We estimated the Spearman rank-correlation coefficient between the odds ratios of first and subsequent studies across all the topics considered. We examined whether the results of the first published studies on a given association were significantly different beyond chance from the results of the subsequently published studies by using a z-score, as described previously22. We also constructed recursive cumulative meta-analysis plots that trace the evolution of the summary odds ratio as more data accumulate over time on the same topic10,11. Finally, we examined with logistic regressions23 whether the number of studies, the sample size of the first study or studies and the availability of a single first study with a clearly proposed genetic contrast influenced the occurrence of statistically significant discrepancies between the results of the first and subsequent studies.","Acknowledgments This work was supported in part by a grant from the General Secretariat for Research and Technology, Greece, funded through the European Union.",NATURE,1,0,1,1,1,1,1,1,1,8 +49,A Multiregion Analysis of Shale Drilling Activity and Rates of Sexually Transmitted Infections in the United States,,,,"Study Design + We conducted an ecologic study that used annual shale drilling data, sociodemographic data, and reported STI rates for all counties in Colorado (n = 64), North Dakota (n = 53), and Texas (n = 254) for the years 2000 to 2016. We selected this period to allow for the modeling of STI rates before the start of shale drilling activity, which occurred in either 2005 or 2006 in each state. Because our time-dependent data varied across each county and year, the unit of analysis was county-year. The ecological study design allowed us to study health indicators that may follow from industrial changes at policy-relevant geographical scales.","We obtained annual reported rates of chlamydia, gonorrhea, and syphilis from the Centers for Disease Control and Prevention, number of active shale wells from Enverus (formerly known as DrillingInfo), and sociodemographic covariates from the US Census Bureau. + + STI Data Acquisition + We obtained the annual rates (cases per 100,000 population) of chlamydia, gonorrhea, and primary and secondary syphilis using the Centers for Disease Control and Prevention's (CDC's) AtlasPlus tool.19 Case data used to calculate these rates are confirmed diagnoses reported to the CDC by county and state health departments, and population denominators are based on calendar year estimates from the US Census Bureau. + + Sociodemographic Data Acquisition + We obtained time-varying data for numerous established sociodemographic risk factors for STI from the Decennial Census and American Community Survey (ACS) provided by the US Census Bureau.20,21 Because the US Census queries people at their “usual residence” and not a temporary one, we included these variables to control for potential confounding due to differences in background demographic characteristics of county residents (not the shifting demographics due to the presence of temporary workers, which are not likely to be detected by these Census surveys). Variables included sex (percent population female), age (percent population 15–29 years of age), race (percent population identifying as white, black or African American, American Indian or Alaska Native, and Asian), ethnicity (percent population identifying as Hispanic or Latino), educational attainment (percent population 25 years and older who graduated high school and percent population 25 years and older with a bachelor's degree), income (median household income in US dollars per year), poverty (percent population who experienced poverty within the last 12 months), and health insurance coverage (percent population with health insurance). Population density was calculated by dividing the 2010 population estimates used by the CDC in formulating STI rates, by county area (in miles squared) as reported by the US Census Bureau in 2010. + Because the availability of sociodemographic data availability varied across the study period, decision rules were applied to assign values to each county-year. Specifically, because ACS data first became available for 2005 to 2009, data from the 2000 Decennial Census were applied to the years 2000 to 2004. Data from the 2005 to 2009 ACS 5-year estimates were applied to the years 2005 to 2009. The ACS 5-year estimates ending in the given year were applied to the years 2010 to 2016 (e.g., the 2011–2015 ACS 5-year estimates were applied to the year 2015). Because the variable percent population with health insurance did not become available until the 2008 to 2012 ACS, the values from the 2008 to 2012 ACS 5-year estimates were assigned to the years 2000 to 2012; the ACS 5-year estimates ending in the given year were then applied to the years 2013 to 2016 for subsequent years, consistent with the assignments of the other covariates. + + Shale Drilling Data Acquisition + We used data pertaining to county-level shale drilling activity from Enverus—a commercially available data set of drilling activity across the United States—to construct a metric for the number of new shale wells drilled or “spudded” per county per year, considering all active wells with a spud date between January 1, 2000, and December 31, 2016. + To focus the analysis on UOG development, we only included oil and gas wells targeting a shale formation. A well was identified as targeting a shale formation if the name of the target formation was identified as a major shale play by the US Energy Information Administration or if the target formation contained the term “shale.” Among the wells meeting our inclusion criteria in Colorado (n = 6543), 96% targeted the Niobrara formation, followed by the Baxter-Mancos (3%), and the Pierre (1%) formations. Among wells meeting our inclusion criteria in North Dakota (n = 12,642), 65% targeted the Bakken formation and 35% targeted the Three Forks formation. Of the wells included in Texas (n = 32,998), 48% targeted the Eagle Ford formation and 44% targeted the Barnett formation followed by the Haynesville-Bossier (3%), Bone Spring (2%), Delaware (2%), and Spraberry (1%) formations. + Based on a visual inspection of the distribution of nonzero values for spuds targeting a shale formation per county-year across all 3 states, we identified 50 shale spuds as a natural cut-point in the distribution and therefore an appropriate delineator of high and low shale drilling activity. Each county-year was classified according to its shale drilling activity: none (0 spuds targeting shale), low (1–49 spuds targeting shale), and high (≥50 spuds targeting shale) for the study period 2000 to 2016.",,". We used multivariable mixed-effects Poisson regression modeling to estimate rate ratios (RR) with 95% confidence intervals (CIs) adjusted for potential confounders and secular trends + + Statistical Analysis + In univariable analyses, we examined whether there were differences in the distribution of individual sociodemographic variables or reported STI rates within county-years with 0, 1–49, and ≥50 spuds targeting shale for Colorado, North Dakota, and Texas (2000–2016) using analysis of variance. + In multivariable models constructed separately for each state, rate ratios (RRs) with 95% confidence intervals (CIs) were calculated for the association between county-year shale drilling activity and reported cases of chlamydia, gonorrhea, and syphilis, using a mixed-effects Poisson regression model fitted using Proc Glimmix in SAS (SAS Institute, Cary, NC). Each model included a log of county population for each county-year as an offset term to account for the impact that variability in population would have on expected STI counts. A county-level random effect was included to establish a baseline STI rate for each county and to control for the potential correlation of rates across time within each county. An observation-level random effect was included to control for any excess variability in the STI case data that was unexplained by the covariates (i.e., overdispersion). Year was included in each model as a categorical variable to account for secular trends in STI counts over time (i.e., the background increase in STI over the study period), with the earliest year for which STI data were available for that state and disease as the reference. Shale drilling activity was included in all models as the independent variable of interest. All sociodemographic covariates were initially included in our final models, to control for any potential confounding resulting from differences in background demographic characteristics of county residents. When 2 were highly correlated (|rSpearman| ≥ 0.7), 1 was removed from the model to avoid estimation troubles caused by multicollinearity. The final models included all remaining sociodemographic covariates, regardless of their statistical significance in the model to more completely account for potential confounding. Models were kept consistent within each state across the 3 STIs. Before inclusion, all covariates were standardized on a state-by-state basis to improve stability during model fitting, and the results were back-transformed to the appropriate scale for interpretation. In sensitivity analyses, we constructed more parsimonious models in which we retained only sociodemographic variables that were statistically significant at P < 0.05. In addition, we reran our models removing the covariates “population density” and “% population female” to verify we were not inappropriately adjusting for variables on the causal pathway, which could occur if these variables were in fact sensitive to demographic shifts resulting from the influx of male workers (in contrast to our assumption). All results from sensitivity analyses with more parsimonious models were consistent with the primary models; therefore, results from only the more fully adjusted models are presented.","Some important limitations of this study should be noted. Based on our exposure classification, there were fewer countyyears in the high shale drilling category for each state, which could have limited statistical power. Also, we did not directly adjust for possible spatially correlated random effects in the data. Other limitations include the reliance on a passive STI surveillance system, which is likely to produce an underestimate of the true STI burden. Although we included year as a categorical variable in our models to account for any secular trends in underlying STI rates, we cannot rule out that the observed elevated STI rates in Texas are due not to a true increase in the community-level burden of STI, but rather to expanded screening, increased use of more sensitive diagnostic tests, or better national reporting. + This study also underscores the need for a better understanding of the UOG worker population and any STI-related health burdens they may be experiencing. Because reported STI rates are aggregated at the county level based on patient's residential address, they may not capture the health burden of the nonlocal UOG workers themselves. To the extent that nonlocal UOG workers are influencing these STI rates, they would likely benefit from improved access to testing and treatment, especially because they may be disconnected from their primary sources of health care. Furthermore, these workers may already be facing numerous other occupational hazards including hazardous respiratory exposures, injuries, and fatalities.29,30 Future research should focus on improving an understanding of the transmission patterns present between nonlocal workers and community members without further stigmatizing nonlocal UOG workers.",,0,0,0,1,1,0,1,1,0,4 +50,‘‘Positive’’ Results Increase Down the Hierarchy of the Sciences,,,,"The sentence ‘‘test* the hypothes*’’ was used to search all 10837 journals in the Essential Science Indicators database, which classifies journals univocally in 22 disciplines. When the number of papers retrieved from one discipline exceeded 150, papers were selected using a random number generator. In one discipline, Plant and Animal Sciences, an additional 50 papers were analysed, in order to increase the statistical power of comparisons involving behavioural studies on non-humans (see below for details on methodological categories). + + To identify methodological categories, the outcome of each paper was classified according to a set of binary variables: 1- outcome measured on biological material; 2- outcome measured on human material; 3-outcome exclusively behavioural (measures of behaviours and interactions between individuals, which in studies on people included surveys, interviews and social and economic data); 4-outcome exclusively non-behavioural (physical, chemical and other measurable parameters including weight, height, death, presence/absence, number of individuals, etc…).","By examining the abstract and/or fulltext, it was determined whether the authors of each paper had concluded to have found a positive (full or partial) or negative (null or negative) support. If more than one hypothesis was being tested, only the first one to appear in the text was considered. We excluded meeting abstracts and papers that either did not test a hypothesis or for which we lacked sufficient information to determine the outcome. All data was extracted by the author. An untrained assistant who was given basic written instructions (similar to the paragraph above, plus a few explanatory examples) scored papers the same way as the author in 18 out of 20 cases, and picked up exactly the same sentences for hypothesis and conclusions in all but three cases. The discrepancies were easily explained, showing that the procedure is objective and replicable.","This study analysed 2434 papers published in all disciplines and that declared to have tested a hypothesis. + + Biological studies in vitro for which the human/non-human classification was uncertain were classified as non-human. Different combinations of these variables identified mutually exclusive methodological categories: Physical/Chemical (1-N, 2- N, 3-N, 4-Y); Biological, Non-Behavioural (1-Y, 2-Y/N, 3-N, 4-Y); Behavioural/Social (1-Y, 2-Y/N, 3-Y, 4-N), Behavioural/Social + Biological, Non-Behavioural (1-Y, 2-Y/N, 3-Y, 4-Y), Other methodology (1-Y/N, 2-Y/N, 3-N, 4-N).","Statistical analyses The strength of the association between ranks of hardness and ranks based on the proportion of positive results was tested with Kendall’s t-c, that between ranks of hardness and positive/ negative outcome (which is a nominal category) was measured by Cramer’s V. The ability of independent variables to significantly predict the outcome of a paper was tested by standard logistic regression analysis, fitting a model in the form: + logit Yð Þ~ln pi 1{pi ~b0zb1Xi1z ...zbnXin + in which pi is the probability of the ith paper of reporting a positive or partial support, and X1,… Xn, represent the predictors tested in each regression model, the details of which are specified in the Results section. Statistical significance of the effect of each variable was calculated through Wald’s test, and the relative fit of regression models (variance explained) was estimated with Nagelkerke’s adjusted R2. Post-hoc statistical power estimations for X2 tests assumed Cohen’s w = 0.1, 0.3 and 0.5, for small, medium and large effects, respectively. Post-hoc statistical power in logistic regression was calculated for a hypothetical binary variable with bimodal distribution and sample frequency equal to the average sample frequency of all dummy variables in the relevant model (e.g. for a regression with disciplinary domain, the average sample frequency of biological and social sciences). This effect was contrasted to the base-rate probability of the reference category (e.g. for disciplinary domain, the proportion of positive results in physical sciences), assuming no other predictors in the model (i.e. R2= 0). OddsRatio = 1.5, 2.5 and 4.5 were assumed to equal a small, medium and large effect, respectively. All analyses were produced using SPSS statistical package. Power analyses were performed using the software G*Power 3.1 [73]. + + Figures Confidence intervals in the graphs were also obtained by logit transformation, using the following equations for the proportion and standard error, respectively: + Plogit~Loge p ð Þ 1{p + SElogit~ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 np z 1 nð Þ 1{p s + Where p is the proportion of negative results, and n is the total number of papers. Values for high and low confidence interval were calculated and the final result was back-transformed in percentages using the following equations for proportion and percentages, respectively: + P~ ex exz1 + %~100P + Where x is either Plogit or each of the corresponding 95%CI values.","Funding: This research was entirely supported by a Marie Curie Intra-European Fellowship (Grant Agreement Number PIEF-GA-2008-221441). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. + + Competing Interests: The author has declared that no competing interests exist.",PLOS,0,0,0,1,1,1,1,1,1,6 +51,"Restoring Study 329: efficacy and harms of paroxetine and + imipramine in treatment of major depression in adolescence","Additional material is published online only. To view please visit the journal online (http://dx.doi. org/10.1136/bmj.h4320) + + Data sharing: Clinical study reports, detailed data tables, and programming code are available on the Dryad Digital Repository (http://dx.doi.org/10.5061/dryad.bv8j6) and at www.Study329.org/ + + Appendix 1: RIAT audit record + Appendix 2: Supplementary tables A-M + Appendix 3: Supplementary information on suicidal and self-injurious behaviours in Study 329",,"BMJ + + We used a tool for documenting the transformation from regulatory documents to journal publication, based on the CONSORT 2010 checklist of information to include when reporting a randomised trial. + + To our knowledge this is the first RIAT analysis of a misreported trial by an external team of authors, so there + are no clear precedents or guides.","Design Double blind randomised placebo controlled trial. + + Setting 12 North American academic psychiatry centres, from 20 April 1994 to 15 February 1998. + + Interventions Participants were randomised to eight weeks double blind treatment with paroxetine (20-40 mg), imipramine (200-300 mg), or placebo. + + Methods We reanalysed the data from Study 329 according to the RIAT recommendations. To this end, we used the clinical study report (SKB’s “final clinical report”), including appendices A-G, which are publically available on the GSK website,9 other publically available documents,10 and the individual participant data accessed through SAS Solutions OnDemand website,11 on which GSK subsequently also posted some Study 329 documents (available only to users approved by GSK). After negotiation,12 GSK posted about 77000 pages of de-identified individual case report forms (appendix H) on that website. We used a tool for documenting the transformation from regulatory documents to journal publication, based on the CONSORT 2010 checklist of information to include when reporting a randomised trial. The audit record, including a table of sources of data consulted in preparing each part of this paper, is available in appendix 1. Except where indicated, in accordance with RIAT recommendations, our methods are those set out in the 1994-96 protocol for Study 329.13 In cases when the methods used and published by Keller and colleagues diverged from the protocol, we followed the original protocol. Because the protocol specified method of correction for missing values—last observation carried forward—has been questioned in the intervening years, we also included a more modern method—multiple imputation— at the request of the BMJ peer reviewers. This is a post hoc method added for comparison only and is not part of our formal reanalysis. When the protocol was not specific, we chose by consensus standard methods that best presented the data. The original 1993 protocol had minor amendments in 1994 and 1996 (replacement of the Schedule for Affective Disorders and Schizophrenia for Adolescents-Present Version with the Lifetime Version (K-SADS-L) and reduction in required sample size). Furthermore, the clinical study report (CSR) reported some procedures that varied from those specified in the proto col. We have noted variations that we considered relevant. + + Randomisation A computer generated randomisation list of 360 numbers for the acute phase was generated and held by SKB. According to the CSR, treatments were balanced in blocks of six consecutive patients; however, there is an inconsistency in that appendix A randomisation code details block sizes of both six and eight. Each investigator was allocated a block of consecutively numbered treatment packs, and patients were assigned treatment numbers in strict sequential order. Patients were randomised in a 1:1:1 ratio to treatment with paroxetine, imipramine, or placebo.","Interventions The study drug was provided to patients in weekly blister packs. Patients were instructed to take the drug twice daily. There were six dosing levels. Over the first four weeks, all patients were titrated to level four, corresponding to 20 mg paroxetine or 200 mg imipramine, regardless of response. Non-responders (those failing to reach responder criteria) could be titrated up to level five or six over the next four weeks. This corresponds to maximum doses of 60 mg paroxetine and 300 mg imipramine. Compliance with treatment was evaluated from the number of capsules dispensed, taken, and returned. Non-compliance was defined as taking less than 80% or more than 120% of the number of capsules, assessed from the numbers expected to be returned at two consecutive visits, and resulted in withdrawal. Any patient missing two consecutive visits was also withdrawn from the study. Patients were provided with 45 minute weekly sessions of supportive psychotherapy,15 primarily for the purpose of assessing the effects of treatment.","Participants 275 adolescents with major depression of at least eight weeks in duration. Exclusion criteria included a range of comorbid psychiatric and medical disorders and suicidality. + + Inclusion criteria + • Adolescents aged 12-18 who met DSM-III-R criteria for major depression for at least 8 weeks + • Severity score <60 on the children’s global assessment scale (CGAS) + • Score ≥12 on the Hamilton depression scale (17 item) (HAM-D) + • Medically healthy + • IQ ≥80 (based on Peabody picture vocabulary test) + Exclusion criteria + • Current or past DSM-III-R diagnosis of bipolar disorder, schizoaffective disorder, anorexia nervosa, bulimia, alcohol or drug abuse/dependence, obsessive compulsive disorder, autism/pervasive mental disorder, or organic psychiatric disorder + • Current (within 12 months) DSM-III-R diagnosis of post-traumatic stress disorder + • Adequate trial of an antidepressant within six months (at least four weeks’ treatment with an adequate dose of antidepressant) + • Suicidal ideation with a definite plan, suicide attempt during current depressive episode, or history of suicide attempt by drug overdose + • Medical illness that contraindicates the use of heterocyclic antidepressants + • Current use of psychotropic drugs (including anxiolytics, antipsychotics, mood stabilisers), or illicit drugs + • Organic brain disease, epilepsy, or “mental retardation” + • Pregnancy or lactation + • Sexually active females not using reliable contraception + • Use of an investigational drug within previous 30 days or five half lives of the investigation drug + + Participants The original study recruited 275 adolescents aged 12-18 who met DSM-IV criteria14 for a current episode of major depression of at least eight weeks’ duration (the protocol specified DSM-III-R criteria, which are similar). Box 1 lists the eligibility criteria. An unknown number of patients (not disclosed in the available documents) identified by telephone screening as potential participants were subsequently evaluated at the study site by a senior clinician (psychiatrist or psychologist). Multiple meetings and teleconferences were held by the sponsoring company with site study investigators to ensure standardisation across sites. Patients and parents were interviewed separately with the K-SADS-L. After this initial assessment, the patient and parent both signed the study informed consent form; there was no mention of a separate assent form in the protocol or in the CSR. A screening period of seven to ten days was used to obtain past clinical records and to document that the depressive symptoms were stable. At the end of the screening period, only patients continuing to meet the inclusion criteria (DSM-III-R major depression and the HAM-D total score ≥12) were randomised. There was no placebo lead-in phase. There were originally six study sites, but this was increased to 12 (10 in the United States and two in Canada). The centres were affiliated with either a university or a hospital psychiatry department and had experience with adolescent patients. The investigators were selected for their interest in the study and their ability to recruit study patients. The recruitment period ran from 20 April 1994 until 15 March 1997, and the acute phase was completed on 7 May 1997. In a small number of patients, 30 day follow-up data for cases that went into the continuation phase were collected into February 1998.","Statistical testing The protocol called for ANOVA testing (generalised linear model) for continuous variables using a model that included the effects of site, treatment, and site × treatment interaction, with the latter dropped if P≥0.10. Logistical regression (2×3 χ2 ) was prescribed for categorical variables under the same model. Both methods begin with an omnibus statistic for the overall significance of the dataset, then progress to pairwise testing if, and only if, the omnibus statistic meets α=0.05. Yet all statistical outcomes in the CSR and published paper were reported only as the pairwise values for only two of the three possible comparisons (paroxetine v placebo and imipramine v placebo), with no mention of the omnibus statistic. Therefore, we conducted the required omnibus analyses, with negative results as shown. The pairwise values are available in table A in appendix 2.","Potential or perceived bias A RIAT report is not intended to be a critique of a previous publication. The point is rather to produce a thorough independent analysis of a trial that has remained unpublished or called into question. We acknowledge, however, that any RIAT team might be seen as having an intrinsic bias in that questioning the earlier published conclusions is what brought some members of the team together. Consequently, we took all appropriate procedural steps to avoid such putative bias. In addition, we have made the data available for others to analyse. + + Strengths and limitations of this study Study 329 was a randomised controlled trial with a reasonable sample size. There was, however, evidence of protocol violations, including some cases of breaking of blinding. The coding of adverse events by the original investigators raised the possibility that some other data might be unreliable. The trial lasted for only eight weeks. Participants had relatively chronic depression (mean duration more than one year), which would limit the generalisability of the results, particularly in primary care, because many cases of adolescent depression have shorter durations.28 Generalisability to primary care would also be limited by the fact that participants were recruited through tertiary settings. + The RIAT analysis broke new ground but was limited in that we could check only 34% (93/275) of case report forms. Time and resources prevented access to all forms because of the difficulties in using the portal for accessing the study data and because considerable amounts of data were missing. The analysis generated a useful taxonomy of potential barriers to accurate reporting of adverse events and, even allowing for the above limitations, showed the value of permitting access to data. + + Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. + + Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: DH has been and is an expert witness for plaintiffs in legal cases involving GlaxoSmithKline’s drug paroxetine. He is also a witness for plaintiffs in actions involving other antidepressants with the same mechanism of action as paroxetine, and is on the advisory board of the Foundation for Excellence in Mental Health Care. DH and JLN are founder members of RxISK. JJ has been paid by Baum, Hedlund, Aristei and Goldman, Los Angeles, CA, to provide expert analysis and opinion about documents obtained from GlaxoSmithKline in a class action over Study 329, and from Forest in relation to paediatric citalopram randomised controlled trials. Some of the authors are in discussions with an academic publisher regarding adapting the case of Study 329 as a book for educational purposes.",BMJ,1,0,1,1,1,1,1,1,1,8 +52,"Empirical Evaluation of Very Large Treatment + Effects of Medical Interventions",Online-Only Material: The eTables 1 and 2 and eFigures 1 and 2 are available at http://www.jama.com,,JAMA,"Study Selection We separated all binary-outcome CDSR forest plots with comparisons of interventions according to whether the first published trial, a subsequent trial (not the first), or no trial had a nominally statistically significant (P.05) very large effect (odds ratio [OR], 5). We also sampled randomly 250 topics from each group for further in-depth evaluation. + + We used the Cochrane Database of Systematic Reviews (CDSR), 2010, issue 7. The CDSR organizes quantitative data on treatment comparisons and outcomes in forest plots.","Data Extraction We assessed the types of treatments and outcomes in trials with very large effects, examined how often large-effect trials were followed up by other trials on the same topic, and how these effects compared against the effects of the respective meta-analyses. + + Categorization of Forest Plots and Definition of Index Trial Forest plots were categorized into 3 groups: those for which a nominally significant very large effect was found in the first published trial (group A); those for which a nominally significant very large effect was observed in a subsequent trial, but not the first one (group B); and those for which no trial had a nominally significant very large effect (group C). When 2 or more trials had the earliest publication year and it was impossible to identify which was published first, we randomly selected 1 trial as the first published study. The index trial is the first published trial with a nominally significant very large effect for group A; the earliest such trial for group B; and the first published trial for group C. + + Data Extraction We used an automated data extraction approach to gather information of all eligible forest plots from the CDSR. Briefly, raw data from each of the 3545 available reviews (stored under a hierarchical structure; CDSR, 2010, issue 7) were systematically and automatically extracted. Specifically, computer scripts written in Python, a general purpose dynamic programming language, were developed to load raw structured extensible markup language files. This format encodes all of the quantitative information from a review into a single file. Next, loaded files for each review were parsed considering the fixed structure of the CDSR. For the latter step, data for each forest plot were extracted using a combination of a Linux C shell-processing language (AWK), a stream editor (SED), the general-purpose programming language from the statistical package Stata 11.0 as well as Python. Validation of the automated approach was performed with the manual extraction of 200 randomly chosen forest plots (100% of agreement). For each eligible forest plot, we extracted the title, comparison, outcome, total number of trials, year of publication of each study, years elapsed between the index trial and the next trial, total number of participants and events across all trials, OR, relative risk (RR), risk difference (RD), and P value of the index trial and we extracted the OR, RR, RD, and P value of the metaanalysis using a random-effects model9 whenever additional trials were available beyond the index trial.","We considered forest plots regardless of the number of included studies (eg, some forest plots encompass only a single trial) and regardless of whether the Cochrane authors had performed quantitative synthesis (meta-analysis) of the data. + + Eligible Topics We accepted very large effects regardless of either the treatment comparison or choice of intervention. We excluded forest plots using outcomes measured on continuous scales and those not including the year of publication of each trial (thus it would be impossible to identify the first published trial). We also excluded reviews with problems in their structure (ie, information that could not be parsed or with inconsistent data hierarchy), protocols, and methodological reviews.","Statistical Analysis Descriptive statistics are expressed as median with interquartile range (IQR) or absolute counts and percentages. Comparisons between independent groups were performed with Fisher exact, Mann-Whitney U, and KruskalWallis tests, as appropriate. Kaplan-Meier plots with the log-rank test were used to compare groups in terms of the probability and time to publication of the next trial after the index trial. Follow-up was censored in 2010. Index trials were compared with the corresponding meta-analyses on the same topic for effect sizes and P values using the Wilcoxon signed-rank test. For meta-analyses, we present the results from a random-effects model (DerSimonian-Laird method) to account for any potential between-study heterogeneity across trials.9 For all analyses, OR estimates from index trials are presented as 1.0 or higher (ie, when the ORwas 1.0, we took the opposite comparison [A vs B was switched to B vs A] and then the meta-analysis estimate on the same topic was computed using the respective comparison). We also performed sensitivity analyses limited to forest plots with index trials published after the year 2000 to see whether regression-to-the-mean continued to be an issue in more recent trials. We calculated how many of the 500 selected topics of groups A and B maintained very large effects with a 2-tailed P.001 including all the available evidence.11 With a P.001 (2-tailed), the treatment effect estimate is more than 2.58-times larger than the standard deviation of the estimate and some nonnull effect is likely to be present (99.5% likely to be present unless the total sample size is still very small or the prior probability of an effect being present was 10%).11,12 These topics can be considered to have effects that have been very well-validated.11 We then recorded what these topics were and what kind of outcomes and interventions they pertained to overall. We also did the same focusing on those topics for which 2 or more trials had been performed. Finally, we also surveyed all the Cochrane forest plots to identify whether there are any with P.001 and with a very large effect pertaining strictly to death as an outcome (not a mortality-related composite) that the systematic reviewers also considered to represent reliable evidence for which they had no major concerns about biases that may decrease the credibility of the very large effect. Given that some mortality estimates may have been presented as logrelative risks (eg, log-hazard ratio) and standard error, we also performed automatic searches across the CDSR using specifically terms mortal*, fatal, survival, and death to see whether any such forest plots may have been missed by focusing on forest plots with binary outcome data, but none were found. All data analyses were performed using Stata (version 11.0, Stata Corp). All P values are 2-tailed with nominal statistical significance claimed for P.05.","Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. + + Funding/Support: Dr Pereira was supported in part by grants from Fundac¸ a˜ o de Amparo à Pesquisa do Estado de Sa˜ o Paulo (Sa˜ o Paulo Research Foundation, FAPESP) + + Role of the Sponsor: The funding agency had no role in the design and conduct of the study; the collection, analysis, and interpretation of the data; or the preparation, review, or approval of the manuscript.",JAMA,1,0,1,1,1,1,1,1,1,8 +53,"Assessment of vibration of effects due to model specification + can demonstrate the instability of observational associations","Toward this goal, the data, code, and figures for this Primer are available in a repository located here: http:// chiragjpgroup.org/voe. + + Supplementary Material Refer to Web version on PubMed Central for supplementary material. + + All data, software code, and additional figures can be found at the following website: http://chiragjpgroup.org/voe",,,"Data source: NHANES 1999–2000, 2001–2002 and 2003–2004 We downloaded NHANES examination, laboratory, questionnaire, and National Death Index (NDI) linked mortality data for 1999–2000, 2001–2002, and 2003–2004 surveys. Mortality information was collected from the date of the survey participation through December 31, 2006 and ascertained via a probabilistic match between NHANES and NDI death certificate information. The NDI matches individuals on personal and demographic criteria, such as social security number and date of birth and its performance has been described elsewhere (e.g., [12]). Overall, 9555, 11021, and 10100 participants were followed in the 1999–2000, 2001–2002, and 2003–2004 surveys respectively, with 611, 470, and 276 assumed death events.","Adjusting variables We chose a set of fifteen variables as our set of possible adjustments. Because there is no perfect consensus on what variables should (or should not) be included as adjustments in association to all-cause mortality, we based our set on a large meta-analysis of 80 studies of physical activity on all-cause mortality [20]. Since age and sex are well-known factors related to mortality, we chose to keep these in all models (“baseline” variables) and then chose 13 other variables as the set of varying adjustments, the 12 that had the highest frequency of use among these 80 investigations (smoking, body mass index (BMI), hypertension, diabetes, cholesterol, alcohol consumption, education, income, family history of heart disease, heart disease, any cancer, physical activity) and race/ethnicity, because NHANES samples are racially heterogeneous previous studies examining mortality in NHANES adjusted for race/ethnicity (e.g., [21, 22]). We coded the 15 adjustment variables as binary, categorical, or as continuous variables. Medical history items, including any hypertension, diabetes, heart disease, family history of heart disease, and cancer were treated as binary variables. We treated alcohol consumption as a binary variable (drinking five drinks per day: yes/no). Physical activity was estimated by deriving metabolic equivalents for self-reported leisure and normal-time activities[13] and treated as ordinal variables based on Health.gov physical activity guideline categories as previously described[14]. Serum total cholesterol in NHANES was assayed in participants who had fasted at least 8 hours prior to survey. Smoking was coded as a 3-category variable (self-reported current or past smoker vs. never smoker). BMI was coded as 5 categories based on recent investigations between BMI and all-cause mortality [23], including underweight (BMI less than 18.5 kg/m2 ), overweight (BMI greater than or equal to 25 and less than 30 kg/m2), obese (BMI greater than or equal to 30 kg/m2 and less than 35 kg/m2 ) or very obese (BMI greater than or equal to 35 kg/m2 ) with the reference group being normal weight (BMI greater than or equal to 18.5 and less than 25 kg/m2 ). Income was coded as tertile of income to poverty ratio (1st and 2nd tertile versus 3rd tertile). Education was coded as less than high school education or high school equivalent (vs greater than high school education). We added race/ethnicity as NHANES participants are representative of general population of the United States (e.g., Whites, Blacks, and Hispanics) and previous studies examining mortality in NHANES have routinely adjusted for race/ethnicity (e.g.,[21, 22]). Race/ethnicity was coded as Mexican American, Non-Hispanic Black, Other Hispanic, and Other (vs. Non-Hispanic Whites). We describe the adjustment variables for survivors and deceased individuals in Table S1 (see Appendix). For analyses of the association of serum Vitamin D with all-cause mortality, we increased the number of rotating adjusting co-variates to 19 (from 13) to observe how the VoE changes under different sets of adjusting co-variates, as the options increase for adjustment further. In addition to the fifteen variables above, we selected urinary creatinine, urinary albumin, serum calcium as documented in a recent investigation vitamin D levels in mortality [24]. Further, we chose serum cadmium as we recently documented a potential association with mortality [25] along with 2 serum nutrient indicators, β-carotene and γ tocopherol, which were associated with type 2 diabetes and cholesterol lipid levels [14, 26] and had consistent VoE patterns.","We estimated the VoE for 417 clinical, environmental, and physiological variables in association with all-cause mortality using National Health and Nutrition Examination Survey data. + + Variables of interest A total of 993 self-reported, clinical, and molecular phenotypes were assayed on participants of NHANES between 1999 and 2004 and we associated 417 of these with all-cause mortality that had a minimum sample size of 1000 and a minimum of 100 deaths. These variables included 1) 179 serum or urine biomarkers of environmental exposures 2) 9 selfreported behavioral factors such as smoking, alcohol consumption and physical activity, 3) 85 self-reported nutritional intake information, 4) 27 self-reported health conditions, 5) 92 clinical factors such as body mass index (BMI), blood pressure, and cholesterol, and 6) 13 demographic variables. Environmental exposure variables are physical/chemical biomarkers of external exposures measured in serum or urine, such as blood lead concentration or assays of infectious agents, such as HIV. Broadly, these included a serum marker of nicotine metabolism (cotinine), dioxins (n=7 markers), furans (n=10), heavy metals (n=15), hydrocarbons (n=21), nutrients (n=15), polychlorinated biphenyls (n=34), pesticides (n=22), phthalates (n=12), estrogenic compounds (n=6), bacterial (n=2), and viral organisms (n=6) (Table S2). With exception of assays detecting infectious agents (which were positive/negative assays), factors were continuous in scale. All continuous exposure markers were mean subtracted and standardized by the standard deviation (z-standardized) to facilitate comparisons. Self-reported behavioral factors included current/past smoker (versus never smoker), alcohol consumption (e.g., “have you ever had five or more drinks per day?”, “how many drinks per day in last month?”), and physical activity. Physical activity was estimated by deriving metabolic equivalents for self-reported leisure and normal-time activities [13] and treated as ordinal variables based on Health.gov physical activity guideline categories for no aerobic activity, low activity (medium intensity activity greater than baseline but fewer than 150 minutes per week), moderate activity (150 to 300 medium intensity minutes a week), and high activity (>300 minutes of medium intensive activity per week or >150 minutes of high intensity per week) as previously described [14, 15]. Self-reported food and nutrient consumption variables were determined from one in-person 24-hour interview (1999–2000, 2001–2002) or two 24-hour (2003–2004) in-person and on the phone interviews using the United States Department of Agriculture and Department of Health and Human Services food recall questionnaires [16–19]. These included daily estimated intake of 68 nutrients and vitamins, including vitamin A, B, C, E, carotenes, carbohydrates, sugars, proteins, fats, minerals (iron, sodium, potassium). All continuous food and nutrient consumption variables were z-standardized for comparison. Clinical variables included body measurements assessed by a health professional, including height, weight, waist circumference, thigh circumference, triceps skinfold, subscapular skinfold, calf circumference. Laboratory values included serum measures of lipids (e.g., fasting LDL-cholesterol, HDL-cholesterol, triglycerides, glucose, insulin), creatinine (urine and serum), albumin (serum and urine), uric acid, total serum protein, C-reactive protein, thyroxine, and thyroid stimulating hormone, and others. Laboratory measures were logtransformed. All continuous clinical measures were z-standardized to facilitate comparison.","We selected 13 variables as adjustment co-variates and computed 8,192 Cox models for each of 417 variables’ associations with all-cause mortality.Assessing the vibration of effects in all-cause mortality We modeled 417 variables separately as a function of time to death with the Cox proportional hazards model. VoE may be utilized with any linear model, including linear or logistic regression. We used the R-project survival and survey library for all analyses and accounted for clusters pseudo-strata, pseudo-sampling units, and participant weights to accommodate the complex sampling of the data [27, 28]. We considered the VoE in the context of 13 adjustment variables not including age and sex. The total number of possible combinations of adjusting variables from the set of 13 total adjustments is 8,192. For all 8,192 models, sample sizes remained constant. Our algorithm for computing the VoE for a variable x (e.g., HDL-cholesterol) is the following: 1. Select a number k from 0 to n total adjustment variables (n=13). Categorical variables are considered as a single group (e.g., education or BMI is selected as a group of variables together) 2. For each combination of k number of adjustment variables (k number of distinct variables from the set of all variables z0 through zn), associate x with all-cause mortality with Cox-proportional hazards and assess the effect size (β) and p-value for x: + Where i0…in are indicator variables (=1 or 0) whether the particular variable is in the model or not for a given k. Thus, the sum of indicator variables is equal to k. The number of iterations in this step is the total number of k number of combinations possible out of a set of n total variables. 3. If k = n, then stop. If k < n, then go back to step 1. for k+1 + + Assessing summary statistics We computed summary statistics for the VoE. These included the 1st, 50th (median), and 99th percentile of effect sizes and p-values. We created summary statistics derived from the distributions of VoE for a variable. The first was the “relative hazard ratio” (RHR), the ratio of the 99th percentile and 1st percentile HR (or the difference between the 99th and 1st percentile of effect size estimates). The RHR measures the difference between the larger and smaller effect sizes and this measure connotes a spread of effect sizes for different combinations of adjustments. The second was the “relative p-value” (RP), which is the difference between the 99th and 1st percentile of −log10(pvalue). We assessed the median effect size and p-value for a given variable for each kth level of adjustment. + + Systematic search for interactions between variables and adjustments The VoE may vary depending on different strata of adjustment variables. Thus, we systematically searched for interactions between variables of interest and the 13 adjustment variables with the inclusion of a multiplicative interaction term. Interactions between variables are very often claimed in observational research, but the search for them is not systematic and the validity of the claimed interactions is often tenuous[29]. Specifically, our procedure to search for interactions between a variable x and the 13 possible adjusting variables was the following: For each adjusting variable k from 1–13: + Where ζk corresponds to the interaction term. We collected the test-statistic and p-value for the interaction term to determine presence of interactions. For categorical adjustment variables, we assessed presence of interaction each category of the variable separately. Thus, we tested for interactions between variables of interest and: 2 categorical variables corresponding to education (< high school and high school education vs. > high school education), 2 variables corresponding to the largest race groups (Non-Hispanic Whites and Mexican Americans vs. Whites), 4 BMI variables (vs. normal weight), 2 variables corresponding to current and past smoking, and 1 variable each for coronary disease, family history for coronary disease, hypertension, diabetes, any cancer, total cholesterol (mean subtracted standardized by the SD), physical activity, drink five drinks per day, age, and male sex resulting in 20 effective tests of interaction for a variable x. To maximize power of detection of interaction, we restricted the search to 107 variables with the least missing data and sample sizes greater than 6,500 (range of sample size = 6,500–8,607). Thus, this resulted in 2,140 total of interactions tested (107*22=2,140). We considered the strongest interactions as those that surpassed a Bonferroni level of statistical significance (p< 0.05/2,140=2x10−5). + For interactions that surpassed Bonferroni level of significance, we computed the VoE for each strata of the adjustment variable separately. For example, if we found a significant interaction between a variable x and any family history of heart disease was found we assessed the VoE for x for samples who answered without family history of heart disease and with family of heart disease separately. If an interaction was found between a variable x and total cholesterol, we categorized samples as having less than 200 mg/dL, greater or equal than 200 and less than 239 mg/dL, and greater than 239 mg/dL total cholesterol. We show the VoE for the strongest interaction between platelet count and total cholesterol (interaction p=1x10−10, total cholesterol main effect p=0.01, and platelet count main effect p=1x10−9) in Fig. S4.","Competing Interests: The authors declare no competing interests + + Funding: This work was supported by a National Institute of Environmental Health Sciences K99 ES023504, R21 ES0250252 and a PhRMA foundation award to CJP.",Journal of Clinical Epidemiology,1,0,0,1,1,1,1,1,1,7 +54,Genome-wide association study meta-analysis of blood pressure traits and hypertension in sub-Saharan African populations: an AWI-Gen study,"Reporting summary Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. + + Data availability The AWI-Gen data set is available from the European Genome phenome Archive (EGA) database (https://ega-archive.org/), with accession number EGAS00001002482 (phenotype dataset: EGAD00001006425; genotype dataset: EGAD00010001996, genome assembly: GRCh37/hg19). The availability of these datasets is subject to controlled access through, the Data and Biospecimen Access Committee of the H3Africa Consortium. The processed data generated in this study are provided in Supplementary Material. The summary statistics reported in the paper are accessible on the GWAS Catalog (https://www.ebi.ac.uk/gwas/). Permission was obtained to access the genotype and phenotype dataset for UKBB (research project number: 63215) (as described in Methods). Publicly available databases include (1) GWAS Catalog17 (https://www.ebi.ac.uk/gwas/; BP, EFO_0004325; SBP, EFO_0006335; DBP, EFO_0006336; HTN, EFO_0000537; PP, EFO_0005763; MAP: EFO_0006340), (2) PhenoScanner37 (http://www. phenoscanner.medschl.cam.ac.uk/, Traits: BP, SBP, DBP, HTN, PP, MAP). Other summary statistics reported in the paper are accessible on the GWAS Catalog (https://www.ebi.ac.uk/gwas/) for (1) Gurdasani, et al.45 African-ancestry UGR cohort (SBP: GCST009053, DBP: GCST009052). (2) Evangelou, et al.16 European-ancestry UKBB & ICBP cohorts (SBP: GCST006624, DBP: GCST006630, PP: GCST006629). (3) Wojcik, et al.46 multi-ancestry PAGE cohort (SBP: GCST008044, DBP: GCST008029). Source data are provided as a Source Data file. Source data are provided with this paper. + + Code availability The H3ABioNet/H3Agwas GWAS pipeline workflow68,80 was employed for QC, association testing, meta-analysis and fine-mapping (as described in the methods section, available at https://github.com/ h3abionet/h3agwas). + + Additional information Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-023-44079-0.",,NATURE,"Ethics statement and consent Ethical approval was obtained from the Human Research Ethics Committee (HREC) (Medical) of the University of the Witwatersrand (Protocol Number: M190927). This was a sub-study to the AWI-Gen study (Protocol Numbers: M121029, M170880, M2210108). Each of the participating sites also obtained ethics approval from their respective ethics committees. AWI-Gen sample data was used as permitted by the informed consent provided by the study participants and according to the H3Africa policies and guidelines (www.h3africa.org).","BP measurements The outcome variables were SBP, DBP, HTN, PP and MAP. A digital sphygmomanometer (Omron M6, Omron, Kyoto, Japan) was used for BP measurements, which were taken three times at 2-minute intervals, with the last two measurements used to calculate the average SBP and DBP levels. PP and MAP were measured and calculated as continuous traits i.e. PP was calculated as the difference between the SBP and DBP and MAP was calculated as the sum of DBP and a third of the PP. HTN (binary trait) was classified according to the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High BP (JNC7) guidelines66 (see Supplementary Data 1). Hypertensive individuals (3683 cases; 6018 controls) were defined by the following conditions: individuals previously diagnosed with HTN and/or individuals taking medication for HTN and/or individuals having either SBP equal/above 140 mmHg or DBP equal/above 90 mmHg10. Adjustments were made for those taking AHM where 15 mmHg were added to SBP and 10 mmHg were added to DBP (N = 2293), as done in previous African studies26,39,40. QC was performed on the phenotype data using Stata V15 (StataCorp, College Station, Texas, 77845, US)67 to assess outliers and distribution (Supplementary Fig. 1). The Winsorise very extreme value approach was used to assess outliers i.e. the values should be <6 standard deviations (SD) above or below the mean, but no such values were observed (Supplementary Fig. 1). + + Genetic data and imputation QC. Genotype data of ~11,000 samples was generated on the 2.3 M SNP H3Africa genotyping array designed to include common African variants (https://chipinfo.h3abionet.org). The H3ABioNet/H3Agwas QC pipeline workflow68 (https://github.com/h3abionet/h3agwas/tree/ master/qc) was used to conduct QC analysis as previously described58 (see Supplementary Note 1). After QC ~ 1.7 million SNPs and 10,903 samples remained. + + Imputation. Genotype imputation was conducted to increase the coverage of genomic variation and allow fine-mapping. The African Genome Resources reference panel (EAGLE2 + PBWT pipeline) at the Sanger Imputation Server (https://imputation.sanger.ac.uk) was used for genotype imputation to increase the coverage of the genome, to narrow down the location of potential causal variants and to capture most haplotype blocks. Post-imputation QC (i.e. removal of indels, rare SNPs) resulted in 13,976,041 SNPs (MAF > 0.01 and info score > 0.6)58.","Study participants Participants were from the AWI-Gen study (10,775 participants, with the majority (89.3%) aged between 40–60 years), located in three African regions (East, West, South) from six sites within four countries (Fig. 1) i.e. East - Kenya (Nairobi); West - Burkina Faso (Nanoro) and Ghana (Navrongo); and South - South Africa (Agincourt, Dikgale, Soweto). Exclusion criteria for the study were: pregnant women, close relatives of existing participants (first and second-degree relatives), recent immigrants (who migrated <10 years ago into the region) and individuals with physical impairments preventing measurement of BP. Further study cohort details can be found in Ramsay et al.35 and Ali et al.36. Singh et al.49 was used as a reference to identify previous GWAS for BP-related traits in African populations, identifying only one study with summary statistics for SBP and DBP in a continental African population i.e. Gurdasani et al.45. + + Only participants with good-quality phenotype and genotype data were used for the GWAS analyses (N = 10,775). The genome assembly (base pair position) was the GRCh37/hg19.","Genetic association analysis The discovery GWAS for the BP-related traits was conducted in two stages (Fig. 1). + + Discovery GWAS (Stage 1 AWI-Gen GWAS). Potential confounders used as covariates in the GWAS were examined for significance by running a general linear model, using STATA V1567. As the participants originate from East, West and Southern Africa, there was significant population structure across regions (Supplementary Fig. 4); moreover, the preliminary analysis indicated relatedness among individuals from some of the AWI-Gen cohorts. Therefore, adjustments based on PCs (addressing genetic population structure) and kinship-matrix (addressing relatedness) were used as covariates. Previously defined confounders were also used as covariates, using Singh et al.49 as a guideline to determine adjustments (except for BMI which was not adjusted for in the previous studies which were included in the Stage 2 GWAS). All genetic association tests were adjusted for the covariates: age, age2 , sex and the first 10 PCs (population structure and geographic region-based adjustments). The H3ABioNet/H3Agwas Association pipeline workflow68 was used to conduct the discovery GWAS (https://github.com/h3abionet/ h3agwas/). Novel associations were defined using the GWAS significant threshold of p < 5E−08, with a suggestive threshold of p < 5E−06. Linear mixed models (LMMs) were used to account for random effects for relatedness. Matrix LMMs were run to test for genetic associations, for an additive genetic model, for four continuous BP traits (SBP, DBP, PP and MAP) and one binary trait (HTN), using the Bayesian LMM association testing approach in BOLT-LMM V2.3.2 mixed model association testing69. This approach accounts for relatedness, ancestral heterogeneity (in samples) and any other unaccounted structure within the data. Independent GWASs for each AWI-Gen region (East, West, South) were conducted and a meta-analysis of summary statistics was con ducted, using Han and Eskin’s random-effects (RE2) model (see Supplementary Note 2.1), in METASOFT v2.0.170. This was implemented in H3ABioNet/H3Agwas Meta-analysis pipeline workflow68 (http://github. com/h3abionet/h3agwas/meta/meta.nf), to evaluate the robustness of associations detected in a joint analysis of the AWI-Gen dataset (Stage 1 GWAS). A power calculation was conducted (study design = continuous trait, independent individuals, hypothesis = gene-interaction, fixed number of samples = 10,903), using Quanto V1.2.371. A graph for power versus effect size (beta) at different allele frequencies (see Supplementary Fig. 2) was constructed in R72. + + Meta-analysis (Stage 2 GWAS). Previous studies, including only African and African-ancestry participants were used for a meta-analysis (sub-population of African participants from the UKBB (https:// biobank.ctsu.ox.ac.uk) and UGR45), to combine with the Stage 1 AWI Gen meta-analysis GWAS, to improve study power (Stage 2). Permission was obtained to access the genotype and phenotype dataset of the UKBB (research project number: 63215). The UKBBa (N = 3060) was previously QCed and imputed, and a discovery GWAS was conducted, following the same methodology used for the Stage 1 GWAS. Gurdasani, et al.45 consisted of four African-ancestry cohorts: UGR (N = 6400), DDS (N = 1165), DCC (N = 1542) and AADM (N = 5231). Diabetes causes the walls of the blood vessels to stiffen, which leads to high BP51–53, therefore AADM, DDS and DCC, which included ~50% diabetic participants, were excluded. The Stage 2 meta-analysis was conducted for SBP and DBP by comparing the Stage 1 GWAS (meta-analysis of AWI-Gen GWAS by region) with the UKBBa dataset (N = 3058) and the UGR cohort (N = 6400)45 summary statistics, following the same methodology used for the Stage 1 meta-analysis. Other BP-related traits (HTN, PP, and MAP) could not be included due to the lack of data availability in cohorts used in the Stage 2 GWAS + + Visualization and interpretation of genetic associations. Miami plots were generated, to display significantly associated SNPs in associated regions, using the qqman package in R73. Genomic control (λ) was evaluated in R72 and quantile-quantile (Q-Q) plots were constructed in FUMA74 as a QC check, to re-evaluate genetic inflation and confounding biases such as cryptic relatedness and population stratification (with the assumption that the regional groupings will be independent of each other – see Supplementary Note 2.2). Several SNPs were identified, that were associated with more than one BP-related trait, meeting suggestive significance (p < 5E−06) in each trait. Regional visualization of associated SNP regions was performed using LD from AWI-Gen in LocusZoom V0.4.875, using a 1MB flanking region, which was compared to data in the GWAS Catalog17. + + Replication with previous findings Replication of the Stage 1 and 2 GWAS with populations of similar genetic ancestry was performed, using the exact replication strategy76. Replication was also tested against the Stage 1 and 2 GWAS, using previous studies: (1) GWAS Catalog17; (2) PhenoScanner37; (3) List of all 3800 published BP-associated SNPs; (4) European-only ancestry population from Evangelou et al.16, consisting of the UKBB & ICBP cohorts (currently the largest published study with 757,601 European ancestry individuals). Warren et al.38 reported only genome-wide SNPs (p < 5E−08) and summary statistics were not available. Therefore, replication of suggestive SNPs (p < 5E−04) could not be assessed for all studies. With the availability of summary statics for Evangelou, et al.16, it was possible to include the replication of suggestive SNPs for bi directional replication analysis. Multiple rows of duplicate SNPs have been included, since the same SNP was found to replicate (p < 5E−04) for more than one trait and/or GW significant, for more than one previous study. Any duplicate signals from the same study across the previous study databases were removed. Replication of the Stage 1 and 2 GWAS with previous studies, was assessed by comparing GW associations (p < 5E−08) against SNPs with suggestive associations (p < 5E−04). In addition, replication of GW signals found in previous studies (p < 5E−08) were compared against the Stage 1 and 2 GWAS suggestive associations (p < 5E−04). The H3ABioNet/H3Agwas Replication pipeline workflow was implemented to conduct replication analysis (https://github.com/ h3abionet/h3agwas/tree/master/replication). The exact replication method was used to test for replication with the GWAS Catalog (see Supplementary Note 2.3). (https://www.ebi.ac.uk/gwas/, accessed on 27 March 2022). The GW associations (p < 5E−08) were also compared against the PhenoScanner database37, since the GWAS Catalog is limited to GW signals with p < 5E−08 with a few suggestive at p < 5E−06, to pick up any missed or additional suggestive signals (p < 5E−04) found within this database (http://www.phenoscanner.medschl.cam.ac.uk). Replication of the Stage 1 and 2 GWAS was also compared against a list of 3800 published BP-associated SNPs listed within Warren, et al.38 Exact replication was tested by using Evangelou et al. (2018) summary full statistics data (currently the largest published study with 757,601 European ancestry individuals), for SBP, DBP and PP, to determine which signals were uniquely identified in studies with African-ancestry populations. Since both genome assemblies were GRCh37/hg19, a direct comparison was evaluated in R72. The different regions of the AWI-Gen datasets were also compared for South, East and West Africa (which were found to be significantly different sub-populations). Novel-associated SNPs were determined by searching for SNPs within a 500 kb region of all SNPs with GW associations (p-value < 5E −08) found in our study. + + In silico functional analysis FUMA74 was used for in silico functional analysis and annotation was performed to select the most likely causal variants from the GWAS summary statistics. The FUMA pipeline (https://fuma.ctglab.nl) was used for functional gene mapping, using the SNP2GENE tool, for positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings. Candidate SNPs were selected in the associated genomic regions with R2 ≥ 0.6 to define independent significant SNPs with GW (p < 5E−08) and MAF ≥ 0.01 for annotation (reference population = 1000 G Phase3 African; included variants in reference panel (non-GWAS tagged SNPs in LD); maximum distance between LD blocks to merge into a locus = 250 kb). Candidate SNPs functional con sequences were predicted by chromosome base-pair position, and reference and alternate alleles, to databases containing known functional annotations (see Supplementary Note 2.4). + + Fine-mapping Fine-mapping to identify potential causal variants was conducted by comparing the GW associations and/or top association SNPs found in Stage 1 and 2 GWAS, with previously reported BP loci. Lead SNPs were defined as SNPs within a genomic region that had the lowest p-value (per BP-trait) i.e. potential causal variants (at 95% confidence interval). The H3ABioNet/H3Agwas Finemaping pipeline workflow68 was used for fine-mapping (https://github.com/h3abionet/h3agwas/ tree/master/finemapping), to identify potential causal variants and credible sets (region set at 300 kb, using p-value z-scores to re estimate beta and se). Shogun stochastic search was performed to identify credible sets of potential causal variants, at a 95% confidence level, using FINEMAP V1.077 which employs Bayesian calculation of posterior probability. + + Polygenic risk score (PRS) The PRS analysis was conducted using trait-specific effect-weighted variants obtained from the discovery GWAS, using PRSice-2 V2.3.578 (see note Supplementary Note 3.1). The AWI-Gen study genotype data was used as the target database and could only be applied to SBP and DBP (due to BP-related trait data availability) from previous study groups by ancestry. Previous studies included: (1) African-ancestry only: A meta-analysis was conducted with the UKBBa dataset (N = 3058) and the UGR cohort (N = 6400)45 summary statistics, using the Han and Eskin’s random-effects (RE2) model in METASOFT v2.0.170, for the PRS African-ancestry only data set; (2) European-ancestry only: Evangelou et al.16 summary statistics, which consisted of UKBB and ICBP cohorts (N = 757,601), was used for the PRS European-ancestry only dataset; (3) Wojcik, et al.46 summary statistics, which consisted of the Population Architecture using Genomics and Epidemiology (PAGE) (N = 49,839 non-European individuals with 17,152 AA) cohort, was used for the overall European multi ancestry dataset (AA, Hispanic/Latino, Asian-ancestry, Native Hawaiian-ancestry, Native American-ancestry). The prediction models were adjusted for the same covariates used for the GWAS analysis i.e. age, age2, sex and the first 10 PCs, generated within PRSice-2 V2.3.578. The adjusted R-squared (adj-Rsq) was used to account for predictors that are not significant in a regression model. The Adj-Rsq was computed using residuals after adjustment (adj-Rsq). The best predictive PRS were estimated using the highest adj-Rsq. The P-value threshold (PT) was determined in PRSice-2 V2.3.578, by calculating the empirical P-value for each PRS (algorithms described in Supplementary Note 3.3). Different PTs were identified for each trait and compared using Rsq, where the best PT was defined by the highest Rsq. In addition, AUROC and AUC metrics were conducted using the pROC79 package in R72, to evaluate the performance and reclassification of a PRS model for the risk prediction. The risk stratification of PRSs was evaluated using quintile plots (comparing the difference in the mean of the phenotypic trait between the upper and lowest quintile. When AUC (Area under the ROC Curve) lower bound >0.5, it suggests statistical significance (with a 95% confidence interval) i.e. the ability to accurately diagnose patients with and without elevated SBP and DBP based on the test.",Competing interests The authors declare no competing interests.,"NATURE + + Peer review information Nature Communications thanks Helen Warren and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.",1,0,1,1,1,1,1,1,1,8 +55,"Analysis of Registered Clinical Trials in Gastroenterology, 2007-2019","(eMethods in the Supplement) + + SUPPLEMENT. eMethods. eReferences.",,"JAMA + + This report follows the STROBE reporting guideline for observational studies.","Stanford University determined that this cross-sectional study was exempt from institutional review board approval and informed consent because all clinical trial data were publicly available. + + Using a previously published protocol,1-3 we applied medical subject heading (MeSH) terms (eMethods in the Supplement) to identify 22 339 potential GI trials registered on ClinicalTrials.gov between October 1, 2007, and December 31, 2019. + + Rigorous methodology was defined as being randomized, double blinded, multisite, and overseen by a data and safety monitoring committee (DMC) and having 50 or more patients enrolled. + + Missing data were addressed via multiple imputations using a published protocol.",The Clinical Trials Research Team manually reviewed and categorized trial disease focus and anatomic location (eMethods in the Supplement).,"Characteristics extracted from ClinicalTrials.gov included funding source (industry, US government, or academic sources) and enrollment number.",,Conflict of Interest Disclosures: Dr Mahipal reported receiving personal fees from Taiho Oncology outside the submitted work. No other disclosures were reported.,JAMA,1,0,1,1,1,1,0,1,1,7 +56,"Public Availability of Published Research Data in + High-Impact Journals","Supporting Information + Appendix S1 Summary of journal policies as they relate to data sharing. (XLS) + Appendix S2 Summary of extracted data from the 500 papers reviewed for the present analysis. (XLS)",,,,"For each journal we documented the policies related to public availability and sharing of data. + + For each journal we documented the policies related to public availability and sharing of data, where available, and as stated in the instructions to authors on the journal’s website (accessed May 2009). This was done by one investigator (AA) and verified by a second (MA). Each paper was reviewed by going through the text, supplementary material and the links available on the online version. We recorded information on country of first and corresponding authors, funding sources, data links and accession numbers, and whether the paper was based on data covered by a journal policy (e.g. paper with microarray data published in a journal requiring public deposition of microarray data). Data extraction from the 500 papers was done by a single investigator (WQ) with cross-checking in the first 50 papers by two investigators (AA and MA). This information was collected in the months of July and August of 2010. Online information was considered missing if links were not available when checking on 2 separate occasions 2 weeks apart.","We reviewed the first 10 original research papers of 2009 published in the 50 original research journals with the highest impact factor. + + We examined the 50 journals with the highest impact factor according to the Journal Citation Reports (Science edition 2007) issued in the Thompson-Institute for Scientific Information Web of Knowledge. Journals that exclusively publish review articles were not included. For each journal, we also reviewed the first 10 original research papers published in 2009.",We compared the impact factor of journals where provision of materials and protocols was a condition of publication versus journals with non-binding instructions or no instructions at all using the Kruskall-Wallis analysis of variance test. We compared the proportion of papers depositing full primary data online by status of US government funding and by geographic origin of corresponding author (US versus non-US) using the Chi square test.,"Funding: These authors have no support or funding to report. + + Competing Interests: The authors have declared that no competing interests exist.",PLOS,1,0,0,0,1,1,1,1,1,6 +57,"Repeatability of published microarray gene expression + analyses","URLs for public databases. J. Craig Venter Institute, http://pga.tigr.org/; Nova dependent regulation of brain-specific splicing, http://splicing.rockefeller.edu/ rawdata.php. + + Note: Supplementary information is available on the Nature Genetics website.",,NATURE,Articles were first identified in a PubMed search using the query strategy Nature Genetics [SO] AND (microarray* OR gene expression profiling) AND (2005 [DP] OR 2006 [DP]). The strategy did not aim to have perfect (100%) sensitivity in identifying all articles using microarrays technology for comparative gene expression analyses but rather to yield an objectively selected sample that would be enriched in eligible articles.,"Evaluation teams and selection of main analysis to reproduce. Four teams of analysts evaluated the 20 potentially eligible articles. The four teams were from University of Alabama at Birmingham (UAB), Stanford/Dana-Farber (SD), London (L) and Ioannina/Trento (IT). Each team was comprised of three to six scientists who worked together to evaluate each article. Each of the eligible articles was randomly allocated to two of the four teams, with randomization conducted by computer pseudorandom numbers. + Each team independently examined its allocated articles for data availability, completeness of available information, obvious errors in the presented analyses and ability to reproduce one specific main analysis from each article. For each eligible article, the result to reproduce was set to be the first eligible analysis (comparison of groups for differential gene expression by microarrays, as above) reported in the results section by a table or figure of the main article (not supplements). By doing this, we ensured that we would focus on an analysis that was a main theme of the paper. When several tables or figures were dedicated to gene expression profiling results, we focused on the first mentioned results. If this first mention pertained to only some of many figure panels, we focused on the alluded figure panels. The teams assigned to common papers agreed first on which table or figure and panels were to be evaluated but thereafter worked entirely independently to locate the pertinent data and conduct the analysis. + + On closer scrutiny of the 20 articles, 2 of them were found to analyze only data that had already been previously published and thus were not eligible per our criteria. Therefore, we present the results of the replication of analyses for the other 18 eligible articles. + + Evaluated items. For each eligible study, the allocated teams of analysts independently considered the following items. First, they determined whether there was any mention in the primary article or its supplements about public availability of datasets and protocols or methods for any of the gene expression profiling experiments described, and whether a GEO or ArrayExpress accession number was provided. Second, they determined whether publicly available datasets covered all or only some of the gene expression profiling experiments described and whether they could be downloaded with sufficient information to determine which array corresponded to which experimental condition. If not, they determined what exactly was not covered and/or not clearly identified (in the case of datasets that do not correspond clearly to specific experimental conditions described in the paper). Third, for each of the publicly available datasets, each team evaluated (i) whether scanned images were publicly available; (ii) whether raw, unprocessed data were available; (iii) whether the processing methods seemed described in sufficient detail (regardless of whether they were considered correct or wrong); (iv) whether processed data were available; (v) whether the array platform was described with detailed descriptions of each array element, as specified by MIAME; (vi) whether any other MIAME incompliance was noted (per MIAME items 1–6); and (vii) whether anything else was missing that is considered essential (that is, information regarding which scanner was used to scan images, which software and version was used and which image processing parameters were used). Fourth, for the selected main analysis to be reproduced, each team determined whether the presented results and methods in the paper were given in sufficient detail for reproduction to be even considered or whether the results or methods were unclear, the methods were wrong or more than one of the previous problems existed. Each team determined whether the specific results of the main analysis are reproduced (i) entirely in principle (the same results were reproduced for all presented results), (ii) partially (some results were the same, others were not possible to reproduce at all) (iii) with some discrepancies, (iv) partially and with some discrepancies or (v) not at all. Each team of analysts first tried to reproduce the selected main analysis starting from the raw, unprocessed data and the described processing methods. If this failed, the perceived reason(s) were recorded. A separate repeatability evaluation starting from the presented processed data (after normalization, standardization and/or other processing) as supplied in each article’s relevant databases was carried out to see whether the final results were reproducible. + + This author collated all evaluations and examined whether there were any discrepancies in the overall final assessments. In two articles where discrepant overall assessments were observed between the teams evaluating the same article, the differing teams convened electronically and/or by teleconference to discuss their discrepancies. Consensus was reached on both articles after discussion. In both articles, the two teams of analysts found the same problems or difficulties in the reproduction effort but had originally ascribed different significance or categorization to them. For one article, one team categorized the same problems as “can reproduce partially with some discrepancies,” the other as “cannot reproduce”; for another article, one team categorized the same problems as “can reproduce with some discrepancies,” the other as “can reproduce partially in principle.” For both cases, the consensus was to categorize as “can reproduce with some discrepancies.” In one other case, one team had not noted that data were publicly available, but even with the publicly available data, there was not sufficient information to reproduce the published analysis. Finally, the lead author (J.P.A.I.) examined all the detailed data extractions and replication of analysis reports and generated the common final tables summarizing the findings. The final summary data were then perused again by all four teams to ensure that there were no errors in the entry and summarization of information.","Here we evaluated the replication of data analyses in 18 articles on microarray-based gene expression profiling published in Nature Genetics in 2005–2006. One table or figure from each article was independently evaluated by two teams of analysts. + + Eligible articles. We selected articles published in Nature Genetics between January 2005 and December 2006 that had used profiling with microarrays in order to examine differential gene expression of two or more groups or samples, one group under two or more conditions, or two or more groups of genes in the same samples. We selected papers where the gene expression profiling was a substantial enough part of the whole investigation to be mentioned in the abstract and to have the respective results presented in at least one table or figure or part thereof. We selected articles regardless of the material used, number of samples, chip used, modeling approach (supervised or unsupervised) and species concerned, and regardless of whether other techniques were used and other types of data were also generated or not. Both cDNA and oligonucleotide probes were eligible. We excluded papers without primary data (editorials, reviews, comments), papers based on data integrated from previous studies and short papers without an abstract (letters to the editor and brief communications). We excluded tiling arrays, DNA methylation arrays, copy number arrays and SNP arrays, but included miRNA array–based expression studies, splicing expression arrays and exon expression arrays. + + The identified items were screened further for eligibility. Of the 56 items retrieved electronically, 20 articles were considered potentially eligible for the project.",,"There was intentionally no communication with the authors of the articles to request additional data or clarifications because we wished to rely only on the information that an investigator would have if they were unable to contact a primary author and receive her assistance. One might argue that a paper is only an ‘advertisement’, and that interested researchers can communicate with the primary authors to obtain the full data, algorithms and methods. However, this may not always work, and one cannot assume that the authors keep extended private records on their published studies for lengthy periods of time, nor can one assume that the authors will remain employed in a position where they can devote time to readers of previous publications. For the value of the publication to persist as long as possible, it is preferable that the full information in the published paper and related links and accession databases is publicly available. We also wanted to avoid any chance of interference by the primary investigators in the independent appraisals by the analysts. + + The four teams of analysts independently sent their evaluations of the allotted papers to one of the authors (V.v.N.) who did not participate in the data extraction and repeatability efforts.",NATURE,1,0,1,1,1,1,0,1,1,7 +58,Honey bee sting pain index by body location,,,,"Twenty-five sting locations were selected throughout the body (see Fig. 1). One location (forearm) was selected as an internal standard, with the a priori assumption that stings to the forearm would induce a median level of pain. The author self-administered five stings per day. The first sting and last sting were the internal standards (forearm). These stings were given a score of “5”, and the three “test” stings were rated relative to the pain of the forearm stings. All stings occurred between 0900 h and 1000 h, to avoid time of day effects. At least 5 min of delay was given between stings, longer if pain from the previous sting persisted. + + Sting locations were randomly ordered by the statistical program R (R Core Team, + 2012). When applicable, the left and right side of the body were alternated. Some locations + required the use of a mirror and an erect posture during stinging (e.g., buttocks). Stinging + occurred before the author did any other honey bee work, to prevent unintentional sting during routine bee work from interfering with the experimental stings. The author had + received approximately 5 stings per day for three months before the experiment, so no + changes in his immune system were to be expected over the course of the experiment + (Light et al., 1975) + + Honey bees were collected from the hive entrance and only guards were selected, as identified by their stance (Seeley, 1985). Guarding is a specialized defensive task (Moore, Breed & Moor, 1987), so these bees are more likely to sting under natural settings (Breed, Guzman-Novoa ´ & Hunt, 2004). Guard bees were collected in a cage, and used immediately. Bees were taken from the cage haphazardly with forceps. To apply the sting, the bee was grabbed by the wings and pressed against the desired sting location. The bee was held against the sting location until the sting was first felt, and kept at the location for 5 s to ensure that the stinger would penetrate the skin. The bee was pulled away after 5 s, leaving the stinger in the skin. The stinger was left in the skin for 1 min, and then removed with forceps. + In total, three full stinging rounds were conducted at the Liddell Field Station of Cornell University in Ithaca, New York (42◦27.6′N, 76◦26.7′W). The author was stung over a total of 38 days, between 20 August 2012 and 26 September 2012. To keep the author as blind to the ratings as possible, notes were kept hidden from previous days. After two stinging rounds had been conducted (each stinging round covered all anatomical sting locations), the scores were reviewed, to see if there was a large discrepancy between scorings per sting location. Only one location differed by 3 units (foot arch), and two locations by 2 units (upper thigh and behind the ear). Even though the consistency between the first two rounds was high, a third round of stinging was performed.","The pain was rated by the author as precisely as possible on a scale of 1–10, relative to the internal standard (score of 5). Lower scores denote less pain; higher scores denote more pain.",The author,"Statistical tests and linear models were analyzed using R, and the packages stats and lme4 (R Core Team, 2012). Descriptive statistics (mean and standard deviation) were summarized for each body location. A linear model was constructed after checking that the data satisfied all linear model assumptions: normality of residuals, constant variance of errors, and no serial correlation. The linear models were used to determine if there were any significant differences in pain rating (response variable) according to the body location, the side of the body, the stinging round, or the stinging date (predictor variables). Models were compared using AIC values, with lower AIC values indicating a better fit. + All the pain ratings collected in this experiment came from one person (the author), to minimize the number of people stung. Statistical testing was used to describe the results, and determine if body location would predict the pain rating. However, because only one person was stung, these data are repeated measures of a single subject (n = 1). The data should therefore be taken to represent only this person, and not be generalized for the public.","This study is limited by its low sample size: one person, the author. + + Funding + This material is based on work supported by a United States National Science Foundation (NSF) Graduate Research Fellowship. The funders had no role in study design, data collection or analysis, decision to publish, or preparation of the manuscript. + Grant Disclosures + The following grant information was disclosed by the author: + United States National Science Foundation (NSF) Graduate Research Fellowship. + Competing Interests + The author declares there are no competing interests.",,0,0,0,1,1,1,1,1,0,5 +59,The Geometric Increase in Meta-Analyses from China in the Genomic Era,,,,Articles selection was done by systematically screening through the meta-analyses published in 2012 in chronological order of PubMed indexing until we identified 50 eligible meta-analyses from each country group.,"We generated separate counts for all meta-analyses worldwide, as well as those with listed affiliation from the People’s Republic of China (China [affiliation] NOT Taiwan [affiliation]) and, for comparison, those with affiliation from the US (USA [affiliation] OR US [affiliation] OR United States [affiliation]), since US has historically been the top producer of meta-analysis publications. + We then separated the meta-analysis publications according to field as follows. First, genetics-related meta-analyses were searched using the strategy ‘‘gene OR genetic OR polymorphism OR genome OR mutation OR haplotype’’. Of those meta-analyses not captured with this strategy, we used the search ‘‘trial OR random* OR treatment’’ to identify treatment-related meta-analyses. Of those captured with neither of these two strategies, we used the search term ‘‘sensitivity’’ to identify meta-analyses of diagnostic performance. Of those not captured with any of these three searches, we used the search ‘‘cohort or case control’’ to identify other meta-analyses mentioning studies with such designs. All remaining meta-analyses were placed in a miscellaneous group. + Given that the greatest share of meta-analyses from China was identified in the genetics-related group, we also mapped the evolution of the number of meta-analyses in genetics (total, from China and from US for comparison). We also evaluated whether genetics-related meta-analyses from China are published in the English or Chinese language, as well as whether they address genetic associations of gene variants or other research gene-related questions. + The HuGE Navigator [5] (last update search performed January 13, 2013) was also used to map annually the evolution of the number of published meta-analyses on genetic associations of gene variants since 2000 around the world and the number of meta-analyses published per year was plotted for the 10 most prolific countries during 2000–2012. + + Given the large amount of genetic meta-analyses from the US and China, we compared genetic meta-analyses from the two countries to describe the current state of meta-analysis approach in the published literature. + + For these 100 meta-analyses, we extracted the following information: journal of publication (so as to identify subsequently also the 2011 Journal Impact Factor from Thomson ISI); number of authors; language of publication; disease/phenotype (cancer, cardiovascular, infectious diseases, other disease, non-disease); type of data included (literature, investigators’ own, both); inclusion of any unpublished data other than those of the meta-analysis investigators; number of genes assessed (1,2,3, .3); number of genetic variants assessed (1,2,3, .3); any new associations proposed (yes/no – if no, whether the previously proposed genes that were probed had been derived from agnostic approaches (GWAS) (none [candidate genes only], some, all – the GWAS Catalog constructed by National Human Genome Research Institute (NHGRI) [12] was consulted to identify whether any of the gene-phenotype associations had been identified in GWAS); models used for data synthesis (fixed effect, random effects, both); relative risks or absolute differences reported in the abstract (relative risk, absolute difference, both, none); largest relative risk (more deviating from 1.00 in either direction) reported in the abstract; largest nominally statistically significant relative risk reported in the abstract; any nominally statistically significant results (P,0.05 or 95% confidence interval excluding the null) reported in the abstract (yes/no); any genome wide statistically significant results (conventionally defined as P,561028 ) reported in the abstract (yes/no); conclusion of the abstract regarding whether there is some association or not (yes/ no); abstract suggesting differences in populations of different ethnicity/ancestry (yes/no); abstract suggesting significant associations only with a particular inheritance model, and if so, which; and any suggestions made in the abstract that more data are needed (yes/no). We also evaluated whether the meta-analyses included any data from GWAS (yes/no); whether the eligibility criteria aimed to include data from Chinese-language studies (yes/ no); whether literature searches included Chinese biomedical literature databases [13] or were limited to western databases such as PubMed and EMBASE; and whether any Chinese-language studies were indeed included in the meta-analysis calculations, and, if so, how many. For comparison, we also assessed whether studies in any other language besides English/Chinese were considered eligible.","We focused more on meta-analyses from China (the current top producer of meta-analyses) versus the USA (top producer until recently). + + We compared in-depth 50 genetic association meta-analyses from China versus 50 from USA in 2012. + + We searched PubMed (last search date September 1, 2012) for publications classified as type ‘‘meta-analysis’’ and performed also counts per publication year from 1995 until 2012. + + We evaluated 100 genetic association meta-analysis articles (50 from China and 50 from the US) published in 2012. We defined genetic association meta-analyses to include studies that use published and/or new data on candidate or GWAS-derived associations (newly proposed, or further validated) of genetic variants with any outcome/phenotype of interest. We included in this category, meta-analyses of variants with pharmacogenetic associations, and meta-analyses of Mendelian randomization provided they also addressed some clinical phenotype. We excluded meta-analyses of somatic mutations and of gene expression data.","We compared the two groups using chi-square test with Yates’ correction, Fisher’s exact test, Freeman-Halton or chi-square test adjusting for trend, and Mann-Whitney U test, as appropriate. With n = 50 meta-analyses in each group, and assuming that 20% of the US meta-analyses would assess candidate gene variants, we had at least 90% power to find a significant difference at alpha = 0.05, if the proportion of meta-analyses from China addressing candidate genes were 50% or higher [14]. One comparison used all 100 meta-analyses; a further analysis focused only on meta-analyses that addressed only genetic variants that have not been validated in GWAS, since the large majority of these associations are likely to be spurious [8,9,10,15,16]. All Pvalues are two-tailed.","Funding: The authors have no support or funding to report. + + Competing Interests: The authors have declared that no competing interests exist.",PLOS,0,0,0,1,1,1,1,1,1,6 +60,Can Sex Improve Nasal Function?—An Exploration of the Link Between Sex and Nasal Function,,,,,"For evaluation of subjective nasal breathing a visual analogue scale (VAS) from 0 (no impairment) to 10 (no nasal breathing possible) was applied. For objective data, nasal resistance and flow were measured with a portable rhinometric device (Rhinomanometer 300, ATMOS Medizintechnik). The measurements were obtained at the participants’ home by themselves. The VAS and the usage of the rhinometric device were explained in detail to the participants. + Assessments of nasal function were performed at 5 specific points namely (1) before sexual activity (baseline), (2) immediately after orgasm, (3) 30 minutes, (4) 1, and (5) 3 hours after sexual climax. ‘‘Immediately’’ was defined as within 1 minute after sexual climax. Climax in female and male is the ‘‘sudden discharge of accumulated sexual excitement during the sexual response cycle, resulting in rhythmic muscular contractions in the pelvic region characterized by sexual pleasure.’’13 The data were only obtained if both individuals experienced sexual orgasm. Same data were collected for the study participants on the following day after application of nasal decongestant spray (0.1% xylometazoline; 1 application per side). + Nasal Obstruction Symptom Evaluation (NOSE) questionnaires were used to assess preexisting impairments of nasal function (range 0-100, lower scores indicate better nasal breathing). The NOSE questionnaire is a validated and reliable questionnaire developed by Stewart et al, consisting of 5 questions assessing nasal obstruction within the past month.14 Lipan et al15 showed that a NOSE score of 30 best differentiates between patients with or without nasal obstruction with higher scores indicating worse obstruction.",All participants also underwent prior anterior rhinoscopy by an otolaryngologist. Participants with acute or chronic rhinitis/rhinosinusitis were excluded. None of the participants had undergone prior nasal surgery or showed signs of nasal polyps,Statistical analysis was performed with an anonymized data set using the statistical software SPSS version 23.0.00 (IBM). The difference between mean scores before and after intervention and between the 2 interventions (‘‘sex’’ and ‘‘spray’’) were analyzed by a t test for dependent samples or in case of less than 16 data sets with Wilcoxon test. A difference was considered statistically significant with P .05.,"The strength of this study is the use of both subjective (VAS) and objective (rhinometric) measurements at different time points. Comparison to nasal decongestants were also very informative. + This study however has major limitations. We were not able to collect rhinometric data in all participants. This could be due to the participants’ inability to focus on the device before and immediately after intercourse. The participants were all health care professionals indicating that our study group does not represent an equally distributed population. Our relatively high mean NOSE score and average VAS at baseline suggest that we selected participants complaining of nasal obstruction. This may be the reason why they agreed to conduct in our study causing a selection bias in our study population. The collection of data by the participants may not be reliable. As the rhinometric measurements were obtained at the participants’ home by themselves, the compliance with the guidelines cannot be guaranteed. Acoustic rhinometric evaluation would have been ideal, but a portable version was unavailable. Also, the results of this study, though interesting, may not be generalizable + + Declaration of Conflicting Interests + The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. + Funding + The author(s) received no financial support for the research, authorship, and/or publication of this article.",,0,0,0,0,1,1,1,1,0,4 +61,"Evaluating the replicability of social science + experiments in Nature and Science between + 2010 and 2015","Code availability. The analysis codes for both the aggregate data and each individual replication are available at the project’s OSF repository (https://osf.io/pfdyw/). + + Data availability. The data reported in this paper and in the Supplementary Information are tabulated in Supplementary Tables 3–6. The replication reports (pre-data collection and final versions) and the data and analysis code for each individual replication are available in subprojects organized in the same repository (https://osf.io/pfdyw/). + + Additional information Supplementary information is available for this paper at https://doi.org/10.1038/ s41562-018-0399-z.",,NATURE,"Methods The methods of the study are detailed in the Supplementary Methods. The replications and the prediction market study were approved by the institutional review board or an ethical review board, and participants gave informed consent to participate.","The replications follow analysis plans reviewed by the original authors and pre-registered prior to the replications. The replications are high powered, with sample sizes on average about five times higher than in the original studies.",We replicate 21 systematically selected experimental studies in the social sciences published in Nature and Science between 2010 and 2015.,,"Acknowledgements Neither Nature Human Behaviour nor the publisher had any involvement with the conduct of this study prior to its submission to the journal. For financial support we thank: the Austrian Science Fund FWF (SFB F63, START-grant Y617-G11), the Austrian National Bank (grant OeNB 14953), the Behavioral and Neuroeconomics Discovery Fund (C.F.C.), the Jan Wallander and Tom Hedelius Foundation (P2015-0001:1 and P2013-0156:1), the Knut and Alice Wallenberg Foundation (Wallenberg Academy Fellows grant to A.D.), the Swedish Foundation for Humanities and Social Sciences (NHS14-1719:1), the Netherlands Organisation for Scientific Research (Vici grant 016.Vici.170.083 to E.-J.W.), the Sloan Foundation (G-2015-13929) and the Singapore National Research Foundation’s Returning Singaporean Scientists Scheme (grant NRF RSS2014-001 to T.-H.H.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. + + Competing interests The authors declare no competing interests.",NATURE,1,0,1,1,1,1,0,1,1,7 +62,"Using prediction markets to estimate the + reproducibility of scientific research","Data deposition: The data reported in this paper have been deposited in the Open Science Framework database, https://osf.io/yjmht. + + This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. 1073/pnas.1516179112/-/DCSupplemental.",,,"The RPP by the Open Science Collaboration (10) sampled papers in the 2008 issues of three top psychology journals: Journal of Personality and Social Psychology, Psychological Science, and Journal of Experimental Psychology: Learning, Memory, and Cognition. In the case of several studies in one paper, typically the last study of each paper was selected for replication.","For each replication, the hypothesis of the original study was summarized by one of the authors of this paper and submitted to the replication team for comments and final approval. In 1 of the 23 studies in the first prediction market, the chosen experiment was changed by the replicating researcher after the survey had been performed but before the trading started (SI ref. 34 in Supporting Information); we thus lack survey data for this study. One of the 21 studies in the second prediction market was later changed for a different experiment to be replicated (SI ref. 59 in Supporting Information), but for completeness we still include the prediction market and survey data for this study (although there are no current plans to replicate this study). + + We transformed this latter measure into a 1–5 scale, and it was used to construct the weighted average belief measure from the survey. Trading in the prediction market took place through a web-based market interface in collaboration with Consensus Point (www.consensuspoint.com/), a leading provider of prediction market research technology. Before starting to trade, participants received information about the trading procedure as well as logins. Trading accounts were initially endowed with $100 (expressed as 10,000 “points”). These points were used to make predictions of successful replication. Predictions were made by buying and selling stocks on the hypotheses on an interface that highlighted the forecasting functionality of the market (Supporting Information). In the prediction market, participants traded contracts that pay $1 (i.e., 100 points) if the study is replicated and $0 otherwise. This type of contract allows the price to be interpreted as the predicted probability of the outcome occurring. For each hypothesis, participants could see the current market prediction for the probability of successful replication. + + To buy stocks, participants chose YES on the trading interface and entered how many points they would like to invest. For each additional point invested in a YES position, the price (and the predicted probability for successful replication) increased. To sell stocks, participants chose NO on the trading interface and entered how many points they would like to invest. For each additional point invested in a NO position, the price decreased. Participants could also buy (sell) shares by increasing (decreasing) an existing YES position, or de creasing (increasing) an existing NO position.","We here report the results from prediction markets set up to quantify the reproducibility of 44 studies published in prominent psychology journals and replicated in the Reproducibility Project: Psychology. + + We chose 23 studies for the first set of prediction markets and 21 studies for the second set of prediction markets, where the chosen studies were scheduled to be replicated within 2 mo after the completion of the prediction market. + + Participants in the prediction market were researchers in various fields of psychology, ranging from graduate students to professors. Fourteen participants were directly involved in one or several replication studies (15 studies in total) and were not allowed to make trades on the outcomes of these specific studies. Sixteen participants participated in both sets of prediction markets. Before the prediction market, the participants filled out a survey. For each study, participants were asked two questions. One was meant to capture their beliefs of reproducibility: “How likely do you think it is that this hypothesis will be replicated (on a scale from 0% to 100%)?” Participants were also asked about their expertise in the area: “How well do you know this topic? (not at all, slightly, moderately, very well, extremely well).”","The trading platform used an automated marker maker implementing a logarithmic market scoring rule (32). This algorithm offers a buying price and a selling price at all times, ensuring that there is always a counterpart with which to trade. More specifically, the algorithm uses the net sales (s) the market maker has done so far in a market to determine the prices for a (infinitesimally small) trade as P = exp(s/b)/(exp(s/b) + 1). + + The market maker ensures that the value of a YES share is $1 minus the value of a NO share. Parameter b determines the liquidity and the maximal subsidies provided by the market maker and controls how strongly the market price is affected by a trade. We set the liquidity parameter to b = 100 (points). This means that, by investing 1,000 points (i.e., 1/10 of the initial endowment), traders can move the price of a single market from 50% to about 55%; and investing the entire initial endowment into a single market moves the price from 50% to 82%. For the first set of prediction markets, investments were settled 5 mo after the market had closed according to actual results of the replications in the cases where the outcome was available and to market value in the cases where the replications were not yet finished. At the time of the close of the market, only eight results were known by the replicating researcher, where all replicating researchers had agreed to not share the results with anyone until after the market closed. For the second set of prediction markets, investments were similarly settled 4.5 mo after the markets had closed. At the time of the close of the second market, one result was known by the replicating researcher; all replicating researchers agreed here too to not share their results with anyone until the market had closed.","Conflict of interest statement: Consensus Point employs B.W. and provided the online market interface used in the experiment. The market interface is commercial software. + + ACKNOWLEDGMENTS. We thank […] the National Science Foundation (Grant CCF-0953516) for financial support.",PNAS,1,0,0,1,1,1,1,1,1,7 +63,"Purified CD34+ cells versus peripheral blood mononuclear cells in the + treatment of angiitis-induced no-option critical limb ischaemia: 12- + Month results of a prospective randomised single-blinded noninferiority trial",,"Number: NCT 02089828 + + Clinical trial registration: This study is registered with ClinicalTrials.gov (NCT 02089828).",The Lancet,"Methods: A randomised single-blinded non-inferiority trial (Number: NCT 02089828) was performed. NO-CLI patients were 1:1 randomised to the PBMNCs and PCCs groups, and compared in relation to safety and efficacy outcomes. + + This randomised single-blinded parallel-group controlled trial was undertaken from April 2014 to December 2017 and was approved by the Ethics Committee of Zhongshan Hospital, which is affiliated with Fudan University. All of the participants provided signed informed consent and were enrolled by the investigators. + + The investigators recorded the participants' demographic data, Rutherford classifications, CLI aetiologies, comorbidities, other disease histories, and medical and surgical histories before randomisation. Then, the eligible patients were randomly allocated 1:1 to the PCCs or PBMNCs groups using a computer-generated randomisation schedule.","Procedures After admission, all of the participants received subcutaneous injections of rhG-CSF (Neupogen®; Amgen, Thousand Oaks, CA, USA) (5–10 μg/kg per day for 4 days) to mobilise the bone marrow cells. Additionally, enoxaparin (4000 IU/day) was administered daily to prevent hypercoagulable states. On the fifth day, a suspension of PBMNCs (200 mL) was collected via leukapheresis (COM.TEC; Fresenius Hemocare GmbH, Bad Homburg, Germany). For the patients in the PBMNCs group, the cells that were separated by leukapheresis were washed 3 times and resuspended in an ethylenediaminetetra-acetic acidphosphate buffered saline solution(200 mL) that contained 0.5% human albumin. For the patients in the PCCs group, CD34+ cells were purified using a magnetic cell sorting system (MiltenyiBiotec GmbH, BergischGladbach, Germany) immediately after leukapheresis. The final cell products were assessed by leukocyte counting and flow cytometry using CD34 antibody. The pharmacists ensured that the implanted CD34+ cell doses ranged from 105 to 106 per kg body weight. The surgeons implanted the cells into the calves/arms and feet/hands of the ischaemic limbs via equidistant intramuscular injections (0.5 mL/site) while the patients were under general anaesthesia. Severely infected wounds were debrided.","The study's inclusion criteria were as follows: the provision of signed informed consent before admission; patients aged 18 to 80 years; the presence of stenotic or occlusive lesions in the limb arteries, as confirmed by computed tomography angiography, magnetic resonance angiography, or digital subtraction angiography; CLI with a Rutherford classification of 4–5 that was anatomically unsuitable for surgery or an endovascular intervention; no improvement for at least 3 months following surgery or an endovascular intervention; rest pain that was not alleviated after at least 1 month of conservative treatments, including regular drug therapy, smoking cessation, dietary control and exercise therapy; and an area of tissue loss that had not diminished in size after at least 1 month of these treatments. The study's exclusion criteria were as follows: the occurrence of serious health events b3 months before admission, including but not limited to myocardial infarction, cerebral apoplexy, pulmonary embolism, severe hepatic dysfunction and renal dysfunction; a diagnosis or suspicion of cancer b5 years before admission; proliferative retinopathy; a life expectancy of b1 year; or contraindications for the administration of recombinant human granulocyte colony-stimulating factor (rhG-CSF).The study's inclusion criteria were as follows: the provision of signed informed consent before admission; patients aged 18 to 80 years; the presence of stenotic or occlusive lesions in the limb arteries, as confirmed by computed tomography angiography, magnetic resonance angiography, or digital subtraction angiography; CLI with a Rutherford classification of 4–5 that was anatomically unsuitable for surgery or an endovascular intervention; no improvement for at least 3 months following surgery or an endovascular intervention; rest pain that was not alleviated after at least 1 month of conservative treatments, including regular drug therapy, smoking cessation, dietary control and exercise therapy; and an area of tissue loss that had not diminished in size after at least 1 month of these treatments. The study's exclusion criteria were as follows: the occurrence of serious health events b3 months before admission, including but not limited to myocardial infarction, cerebral apoplexy, pulmonary embolism, severe hepatic dysfunction and renal dysfunction; a diagnosis or suspicion of cancer b5 years before admission; proliferative retinopathy; a life expectancy of b1 year; or contraindications for the administration of recombinant human granulocyte colony-stimulating factor (rhG-CSF).","The major amputation-free survival (MAFS) and total amputation-free survival (TAFS) rates were calculated. + + Statistical analyses We calculated the study's sample size using a non-inferiority test of 2 proportions with a randomisation ratio of 1:1. Regarding a reference group parameter, MAFS at 6 months after the transplantation of PBMNCs into the CLI patients was estimated to be approximately 93%, which was based on the findings from previous clinical trials [6,17,18]. Three publications that describe studies investigating PCC transplantation suggested that the MAFS rate at 6 months post-transplantation ranged from 69% to 94% [8–10]. Based on these data and our experience, a non-inferiority margin of −19%(20% of the MAFS in the reference group) was formulated. Assuming a 1-tailed type I error of 5% and a power of no b80%, a sample size of 23 patients/group was needed to detect the non-inferiority of MAFS at 6 months post-transplantation in CLI patients who had been treated with PCCs or PBMNCs. Given a withdrawal rate of b10%, sample sizes of 25 patients/group were finally determined. The quantitative data are presented as the means and standard deviations (SDs) or as the medians with the interquartile ranges (IQRs), depending on the distribution of the data. The categorical data are presented as numbers and percentages. We used an intention-to-treat approach, considering all of the patients randomly assigned to the study, to evaluate all of the primary outcomes and some of the safety and secondary outcomes, including all-cause mortality, complete wound healing, rest-pain alleviation, and Rutherford class. Any patient who was lost to follow-up was considered the worst-case scenario. Pearson's chi-squared test with or without Yete's continuity correction or Fisher's exact test were used to compare the groups in relation to these results. A linear mixed model was used to analyse the effects of the cell type on the longitudinal changes of the continuous variables and to determine the presence of any interactions between the individual groups and the time point. The Wilcoxon signed-rank test was used to compare the QoL scores at baseline and at 1-year post-transplantation. The MAFS, TAFS, and rest-pain relief probabilities were depicted by plotting Kaplan-Meier curves and compared using the Breslow-Wilcoxon test. Regarding the parallel experiment, the differences among N2 groups in relation to the continuous variables at the longitudinal time points were analysed using two-way analysis of variance, and the comparisons between the groups were assessed using Dunnett's t-tests with adjustments for significance. All of the tests were 2-sided, and a p value b 0.05 was considered statistically significant. The statistical analyses were performed using PASW software, version 19 (IBM Corporation, Armonk, NY, USA).","Fund: Training program for outstanding academic leaders of Shanghai health and family planning system (Hun dred Talent Program，Grant No. 2018BR40); China National Natural Science Funds (Grant No. 30801122); The excellent core member training programme at Zhongshan Hospital, Fudan University, China (Grant No. 2015ZSYXGG02); and Zhongshan Funds for the Institute of Vascular Surgery, Fudan University, China. + + All of the patients were masked before and after the interventions. During treatment, the surgeons who performed the cell transplantations knew which cellular treatment each patient received but did not participate in the patients' follow-up assessments or data collection or analysis. Another group of surgeons who were blinded to the patient allocation to the groups made independent decisions about major or minor amputations after the cell transplantations. The staff who managed the patients' follow-up assessments, collected the data, and undertook the statistical analyses were also masked. The masking was removed if a serious adverse event occurred that was related to the trial, a patient died or was lost to follow-up, or if an emergency required unmasking. When the 12-month follow-up period ended, the database was locked, and all of the investigators were unmasked. + + Funding Training program for outstanding academic leaders of Shanghai health and family planning system (Hundred Talent Program,Grant No. 2018BR40); China National Natural Science Funds (Grant No. 30801122); The excellent core member training programme at Zhongshan Hospital, Fudan University, China (Grant No. 2015ZSYXGG02); and Zhongshan Funds for the Institute of Vascular Surgery, Fudan University, China. + + Declaration of interests All of the authors declare no conflicts of interest. + + Roles of the funding sources Staff at the organisations that provided funding did not participate in the study's design; the collection, analysis, or interpretation of the data; or the writing of the report. All of the authors had full access to all of the data during the study, and the corresponding author had final responsibility for the decision to submit the manuscript for publication.",The Lancet,0,1,1,1,1,1,1,1,1,8 +64,Aspirin in Patients With Previous Percutaneous Coronary Intervention Undergoing Noncardiac Surgery,Statistical code and data set: Not available.,"ClinicalTrials.gov: NCT01082874 + + Study protocol: Available at ClinicalTrials.gov.",Annals of Internal Medicine,"Design: Nonprespecified subgroup analysis of a multicenter factorial trial. Computerized Internet randomization was done between 2010 and 2013. + + Setting: 135 centers in 23 countries. + + Design Overview POISE-2 was an international, randomized controlled, factorial trial that separately evaluated the effects of aspirin versus placebo and clonidine versus placebo in patients having noncardiac surgery. Patients were allocated in a 1:1:1:1 ratio to receive aspirin and clonidine, placebo and clonidine, aspirin and placebo, or placebo for both drugs. Full details of the trial design and results are reported elsewhere (10 –12). Institutional review boards approved the trial before recruitment started at participating centers. + + After giving written informed consent, patients were randomly assigned before surgery by a 24-hour computerized Internet system that concealed randomization. Block randomization, stratified by center and aspirin stratum, was used.","Intervention: Aspirin therapy (overall trial, n = 4998; subgroup, n = 234) or placebo (overall trial, n = 5012; subgroup, n = 236) initiated within 4 hours before surgery and continued through out the perioperative period. Of the 470 subgroup patients, 99.9% completed follow-up. + + Patients received aspirin or identical-appearing placebo (200 mg) within 4 hours before surgery and continued at a dosage of 100 mg/d for 30 days in the initiation stratum and for 7 days in the continuation stratum, after which patients resumed regular aspirin dosing. Study personnel assessed study drug adherence through nursing records in the hospital and through patient reporting after discharge. + + Patients had a troponin measurement (or creatine kinase–MB if troponin was not available) 6 to 12 hours after surgery and on the first, second, and third days after surgery. Electrocardiography was done when an elevated troponin or creatine kinase–MB level was detected. Research personnel followed patients until 30 days after randomization, collected data, and submitted case report forms and supporting documentation directly to the data management system.","Patients: Adults aged 45 years or older who had or were at risk for atherosclerotic disease and were having noncardiac surgery. Exclusions were placement of a bare-metal stent within 6 weeks, placement of a drug-eluting stent within 1 year, or receipt of nonstudy aspirin within 72 hours before surgery. + + Setting and Participants Patients aged 45 years or older who were having noncardiac surgery with an expected postoperative stay of at least 1 night were eligible if they had or were at risk for atherosclerotic disease. The trial excluded patients who received a bare-metal stent within 6 weeks or a drug-eluting stent within 1 year before randomization because of the risk for stent thrombosis as sociated with premature antiplatelet withdrawal. Patients who took nonstudy aspirin within 72 hours before surgery were also excluded to ensure unimpaired hemostasis before surgery. Participants were recruited in 135 centers in 23 countries from July 2010 to December 2013. Eightytwo centers from 21 countries enrolled patients with a history of PCI. Research personnel enrolled patients in an initiation stratum if they were not receiving longterm aspirin and in a continuation stratum if they were receiving long-term aspirin (defined as daily aspirin for at least 1 month within the 6 weeks before surgery). Patients in the aspirin continuation stratum had to dis continue aspirin therapy at least 3 days before surgery.","Statistical Analysis A statistical analysis plan was finalized before these substudy analyses were begun (Supplement). We expected aspirin to have a greater beneficial effect in patients with a history of PCI than in those without. We analyzed patients in the groups to which they were allocated, according to the intention-to-treat principle. Patients lost to follow-up before day 30 after randomization with no event reported were censored on the last day their status was known. All statistical analyses were done using SAS, version 9.4 (SAS Institute). For the primary and secondary outcomes, we did subgroup analyses based on whether patients had prior PCI (prior PCI vs. no prior PCI). For these subgroup analyses, we used Cox proportional hazards models that incorporated tests of interaction. These models adjusted for clonidine allocation. For the primary outcome, we tested for the proportional hazards assumption by including a time–aspirin allocation interaction term in the Cox proportional hazards model (time log-transformed). We found no evidence that the proportional hazards assumption had been violated; all P values were at least 0.55. We considered a P value for interaction less than 0.05 to be significant and to provide some evidence of a subgroup effect. In instances where the test for interaction was not significant, we considered the overall trial result (with the larger sample size) the likely best estimate of effect for all patients, including those within the subgroups. Estimates of the hazard ratios (HRs) and 2-sided 95% CIs were calculated using the Cox proportional hazards models. We also determined the Kaplan– Meier estimates of 30-day cumulative risk. We report between-group differences in proportions between the treatment groups as absolute risk reductions (ARRs) and increases (ARIs). We determined the 95% CIs for these differences. Among patients with a history of PCI, we did subgroup analyses based on the type of stent (bare-metal vs. drug-eluting), timing of PCI (≤1 year vs. >1 year before surgery), and preoperative use of an antiplatelet medication (use within 7 days vs. no use within 7 days before surgery) for the primary outcome. We used the same analytic approach as in the analyses comparing the prior-PCI versus no-prior-PCI subgroups.","Patients, clinicians, data collectors, and outcome adjudicators were blinded to treatment assignment. + + Limitation: Nonprespecified subgroup analysis with small sample. + + Primary Funding Source: Canadian Institutes of Health Research. + + Patients, clinicians, data collectors, and outcome adjudicators were blinded to study drug allocation. + + Role of the Funding Source POISE-2 was supported by grants from the Canadian Institutes of Health Research, the Australian National Health and Medical Research Council, and the Spanish Ministry of Health and Social Policy. Bayer Pharmaceuticals provided the aspirin used in the study, and Boehringer Ingelheim provided the clonidine and some funding. No donor or funder had a role in the design, conduct, data collection, data analyses, or manuscript preparation. The Population Health Research Institute (McMaster University, Hamilton, Ontario, Canada) was the trial coordinating center. The investigators and members of key committees and groups are reported in the Supplement. + + Financial Support: By the Canadian Institutes of Health Research, the Australian National Health and Medical Research Council, the Spanish Ministry of Health and Social Policy, and Boehringer Ingelheim. + + Disclosures: Dr. Sessler reports grants from the Canadian Institutes of Health Research during the conduct of the study. Dr. Meyhoff reports grants from Ferring Pharmaceuticals, Merck Sharp & Dohme, and Boehringer Ingelheim outside the submitted work. Dr. Xavier reports grants from Cadila Pharmaceuticals; Boehringer Ingelheim; AstraZeneca India; Sanofi-Aventis; Pfizer; National Institutes of Health; National Heart, Lung, and Blood Institute; Bristol-Myers Squibb; and UnitedHealth outside the submitted work. Dr. Painter reports grants from the Australian and New Zealand College of Anaesthetists Research Foundation outside the submitted work. Dr. Diemunsch reports personal fees from Ambu and the French government and grants and personal fees from Fisher & Paykel outside the submitted work. Dr. Yusuf reports grants and personal fees from Bayer and AstraZeneca and grants from Boehringer Ingelheim and Cadila Pharmaceuticals outside the submitted work. Dr. Devereaux reports grants from Abbott Diagnostics, Boehringer Ingelheim, Covidien, Octapharma, Philips Healthcare, Roche Diagnostics, and Stryker outside the submitted work and participating in an advisory board meeting for GlaxoSmithKline, an expert panel meeting for AstraZeneca, and consultancy meetings for Boehringer Ingelheim (2014) and Roche Diagnostics (2016). Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje /ConflictOfInterestForms.do?msNum=M17-2341.",Annals of Internal Medicine,1,1,1,1,1,1,1,1,1,9 +65,Patient Preference for Waxed or Unwaxed Dental Floss,,,,"Part 1 of the study consisted of 100 patients (Group 1) randomly presenting for routine dental examinations who volunteered to participate in the study. + + Each patient was given a 30 cm length of similar appearing standard white waxed or bonded unwaxed Control* brand dental floss dispensed from an unmarked container. Each was then asked to floss his or her choice of an anterior contact followed by a molar contact. An identical length of the second type of floss was then provided and the procedure was repeated in the same two selected contact areas. Fifty patients sampled waxed floss first and 50 sampled unwaxed first. + + All participants had anterior teeth with proximal contacts and at least one molar with molar or premolar proximal contact. Specific flossing technique instructions were not given, and the patients had the freedom to randomly select contact areas to floss. Some were provided with minor assistance, if necessary, to find suitably located contacts or to manipulate the floss. The presence or absence of a restoration was not a factor in the selection of contact areas. + + Part 2 of the study was conducted as above with an additional 50 patients (Group 2). + + Johnson and Johnsont brand floss was supplied to this group in both waxed and bonded unwaxed forms. + + Part three included an additional 50 patients (Group 3) who were asked to compare Johnson and Johnson mint flavored waxed floss and plain white waxed floss of the same brand.","After sampling both types of floss, the patients were orally asked which floss they preferred. If the floss shredded or frayed, this was noted along with other comments made by the patients including ease or difficulty of use in each area, and whether or not either floss hurt. All had an immediate and clear floss preference after performing the test. The patients were also asked how often they flossed (times per week), and what type of floss they purchased for home use (waxed or unwaxed).","There were 73 males and 27 females ranging in age from 16 to 69 years. The mean age was 33.1 years. All were evaluated by a single examiner (RHB) over a 2 month period + + There were 39 males and 11 females ages 23 to 60 years old with a mean age of 33 years. + + There were 43 males and 7 females ages 18 to 70 years old with a mean age of 34 years.",,,,0,0,0,1,1,1,0,0,0,3 +66,Impact of wet underwear on thermoregulatory responses and thermal comfort in the cold,,,,"Long-legged/long-sleeved underwear manufactured in a 1-by-l rib knit structure from three different 100% fibre-type materials-cotton, wool, and polypropylene-was tested as part of a two-layer clothing system. The underwear manufactured from 100% polypropylene was tested in two different knit structures: l-by-l-rib knit and a fishnet construction. In addition, a double-layer underwear ensemble manufactured from wool/polypropylene (47% wool / 53% polypropylene) in an interlock knit structure was tested. This double-layer textile was different to the others both in respect to fibre-type and knit structure, but we wanted to include it, because this type of underwear is becoming increasingly popular. It was compared with the underwear in the fibre-type group. Measurements of selected physical characteristics of the experimental textiles were performed on single samples of cloth in accordance with standard procedures: fabric thickness in mm (ASTM:DI776-64), weight in g*m^(-2), thermal resistance in m^2*K^(-1)*W^(-1) (ISO/S085-Part 1) and water vapour resistance in equivalent air layer in nun (CAN2-4.2-M77). The physical characteristics of the textiles used in the present study are shown in table 1. Before being tested in the laboratory, all samples were laundered and air-dried as described below. . + For each subject, the order in which the underwear was tested was randomized. The clothing outer-layer comprised trousers and a jacket made of 65% polyester and 35% cotton. During the cold exposure, cotton gloves and sneakers were worn. Before any testing was done, all underwear and outerwear were laundered and air dried to remove any excess finishing chemicals in the textiles. To prevent textile characteristics from changing during the experiment period, clothing was laundered without the use of any detergent. + + 2.3. Experimental protocol + All five underwear materials were tested wet as a part of a two-layer ensemble. The polypropylene underwear made by 1-by-l-rib was, in addition, tested dry to investigate the importance of water. To simulate clothing wet from sweating, underwear was placed in an air-tight bag with 175 g water and then left in a warm oven (50°C) overnight in order to dampen the underwear equally. This procedure gave a satisfactory distribution .of water in the cIothing. The amount of water added, 100 g and 75 g to vest and trousers, respectively, was based on sweat amounts in the underwear in previous experiments after heavy sweating (Nielsen and Endrusick 1988, Nielsen and Endrusick 1990). + To standardize the initial heat content of the different clothing systems, wet or dry, thus eliminating this as a factor of variation for the heat exchange in the body-clothing environment during the experiment a rigid procedure was followed. The dry clothing was stored in an auxiliary chamber for at least 2 h before the experimental procedure began (air temperature 25°C, relative humidity 80%). After arrival the test-subjects were equipped with recording instruments for measuring body temperatures, and were dressed in the auxiliary chamber. The underwear was brought to this chamber only 2 min before the dressing procedure began, in order to prevent the wet underwear from loosing water due to cooling during the dressing procedure. Individuals were tested at the same time of the day, to avoid influence of a diurnal variation in body temperatures. + Subjects were tested for a single 60 min period with the dressed subject sitting at rest in a netchair in a climatic chamber. Air temperature in the climatic chamber was 10°C, relative humidity 85%, and the air velocity < 0.1 m*s^(-1).","Skin temperatures, + rectal temperature and weight loss were measured every minute during the test + period. Heart rate was recorded every 10 min. Clothing weight and nude body weight + were measured before and after the test period. Subjective ratings on sensation of + temperature, humidity, and thermal comfort were collected before and after the dressing + procedure, and then every 10 min during the test period + + 2.4. Physiological variables + Skin temperatures were measured with thermistors (Craftemp, Astra Meditec) at 14 locations (forehead, neck, chest, abdomen, upper back, lumbar back, upper arm, forearm, dorsal hand, anterior thigh, posterior thigh, shin, calf, dorsal foot). In addition, an estimate of core temperature was made using a rectal thermistor (150 mm, YSI 701, Yellow Spring Instruments) inserted 80nim beyond the anal sphincter. The subject's nude weight and total loss of mass were measured on a custom-made scale (Hottinger Baldwin DK 38). Heart rate was obtained with a chest electrode belt with a heart rate meter (Sport Tester PE-3000). Water-loss from the clothing was determined by repeated weighing of each individual clothing component before and after the experiment on a scale (Maul 16520).","2.1. Subjects + Eight healthy male college students volunteered for the present study. Their physical characteristics were (mean ± SD) age of 25 ± 3.6 years, weight 77 ± 7·4 kg, height of ].84 ± 0.08 m and DuBois surface area (AD) of 1.99± 0.12 m.","2.6. Calculations + Mean skin temperature was calculated as an average of measurements from the 14 different skin sites according to the equation proposed by Olesen et al. (1972). Loss of water from the dressed subject during the experimental period was determined from the continuous monitoring of loss of mass on the platform scale. Due to a discrepancy between the weight loss measured on the platform scale during the experiment, and weight loss from test-people and clothing separately, it is likely that a considerable amount of water was lost during the dressing procedure. To get a correct measure of the amount of water in the underwear at the start of the experiment, the amount was estimated from the total weight loss measured during the experiment added to the amount of water that was left in the clothing system. This was corrected for mass of respiratory water loss according to Fanger (1970) and metabolic loss of mass according to' Kerslake (1972). The following mean values were used in the calculation; 70 W (metabolism). 0.311 min^(-1) (VO2) and 0.85 (RQ). + The difference in response with the various underwear ensembles was assessed by a one way ANOVA for repeated measures (referred to as time) of the changes in mean skin temperature, rectal temperature, continuous weight loss, thermal comfort and various ratings on sensation of temperature and humidity, for every 10 min (3-point moving average). An ANOVA was calculated from the data of nude body weight and clothing weight. Scheffe's method was used"" as a post-hoc test to locate significant differences between means during the experimental period, in the event that an ANOVA revealed a significant main effect. Mean values are presented ± SD for 8 people. All differences reported are significant at the p <= 0·05 level, and for 0.05 < p < 0.1 differences will be referred to as a tendency in the data.","This study was supported by The Nordic Fund for Technology and Industrial + Development, and The Danish Work Environmental Fund. The authors want to express their appreciation to the Nordic Industrial Research Education Committee. + + However, at present it is difficult to have any reasonable explanation why the faster evaporation rate on the polypropylene compared to wool/polypropylene underwear during the experiment gave a significant difference in sensation of temperature and thermal comfort votes, but no significant difference in the mean skin temperature.",,0,0,0,1,1,1,1,1,0,5 +67,Persistent pain and sensory disturbances after treatment for breast cancer: six year nationwide follow-up study,Data sharing statement: No additional data available.,Trial registration Clinicaltrials.gov NCT No 01543711.,BMJ,"Design Repeated cross sectional study in a previously examined nationwide cohort. All eligible women who underwent surgery for primary breast cancer in Denmark in 2005 and 2006 and were examined in 2008 were surveyed again with the same questionnaire. + + Setting Surgical centres in Denmark + + Study design From 2005 to 2005, 5119 women aged 18-70 were treated for unilateral primary breast cancer in Denmark. In 2008, with a mean follow-up of 26 months, a questionnaire was sent to 3754 eligible patients and returned by 3253 (87%).14 The present questionnaire study was a follow-up of the same cohort in 2012, at which time 2828 of the 3253 patients were eligible in the Danish Breast Cancer Cooperative Group (DBCG) database,15 according to the inclusion and exclusion criteria below. + + Setting A questionnaire, identical to the one used in the first study,14 was sent to all eligible patients on 1 February 2012 (see appendix). Those who did not respond received a second questionnaire on 5 March 2012. To minimise selection bias, a second reminder was sent on 30 March 2012 to the patients not responding to the second questionnaire. Data collection ended on 8 May 2012.","Data concerning treatment, cancer recurrence, and demographics were retrieved from the Danish Breast Cancer Cooperative Group database.15 The database has previously been validated for 1999-2004. Only about 3% of women aged 18-69 with new primary breast cancer are not available in the database.16 The database receives information from all departments of surgery, pathology, and oncology in Denmark. Data on mortality were retrieved from the Danish Civil Registration System. In 2008, information regarding reconstructive or corrective surgery was retrieved from the Danish National Patient Registry.17 In the present study, patients could report reconstructive surgery performed after 2008. Linkage between the different registers is possible because of a unique civil registration number assigned to all Danish citizens. + + Treatment Patients were treated according to the 2004 protocol of the Danish Breast Cancer Cooperative Group,16 which was based on the recommendations from the international expert consensus on primary therapy of early breast cancer in 2003.19 There were 12 major treatment groups divided according to the type of surgery and adjuvant radiotherapy and chemotherapy. Treatment details are described elsewhere.14 Oncological follow-up was performed systematically on all patients according to the protocol and registered in the database. + + Questionnaire The questionnaire used was developed for the assessment of persistent pain after treatment for breast cancer, sensory disturbances, functional impairment, and self reported lymphoedema.14 20 This questionnaire used accepted means of measuring pain21 and was content validated in the breast cancer population.","Participants In 2012, 2828 women were eligible in our database, and 108 were excluded. Exclusion criteria were death; new, recurrent, or other cancer; reconstructive breast surgery; and emigration. + + Participants All women who participated in the 2008 study were assessed for inclusion. Exclusion criteria were death and emigration. We also excluded women with recurrent, new primary, and contralateral cancer, metastatic disease, other malignant disease, and reconstructive/corrective breast surgery as they represent different pathophysiological mechanisms for persistent pain and represent only a minority of women who survive breast cancer.","Statistics All statistical methods were computed with SPSS version 19 (IBM, NY, USA). Univariate analyses were carried out to test for significant associations between covariates and outcomes with Wald χ2 test. Multivariate logistic regression models were then used to examine the concomitant influence of age and methods of treatment on pain, moderate to severe pain on at least a weekly basis, and sensory disturbances. We excluded year of surgery from all multivariate models and endocrine therapy from all pain models as these were not associated with the outcomes in the univariate analyses. For comparability with the previous study, we included type of surgery in the final multivariate analyses.14 Factors included in the models were type of surgery (mastectomy v breast conserving surgery), extent of axillary surgery (axillary lymph node dissection v sentinel lymph node biopsy), radiotherapy (locoregional radiotherapy + breast radiotherapy/anterior thoracic radiotherapy, breast radiotherapy alone v none), chemotherapy (cyclophosphamide, epirubicin, and fluorouracil v none), age, and, in the analysis with sensory disturbances as outcome, endocrine therapy. Adjusted odds ratios and 95% confidence intervals were calculated and the Wald χ2 test was used to test the overall significance of each parameter. Tests for interaction between age and the different methods of treatment and between axillary procedure and breast procedure on pain and sensory disturbances were performed pairwise in separate models applying the Wald χ 2 test. To assess pain progression or regression since the 2008 questionnaire study, we computed the difference in worst reported pain numerical rating score between 2008 and 2012. A difference of at least 2 in pain reporting was considered clinically relevant according to the IMMPACT recommendations.22 We subsequently performed multivariate logistic regression analysis to examine the influence of treatment modalities and age on pain progression of ≥2. Associations between pain in the surgical area and sensory disturbances, and pain in the surgical area and pain elsewhere, were analysed with Fisher’s exact test. Two tailed P values were calculated and the level of significance was set at 0.05. Analyses were carried out to assess possible selection bias of non-respondents. All odds ratios reported in the text are the adjusted values. The adjusted number needed to be exposed and exposure impact number for axillary lymph node dissection versus sentinel lymph node biopsy were calculated with the method suggested by Bender et al.","Funding: This study was partially funded by a grant from the Danish Cancer Society and the research leading to these results is part of the Europain Collaboration, which has received support from the Innovative Medicines Initiative Joint Undertaking, under grant agreement no 115007, which receives financial contribution from the European Union’s Seventh Framework Programme (FP7/2007‐2013) and EFPIA companies. + + Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.",BMJ,1,1,1,1,1,1,1,1,1,9 +68,A case of childhood-onset fluency disorder reduced by escitalopram,,,,"After one month of taking this dosage, the patient's symptoms were somewhat lessened, but he requested a more effective drug and changed to sertraline 2,4). However, sertraline did not work at all and the drug was discontinued after one month. This drug was effective (he could realize that the drug was effective after 3 or 4 days) and his disease became mild and almost remission. + It was continued at a small dose of paroxetine 10mg/day to minimize side effects, but the patient disliked the sexual dysfunction and discontinued it on his own. The patient does not develop a withdrawal syndrome, but his stuttering flares up. The patient is still on escitalopram 10mg/day because stuttering tends to flare up after stopping the drug. escitalopram also causes sexual dysfunction like paroxetine but the patient is treated with sildenafil. The patient says that the sexual dysfunction is stronger with paroxetine than with escitalopram, and he did not notice any sexual dysfunction during the first dose of escitalopram.",,"Case] 28 years old, male (right-handed) + (The content has been slightly altered to protect your privacy.) + Family history: nothing of note, no relatives with childhood-onset fluency disorder Medical history: nothing of note + By the age of 4 or 5 years old, he was aware of his stuttering. He underwent treatment with a speech therapist after entering elementary school, but it was ineffective and was discontinued after a year. + His personality is serious, honest and friendly. He is well-liked by people. He is of medium build, and his grades are not very good. He was bullied in elementary and junior high school because of his stuttering. After graduating from high school, he got a job at a small auto repair shop, a distant relative of his parents. He worked there for 10 years without any problems (no ""torment"" because it was a small repair shop).",,,,0,0,0,1,0,1,0,0,0,2 +69,Nonmetastatic Medulloblastoma of Early Childhood: Results From the Prospective Clinical Trial HIT-2000 and An Extended Validation Cohort,ASSOCIATED CONTENT See accompanying editorial on page 2010 Data Supplement Protocol,"(ClinicalTrials.gov identifier: NCT00303810) + + CLINICAL TRIAL INFORMATION NCT00303810",Journal of Clinical Oncology,,"DNA methylation profiles of infantile sonic hedgehog-activated medulloblastoma (SHHINF) were subdivided into iSHH-I and iSHH-II subtypes in the HIT-2000-BIS4 cohort and a validation cohort (n 5 71) from the HIT group and Russia. + + Staging Procedures in HIT-2000 Tumors from all patients underwent central neuropathologic review according to the WHO classification valid at surgery. Central review of contrast-enhanced presurgical and postsurgical cerebral magnetic resonance imaging (MRI), spinal MRI, and cytospin examination of CSF was available for 72 patients (83%). Subtotal resection was defined as a residual tumor $ 1.5 cm2 on an early postoperative MRI. + + Post Hoc Workup of Tumor Tissue Histopathology was reevaluated for all tumors according to the 2007 WHO classification. One was initially classified as DMB and described accordingly in 20119 but was reclassified as CMB after a rereview in 2014. For patients with available tumor material, tumors were classified according to DNA methylation profile using the Heidelberg Brain Tumor Classifier Version 11b4.24,25 Patients with nonmedulloblastoma histology on rereview or classified as nonmedulloblastoma on DNA methylation profiling were excluded (n 5 4; Fig 1). Targeted next-generation sequencing was performed for selected cancer genes,26 where sufficient tumor DNA could be collected. Methylation profiles of infantile-type SHH-activated medulloblastoma (SHH-INF) were further subclassified by t-distributed stochastic neighbor embedding (t-SNE) to differentiate between iSHH-I and iSHH-II (Data Supplement, online only). + + Treatment in HIT-2000-BIS4 Patients treated until 2006 received 3 cycles of HIT-SKK chemotherapy with intraventricular MTX, followed by 2 cycles of modified HIT-SKK chemotherapy (mSKK).9 Starting in 2006, patients with CMB or LCA, or patients with DMB/MBEN in incomplete remission received 54 Gy of focal radiotherapy to the tumor bed with a 2-cm safety margin after 3 cycles of HIT-SKK chemotherapy (Fig 1; Data Supplement). Quantification of the cumulative dose of intraventricular MTX was previously defined.27 + + Neuropsychological Assessment Cognitive function was assessed 5 years after diagnosis using the Wurzburger Psychologische Kurzdiagnostik ¨ (WUEP-KD) short battery.28 The Developmental Test of Visual-Motor Integration (VMI), Raven’s Coloured Progressive Matrices (CPM), Kaufman Assessment Battery for Children (KABC) number recall subtest (KABC-NR), and Riddels subtest (KABC-Riddels) were used to de scribe cognitive function. Overall intelligence quotient (IQ) was defined as the mean value of VMI, CPM, and KABC-NR.","From 2001-2011, 87 patients received systemic chemotherapy and intraventricular methotrexate. + + Patients were eligible for the multiarm trial HIT-2000 (ClinicalTrials.gov identifier: NCT00303810) based on the following criteria: age, 21 years with a histologic diagnosis of medulloblastoma, ependymoma or CNS–peripheral neuroectodermal tumor according to the WHO classification valid at the time of inclusion and initial neurosurgical resection between January 1, 2001, and December 31, 2011. A total of 87 patients were eligible and stratified into the treatment scheme HIT-2000-BIS4 (patients with nonmetastatic disease, 4 years of age at surgery). Outcomes of 45 patients treated from 2001 to 2006 were reported previously.9 The HIT-2000 trial was approved by the central ethics committee in Wuerzburg, Germany. Written informed consent, including consent for molecular analysis, was obtained from the legal representatives of all participants before inclusion. + + The validation cohort for SHH subtyping consisted of 71 additional patients treated between 1993 and 2018 with nonmetastatic medulloblastoma, classified as SHH-INF by DNA methylation profiling using the Heidelberg brain tumor classifier and treatment according to the HIT-SKK protocols. Patients were treated within HIT study group centers or in the Burdenko Neurosurgical Institute in Moscow, Russia (Burdenko cohort). HIT registries were approved by the ethics committee in Wuerzburg (ClinicalTrials.gov identifier: NCT02238899) and Hamburg (ClinicalTrials.gov identifier: NCT02417324), Germany. The data collection from the Burdenko cohort was approved by the ethics committees of the Burdenko Neurosurgical Institute in Moscow and Heidelberg. Written informed consent was obtained from the legal representatives of all participants before inclusion.","Statistics Progression-free survival (PFS) was defined as the time from the first tumor surgery to progression, relapse, or death. Overall survival (OS) was defined as the time from the first tumor surgery to death from any cause. CSI-free survival was defined as time from the first tumor surgery to craniospinal radiotherapy or death from any cause. All three were censored at last follow-up for patients without an event. Survival rates were estimated using the Kaplan-Meier method. Survival data were compared using the log-rank test, categorical variables were compared using Fisher’s exact test, and steady variables were compared using the Welch test. For comparison of neuropsychological test results with the normal population, results were compared using a 1-sample t test against a mean value of 100 for IQ scores. All statistical tests were 2-sided. In the HIT-2000 protocol, no statistical endpoint was set for the HIT-2000-BIS4 stratum; therefore, all P values are to be considered explorative. The local significance level was set at .05. No adjustment for multiple testing was performed. Analysis and data visualization were performed using R 3.5.2, with the survival, survminer, ggplot2, conumee, and complexheatmaps packages.","SUPPORT Supported by the German Childhood Cancer Foundation (DKS# 2001.03, 2004.03, 2005.13, 2006.05, 2008.01, 2009.18, 2010.18, 2012.01, 2013.07, and 2015.04 to S.R. for HIT 2000, HIT2000interim Registry and I-HIT-MED Registry; DKS# 2013.03 to H.O. and P.G.S. for neuropsychological follow-up; DKS# 2015.01 and 2017.01 to S.P. for molecular analysis; DKS# 2011.02, 2008.07, 2006.13, 2005.07, 2003.09, 2001.05 to M.W.-M. for neuroradiologic review, DKS# 2011.01, 2009.19 and 2006.03 to T.P. for neuropathologic review and DKS# 2011.04, 2008.11, 2005.09, 2003.11, 2001.06 to A.F. for statistical support). U.S. received support from the Fordergemeinschaft Kinderkrebszentrum Hamburg. M.B. ¨ received funding from the Styrian Childhood Cancer Foundation – Steirische Kinderkrebshilfe in the context of this work. A.K. is supported by the Helmholtz Association Research Grant (Germany). M.R., A.G., and O.Z. are supported by the Russian Science Foundation Research Grant No. 18-45-06012. M.K. and S.P. received support from The Deutsche Krebshilfe (project No. 111537). A.F. received grants from the Institute of Biostatistics and Clinical Research for the conduct of this study. + + AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST AND DATA AVAILABILITY STATEMENT Disclosures provided by the authors and data availability statement (if applicable) are available with this article at DOI https://doi.org/10.1200/ JCO.19.03057. + + Financial support: Olga Zheludkova, Martin Benesch, Paul Gerhardt Schlegel, Stefan Rutkowski + + AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I 5 Immediate Family Member, Inst 5 My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center. Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments). + Martin Mynarek Employment: Medac (I), Novartis (I) Stefan Pfister Research Funding: Eli Lilly (Inst), Bayer (Inst), Roche (Inst), Pfizer (Inst) Patents, Royalties, Other Intellectual Property: Patent on using DNA methylation profiling for tumor classification Andreas von Deimling Consulting or Advisory Role: Bristol-Myers Squibb Research Funding: Bayer Patents, Royalties, Other Intellectual Property: Patent for IDH1R132H antibody H09 administered by the German Cancer Center (DKFZ), patent for BRAFV600E antibody VE1 administered by the German Cancer Center (DKFZ) Travel, Accommodations, Expenses: Roche Felix Sahm Honoraria: Medac, Illumina, AbbVie Consulting or Advisory Role: Abbie Speakers’ Bureau: Agilent, Illumina, Medac Travel, Accommodations, Expenses: AbbVie, Agilent Markus J. Riemenschneider Consulting or Advisory Role: Bristol-Myers Squibb Travel, Accommodations, Expenses: Bristol-Myers Squibb Christian Mawrin Stock and Other Ownership Interests: Merck (I) Honoraria: Bayer Schering Pharma Research Funding: Bayer Schering Pharma (Inst) Travel, Accommodations, Expenses: Bayer Schering Pharma, Medac Jens Schittenhelm Stock and Other Ownership Interests: Qiagen Wolfgang Bruck ¨ Honoraria: Teva Pharma, Novartis, Biogen, Celgene, Roche Consulting or Advisory Role: Celgene, Roche, Novartis, Teva (Inst), Novartis (Inst) Expert Testimony: Teva Travel, Accommodations, Expenses: Teva, Celgene, Novartis, Biogen Christian Hartmann Honoraria: AbbVie Consulting or Advisory Role: AbbVie Patents, Royalties, Other Intellectual Property: Patent fees for IDH1 R132H specific antibody via DKFZ Travel, Accommodations, Expenses: AbbVie Matthias Meinhardt Honoraria: Biogen Christine Haberler Consulting or Advisory Role: Bayer, Roche Martin Benesch Consulting or Advisory Role: Bayer, Pierre Fabre Paul Gerhardt Schlegel Consulting or Advisory Role: Bellicum Pharmaceuticals Bjorn-Ole Juhnke ¨ Employment: MVZ Hanse-Histologikum (I) Andreas Faldum Research Funding: Photonomic (Inst), NeraCare (Inst), Nexilis (Inst) Stefan Rutkowski Consulting or Advisory Role: Bristol-Myers Squibb, Celgene Research Funding: Riemser Pharma (Inst). + No other potential conflicts of interest were reported.",Journal of Clinical Oncology,1,1,1,0,1,1,1,1,1,8 +70,"Effect of Honey, Dextromethorphan, and + No Treatment on Nocturnal Cough and Sleep Quality + for Coughing Children and Their Parents",,"Trial Registration: clinicaltrials.gov Identifier: NCT00127686. + + the trial was registered at http://www.clinicaltrials.gov",JAMA,"Design: A survey was administered to parents on 2 consecutive days, first on the day of presentation when no medication had been given the prior evening and then the next day when honey, honey-flavored DM, or no treatment had been given prior to bedtime according to a partially double-blinded randomization scheme. + + Setting: A single, outpatient, general pediatric practice. + + After stratification for age (ages 2-5, 6-11, and 12-18 years), each child was randomly assigned in a partially double blinded fashion to receive artificially honey-flavored DM (17 mg/5 mL prepared using DM hydrobromide powder [100% pure United States Pharmacopeia grade], artificial honey flavoring, coloring, stevia liquid extract, methocel, and simple syrup [Professional Compounding Centers of America, Houston, Texas]), buckwheat honey, or nothing in a 10-mL syringe. A compounding pharmacy prepared the DM to approximate the consistency, texture, flavor, smell, and sweetness of honey.","Intervention: A single dose of buckwheat honey, honey-flavored DM, or no treatment administered 30 minutes prior to bedtime. + + Subjective parental assessments of their child’s cough and sleep difficulty on the previous night were assessed after informed consent was obtained through previously validated questions using a 7-point Likert scale (Figure 1).19 Trained study coordinators were responsible for survey administration, and survey responses ranged from extremely (6 points) to not at all (0 points). In an effort to study a population that was likely to receive a therapeutic intervention by parents, minimum symptom severity criteria for enrollment were established. + + Dosage for DM approximated typical OTC label recommendations, with children aged 2 to 5 years receiving 8.5 mg/dose (1/2 teaspoon), children aged 6 to 11 years receiving 17 mg/dose (1 teaspoon), and children aged 12 to 18 years receiving 34 mg/dose (2 teaspoons). Of note, these concentrations slightly exceed typical OTC products, which contain 15 mg/5 mL, and were the result of the compounding process but may be more likely to achieve a beneficial effect based on our previous analyses.20 For the honey group, the volume of honey dispensed was equivalent to the age-driven volume dispensed for DM. The bags and syringes were refrigerated prior to being dispensed. Parents were instructed that their child’s treatment could be given with a noncaffeinated beverage and should be administered within 30 minutes of the child going to sleep. A second survey asking the same questions as those answered at enrollment was then administered via telephone interview the following day to the same parent by trained study coordinators (J.B., A.M., Sarah Sturgis, CRNP, Jennifer Stokes, RN, Susan LaTournous, RN, and Diane Kitch, RN), who were blinded to the treatment group, to assess symptom severity for the night when DM, honey, or no treatment was given. No physician examination was performed on the second study day unless dictated by illness progression.","Participants: One hundred five children aged 2 to 18 years with upper respiratory tract infections, nocturnal symptoms, and illness duration of 7 days or less. + + From September 2005 through March 2006, patients were recruited from a single university-affiliated pediatric practice in Hershey, Pennsylvania, on presentation for an acute care visit. Eligible patients were aged 2 through 18 years with cough attributed to URIs. The URIs were characterized by the presence of rhinorrhea and cough for 7 or fewer days’ duration. Other symptoms may have included but were not limited to congestion, fever, sore throat, myalgias, and headache. Patients were excluded if they had signs or symptoms of a more treatable disease (eg, asthma, pneumonia, laryngotracheobronchitis, sinusitis, allergic rhinitis). They were also ineligible when they had a history of reactive airways disease, asthma, or chronic lung disease or were using a drug known to inhibit the metabolism of DM, such as selective serotonin reuptake inhibitors. Subjects were also excluded if on the prior evening they had taken a medication that included an antihistamine or DM hydrobromide within 6 hours of bedtime or DM polistirex within 12 hours of bedtime on the evening prior to or on the day of enrollment. Patients were not excluded when analgesic medications such as acetaminophen or ibuprofen were administered on either night of the study. While many more patients with URIs presented to the practice during the recruitment period, the exclusions, particularly the exclusion of taking medication on the previous evening, disqualified many subjects. + + Only parents who answered at least somewhat (3 points) for a mini mum of 2 of the 3 questions related to nocturnal cough frequency, effect on the child’s sleep, and effect on parental sleep based on the previous night’s symptoms were eligible.","The prospectively estimated sample size necessary to detect a 1-point difference between any 2 treatment groups with 80% power was 35 subjects per treatment group for a total sample size of 105 subjects with α=.05. This calculation was based on a 2-sided, 2-sample t test inflated to reflect the loss of efficiency that would result if it was necessary to use Wilcoxon-Mann-Whitney tests for pairwise comparisons of the treatments. The 1-point difference for the primary outcome has been used previously,6 and it resulted in a sample size that is greater than several other well-known and similar clinical trials.21,22 The principal outcome measure of interest was the change in the frequency of cough between the 2 nights, and secondary outcome measures of importance were changes in the cough severity, the bothersome nature of the cough, the effect of the cough on sleep for both the child and parents, and the combined score of these 5 measures. Baseline characteristics were compared between treatment groups using a x2 test for sex, a Kruskal-Wallis test for age, and 1-way analysis of variance for the remaining variables. The cough outcomes showed no significant departures from normality; therefore, treatment group comparisons were conducted using 1-way analysis of variance. The Tukey method was used to adjust P values for the pairwise treatment comparisons for each cough outcome. These analyses were extended to include age (in continuous form) and sex separately in analysis of covariance models. As adjustment for these covariates did not change the findings, the results of the unadjusted analyses are reported. Fisher exact tests were used to compare adverse event rates between treatments.","The randomization sequence was constructed by a statistician not affiliated with the study (Susan Boehmer, MS) and was then used by the study coordinators to assign treatment groups. The syringes used for all of the 3 treatment groups were opaque and were placed in brown paper bags to avoid investigator unblinding. Although the no-treatment group was not blinded to their treatment arm, the honey and DM groups remained blinded. + + Financial Disclosure: Dr Paul has been a consultant to the Consumer Healthcare Products Association and McNeil Consumer Healthcare. + + Funding/Support: This work was supported by an un restricted research grant from the National Honey Board, an industry-funded agency of the US Department of Agriculture.",JAMA,0,1,1,1,1,1,1,1,1,8 +71,Thought force moves human cells,,,,"In the following experiments some human cells in blood will be shown. Blood is significantly diluted with water. The liquid is put under the microscope and its image will be captured. My equipment is shown in FIG. 2 + + In the following study human cells in blood moved by though force will be presented.",,,,,,0,0,0,1,0,0,0,0,0,1 +72,"Unilateral transplantation of human primary fetal tissue in + four patients with Huntington’s disease: NEST-UK safety + report ISRCTN no 36485475",,ISRCTN no 36485475,BMJ,"Trial design The trial design has been influenced by a number of constraints. After extensive discussions with ethical advisors, both at the UK Medical Research Council, who are sponsoring the trial, and in the local research ethics committee at Addenbrooke’s Hospital, Cambridge, it was decided that small numbers of patients should be involved until it can be demonstrated that the procedure does not cause harm and there is preliminary, but convincing evidence of efficacy. In addition, the technical aspects of tissue collection and surgery need to be optimised before involvement of larger numbers of patients. Sham surgery (that is, a burr hole with or without stereotaxic placement of the needle and infusion of vehicle, under general anaesthetic, with blinding of the patients and clinicians as to the patient’s status), as advocated by some for clinical trials of transplantation in PD,31 remains controversial32 33 and has been considered to be inappropriate by the European groups at this early stage of development of transplantation for HD. Furthermore, from both experimental and clinical studies it is known to take at least a year for the donor tissue to develop and connect to the host before the first signs of functional engraftment can be expected, making a two year follow up the shortest period likely to yield any clear conclusions regarding efficacy. Based on these considerations, we have embarked on a two phase safety study. In phase 1, four HD patients have received unilateral intrastriatal grafts of human fetal striatal tissue with six months of postoperative assessment to record all surgically related complications. Following the absence of serious adverse effects in phase 1 of the trial, phase 2 will examine the safety of bilateral implants. This will involve the four patients in this study being considered for transplants in the contralateral striatum, and a further six patients will receive bilateral implants with a shorter interoperative interval of 2–14 days. Thereafter, all patients will progress to a longer term assessment of efficacy over a minimum of two years after the second transplant.","Stereotaxic placements of cell suspensions of human fetal ganglionic eminence were made unilaterally into the striatum of four patients with early to moderate HD. All patients received immunotherapy with cyclosporin A, azathioprine, and prednisolone for at least six months postoperatively. Patients were assessed for safety of the procedure using magnetic resonance imaging (MRI), regular recording of serum biochemistry and haematology to monitor immunotherapy, and clinical assessment according to the Core Assessment Protocol For Intrastriatal Transplantation in HD (CAPIT-HD). + + Details of the tissue transplanted in each case is shown in table 1. + + A high vaginal sample was cultured for pathogens and collection was performed in aseptic conditions during routine terminations of pregnancy that were per formed under general anaesthetic with ultrasound guidance. Tissue was collected in hibernation medium and heparin on ice for transportation to the laboratory where it was dissected in phosphate buffered saline supplemented with 0.9% glucose in a tissue culture hood with the aid of a microscope. Striatal tissue was identified and washed four times with phosphate buffered saline/glucose to minimise any contamination from vaginal secretions. Samples were taken at each stage of cell preparation for microbiological culture. Diced pieces of fetal striatum (about 1 mm3) were stored for up to five days in hibernation medium, a technique demonstrated not to have a significant adverse effect on tissue viability.40 41 Tissue from two whole ganglionic eminences derived from one fetus was taken for unilateral transplantation into the striatum of each patient. On the day of transplantation, tissue pieces were washed free of the hibernation medium with phosphate buffered saline/glucose and subjected to an enzymatic digestion using trypsin (Worthington, 240U) for 20 minutes. Following this, DNase and trypsin inhibitor were added in a ratio of 1:1:1 and the tissue was spun at 1000 rpm for three to five minutes. The supernatant was removed and the tissue washed in Dulbecco’s modifed Eagle’s medium before adding 0.2 ml of grafting medium and triturating 10–15 times with a 200 µl disposable plastic pipette tip. + + Neurosurgery and anaesthesia The neurosurgical and anaesthetic procedures are described in full in Watts et al. 42 All patients were subject to preoperative magnetic resonance imaging (MRI) for presurgical planning of stereotaxic tissue placement. Three of the patients required general anaesthesia for this, two because involuntary head movements interfered with image quality and one because of severe claustrophobia. Patients were allowed to breathe spontaneously using a propofol based technique. Patients were fully monitored with MR compatible monitors. Final planning took place under general anaesthesia on the day of surgery and included both 3T MRI and computed tomography (CT) for co-registration to ensure that there was no distortion of the coordinates on the MRI. For the transplantation surgery patients were ventilated and anaesthetised. Implantation took place through a burr hole using a specially manufactured needle of the minimum diameter compatible with accurate positioning (courtesy of the transplantation programme of the University of Lund, Sweden43). The aim was to deposit six tracts (two in the caudate, two in the anterior putamen, and two in the posterior putamen), and that each tract should comprise five deposits of 2.4 µl of the final tissue suspension deposited at 1 mm–2 mm intervals as the needle was withdrawn (12 µl per track, 60 µl total), although in some cases this had to be modified because of caudate atrophy in the host (see table 1). All injections were made into the non-dominant right hemisphere. Prophylactic antibiotics (1 g cefotaxime and 500 mg metronidazole) were administered intravenously with the premedication and continued thrice daily for 48 hours postoperatively. + + Immunosuppression Preoperatively 200 mg cyclosporin A and 60 mg of prednisolone EC was administered orally about six hours before beginning the procedure. At premedication 1 g methyl prednisolone was administered intravenously along with pro phylactic antibiotics, the latter being continued for 48 hours after the transplantation. “Triple” immunosuppression continued postoperatively and comprised oral cyclosporin A, with a trough therapeutic level of between 200 ng/ml and 300 ng/ml; prednisolone, starting at 40 mg and reducing to 5 mg daily by 12 weeks; and azathioprine at 1.5 mg/kg per day. Osteoporosis prophylactic treatment with Didronel PMO packs was instituted as soon as possible after transplantation. Gastric lining protection was instituted at premedication with ranitidine 150 mg twice daily or omeprazole 20 mg daily. Any longstanding treatments were continued, and septrin prophylaxis was given postoperatively. + + Postoperative care Patients were mobilised on the day after surgery. To enable detailed postoperative assessment, patients were kept in hospital for one week after surgery. Neurological status, general examination (including blood pressure), biochemistry (renal function, liver function, glucose, trough cyclosporin levels), inflammatory markers (erythrocyte sedimentation rate and C reactive protein), haematological (full blood count) assessment were monitored daily in the first postoperative week. After discharge on day 7, follow up was performed with each of the above assessments weekly for the first six weeks then monthly thereafter. Creatinine clearance assessments were undertaken monthly. This constituted the minimum period of follow up for the safety assessment to six months. We continue to see patients at a minimum of six monthly intervals postoperatively, and will do so for a minimum period of two years after last surgical intervention according to the CAPIT-HD protocol, but with the intention to maintain follow up for life. + + Clinical assessment All patients are assessed on a regular basis using the consensus CAPIT-HD core assessment battery, which comprises the Unified Huntington’s disease rating scale (UHDRS; see below) and additional neuropsychological and neuropsychiatric tests, along with MRI and positron emission tomography (PET) scans at regular defined intervals preoperatively and postoperatively.34 The UHDRS has been established as a valid assessment tool for relevant features of HD, and seems to be appropriate for repeated administration during clinical studies.44 The UHDRS comprises four domains of clinical performance; motor, functional capacity, cognitive functions, and psychiatric abnormalities, all of which are recorded according to specified scales of severity. In addition, patients received further assessments including timed hand tapping tests, similar to those used in PD,45 along with further computerised neuropsychiatric tests, and computerised neuropsychological tests (CANTAB46), not reported here. In this paper we present the preliminary UHDRS results and the hand tapping test (on the side contralateral to the graft) to evaluate the effect of the transplant in the immediate postoperative period. Further assessments relevant to efficacy (compared with safety) will be the subject of a future report. + + Imaging In addition to the regular general medical assessments and blood tests to monitor immunosuppressive therapy, the assessment protocol also included 3 Tesla MRI imaging for assessment of graft placement and tissue growth and PET scans with the dopamine D2 receptor ligand, (11C)raclopride. PET and MRI scans were performed 12 months before, and just before surgery, and will subsequently be performed at one and two years after transplantation to determine the presence of striatal-like tissue within the grafts. All patients were imaged in the three months before trans plantation using 3 Tesla MR imaging at the Wolfson Brain Imaging Centre (Bruker Medical, Etlingen, Germany). Imaging was repeated immediately befoe surgery with a Leksel stereotactic frame in place42 using the following sequences: T2/proton density (repetition time (TR) 6246 ms, echo time (TE) 120 ms/20 ms, slice thickness 4 mm, 1 mm gap, field of view (FOV) 35.8×16.8 cm, matrix size 512×240); FLAIR (TR 11500 ms, TE 135 ms, inversion time 2214 ms, FOV 35.8×16.8 cm, matrix size 512×240) and a 3D SPGR sequence (TR 20 ms, TE 5 ms, flip angle 20°, FOV 25.6×25.6×25.6 cm, matrix size 256×256×128) giving a spatial resolution of 1×1×2 mm. Imaging was repeated five to seven days postoperatively using the same T2/PD and FLAIR sequences as well as a haemosiderin sensitive gradient echo sequence (TR 1569 ms, TE 30 ms). These sequences were repeated at three and six months posttransplantation.","Patient selection Inclusion criteria required for the trial patients: • to be over 18, • to have genetically confirmed HD, • to be in the early to moderate stage of the disease, • to have demonstrable motor signs, • to have one close primary informant (typically close relative or caregiver) to assist with patient support and assessment of day to day function, • to have participated for a minimum of one year preoperatively in the NEST-UK programme to assess the longitudinal development of HD and for the validation of reliable neurological, psychological, psychiatric, and imaging instruments to be used in the core assessment of intracerebral transplantation (CAPIT-HD34). Exclusion criteria: • advanced disease, precluding the ability to give informed consent, • very early disease, such that patients are still employable in their usual occupation, • the presence of other concurrent major illness, • current serious psychiatric symptoms. Selection of patients was made by a committee comprising representatives from each of the participating patient assessment centres. The final inclusion of patients was by random selection from a larger reference group in the NEST-UK cohort considered to be suitable for transplantation meeting the inclusion and exclusion criteria, although the first four were chosen solely from the Cambridge cohort of patients to facilitate the process of establishing the trial protocols.",,Competing interests: none declared.,BMJ,0,1,1,1,1,1,0,1,1,7 +73,"DOSE–VOLUME CONSTRAINTS TO REDUCE RECTAL SIDE EFFECTS FROM + PROSTATE RADIOTHERAPY: EVIDENCE FROM MRC RT01 TRIAL ISRCTN 4777239",,ISRCTN 47772397,ISRCTN 47772397,"Data from a large multicenter randomized trial were used to investigate the correlation between seven clinically relevant rectal toxicity endpoints (including patient- and clinician-reported outcomes) and an absolute 5% increase in the volume of rectum receiving the specified doses. + + Treatment planning data were collected from participating RT01 centers and standardized using in-house software GUINESS (Graphical User Interface for the aNalysis and modElling of clinical StudieS). + + The present study used a subset of the main trial data set; frozen in November 2007 (median follow-up, 60 months).","The treatment planning data were imported, and the three-dimensional dose distribution was reconstructed and analyzed for each patient. + + Normal tissue contours were reviewed centrally by one of us (H.C.), and minor adjustments were undertaken as necessary to ensure consistency. The rectum was outlined from the anus taken at the level of the ischial tuberosities or 1 cm below the planning target volume, whichever was more inferior to the rectosigmoid junction. The conformal planning technique for the trial has been previously reported (11). In brief, the centers could use three or four fields in the treatment plan for the initial 64 Gy. The treatment plans of patients randomized to receive the additional 10 Gy to prostate only used four or six fields. The treatment plans of the patients who were prescribed 74 Gy with two separate phases were summed together to generate a combined dose–volume histogram. The only dose constraint placed on normal tissues in the trial protocol was that no area in the rectum or bladder outside the planning target volume could receive more than the randomized prescription dose. Detailed follow-up data were available for the late rectal toxicity endpoints assessed using physician-completed Royal Marsden Hospital scores (12), Radiation Therapy Oncology Group questionnaires (28), and Late Effects of Normal Tissues/Subjective, Objective, Management, Analytic (LENT/SOMA) grading (29). Also, the patient-completed University of California, Los Angeles, Prostate Cancer Index (UCLA-PCI) questionnaire (30) was used to assess patients’ quality of life. Seven late rectal toxicity endpoints were chosen to represent clinically relevant effects. These were (1) rectal bleeding (Royal Marsden Hospital scale), (2) proctitis (Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer), (3) subjective assessment of sphincter control (LENT/SOMA), (4) subjective assessment of stool frequency (LENT/SOMA), (5) management of sphincter control (LENT/SOMA), (6) frequency of loose stools (UCLA-PCI), and (7) urgency (UCLA-PCI). Late toxicities were deemed to be those reported at or after the 6-month assessment. The toxicity scales were harmonized by taking the definitions of each point on each scale and classifying them as none (Grade 0), mild (Grade 1), or moderate/severe (Grade 2), in terms of the affect on the patient. In this harmonization, the management of sphincter control classified using the LENT/SOMA system was dichotomized, because it was thought that the requirement of any management intervention should be classified as Grade 2 (moderate/severe). Table 1 lists how the different scoring schemes were translated into a common scoring system. The worst recorded symptom level during the follow-up period was analyzed for each outcome. + + To establish whether applying dose–volume constraints might reduce the incidence of late rectal toxicity, two sets of constraints were tested: those used in the current U.K. Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer (CHHiP ISRCTN97182923) trial (26) (derived from a published data review in 2000); and those recommended in the recent report by Fiorino et al. (21). We investigated the population effect on the incidence of the seven defined endpoints by comparing the incidence of complications for patients whose treatments plans failed each constraint compared with those whose treatment plan achieved the constraint.","Only patients with >2 years of follow-up and complete dosimetric data were included in the present study. For each patient, the maximal side effect recorded during follow-up for each toxicity was used. + + Because some of the mild symptoms considered in the present study were already prevalent in the trial population before treatment, the patients who reported symptoms before RT were excluded from the analysis of that endpoint only, according to the criteria listed in Table 1.","The results were quantified using odds ratios. Rectal dose–volume constraints were applied retrospectively to investigate the association of constraints with the incidence of late rectal toxicity. + + Statistical analysis Logistic regression analysis was used retrospectively to investigate how each of the defined endpoints was influenced by the dose distribution to the rectum (regarded as a solid rectum). The two toxicity grades were dichotomized to consider the odds ratios (ORs) for experiencing any toxicity or moderate/severe (Grade 2 or greater) toxicity. The volume of rectum receiving at least a defined dose level was the independent variable in each model and was treated as continuous. The resulting ORs were defined as the change in the odds of reporting a specified toxicity, given a 5% absolute increase in the rectal volume receiving at least the defined dose. An OR >1 indicates an increased risk of reporting the specified late rectal toxicity. The ORs were calculated using Stata, version 10 (College Station, TX) for the discrete dose levels. The uncertainty of the ORs was summarized using 95% confidence intervals; p < 0.05 was taken as suggesting evidence of effect. ORs for the constraint analysis were defined as the odds of reporting a specified late rectal toxicity as a result of the treatment plan failing to meet a suggested constraint relative to the odds if the constraint had been met. ORs were calculated using the Statistical Program for Social Sciences, version 15 (SPSS, Chicago, IL).",,Int. J. Radiation Oncology Biol. Phys.,0,1,1,1,1,1,1,0,1,7 +74,"Vitamin D supplementation to prevent + infections: a sub-study of a randomised + placebo-controlled trial in older people + (RECORD trial, ISRCTN 51647438)",,ISRCTN 51647438,ISRCTN 51647438,"a randomised placebo-controlled trial + + Five thousand two hundred and ninety-two participants were randomised within a factorial design to 800 IU (20 µg) daily vitamin D3, 1,000 mg calcium (calcium carbonate), both, or placebo, and followed up for 24–62 months. The trial was based in 21 centres in England and Scotland. Ethical approval was obtained from the Multicentre Research Ethics Committee for Scotland and each centre’s Local Research Ethics Committee. Participants gave written informed consent. Full details and main results of the trial are reported elsewhere [22]. + + Methods UMCG cohort After participation in the European Cooperative Acute Stroke Study (ECASS) II, our centre started with tPA treatment for eligible stroke patients and served as referral centre for regional community hospitals. An ongoing prospective registry of patients treated with t-PA was started in April 2002. This study analysed the period between April 2002 and January 2006.","In March 2002, when 25-hydroxyvitamin D3 levels are lowest in older people in the northern hemisphere [19], all trial participants who were alive, or had not withdrawn from filling in questionnaires were sent a reply-paid postal questionnaire. This asked if they had had an infection or received antibiotics in the previous week. + + Neurological deficit before start of t-PA treatment was recorded with the National Institute of Health Stroke Scale (NIHSS). All patients had a brain CT scan, blood investigation and electrocardiography. Baseline variables such as gender, age, vascular risk factors, serum glucose concentration and antiplatelet medication were recorded. Stroke-subtypes were defined into lacunar infarcts (LACI) and non-lacunar infarcts (total anterior circulation infarcts (TACI) and partial anterior circulation infarcts (PACI) and posterior circulation infarcts (POCI)) according to the Oxfordshire Community Stroke Project Classification [14]. Patients were treated with intravenous t-PA according to the NINDS protocol. After treatment, patients were monitored in a stroke unit, where early rehabilitation was started by a multidisciplinary team. We did not routinely perform a brain CT scan after each thrombolysis. For the safety analysis, we defined the following outcome measures: incidence of symptomatic intracerebral haemorrhage (SICH), early in-hospital mortality within 7 days and 3-month mortality. SICH was defined as a neurological deterioration within 48 h following thrombolysis, with an intraparenchymal haematoma demonstrated by CT scan, which could explain the deterioration. Functional outcome was assessed after 3 months using the modified Rankin Scale (mRS). The mRS was divided into favourable outcome (mRS 0–1) and unfavourable outcome (mRS 2–6). Data were analysed separately in the young and old age groups and compared between both groups.",Inclusion and exclusion criteria were based on those of the NINDS trial.,"We compared all participants who had been randomised to take vitamin D3 with all participants who had not been randomised to D3 (i.e. intention-to-treat analysis), using multiple logistic regression (adjusted for the trial minimisation factors of gender, age, type of enrolling fracture and time since fracture). + + Statistical analysis All statistical analyses were done using SPSS version 11.0. The Mann–Whitney U and the t-test were used for continuous and ordinal variables, and the χ2 test, or Fisher exact test, for dichotomous variables. Confidence intervals for proportions were calculated using Wilson’s method. For the functional outcome and 3-month mortality, a multivariate analysis was done to adjust for possible confounders: NIHSS score, time from onset until treatment, stroke subtype (lacunar versus non-lacunar) and blood glucose concentration.",Conflict of interest statement None declared for the authors. Conflict of interest statements for other members of the RECORD Trial Group are given in reference number 22.,Age and Ageing,0,1,1,1,1,1,1,1,1,8 +75,"Granulocyte-Colony–Stimulating Factor Mobilizes Bone + Marrow Stem Cells in Patients With Subacute + Ischemic Stroke",,"ISRCTN 16784092 + + The study [...] was registered for a trial number (ISRCTN 16784092)",ISRCTN 16784092,"Pilot Randomized, Controlled Trial + + We performed a 2-center, dose-escalation, double-blind, randomized, placebo-controlled pilot trial (ISRCTN 16784092) of G-CSF (6 blocks of 1 to 10 g/kg SC, 1 or 5 daily doses) in 36 patients with recent ischemic stroke. + + Design We performed a prospective, 2-center, double-blind, dose-escalation, randomized, placebo-controlled, Phase IIa trial of G-CSF in patients with subacute ischemic stroke. A dose-escalation design was used, because the effects of G-CSF on stem cell mobilization are poorly documented in elderly patients with significant comorbid disease, and it was conceivable that the marrow would be either under- or supersensitive to therapy. Such designs are frequent in stroke.19 The study was approved by the Nottingham Local Research Committee (June 5, 2003), had a Medicines and Healthcare Products Regulatory Agency Clinical Trial Authorization (March 10, 2003), was registered for a trial number (ISRCTN 16784092), and was performed according to the Declaration of Helsinki and the International Conference on Harmonization of Good Clinical Practice. + + Computerized randomization was performed with minimization on age, sex, baseline severity (Scandinavian Neurological Stroke Scale [SNSS]), and baseline CD34 and leukocyte counts.","Circulating CD34 stem cells were measured by flow cytometry; blood counts and measures of safety and functional outcome were also monitored. + + Intervention Patients were randomized to receive either subcutaneous human recombinant G-CSF (filgastrim, Amgen; purchased from the hospitals’ pharmacies) or placebo (saline) in a dose-escalation design. Dose blocks comprised 6 patients (4 active and 2 placebo in random order) and ranged from 1 dose of 1 g/kg (105 U/kg) to 5 daily doses of 10 g/kg (106 U/kg; Figure 1); the latter dose is standard after bone marrow transplantation. When designing the protocol, we had allowed higher doses (30 g/kg given either once or daily for 5 days) to be given, depending on the achieved CD34 count; review by the Data Monitoring Committee advised that testing of these doses would be unnecessary. + + Laboratory Measures CD34 count was performed by flow cytometry (FACScalibur, Becton Dickinson, Oxford, UK). Blood cells were labeled with fluorescein isothiocyanate- and phycoerythrin-tagged antibodies against CD34 and added to tubes containing latex beads (TruCount, Becton Dickinson).20 Full blood counts were analyzed by the NCH and QMC Hematology Department staff using standard hematology analysers. C-reactive protein (CRP) was measured with a commercial high-sensitivity, wide-range ELISA kit (Kalon Biological Ltd, Aldershot, UK).","Thirty-six patients, whose mean SD age was 76 8 years and of whom 50% were male, were recruited. + + Subjects Adult patients with recent (7 to 30 days postictus) ischemic stroke and motor weakness (arm and/or leg, MRC grade 5/5) were identified and enrolled from Nottingham City Hospital (NCH) and Queen’s Medical Centre (QMC) by M.R.W. and N.S. + + The principal exclusion criteria included premorbid dependency (modified Rankin scale [mRS] 3), primary intracerebral hemorrhage, dementia, coma, malignancy, sickle cell disease, and pregnancy. Full written, informed consent was obtained from patients before randomization, or assent was received from a relative/caregiver if the patient was incompetent owing to being obtunded, confused, or dysphasic. + + Subjects Thirty-six patients were enrolled between August 2003 and November 2005 (Figure 1). The baseline characteristics were matched for age, sex (Table 1), and baseline CD34 (Table 2). Patients randomized to G-CSF had a trend to milder stroke (SNSS) and were more likely to have a history of diabetes (P 0.07). Patients were enrolled between 7 and 28 days after stroke, G-CSF median of 14 days (IQR, 10 –18), and control median of 12 days (IQR, 10 to 17). No patients were lost to follow-up, and all patients received all prescribed G-CSF or placebo injections.","Statistical Methods Data on CD34, full blood count, and safety (serious adverse events, death, impairment) were assessed after each dosing block of 6 patients by the Data Monitoring Committee (comprising M.S.D., N.R., and P.M.B.). A decision was then made on whether to proceed to the next dosing block. Data on other measures were pooled by treatment group. The primary analysis was peak CD34; peak blood count parameters and comparison of areas under the curve (AUCs) across 10 days were also performed for CD34, blood counts, and temperature. Data are presented as mean (with SD), median (with interquartile range [IQR]), or number (and percentage) and were analyzed with Fisher’s exact test, Mann-Whitney U test, ANCOVA, Kruskal-Wallis test, or ordinal logistic regression, as appropriate. All analyses were performed with SPSS (Apple Mac, version 11; SPSS Inc). Analysis was by intention to treat, and significance was taken at P0.05.","All measures were made blinded to treatment. + + Sources of Funding The trial was supported by the Stroke Association (01/03). Support was also received from the BUPA Foundation (N.S., L.J.G.) and the Hypertension Trust (M.R.W.). P.M.B. is a Stroke Association Professor of Stroke Medicine. + + Disclosures None.",Stroke,0,1,1,1,1,1,1,1,1,8 +76,"Integrating physical and psychological approaches to treatment in low + back pain: the development and content of the STarT Back trial’s + ‘high-risk’ intervention (StarT Back; ISRCTN 37113406)",,,,"A new randomised controlled trial of intervention in low back pain has been described recently. In this trial, a screening and targeted approach was found to be more effective and cost-effective than current best practice. + + It offers a systematic approach, termed ‘psychologically informed practice’, to the integration of physical and psychological approaches to treatment for the management of people with low back pain by physiotherapists. + + The structure of the final high-risk training course com prises a 6-day programme, consisting of blocks of 2 days with time in between to put skills into practice, with additional mentoring sessions.","The methods of delivery include a mixture of didactic teaching, small group discussion, role play and elicitation of psychosocial risk factors with simulated patients, supplemented by comprehensive written material and handouts. Prior to attending the course, trainees are given key references designed to provide: a general orientation to the biopsychosocial framework; recent research knowledge about the nature of pain, central pain mechanisms and the development of disability; and an overview of psychological factors and their role in the transition between acute and chronic pain. This material is discussed and referred to during the training. The core topics covered during the training are shown in Box 4. The course is followed by 12 months of formal, monthly clinical mentoring in a group, in addition to direct access (by phone or e-mail) to the trainers to enable discussion of problematic cases. In keeping with modern educational theory, and its recommendation of triangulation, a range of teaching and learning methods were used and are described below. + + Formal trainer-led teaching Teaching on core topics is presented in interactive presentations of 30 to 45 minutes, with handouts, opportunity for discussion and clarification. Bullet-pointed text material is supplemented wherever possible with illustrative material and patient audio/video clips, and sessions are interspersed with more interactive and experiential training. + + Group discussions In these sessions, the trainees are invited to use ‘paper patients’ (with anonymised real patient biographies in addition to some constructed biographies) as a basis for developing their knowledge and practice in a range of skills using a systematic approach. Various ways of addressing specific issues are compared and contrasted. Key topics addressed in these discussion sessions include: identifying the nature and possible psychological factors contained within the patient histories; understanding the psychological influences on patient presentation; identifying potential targets for intervention; and identifying potential psychological obstacles to re-activation. Trainees are then encouraged through practice in pairs (role play) to develop tailored, patient-focused intervention strategies which are discussed amongst the trainees and with the trainers. The trainees then attempt to use these strategies with their patients in between the blocks of training, and their progress is reviewed at the subsequent training session. Back-up written and audio materials to use with patients in treatment sessions are also provided. + + Experiential learning Three types of experiential learning are invoked: (1) role play; (2) conducting an interview with a simulated patient; and (3) practice with patients in between training and mentoring sessions, and discussion of this in the next session. + + Role play Role plays are conducted in a variety of different formats ranging from role play in pairs and triads, to ‘stop/start’ role play techniques.Role play in triads involves the trainees being grouped into triads with each trainee being asked independently to identify the most awkward/difficult/uncomfortable question that they might be asked by patients or the most difficult situation. Trainee A’s questions are given to Trainee B who plays the part of a patient and asks the questions to Trainee C who responds to them as a treating physiotherapist. The procedure is repeated for each of the three sets of questions in turn so that each trainee has the opportunity to see how their colleagues deal with their questions or situations. The trainers also played the parts of both patient and therapist so that the trainees had an opportunity to observe and discuss different ways in which therapists might interact with patients. The ‘stop/start’ method involves a trainee playing the role of the clinician in front of the group with the discourse between them and the ‘patient’ being stopped by the trainers at key points. The group then discuss the different ways that the clinician could proceed, and the clinician then role plays one or more of these. Other volunteers may take over the role of the clinician. The sessions conclude by identifying the key lessons learned from the role plays in terms of managing difficult issues or situations. + + Conducting an interview with a simulated patient Case biographies are made available to professional actors who are accustomed to assisting medical training by playing the part of patients. The trainees are initially given no information about the ‘patients’ except that they have low back pain. They are asked individually, in the presence of both clinical trainers, to conduct a biopsychosocial assessment, paying particular attention to eliciting the psychosocial risk factors using good communication skills, with a view to development of a treatment plan. The interviews are video recorded and are evaluated in terms of the style and content of the interview. The trainees initially evaluate their own performance and are then offered feedback by the trainers and the simulated patient. + + Formal clinical mentoring and access to trainers Trainees are asked to keep a record of the patients they see and invited to discuss them during the clinical mentoring sessions(described below). They are encouraged specifically to attempt the identification and management of risk factors with their patients, and to discuss these within the group. The physiotherapists and the two trainers (CJM and GS) meet for a 2-hour session on a monthly basis. The meetings comprise reviews of clinical cases, presented in turn by each of the physiotherapists, and further clarification and expansion of course content, focusing on particular topics suggested by the physiotherapists. The mentoring has two main functions: (1) to use the clinical material to illustrate general principles and the application of specific knowledge and skills to the assessment or management of individual patients; and (2) to offer reassurance, support and encouragement to the physiotherapists to build their confidence in managing the high-risk group of patients. A ‘helpline’ is provided to facilitate direct access to the trainers in the event of significant or urgent clinical decisions which arise between mentoring sessions.","Nested within the intervention arm were three different interventions targeting patients identified as ‘low’, ‘medium’ or ‘high’ risk dependent on the presence of (mainly) psychosocial risk factors.",,"Funding: Arthritis Research Campaign (arc) Research. Project Grant #17741 + + Conflict of interest: None declared.",Physiotherapy,0,0,0,1,1,1,0,1,1,5 +77,"A Randomized Controlled Trial of the Effect + of Real-Time Telemedicine Support + on Glycemic Control in Young Adults With + Type 1 Diabetes (ISRCTN 46889446)",,ISRCTN 46889446,ISRCTN 46889446,"Randomized Controlled Trial + + RESEARCH DESIGN AND METHODS — A 9-month randomized trial compared glucose self-monitoring real-time result transmission and feedback of results for the previous 24 h in the control group with real-time graphical phone-based feedback for the previous 2 weeks together with nurse-initiated support using a web-based graphical analysis of glucose self-monitoring results in the intervention group. + + RESEARCH DESIGN AND METHODS — A randomized, controlled, parallel-group trial design was used + + Trial procedures Ethics and consent. The Oxford Research Ethics Committee approved the study. Patients were invited to participate in the trial on attendance at a routine clinic appointment or by a written invitation. They received an information leaflet explaining the trial, and at least 48 h elapsed before those agreeing to participate attended a research clinic appointment where the nature of the trial was further explained. They were given the opportunity to have any questions about the trial answered before being asked to provide written informed consent using a standard form. + + Randomization Randomization was carried out centrally by the trial administrator following the assessment visit. A computer program (MINIM; Evans, Day and Royston, University of London, London, U.K.) was used to perform a minimization procedure that adjusted the randomization probabilities to balance sex and psychiatric score between the intervention and control groups. Earlier work had indicated that significant psychological distress was common in young adults with diabetes (11). We therefore wanted to ensure that these individuals were evenly distributed between the two randomized groups. Randomization was conducted independently of the DSN.","In total, the intervention and control groups transmitted 29,765 and 21,400 results, respectively. + + Interventions Patients from both groups were given a blood glucose monitor (One Touch Ultra) and a general packet radio system mobile phone (Motorola T720i) that incorporated the option of recording their insulin dose, food intake, and activity levels in an electronic patient diary. The glucose self-monitoring results were automatically transmitted by the phone to a remote server with data processing facilities. + + Intervention group The experimental intervention consisted of clinical advice and structured counseling from a diabetes specialist nurse (DSN) in response to real-time blood glucose test results. Immediate graphical feedback of results was provided with blood glucose readings displayed as a time series for the previous 24 h and as a color-coded histogram to indicate proportion of values within target ranges during the previous 2 weeks (intensive feedback). The DSN checked the readings fortnightly or more often and had access to summaries and graphical displays of data via a secure webpage for each patient. Patients also had the option to access their own web page. The DSN telephoned the patients to identify concerns and problems, and possible solutions were discussed collaboratively. Realistic goals were agreed upon, and patients were encouraged to develop an action plan to address them. The treatment plan encouraged patients to adhere to a multiple insulin injection basal bolus regimen, unless it was contraindicated. + + Control group The results were transmitted to the server for data storage but were not available to the DSN. Feedback presented on the phone screen consisted of a graphical time series of blood glucose readings for the previous 24 h only (minimal feedback), and access to the data were available only in plain diary format on the patient’s personal webpages. + + Measures The primary outcome measure was A1C measured blind to group allocation by a high-performance liquid chromatography method using a Biorad Diamat automated glycosylated hemoglobin analyzer (Biorad Laboratories, Hemel Hempstead, Hertfordshire, U.K.). Baseline data on duration of diabetes, weight, BMI, and the Revised Clinical Interview Schedule (RCIS) were also collected. The RCIS is a standardized, semistructured interview to assess symptoms associated with anxiety and depression (10). It has been widely used and applied to the assessment of young adults with diabetes (11) and has a case threshold of 12 (12). We also recorded the frequency and results of blood glucose readings taken by each participant, time spent in telephone contact with the nurse, and any technical problems. + + Assessment After giving their consent, participants completed study questionnaires and were assessed for psychiatric morbidity using the RCIS. A venous blood sample was taken for measurement of A1C, creatinine, total cholesterol, and nonfasting triglycerides. Patients were instructed in the use of the blood glucose monitor and the mobile phone. The DSN negotiated appropriate times of the day to contact by telephone patients in the intervention group. + + Follow-up for the intervention group Participants assigned to the intervention group were contacted by the DSN within a week of their assessment visit. They were told that they would be contacted fortnightly and that they would be able to receive feedback via the mobile phone and, if they had access, via the internet. Personalized objectives were set by patients following discussion with the DSN with the aim of establishing 1) regular blood glucose monitoring at appropriate times, 2) optimization of the basal insulin dose, 3) optimization of short-acting insulin dose, and 4) appropriate adjustment of short-acting insulin dose with food and physical activity. The DSNs supported behavior change by encouraging participants to identify their own objectives and goals based on a patient-centered model of care (13). A follow-up visit was made to the regular clinic 4 months after assessment. Information on diabetes management was recorded together with a record of the frequency of hypoglycemia and hospitalization for any causes. + + Follow-up for the control group Participants assigned to the control group were contacted by the DSN within a week of their assessment visit and told that they would be able to contact a DSN by tele phone as required for the duration of the study. A follow-up visit was made to the regular clinic 4 months after assessment, and the same information was recorded as for the intervention group. + + Final study visit At the final 9-month clinic visit (1 month) a further blood sample was taken for measurement of A1C. Questionnaires were again administered. If participants were not seen within the specified time interval, any subsequent A1C results were also recorded. + + Standardization of the intervention The trial used intervention protocols to support the DSNs in adopting a consistent approach to telephone contacts with patients. A sample of contacts with participants was tape recorded and reviewed by the investigators to confirm use of patient-centered techniques.","Young Adults With Type 1 Diabetes + + All patients aged 18–30 years with HbA1c (A1C) levels of 8–11% were eligible for inclusion. + + A total of 93 patients (55 men) with mean diabetes duration (means + SD) 12.1 + 6.7 years were recruited from a young adult clinic. + + We invited patients who were registered either with the Pediatric Transition Clinic or the Young Adult Diabetes Clinic in Oxford, U.K., to participate. Inclusion criteria were a diagnosis of type 1 diabetes; age 18–30 years inclusive; twice daily, three times daily, or basal bolus insulin therapy; and suboptimal or poor glycemic control with a lower A1C limit of 8.0% and an upper limit A1C limit of 11.0% for the last two results. We excluded patients with any contraindication to tight glycemic control, who were unable to give consent, who had other concurrent severe diseases, who were not prepared to undertake blood glucose testing during the study period, or who were with another member of the family participating in the trial.","Power calculations Using a two-sided test at a 5% level of statistical significance, the trial was designed to have a 80% statistical power to detect a difference in the mean change in A1C from baseline to end of trial between the intervention and control groups of 0.7% based on baseline mean A1C of 9.0 1.2%. We aimed to recruit 100 patients, allowing for 6% drop-out. + + Analysis Case report forms were entered onto computer and checked for range and consistency. The primary analysis was planned as intention to treat. For any patients randomized but lost to follow-up, the results were imputed from the last appointment. Results are presented as means SD. Changes in A1C from baseline are presented as the mean change of the individual values with 95% CIs. An exploratory analysis was conducted to investigate the difference between the two groups in change of proportion of participants achieving a reduction in A1C 0.7% and value of 8.0% by the end of the trial. The level of 8.0% was chosen as one of the entry criteria for the trial representing the difference between good and moderate-to-poor control, and a reduction in A1C of 0.7% was the protocol-specified difference that the trial was designed to detect. Statistical analyses were carried out using the Statistical Package for the Social Sciences Version 11.0 (SPSS, Chicago, IL). We examined the difference between groups in the mean individual changes in A1C from randomization to the end of the trial using an unpaired t test. We also con ducted an analysis of the within-group mean change from baseline to the 4-month visit and from baseline to the end of the trial, using paired t tests. T tests were also used to examine differences in the mean numbers of blood glucose results transmitted. The Mann-Whitney test was used to compare mean blood glucose results recorded between allocated groups. A 2 test was used to examine the proportion of participants with both a fall of A1C of 0.7% and a final A1C of 8%. Associations between number of weeks of monitoring and the telephone contact time spent by the study nurse were analyzed with a Pearson correlation coefficient. We set the level of statistical significance at P 0.05 for the main prespecified study outcome analysis and P 0.01 for other analyses.","The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. + + Acknowledgments— A.J.F. is funded by a National Health Service Research and Development Career Development Award. O.J.G. is funded by an Engineering and Physical Sciences Research Council Research Grant. The study was funded by an unrestricted grant from the Vodafone Group Foundation. Life-scan supplied the blood glucose meters.",Diabetes Care,0,1,1,1,1,1,1,1,1,8 +78,"A double-blind, placebo-controlled, randomiseddesigned GABA tea study in children diagnosed + with autism spectrum conditions: a feasibility + study clinical trial registration: ISRCTN 72571312","Data availability statement The data that support the findings of this study are available on request from the corresponding author, PH. The data are not publicly available due to restrictions as their containing information could compromise the privacy of research participants.",clinical trial registration: ISRCTN 72571312,clinical trial registration: ISRCTN 72571312,"A randomised-designed GABA tea study + + A double-blind, repeated measures design was employed. + + Sample size was determined based on a feasibility study with strict inclusion criteria and sufficient power in case of statistical analyses. Recruitment occurred from September 2016 to April 2017: study duration from September 2015 to September 2017. + + Order of tea was assigned to next participant thus ensuring a random allocation. + + Ethical approval for the study was obtained from the Research Ethics Committee. Clinical Trial Registration occurred post-study following study publication guidelines. The authors confirm that all ongoing and related trials for this intervention will be registered. After parental consent to take part in the study was obtained, the parent and child were invited to an assessment session at the University.","Measures were taken after each tea condition. Sensory and ASC profiles were scored using parental questionnaires. Motor skills were assessed using a gold standard coordination assessment. Sleep was monitored using an actiwatch and anxiety measured through cortisol assays. Subjective views were sought from parents on ‘best’ tea. + + Participants completed a battery of performance measures and caregivers completed a set of questionnaires about their child’s behaviour. Children’s sleep quality and duration were monitored using actigraphy, and saliva samples were collected for analysis of cortisol. Due to the small number of participants being involved in a repeated measures study, the authors chose to test a number of variables (subjective, objective and hormonal) in order to ensure that any findings were further substantiated at various levels of observation. Standard measures of intelligence such as the full scale WASI-II [131], which require a spoken response, appear to underestimate the abilities of children with autism [132]. Therefore, in the current study, performance was ascertained using only the non-verbal IQ matrices subset of the WASI-II [130] and receptive language measure (BPVS-III; [133]). + + Performance measures Autism Diagnostic Observation Schedule – 2nd Edition (ADOS-II; [129]). The ADOS-II is a standardised diagnostic instrument for diagnosis of ASC. It was utilised in the present study to independently confirm participants ASC diagnosis and indicate severity of ASC symptoms in order to ensure full and robust measurement of ASC symptomology. It consists of a semi-structured interview that provides a number of social prompts and opportunities to code quality of social and communicative behaviours. It also includes a rating indicating the severity of ASC symptoms, whilst accounting for the person’s age and expressive language level. The ADOS-II was validated on 381 individuals aged between 15 months to 40 years with and without disabilities, with a further 1139 children aged between 14 months to 16 years recruited to revise the algorithms. Inter-rater reliability showed over 80% agreement on all modules with a high level of discriminative validity between aut ism and TD resulting in specificities of 50–84 and sensitivities of 91–98 [130]. An age dependent criterion score is used to diagnose ASC, where a higher score indicates more severe autism characteristics. The British Picture Vocabulary Scale III (BPVS-III; [133]). The BPVS-III is a standardised non-reading assessment of receptive language. Each item within the assessment requires the child to identify the correct image out of four pictures provided, which matches a word provided by the researcher. The test covers a range of subjects, including verbs, animals, emotions, toys and attributes. The BPVS-III was normed on 1480 children aged 3–16 years with and without disabilities. Internal reliability is .91 and validity with the Wechsler Intelligence Scale for Children (2005) = .76 [133]. The BPVS-III has a standardised mean score of 100, where 115 is above average. Wechsler Abbreviated Scale of Intelligence – 2nd Edition (WASI-II; [131]). The WASI-II is a brief standardised measure of verbal and non-verbal intelligence. The matrices subset was used in the current study to measure non-verbal reasoning. The WASI was normed on approximately 2900 individuals aged 6–90 years with and without disabilities. Matrix Internal Reliability is .87–.94 and validity with the Wide Range Intelligence Test (WRIT) is .71 [131]. The WASI-II provides a stan dard mean score of 100 for TD children, and where a <84 is considered below average and >115 is considered above average. + + Parent-report questionnaires Primary Outcome Measure – The Autism Spectrum Ratings Scale (ASRS; [134]). The ASRS (6–18 Years, Parent form) is used to quantify observations of a child that are associated with ASC. The form is composed of 71 questions based on a Likert scale of Never, Rarely, Occasionally, Frequently and Very Frequently, scoring 0–4. Raw scores are converted into T scores, where T scores above 60 are considered to show increased concern, and are classified as low, average, slightly elevated, elevated and very elevated. Scores can be apportioned into social communication, unusual behaviours and self-regulation, each of which can be further divided into treatment scales for peer socialisation, adult socialisation, social and emotional reciprocity, atypical language, stereotypy, behavioural rigidity, sensory sensitivity and attention. An overall score for ASC based on DSM-5 criteria for an ASC can also be attained and raw scores for the DSM-5 criteria were utilised within this study. Such criteria include difficulties with social communication, unusual behaviours and self-regulation. The ASRS was normed on over 7000 children aged 6–18 years with and without disabilities. Internal reliability was .95–.96 based on the DSM-IV, and the test shows good validity, with 90.3% sensitivity and 92.2% specificity on accurately predicting group membership [134]. Secondary Outcome Measure – Sensory Profile (SP; [135]). The SP is a standardised, 125-item, parent report questionnaire for children aged 3–10 years that assesses the frequency of a child’s responses to differing sensory modulation, processing and emotional events. The SP consists of three domains: sensory responsivity, which includes auditory, visual, vestibular, tactile, oral and multi-sensory processing; modulation, which includes modulating sensory responsivity with relation to endurance and tone, proprioception, movement affecting activity, emotional responses and visual filtering; behavioural emotional response, which considers the behavioural outcomes of sensory responsivity. Lower scores on the SP indicate greater difficulties in a particular area of sensory responsivity. The SP was normed on 1187 children aged 3–14 years with and without disabilities. Internal reliability includes internal consistency estimates (range = .47–.91) and convergent and discriminant validity was determined by demonstrating high correlations with scores on the school function assessment [135]. + + Objective measures Secondary Outcome Measure – The Movement Assessment Battery for Children – 2 (MABC2. [136]): This is a standardised assessment of motor coordination for children aged 3–16 years and is a revision of the Test of Motor Impairment (TOMI; [137]). It is comprised of three components: manual dexterity, ball skill and balance. Examples of test content include placing pegs onto a board, throwing a beanbag onto a target and walking heel to toe along a line. The Movement-ABC 2 was normed on 1172 children aged 3–16 years with and without disabilities. Normed scores for TD children yield a mean score of 100, and where a standardised score of 115 is considered above average; however, in the present study raw scores were used in order to analyse findings from each com ponent in greater detail. Internal reliability includes internal consistency estimates (range = .92–1.00) and validity with the ‘Draw-a-Man’ test = .66 [138]. Secondary Outcome Measure – Actigraphy sleep monitoring. Participants were asked to wear an actiwatch (Actiwatch 2, Philips Respironics) on their non dominant wrist to measure sleep quality, duration and timing. Actigraphy provides a reliable and valid method for measuring sleep patterns in a natural setting over a prolonged period and is 80% concordant with laboratory-based sleep studies for determining sleep and wake but benefits from minimal disruption to sleep and routine [139]. Due to individual variability across nights, it is recommended that actigraphy be used for at least five and preferably seven nights to reliably score a person’s normal sleep patterns; thus children were requested to wear the actiwatch continuously for one week [140]. Parents were requested to keep a sleep diary of their child’s bedtime and wake times, which was used to support analysis of actigraphy data. Actigraphy data were analysed in one-minute epochs using Philips Actiware (Philips Respironics). Secondary Outcome Measure – Hormonal sampling. Participants were requested to collect saliva samples via passive drool in the afternoon, the evening before bed, and immediately upon waking. Parents were trained in the use of saliva collection devices and were provided with written instructions. It was requested that children avoid ingesting substances that may interfere with analysis (e.g. chocolate, aspirin) on the day; and avoid eating for at least 30 min before the saliva collection. They were requested to rinse their mouth ten minutes before the saliva collection, and then to remain seated and avoid moving around too much. Parents froze the samples immediately and returned them at their appointment in a cool bag with two frozen ice packs. Samples were then frozen at −80°C until the day of analysis. Prior to assaying, all samples were defrosted and centrifuged for 15 min @ 1500 g. Cortisol (Cat no. 1-3002) levels were measured using expanded range high sensitivity enzyme immunoassay kits (Salimetrics LLC, State College, PA, USA). Melatonin (Cat no. 1-3402) levels were measured using enzyme immunoassay kits. All saliva specimens were assayed in duplicate and absorbance values determined using a UV-Vis spectrophotometer (Epoch 2, Bio Tek Ltd, Winooski, VT, USA). Unknown values were determined by non-linear regression curve fit software (Prism version 4.0, La Jolla, USA). Tea intervention. Participants were required to drink three different teas. Each was made using the following method: one tea-loaded 47 mm tea infuser, 300 ml freshly boiled water, 120 s of infusion. Participants were advised that they could drink the tea hot or cold, perhaps adding fruit squash or other flavourings if they preferred, keeping this variable the same for each tea throughout the study. Teas were analysed for exact com ponents by Hungkuang University Functional Food Research Laboratory. The three teas were: GABA Oolong (GABA 279 mg/100 g, L-Theanine 104.48 mg/100 g); Placebo Jiao Gu Lan (GABA 157 mg/100 g, L-Theanine 0 mg/100 g); L-Theanine Gyokuro Green (GABA 156 mg/100 g, L-Theanine 1340 mg/100 g). The placebo needed to be a fluid as it was necessary to ensure that cognition was not influenced by differing daily fluid intake [141–142]. It was also felt that a sweet and visibly similar fluid that was not tea would be ideal. Jiao Gu Lan is not a tea, but a tisane (a herbal tea). An active placebo was chosen as GABA is found in all teas and tisanes due to the picking process and stress on the plant, however in highly concentrated GABA tea, the leaves are left in low or deficient oxygen environments, further increasing the stress and consequently GABA [143]. Thereby the magnitude of difference in the level of GABA between the GABA tea and placebo was deemed acceptable. The teas were respectively labelled A, B and C and the study was double-blinded to eliminate examiner bias and participation expectancy effects. Teas were given in three orders to counterbalance and combat order affects and ensure an allocation ratio of 1:1. (Participants 1, 2 & 3 received Tea A, B then C; Participants 4, 5 & 6 received Tea B, C then A; Participants 7, 8 and 9 received Tea C, A then B). + + The child was requested to drink four 300 ml cups of the given tea each day for two weeks. This dosage was calculated based on the necessity to achieve a ‘natural’, non-invasive and safe dose. Readily available GABA supplements varied between doses of 200–750 mg. With the GABA Oolong tea the dose would be approximately 280 mg per 100 g tea. Based on using 3.5 g per tea portion this equates to 9.8 mg of GABA; multiplied by 4 throughout the day being 39.2 mg of GABA. This dose is calculated as almost double the placebo (22.2 mg per day of GABA). + + During this session trained researchers carried out the following assessments: ADOS-II, BPVS III and WASI-II non-verbal subsets. Following this the parent was given the first tea, saliva collection devices and tubes, an actiwatch, sleep diary, and full written instructions. Following seven days of tea, the child wore an actiwatch for seven days. At the end of the second week of drinking the given tea, the parent collected and froze the saliva samples from their child. Parents and children then returned to the University with their saliva samples, actiwatch and sleep diary. The participant’s parent completed the SP and ASRS based on their child’s behaviour during the previous 2 weeks alone, whilst the child completed the MABC2 with the examiner. They were then provided with the next tea, saliva collection devices and tubes, another actiwatch, sleep diary, and written instructions. This process was followed by a washout week before starting again with the second and third teas. Thus, the process lasted eight weeks. At the end of the eighth week the parent was also asked to write down which tea they felt was most beneficial and which tea was not. This was not shown to the examiner and was sealed in a folder until the end of the study. Table 1 shows the study timetable.","children diagnosed with autism spectrum conditions + + Methods: Nine children took part: (5 male, 4 female). Each child participated in three tea conditions: high GABA, high L-Theanine (a compound that increases GABA), placebo with low GABA. + + Participants Nine children (5 male, 4 female) aged 9y 5 m to 13y 9 m (mean age 11y 7 m) with confirmed ASC took part in the study. They were recruited from local ASC support groups in Warwickshire and Leicestershire, UK. All nine children had a pre-existing diagnosis of ASC from a trained clinician according to DSM-5 criteria. ASC diagnosis was also confirmed by the research team using the Autism Diagnostic Observation Schedule General – 2nd Edition (ADOS-2) [130], administered by a research reliable rater. Participants were recruited based on APA DSM-5 ASC criteria [1] and various levels of cognitive functioning were apparent, representing the variability and diversity of their individual differences. However, strict inclusion criteria were adhered to: diagnosis of ASC, no known co-occurring ADHD, genetic or medical conditions, no current medication, a willingness to drink tea, the ability to wear a watch without tactile sensitivity, younger than 14 (due to a large increase in testosterone levels after this point (Mayo Foundation for Medical Education and Research website, 1995– 2017)), and both parent and child commitment to four university visits and precise tea making and drinking requirements.","Analysis Data were analysed both qualitatively and quantitatively. Qualitatively parental report of the best and worst tea was utilised. Quantitatively each child’s manual dexterity (MABC2), gross motor skills (MABC2), SP, DSM-5 scale, sleep quality and duration, and cortisol levels were analysed separately for differences between the placebo and both GABA tea and L-Theanine Tea, using % difference in proportion to placebo. This analysis was chosen in order to explore the impact of the three tea conditions on a case by case basis, due to the individual ism of each participant in addition to the fully holistic approach. Following this, group data were analysed using SPSS (version 24) using a repeated measures ANOVA with a simple contrast to compare scores on each of the above variables for the GABA and L-theanine teas to scores for the placebo tea. The Bonferroni correction was used to correct for multiple comparisons. + Cook’s distance was used to identify outliers and partial eta squared (ηp2) noted for Power analysis, where an effect size of above 0.14 was considered large [141]. Where sphericity was violated, the Greenhouse-Geisser estimate was used to adjust degrees of freedom and the F statistic, and multivariate statistics with Wilks’ Lambda are reported. A nonparametric one sample test was then utilised to query the significance of the parental perceived benefits of the best tea. It is important to note here that participant 9 experienced a period of increased stress during the GABA tea trial.","A double-blind study + + Funding This work was funded by Coventry University, UK. + + Acknowledgements This work was funded by Coventry University, UK. Local Support groups and Parents Mie Leaf Tea, 99-105 Camden High Street, London, NW1 7JN, UK. + + Disclosure statement No potential conflict of interest was reported by the authors.",Nutritional Neuroscience,1,1,1,1,1,1,1,1,1,9 +79,"Predicting pain and function outcomes + in people consulting with shoulder + pain: the PANDA-S clinical cohort and + qualitative study protocol","Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (http://dx.doi.org/10.1136/ bmjopen-2021-052758). + + Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.",Trial registration number ISRCTN46948079.,BMJ,"Methods and analysis The Prognostic And Diagnostic Assessment of the Shoulder (PANDA-S) study is a longitudinal clinical cohort with linked qualitative study. + + Study design Multicentre observational cohort study, including patients presenting with shoulder pain in general practices, and National Health Service (NHS) physiotherapy services (including self-referrers to physiotherapy), with a linked qualitative study. Figure 1 details the recruitment methods and participant flow through the study. + + Recruitment Potential participants consulting with shoulder pain will be identified through one of three methods: i. Identification using an automated medical record template (pop-up) in GP sites, activated when a Read/ Systematised Nomenclature of Medicine (SNOMED) code for shoulder pain is entered into the medical record because of a patient consultation. ii. Identification using an Egton Medical Information Systemts (EMIS) embedded ‘referral’ form which will autopopulate for eligible patients when triggered by the clinician in physiotherapy sites. iii. Identification of patients from waiting lists for physiotherapy. Referrals received from GPs, other health care professionals or self-referrals will be centrally triaged by senior physiotherapists using the PANDA-S eligibility checklist. Potential participants will be asked for consent to share their contact details with the Keele Clinical Trials Unit who will send them a study pack, or a study pack will be sent directly from the GP or physiotherapy practices, depending on site preference. The study pack will contain: an invitation letter; a participant information leaflet; baseline questionnaire with consent form and eligibility screening questions; prepaid reply envelope. Patients interested to take part in the study will be asked to complete the consent form and answer eligibility questions relating to whether they have received treatment (eg, supervised exercise, injection, surgery) for their shoulder pain in the 6 months prior to consultation. Those who have not yet received treatment are eligible and invited to complete and return the baseline questionnaire. As this is an observational study, all participants will continue to receive care as usual for their shoulder pain.","Participants will complete questionnaires at baseline, 3, 6, 12, 24 and 36 months. Short-term data will be collected weekly between baseline and 12 weeks via Short Message Serevice (SMS) text or software application. Participants will be offered clinical (physiotherapist) and ultrasound (sonographer) assessments at baseline. Qualitative interviews with ≈15 dyads of patients and their healthcare professional (general practitioner or physiotherapist). + + Data collection Data collection will be carried out by postal questionnaire at baseline, 3, 6, 12, 24 and 36 months. Since June 2020, in response to the COVID-19 pandemic, follow-up questionnaires have also been made available as online surveys. Short-term data will be collected weekly through a specifically designed smartphone/tablet Shoulder Pain application (App) or text messages over 12 weeks. Clinical data will be collected during a clinical assessment comprising a shoulder examination by a physiotherapist and an US. In response to the pandemic, face-to-face clinical assessments will be carried out (or paused) in accordance with national and local restrictions. Table 1 provides an overview of the content and timing of data collection for this study. + + Follow-up data collection Participants will be sent follow-up questionnaires at 3, 6, 12, 24 and 36 months after the return of their baseline questionnaire; these follow-up questionnaires will be sent by post or a link to an online questionnaire will be sent by email. Non-responders to follow-up questionnaires will receive a reminder questionnaire after 2 weeks, 4 weeks and a telephone call a further 2 weeks later if no response has been received, with the option of completing a short (Minimum Data Collection) questionnaire by telephone, and if no telephone contact can be made, by post. Short-term data collection On return of the baseline questionnaire participants will be offered the option of completing the shoulder pain App or text messages reporting their pain and function (0–10 NRS) weekly for 12 weeks. The App also collects weekly data across eight further domains using single item questions: self-efficacy, work absence, mood, sleep, medication use, fear of movement, worry, treatment and recovery expectations. + + Physical examination The assessment will include a standardised history based on questions regarding duration, severity, impact and (self) management of shoulder pain. The physical examination will include an examination of the neck using repeated movements through flexion, extension and side flexion to assess whether the patient’s shoulder pain is related to a neck problem. Shoulder range of movement will be visually assessed (in degrees) during active abduction (in degrees) and external rotation, compared with the contralateral side. Additional tests designed to distinguish between different shoulder conditions have variable reliability and diagnostic test accuracy, but their selection was informed by systematic reviews:14 16 17 ► Painful arc, Neer sign and Hawkins-Kennedy tests. ► External rotation lag sign. ► Glenohumeral external rotation (50% reduction compared with the less/non-painful side). ► Scapular assistance test. ► Empty Can and Full Can test. ► Scarf test and Bear Hug test ► Step-standing elevation. ► Muscle performance tests aiming to identify weakness and pain. Anthropometric measurements will include height (in centimetres) and weight (in kilograms) and waist-hip circumference (in cm). To assess balance, strength, and mobility, we will include a brief standardised protocol, consisting of grip strength, lower limb strength (sit-to stand) and a balance test. Following the assessment, the research physiotherapist will record their opinion regarding the pathoanatomical classification of the shoulder problem (rotator cuff disorder, frozen shoulder, glenohumeral osteoarthritis, acromioclavicular joint pain, instability, neck-related dysfunction), and rate their confidence in this classification using a 0–10 NRS. The physiotherapist will also estimate the participant’s prognosis, through answering the question ‘Do you think this participant will have interfering shoulder pain in 6 months’ time? Yes/No/Don’t know’. + + Ultrasound assessment The US will be performed by experienced ultrasonographers/radiologists using high-resolution ultrasound systems and transducers40 according to a standardised scanning protocol.41 The structures scanned will include long head of biceps tendon, rotator cuff (subscapularis, supraspinatus, infraspinatus and teres minor tendons and muscles), posterior glenohumeral joint, subacromial/deltoid bursa and acromioclavicular joint. A standardised structured report based on42 will include information regarding tendon and bursal pathology including structural appearances, site and size of tendon tears, observed glenohumeral or acromioclavicular fluid, synovitis or cortical bone changes and muscle atrophy. Dynamic scanning of some shoulder movements will be performed to assess for restriction or instability. Colour Doppler will be used to assess the presence of neovascularisation in any areas of tendon, sheath or bursal abnormality. Both shoulders will be scanned to enable later analysis of abnormalities in affected versus pain-free shoulders. + + Qualitative interview study Recruitment of patient-clinician dyads Patient-participants: Questionnaires will be screened to enable a purposive sampling frame to be applied. A range of participant characteristics will be sampled for, including age, sex, reported pain intensity, pain duration, shoulder diagnoses, socioeconomic status, health literacy and Fit Note status (ie, absent from work or not). Participants who are selected for interview will be sent an invitation letter, reply slip and participant information leaflet about the interview. Those who return a reply slip indicating a willingness to be interviewed will be telephoned to arrange the interview. + + Semistructured interviews will be carried out with approximately 15 participant–clinician dyads (ie, approximately 30 interviews in total). The final number of interviews will be guided by data saturation, defined in terms of ‘informational redundancy’45—the point at which additional data no longer offers new insights.","At least 400 people presenting to general practice and physiotherapy services in the UK will be recruited. + + Study population Potential participants will be identified when they consult with an episode of shoulder pain at general practices, or NHS physiotherapy service (including self-referrers to physiotherapy) in five regions in the UK: Staffordshire, Cheshire, Oxfordshire, Birmingham and Gloucestershire. Recruitment of participants started in February 2019, with baseline data collection planned to be completed in September in 2021. Follow-up data collection is planned to be completed in September 2024. + + Eligibility criteria Potential participants must be registered at participating general practices or referred to NHS physiotherapy (including self-referrers), aged 18 years or over and presenting with a new episode of shoulder pain. Previous studies of shoulder pain in primary care indicate that many people consult quite late in the trajectory of their shoulder pain episode, with the median/mean duration of symptoms at presentation varying between 12 weeks and 1year.4 5 21 22 Based on discussion with our clinical advisory group, a new care episode will be defined as no shoulder pain related consultation, no injection, surgery or physiotherapy-led exercise for shoulder pain, in the last 6 months, reflecting a point in time when primary care clinicians make (new) decisions regarding advice, treatment or referral. Potential participants will be excluded on the basis of the following criteria: + ► Present to their GP or physiotherapist with symptoms or signs indicative of serious pathology (eg, fractures, infection). ► Have shoulder pain caused by stroke-related subluxation. ► Have a diagnosis of inflammatory arthritis (eg, rheumatoid arthritis or polymyalgia rheumatic). ► Have shoulder pain caused by cervical pathology. ► Are considered by the GP or physiotherapist to be vulnerable (eg, severe physical and/or mental health problems, dementia).","Short-term and long-term trajectories of Shoulder Pain and Disability Index (using SPADI) will be described, using latent class growth analysis. Health economic analysis will estimate direct costs of care and indirect costs related to work absence and productivity losses. Multivariable regression analysis will be used to develop a prognostic model predicting future levels of pain and disability at 6months using penalisation methods to adjust for overfitting. The added predictive value of prespecified physical examination tests and ultrasound findings will be examined. For the qualitative interviews an inductive, exploratory framework will be adopted using thematic analysis to investigate decision making, perspectives of patients and clinicians on the importance of diagnostic and prognostic information when negotiating treatment and referral options. + + Analysis cohort study (objectives 1–5) A detailed analysis plan will be written for each of the study objectives; a summary is given here. Most analyses will be conducted using Stata software v16. + + Objective 1 Investigate pain and function trajectories (overall prognosis): Descriptive statistics (estimates and measures of dispersion) will be used to report baseline characteristics of the study population, and the course of symptoms over time, for the primary outcome (SPADI) and secondary outcome measures. For each follow-up time point (0, 3, 6, 12, 24, 36 months), we will report means (SD) for continuous outcomes, and proportions (n, %) for binary outcomes, based on longitudinal models that account for correlated responses over time. Attrition (n,%) will be described for each follow-up time point. Baseline characteristics among those lost during follow-up (whose outcomes are hence not fully observed) will be summarised and compared with characteristics of those remaining in the study to assess for risk of attrition bias. Latent class growth analysis or other latent trajectory analysis will be used to identify distinct groups of participants with similar short-term trajectories of shoulder pain and function scores (0–10 NRS) using weekly measurements of outcome data at up to 12 time points over the first 3 months. For inclusion in the analysis, participants will be required to have available data in week 1 and at ≥2 further time points. The optimal number of trajectories will be selected using a combination of statistical, parsimony and interpretability criteria.46 Appropriate polynomial functional form for each trajectory will be chosen, based on the significance of the estimated parameters related to each polynomial component. Participants will be assigned to trajectories according to maximum probability assignment principle. The number of trajectories will be increased, and model fit assessed using Bayesian information criterion (BIC) and sample size adjusted BIC. The Lo, Mendell and Rubin adjusted likelihood ratio test (LRT),47 and the bootstrap LRT were used to assess whether there was a significant improvement in model fit between k-1 and k trajectory models. The following criteria will also be used for model selection: (1) delineation of trajectories assessed by higher entropy, (2) average posterior probability of trajectory membership >0.7, (3) trajectory membership ≥4%and (4) clinical relevance and interpretation of the identified trajectories. Mplus software is planned to be used for analysis of pain and function trajectories.48 Baseline characteristics of subgroups showing distinct trajectories will be described, including any treatment received for shoulder pain during the first 3months. Similar methods will be used to describe long-term trajectories, using outcome data at 6, 12, 24 and 36 months. Based on previous studies investigating trajectories in other conditions (n=350–700)49 50 we expect to identify between three and five classes, for which a sample size between 400 and 500 participants should be sufficient. The GRoLTS checklist for reporting latent trajectory studies will be followed. + + Objective 2 Describe healthcare resource use and productivity losses: Healthcare costs will be estimated by combining resource use data with unit costs, obtained from standard sources including the British National Formulary for drugs,52 NHS Reference costs53 and Unit Costs of Health and Social Care.54 Productivity costs will be estimated using the human capital approach with salary costs based on respondent job-specific average wage estimates identified from annual earnings data and UK Standard Occupational Classification coding.55 Responses to the EQ-5D-5L at each time point will be converted to utility values obtained using the cross-walk value set, in line with current National Institute for Health and Care Excellence recommendations.56 Utility values will also be converted into quality-adjusted life-years (QALYs) using the area under the curve approach linking utility scores at various time points. A descriptive analysis of resource use, healthcare costs, time off work, productivity costs, EQ-5D-5L utility values and total QALYs will be conducted, with presentation of means and confidence intervals obtained by non-parametric bootstrapping. + + Objective 3 Develop a prognostic model for predicting individuals’ level and risk of pain and disability: We will develop and validate a multivariable prediction model for reliably estimating expected levels of pain and disability (using SPADI total score as a continuous outcome) over 6 months follow-up. Development of prognostic prediction model will be guided by the PROGRESS framework57–59 and reported using Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis reporting guidelines. The number of variables (candidate predictors) for potential inclusion will be restricted to meet sample size requirements (see below), based on existing or emerging evidence regarding the prognostic value of variables, combined with clinical and patient expertise, and consider sociodemographic variables, lifestyle factors, shoulder pain characteristics, comorbidity and psychosocial factors. Candidate predictors will be based on participant self-report to allow wide App of the prognostic model, with data extracted from the baseline questionnaire. Multivariable linear regression using the elastic net penalty (to penalise for potential overfitting and to allow variable selection). Continuous prognostic variables will not be categorised during the process of developing the models, with splines or fractional polynomials used to examine non-linear associations with outcome. Prognostic subgroups will be defined based on predicted SPADI values at 6 months, using a priori defined thresholds for SPADI for recovery (eg, SPADI score <20) or persistent high levels of pain and disability (eg, SPADI score ≥50). We will additionally describe predictive performance of the model to accurately predict the prob ability of individuals with shoulder pain to experience recovery and risk persistent high SPADI scores. Internal validation will be undertaken using bootstrapping of the entire development dataset, and optimism-adjusted estimates of predictive performance produced for calibration (eg, R2, calibration-in-the-large, calibration slope) and discrimination (eg, C-statistic, area under the curve) for predicted risks. We have estimated minimum sample size using the approach proposed by Riley et al, 60 61 and using the Stata pmsampsize command, aiming to reduce overfitting of the prediction model. Based on previous studies, we expect R2 to be 0.5 when including baseline level of the primary outcome (SPADI total score) in the model as planned. Based on an expected mean change of 25 points and SD of 235 and a model including 20 candidate predictors, the required minimum sample size is 254 participants. Accounting for loss to follow-up of 25% we need to recruit at least 339 participants to the cohort. When using a binary outcome, a minimum sample size of 377 participants with follow-up (503 at baseline) would be needed. + + Objective 4 Explore the added prognostic value of physical examination tests and US findings: Due to lockdown measures during the COVID-19 pandemic, a much smaller number of participants than originally planned can be invited for a clinical assessment. Given the expected small sample size, the statistical analysis of data from the clinical assessment will focus on testing a priori defined hypotheses, informed by previous literature and clinical expertise, and explore the value of adding specific physical examination tests or US findings for predicting outcome (higher SPADI scores over 6 months follow-up), over and above prognostic information included in the prediction model using self-report data only. Assuming R2 from the prediction model will be 0.5 using 20 predictors (as described above), to have 80% power to detect one additional predictor adding 0.05 to the R2 to the model, we would need 74 participants without drop-out, and 99 participants assuming 25% will drop-out.62 + + Objective 5 Explore candidate predictors of response to commonly used treatments in a real-life, observational setting: Developmental work (systematic review, workshops with clinicians and international choice-based conjoint-survey of clinicians)63 has generated a shortlist of candidate treatment moderators that may modify the response to commonly used treatments for shoulder pain in primary care (advice and pain relief only, corticosteroid injection, exercise/mobilisation), as recorded by participants in the three and 6months follow-up questionnaires. These candidate moderators will include: symptom duration; presumed cause of shoulder pain (injury or other); coexisting neck pain; psychosocial complexity (fear avoidance, catastrophising, anxiety, depression); positive expectations or preferences regarding treatment and comorbidity (in particular diabetes). Linear (random effects) regression analysis will be used to estimate the outcomes of treatment received (eg, corticosteroid injection compared with advice/analgesics only), using SPADI score over 6 months follow-up as the primary outcome. Propensity score methodology (using matching, stratification or inverse probability of treatment weighting approach) will be used to adjust for confounding by indication due to observed covariates. Sensitivity analysis will be performed to assess the robustness of findings to potential unmeasured confounding, using the E value approach.64 The effects of moderator*treatment interactions will be explored, and overall treatment outcomes as well as outcomes for relevant subgroups (where relevant moderator*treatment interactions will be identified) described. Based on previous primary care studies7 and our GP survey65 we expect that 20%–40% of patients receive an injection and 25%–50% of patients see a physiotherapist following GP consultation. Depending on the distribution of candidate predictors, this will give subgroups of ≥100to explore the role of candidate moderators. These are exploratory analyses, given that predictors of treatment effect need to be confirmed using data from randomised trials, but will offer insight into their value in the broader population of people with shoulder pain presented in routine primary care. + + Analysis qualitative study (objective 6) All interviews will be audiorecorded, fully transcribed and then cleaned and anonymised. An inductive, exploratory framework will be adopted using thematic analysis and influenced by grounded theory.66 The constant comparison method67 will be used in the analysis, looking for connections within and across interviews, and across codes, highlighting data consistencies and variation. The participant–clinician dyad will be the unit of analysis. Exploring dual perspectives on the consultation can provide a rich data source which can strengthen trustworthiness of data.68 Comparisons will be made between the matched participant and clinician interviews, looking for similarities and differences in the separate accounts given. Analysis will, therefore, draw comparisons both between clinician and participant perceptions of specific consultations as well as between different clinician–participant dyads across the sample.","Funding NIHR Programme Grants for Applied Research (RP-PG-0615-20002). This study is funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme in collaboration with Versus Arthritis (RP PG-0615-20002). CM is funded by the National Institute for Health Research (NIHR) Applied Research Collaboration West Midlands, and the National Institute for Health Research (NIHR) School for Primary Care Research. The cohort study is co-funded by Versus Arthritis. + + Competing interests None declared.","BMJ + + Provenance and peer review Not commissioned; externally peer reviewed.",1,1,1,1,1,1,1,1,1,9 +80,"Autologous Transplantation, Consolidation, and + Maintenance Therapy in Multiple Myeloma: + Results of the BMT CTN 0702 Trial",ASSOCIATED CONTENT Appendix Data Supplement Author affiliations and support information (if applicable) appear at the end of this article.,"Clinical trial information: NCT01109004. + + Clinicaltrials.gov identifier: NCT01109004",Journal of Clinical Oncology,"PATIENTS AND METHODS Patients with symptomatic MM within 12 months from starting therapy and without progression who were age 70 years or younger were randomly assigned to AHCT/AHCT + len (n = 247), AHCT + RVD + len (n = 254), or AHCT + len (n = 257). The primary end point was 38-month PFS. + + The Blood and Marrow Transplant Clinical Trials Network (BMT CTN) 0702 trial (Clinicaltrials.gov identifier: NCT01109004) was a phase III study undertaken at 54 US transplantation centers. + + The study was approved by the institutional review boards of the participating centers, and all patients provided informed consent. + All patients were randomly assigned in a 1:1:1 manner at the time of enrollment, which occurred within 7 days before the first high-dose melphalan conditioning regimen. Random assignment was stratified by disease risk and transplantation center. + + Patients without cytogenetic analysis available and b2-microglobulin level of 5.5 mg/L or lower or with deletion 13 detected by fluorescence in situ hybridization were classified as standard risk.","Procedures All enrolled patients were to receive high-dose melphalan (200 mg/m2 ) followed by mobilized autologous peripheral blood stem-cell infusion (minimum 2 3 106 CD34+ cells/kg). Subsequent therapy was based on random assignment at the time of enrollment. The second phase of therapy started be ween 60 and 120 days after the first AHCT, once patients had sufficiently recovered. Patients randomly assigned to a second transplantation (AHCT/AHCT + len) received high-dose melphalan (200 mg/m2 ) followed by autologous peripheral-blood stem-cell infusion. Patients randomly assigned to RVD consolidation (AHCT + RVD + len) received four cycles of len 15 mg/d on days 1 to 14; bortezomib 1.3 mg/m2 on days 1, 4, 8, and 11 of every 21-day cycle; and dexamethasone 40 mg per day on days 1, 8, and 15. After their initial interventions, all patients received len starting at 10 mg per day for 3 months and increasing to 15 mg per day.4 Dose adjustments for toxicity were permitted (Data Supplement).","The study population had a median age of 56 years (range, 20 to 70 years); 24% of patients had high-risk MM, 73% had a triple-drug regimen as initial therapy, and 18% were in complete response at enrollment. + + Patients with symptomatic MM who were 70 years old or younger and who received at least two cycles of any regimen as initial systemic therapy without disease progression and who were within 2 to 12 months of the first dose of initial therapy were eligible (Data Supplement).","Statistical Analysis The study design estimated PFS to range from 30% to 60% at 3 years after transplantation based on current literature at the time of study design.13 At the two-sided P = .01667 level, a sample size of 250 participants per arm yields 81% power to compare a proportion of 0.60 in arm 1 with a proportion of 0.45 in arm 2, 84% power to compare a proportion of 0.45 in arm 2 with a proportion of 0.30 in arm 3, and nearly 100% power to compare arm 1 with arm 3 (Data Supplement). Participants were randomly assigned using permuted blocks within strata. The primary analysis of PFS included all participants according to their randomly assigned treatment, regardless of treatment received (in tent-to-treat population). Planned interim analyses for futility and efficacy for the primary outcome were conducted approximately 1 and 2 years after the last patient was randomly assigned. In addition, analysis for futility as a result of nonadherence to the assigned treatment was conducted for each arm. The analyses for efficacy consisted of three stratified log-rank tests comparing each pair of treatment groups at the overall P = .01667 level in error in order to maintain studywide type 1 error at .05, further adjusted using O’Brien Fleming boundaries.14,15 For tests of other outcomes, tests were performed pairwise at the P = .01667 level to maintain type I error at a = .05 for each outcome at each time point tested. PFS and OS were estimated using the Kaplan-Meier method, and comparisons were tested using a two-sided log-rank test stratified on risk status. In the presence of competing risks, the cumulative incidence was estimated using the method of Gooley et al,16 and pairwise com parisons were tested using Gray’s test.17 Cox proportional hazards models with treatment group and risk strata (with and without interactions)18 were used to estimate hazard ratios (HRs) and 95% CIs, and effects were tested at the P = .05 level. None of the interactions were significant in the models (OS, P = .53; PFS, P = .74); therefore, the models without interactions are reported here. Treatment group differences in QOL were tested using pairwise t tests or Wilcoxon rank sum tests if the assumptions of the t test were not met. Treatment group differences in disease response were tested using pairwise x2 tests. Statistical analyses were performed with the use of SAS software, version 9.4 (SAS Institute, Cary, NC). The data cutoff was August 15, 2017.","The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the funding parties. + + AUTHOR’S DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST AND DATA AVAILABILITY STATEMENT Disclosures provided by the author and data availability statement (if applicable) are available with this article at DOI https://doi.org/10.1200/ JCO.18.00685. + + AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/site/ifc. Edward A. Stadtmauer Consulting or Advisory Role: Celgene, Takeda, Novartis, Teva, Janssen, Amgen, Sanofi Marcelo C. Pasquini Honoraria: Celgene Consulting or Advisory Role: Pfizer, Medigene (Inst) Beth Blackwell Research Funding: Confidential (Inst), Celgene (Inst), Takeda (Inst) Parameswaran Hari Honoraria: Celgene, Millennium, Sanofi, Amgen, Spectrum Pharmaceuticals, Novartis Consulting or Advisory Role: Celgene, Sanofi, Spectrum Pharmaceuticals, Takeda, Bristol-Myers Squibb, Janssen, Amgen Research Funding: Millennium (Inst), Celgene (Inst), Onyx (Inst), Spectrum Pharmaceuticals (Inst) Steven Devine Honoraria: Incyte, Bristol-Myers Squibb, Kiadis Consulting or Advisory Role: Incyte Yvonne Efebera Honoraria: Takeda Speakers’ Bureau: Takeda, Janssen, Akcea Siddharta Ganguly Honoraria: Seattle Genetics, Amgen, Janssen, Kite Pharma, Daiichi Sankyo Consulting or Advisory Role: Amgen, Kite Pharma Speakers’ Bureau: Seattle Genetics Research Funding: Daiichi Sankyo (Inst), Janssen (Inst) Travel, Accommodations, Expenses: Daiichi Sankyo, Seattle Genetics, Amgen, Kite Pharma Cristina Gasparetto Leadership: Celgene Honoraria: Takeda Consulting or Advisory Role: Celgene, Takeda, Karyopharm Therapeutics, Amgen, Janssen Research Funding: Celgene (Inst) Travel, Accommodations, Expenses: Celgene, Karyopharm Therapeutics Nancy Geller Stock and Other Ownership Interests: Danaher Corporation Mary M. Horowitz Consulting or Advisory Role: Magenta (Inst) Research Funding: Biovitrum (Inst), Telomere Diagnostics, Gamida Cell, Jazz Pharmaceuticals (Inst), Magenta (Inst) John Koreth Consulting or Advisory Role: Amgen, Equillium, Fortress Biotech Research Funding: Millennium, Bristol-Myers Squibb, Miltenyi Biotec, Prometheus Patents, Royalties, Other Intellectual Property: Use patents for low-dose interleukin-2 in immune inflammation, assigned to Dana-Farber Cancer Institute (Inst) Travel, Accommodations, Expenses: Amgen Heather Landau Consulting or Advisory Role: Celgene, Takeda, Caelum Biosciences, Juno Therapeutics Research Funding: Takeda Claudio Brunstein Consulting or Advisory Role: Bayer (I), Elcelyx (I), Gilead Sciences (I) Research Funding: Gamida Cell, Astex Pharmaceuticals, Amgen, Bayer (I) Philip McCarthy Honoraria: Celgene, Karyopharm Therapeutics, Bristol-Myers Squibb, Sanofi, Janssen, The Binding Site Consulting or Advisory Role: Celgene, Bristol-Myers Squibb, Karyopharm Therapeutics, Sanofi, Janssen, The Binding Site, Magenta Research Funding: Celgene (Inst) Muzaffar H. Qazilbash Consulting or Advisory Role: Amgen Speakers’ Bureau: Merck, Sanofi Research Funding: Amgen, Tesaro Nina Shah Stock and Other Ownership Interests: Indapta Therapeutics Consulting or Advisory Role: Takeda, Celgene, Indapta Therapeutics, TeneoBio, Bristol-Myers Squibb, Sanofi Research Funding: Celgene, Bluebird Bio, Janssen David H. Vesole Stock and Other Ownership Interests: Amgen, AbbVie, Biogen, Gilead Sciences, Johnson & Johnson, Eli Lilly, Novartis Honoraria: Amgen, Takeda Speakers’ Bureau: Amgen, Celgene, Janssen Oncology, Takeda Ravi Vij Consulting or Advisory Role: Bristol-Myers Squibb, Celgene, Janssen, Sanofi, Karyopharm Therapeutics, Jazz Pharmaceuticals, Amgen, Takeda, AbbVie Research Funding: Amgen, Takeda, Celgene, Bristol-Myers Squibb Travel, Accommodations, Expenses: Celgene, Bristol-Myers Squibb, Sanofi, Janssen, DAVA Oncology, Karyopharm Therapeutics, Amgen, Takeda, AbbVie Dan T. Vogl Consulting or Advisory Role: Celgene, Amgen, Karyopharm Therapeutics, Teva, Janssen Research Funding: Millennium (Inst), Acetylon Pharmaceuticals (Inst), GlaxoSmithKline (Inst), Calithera Biosciences (Inst), Constellation Pharmaceuticals (Inst) Travel, Accommodations, Expenses: Amgen Sergio Giralt Honoraria: Celgene, Takeda, Amgen, Jazz Pharmaceuticals, Sanofi Consulting or Advisory Role: Celgene, Takeda, Sanofi, Jazz Pharmaceuticals, Amgen, Janssen Research Funding: Celgene (Inst), Celgene (Inst), Takeda, Miltenyi Biotec (Inst), Johnson & Johnson, Amgen Travel, Accommodations, Expenses: Celgene, Sanofi, Amgen, Jazz Pharmaceuticals George Somlo Consulting or Advisory Role: AstraZeneca, AbbVie, Pfizer, Takeda, Genentech Speakers’ Bureau: Takeda Research Funding: Celgene (Inst), Genentech (Inst), Agendia (Inst) Other Relationship: AbbVie Amrita Krishnan Stock and Other Ownership Interests: Celgene (I), Kite Pharma (I) Consulting or Advisory Role: Celgene, Onyx, Janssen Oncology, Takeda, Kite Pharma, Seattle Genetics Speakers’ Bureau: Celgene, Onyx, Janssen Oncology, Takeda Research Funding: Celgene (Inst), Takeda (Inst) + No other potential conflicts of interest were reported.",Journal of Clinical Oncology,1,1,1,1,1,1,1,1,1,9 +81,"Double unrelated umbilical cord blood vs + HLA-haploidentical bone marrow transplantation: + the BMT CTN 1101 trial","Deidentified individual participant data that underlie the reported results will be made available upon publication on the Web site of the NHLBI’s Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). + + The online version of this article contains a data supplement.",This trial was registered at www.clinicaltrials.gov as #NCT01597778.,,"Between June 2012 and June 2018, 368 patients aged 18 to 70 years with chemotherapy-sensitive lymphoma or acute leukemia in remission were randomly assigned to undergo UCB (n 5 186) or haploidentical (n 5 182) transplant. + + Study design Randomization for the Blood and Marrow Transplant Clinical Trials Network protocol #1101 (BMT CTN 1101) was performed at Emmes Corporation at a 1:1 ratio using random block sizes stratified by transplant center. The primary end point was PFS 2 years after randomization, as assessed by intention-to-treat (ITT) analysis. Prespecified secondary end points included in cidences of neutrophil and platelet recovery, acute and chronic GVHD, nonrelapse mortality, relapse/progression, and overall survival (OS). Enrollment began on 19 June 2012 and ended 30 June 2018 without reaching the accrual goal of 410 patients. The Data Safety Monitoring Board (DSMB) closed the trial in con sultation with the study’s sponsor, the National Heart, Lung, and Blood Institute (NHLBI), due to slow accrual. Three hundred sixty-eight patients (90% of planned accrual) enrolled from 33 centers. Supplemental Table 1 (available on the Blood Web site) lists the participating centers and the site principal investigators. The analysis included data collected as of 1 August 2019.","Reduced-intensity conditioning comprised total-body irradiation with cyclophosphamide and fludarabine for both donor types. Graft-versus-host disease prophylaxis for UCB transplantation was cyclosporine and mycophenolate mofetil (MMF) and for haploidentical transplantation, posttransplant cyclophosphamide, tacrolimus, and MMF. + + Treatment The treatment plans are shown in Figure 2. Patients randomized to the double cord arm received fludarabine, cyclophosphamide, and either 200 or 300 cGy total-body irradiation (TBI), with the higher TBI dose given to patients who had not received cytotoxic chemotherapy within 3 months of enrollment or an autologous hematopoietic stem cell transplant within 24 months of enrollment. GVHD prophylaxis commenced 3 days prior to transplantation and comprised 15 mg/kg mycophenolate mofetil 3 times daily (with a maximum daily dose of 3 g) through day 35 and cyclosporine adjusted to maintain a trough level of 200 to 400 ng/mL through day 100 and tapered by 10% weekly until discontinued between days 180 and 200. For patients receiving haploidentical bone marrow, the conditioning regimen included cyclophosphamide, fludarabine, and 200 cGy TBI. GVHD prophylaxis consisted of 50 mg/kg cyclophosphamide IV daily on days 3 and 4, 15 mg/kg mycophenolate mofetil 3 times daily from days 5 through 35, and tacrolimus adjusted to maintain a concentration of 5 to 15 ng/mL from day 5 through day 180.","Treatment groups had similar age, sex, self-reported ethnic origin, performance status, disease, and disease status at randomization. + + Patients Eligible patients were aged 18 to 70 years and had high-risk acute leukemia, Hodgkin or non-Hodgkin lymphoma, performance score of 70 or higher, adequate organ function, and availability of 2 cord blood units and at least 1 haploidentical relative (parent, full or half sibling, offspring or second-degree relative). Each cord blood unit had to have a cell dose of at least 1.5 3 107 nucleated cells per kilogram patient body weight at cryopreservation and be HLA matched to the patient at 4 or more loci (HLA-A, -B at the antigen level and -DRB1 at the allele level). The haploidentical relative had to be matched to the patient for at least 1 allele each of the HLA-A, -B, -C, and -DRB1 genes and was required to donate bone marrow. We excluded a cord blood unit or a haploidentical donor if the patient had donor-specific antibodies against the high-expression HLA-A, -B, -C, or -DRB1 alleles with mean fluorescence intensity .1000. Details of the inclusion and exclusion criteria are provided in the treatment protocol document, section 2.2 (supplemental Material). All patients provided written informed consent. One hundred eighty-six patients were randomly assigned to receive cord blood transplants and 182 patients to receive haploidentical transplants. Of the 186 patients randomized to the cord blood arm, 172 received the treatment as assigned; 8 patients relapsed before transplant, 3 withdrew consent, 1 crossed over to receive haploidentical bone marrow, and 2 were transplanted off protocol at the investigator’s discretion (Figure 1). Of the 182 patients randomized to the haploidentical bone marrow arm, 153 received the treatment as assigned; 10 patients relapsed before transplant, 1 died without relapse, 4 withdrew consent, 11 crossed over to receive cord blood, and 3 were transplanted off protocol at the investigator’s discretion.","Statistical analysis The primary analysis was a comparison of PFS at 2 years after randomization using ITT analysis. We selected a pointwise comparison due to concerns about potential nonproportional hazards. The sample-size target of 205 patients in each group aimed at providing 80% power for a 2-sided test to detect a 15% difference in 2-year PFS, assuming baseline PFS of 35% to 40% at 2 years, and accounting for up to 5% of patients not trans planted and 5% loss to follow-up by 2 years. PFS times were calculated from the day of randomization. + + The x2 statistic was used to compare categorical variables and the Mann-Whitney test to compare continuous variables between the treatment groups. PFS and OS were estimated using the Kaplan-Meier method.8 PFS was compared between treatment arms using a pointwise Z test of the difference in 2-year probabilities, whereas OS was compared using the log-rank test. The first occurrence of relapse or progression or death was an event for PFS and death from any cause an event for OS. Patients without an event were censored at last follow-up or at 2 years after randomization, whichever came first. We calculated the cumulative incidence of hematopoietic recovery, acute and chronic GVHD, nonrelapse mortality, and relapse/progression using the Aalen-Johansen estimator9 to accommodate competing risks. Neutrophil and platelet engraftment were compared between groups using pointwise estimates at day 56 and day 100, respectively, whereas acute and chronic GVHD, nonrelapse mortality, and relapse/progression were compared using the Gray test. + + A Cox proportional hazards regression analysis identified predictors of PFS while assessing the treatment effect.10 Results are expressed as hazard ratios (HRs) with 95% CIs. All variables studied met the assumptions for proportionality. Multivariable modeling included disease, disease risk, age at randomization, and performance score. Other variables (sex and ethnic origin) did not meet the prespecified requirement for inclusion in the model (P , .1 between treatment arms). An effect of transplant center on the primary end point was explored using not only a piecewise exponential PFS model, adjusted for the same variables as in the Cox regression model mentioned earlier, but also adding random effects for both the intercept term as well as the treatment by center interaction effect. All P values are 2-sided; values of P , .05 were considered to indicate statistical significance. Analyses were performed with SAS software, version 9.4 (SAS Institute). + + B.L. and P.D. were responsible for analyzing the data, and all authors had access to the primary clinical trial data.","Acknowledgments This work was supported by grants U10HL069294 and U24HL138660 to the Blood and Marrow Transplant Clinical Trials Network from the National Heart, Lung, and Blood Institute and the National Cancer Institute of the National Institutes of Health. + + The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. + + Conflict-of-interest disclosure: The authors declare no competing financial interest. + + The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.",Blood,1,1,0,1,1,1,1,1,1,8