tbuckley/cabot-search huggingface dataset:
Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers
Authors: S. Trebeschi, S.G. Drago, N.J. Birkbak, I. Kurilova, A.M. Cǎlin, A. Delli Pizzi, F. Lalezari, D.M.J. Lambregts, M.W. Rohaan, C. Parmar, E.A. Rozeman, K.J. Hartemink, C. Swanton, J B A G Haanen, C.U. Blank, E.F. Smit, R.G.H. Beets-Tan, H.J.W.L Aerts
Journal: Annals of Oncology (2019)

IntroductionImmunotherapy is regarded as one of the major breakthroughs in cancer treatment. Despite its success, only a subset of patients responds—urging the quest for predictive biomarkers. We hypothesize that artificial intelligence (AI) algorithms can automatically quantify radiographic characteristics that are related to and may therefore act as noninvasive radiomic biomarkers for immunotherapy response.Patients and methodsIn this study, we analyzed 1055 primary and metastatic lesions from 203 patients with advanced melanoma and non-small-cell lung cancer (NSCLC) undergoing anti-PD1 therapy. We carried out an AI-based characterization of each lesion on the pretreatment contrast-enhanced CT imaging data to develop and validate a noninvasive machine learning biomarker capable of distinguishing between immunotherapy responding and nonresponding. To define the biological basis of the radiographic biomarker, we carried out gene set enrichment analysis in an independent dataset of 262 NSCLC patients.ResultsThe biomarker reached significant performance on NSCLC lesions (up to 0.83 AUC, P < 0.001) and borderline significant for melanoma lymph nodes (0.64 AUC, P = 0.05). Combining these lesion-wide predictions on a patient level, immunotherapy response could be predicted with an AUC of up to 0.76 for both cancer types (P< 0.001), resulting in a 1-year survival difference of 24% (P = 0.02). We found highly significant associations with pathways involved in mitosis, indicating a relationship between increased proliferative potential and preferential response to immunotherapy.ConclusionsThese results indicate that radiographic characteristics of lesions on standard-of-care imaging may function as noninvasive biomarkers for response to immunotherapy, and may show utility for improved patient stratification in both neoadjuvant and palliative settings.
Assessing tuberculosis control priorities in high-burden settings: a modelling approach
Authors: Juan F Vesga, Timothy B Hallett, Michael J A Reid, Kuldeep Singh Sachdeva, Raghuram Rao, Sunil Khaparde, Paresh Dave, Kiran Rade, Maureen Kamene, Eunice Omesa, Enos Masini, Newton Omale, Elizabeth Onyango, Philip Owiti, Muthoni Karanja, Richard Kiplimo, Sofia Alexandru, Valentina Vilc, Valeriu Crudu, Stela Bivol, Cristina Celan, Nimalan Arinaminpathy
Journal: The Lancet Global Health (2019)

BackgroundIn the context of WHO's End TB strategy, there is a need to focus future control efforts on those interventions and innovations that would be most effective in accelerating declines in tuberculosis burden. Using a modelling approach to link the tuberculosis care cascade to transmission, we aimed to identify which improvements in the cascade would yield the greatest effect on incidence and mortality.MethodsWe engaged with national tuberculosis programmes in three country settings (India, Kenya, and Moldova) as illustrative examples of settings with a large private sector (India), a high HIV burden (Kenya), and a high burden of multidrug resistance (Moldova). We collated WHO country burden estimates, routine surveillance data, and tuberculosis prevalence surveys from 2011 (for India) and 2016 (for Kenya). Linking the tuberculosis care cascade to tuberculosis transmission using a mathematical model with Bayesian melding in each setting, we examined which cascade shortfalls would have the greatest effect on incidence and mortality, and how the cascade could be used to monitor future control efforts.FindingsModelling suggests that combined measures to strengthen the care cascade could reduce cumulative tuberculosis incidence by 38% (95% Bayesian credible intervals 27–43) in India, 31% (25–41) in Kenya, and 27% (17–41) in Moldova between 2018 and 2035. For both incidence and mortality, modelling suggests that the most important cascade losses are the proportion of patients visiting the private health-care sector in India, missed diagnosis in health-care settings in Kenya, and drug sensitivity testing in Moldova. In all settings, the most influential delay is the interval before a patient's first presentation for care. In future interventions, the proportion of individuals with tuberculosis who are on high-quality treatment could offer a more robust monitoring tool than routine notifications of tuberculosis.InterpretationLinked to transmission, the care cascade can be valuable, not only for improving patient outcomes but also in identifying and monitoring programmatic priorities to reduce tuberculosis incidence and mortality.FundingUS Agency for International Development, Stop TB Partnership, UK Medical Research Council, and Department for International Development.
Abstract P154: Short-Term Health Care Expenditures Increase After Workplace Wellness Program
Authors: Douglas E Levy, Susan Regan, Anne N Thorndike
Journal: Circulation (2017)

Introduction: A major goal of workplace wellness programs is to improve employee health and lower health care costs. Research on wellness program effectiveness is often limited by either a lack of a control comparison groups or confounding when the intervention and control groups differ on baseline health. Our study objective was to assess the effect on health expenditures of an employee wellness program (BeFit), already shown to improve diet, physical activity, cholesterol, and BP. We compared participants to a matched non-participant control group. Hypothesis: We hypothesized that health care costs would be lower for participants than for non-participants. Methods: BeFit is a 10 week nutrition/exercise program that includes measurement of cardiovascular risk factors, weekly meetings with a nutritionist and personal trainer, gym membership, and team competition to achieve weight and exercise goals. For this study, participants were matched by age, sex, period of employment, and pre-participation Diagnostic Cost Group (DCG) risk score (a predictor of future health care use based on past-year use), to two non-participant control employees. Health expenditures were gathered from claims data obtained by the employer’s human resource department. Subjects in the analysis had at least 12 months pre- and post-program claims data. Within-subject quarterly health care cost trends were compared after subjects’ BeFit start dates using multivariable generalized least squares regression controlling for age, sex, and baseline health. Control subjects were assigned the start date of the subject to whom they were matched. Expenditures were capped at the 99 th percentile ($42,393) so results were not unduly influenced by extreme events unlikely to be affected by a wellness program. We analyzed overall, domain-specific (outpatient, inpatient, pharmaceutical), and diagnosis-specific costs. Results: From 2010-2014, 412 BeFit participants and 824 controls met the inclusion criteria (77% female, mean age 41 [range 23,78], mean baseline DCG risk score of 92.3 [range 3, 2315]). After participation in BeFit, the regression-adjusted health expenditures decreased by $15/quarter among BeFit participants compared to $85/quarter among control subjects (95% CI for difference $27, $113). Trends were significantly more negative in the control group for outpatient, inpatient, and pharmaceutical costs, as well. There were no differences in trends for cardiovascular or diabetes-related costs. Conclusions: Contrary to our hypothesis, trends in health expenditures decreased more for the matched control group than for participants in the employee wellness program. This result may be due to increased attention to health and higher health care use spurred by participation in the program. Further work is necessary to understand the long-term impact of wellness programs on health and health expenditures.
Rebuilding More of Me
Authors: Sourav Sengupta
Journal: JAMA (2019)

Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA HomeNew OnlineCurrent IssueFor Authors Podcasts Clinical Reviews Editors' Summary Medical News Author Interviews More Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA journal
Oncolytics Virus Replication Using Pelareorep (Reolysin) and Carfilzomib in Relapsed Myeloma Patients Increases PD-L1 Expression with Clinical Responses
Authors: Craig C Hofmeister, Douglas W. Sborov, Domenico Viola, Ada Dona, Gerald J Nuovo, Don M. Benson, Sagar Lonial, Jonathan L Kaufman, Ajay K Nooka, Leonard Heffner, Madhav V Dhodapkar, Flavia Pichiorri
Journal: Blood (2018)
Sue Povey: molecular geneticist who masterminded human gene naming
Authors: Penny Warren
Journal: BMJ (2019)

Photo credit: Philip and Nicola Povey

Publication of the complete sequence of the human genome in 2003 was a landmark event, and Sue Povey, Haldane professor of human genetics, played a key part in its success. She led the team at University College London that was part of the Human Genome Project, and successfully took on the hugely complex task of organising gene nomenclature.

Born in 1942, Povey grew up in Leeds with her younger brother Philip. Her father, Jack, was an intelligence officer in the Royal Air Force, who later taught physics, and her mother, Margaret, practised as a GP. Povey learnt about wild flowers and birds from her mother, and it would remain one of her lifelong interests. She became interested in other aspects of natural history too, borrowing books such as On the Origin of Species from her grandfather, who was a doctor and interested in genetics.

After a stellar academic career at Notre Dame Collegiate School in Leeds, Povey studied natural sciences and genetics …
House dust mite allergy in Italy—Diagnostic and clinical relevance of Der p 23 (and of minor allergens): A real‐life, multicenter study
Authors: Giorgio Celi, Ignazio Brusca, Enrico Scala, Danilo Villalta, Elide Pastorello, Laura Farioli, Gabriele Cortellini, Gaia Deleonardi, Pietro Galati, Laura Losappio, Giuseppina Manzotti, Barbara Pirovano, Lionello Muratore, Francesco Murzilli, Francesco Cucinelli, Antonino Musarra, Marcello Cilia, Eleonora Nucera, Arianna Aruanno, Francesco Ria, Maria Francesca Patria, Elena Varin, Battista Roberto Polillo, Vittorio Sargentini, Oliviero Quercia, Carina Gabriela Uasuf, Stefania Zampogna, Michela Carollo, Stefania Graci, Stefano Amato, Gianni Mistrello, Riccardo Asero
Journal: Allergy (2019)

Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
QIM19-128: Improving Oral Chemotherapy Safety in Adult Neuro-Oncology Clinics
Authors: Megan Gershon, Justine Pena, Chamnjot Bains, Sarah Salas, Tresa McGranahan, Seema Nagpal
Journal: Journal of the National Comprehensive Cancer Network (2019)

Background: The development of oral chemotherapies (OC) have transformed cancer care for millions of patients. Most patients with brain tumors have temozolomide (TMZ) delivered to their home. While this has improved the patient experience, it presents significant challenges to safety of prescription, administration, and side effect monitoring. While there are guidelines for documentation, there is not a best practices system for managing OC. This project identified areas of latent errors and implemented a standardized process for OC management. Methods: After review of the literature, we developed a process map for our institution’s practice and performed hazard analysis. We then evaluated the process at 3 other neuro-oncology practices. Based on these evaluations, changes were implemented at several stages (Table 1). Objective binary measures that could be recorded for every TMZ prescription were collected by chart review of the 6 months prior to process change. These measures were monitored every 2 weeks after process change implementation using run charts. A baseline process mean was calculated for each measure from the 6 months before program implementation. Successful change implementation was defined as 7 consecutive 2-week averages that were continually on one side of the process mean. Results: At the time of this abstract submission, we had successfully reduced refills for OC and increased documentation of dose calculation and dose ordered. There is improvement in independent dose calculation by 2 providers and dedicated chemotherapy teaching visits; however, these have not yet reached criteria for process change. Additionally, oral chemotherapy order sets were created in the electronic medical records system and an on-site specialty pharmacy was added as another safety measure in OC management. Conclusions: This project used published studies and multi-institutional process mapping and hazard analysis to implement a standardized ordering of TMZ for patients with brain tumors. This process can be implemented for OC management in other oncology practices.
Pregnancy-Adapted YEARS Algorithm for Diagnosis of Suspected Pulmonary Embolism
Authors: Liselotte M. van der Pol, Cecile Tromeur, Ingrid M. Bistervels, Fionnuala Ni Ainle, Thomas van Bemmel, Laurent Bertoletti, Francis Couturaud, Yordi P.A. van Dooren, Antoine Elias, Laura M. Faber, Herman M.A. Hofstee, Tom van der Hulle, Marieke J.H.A. Kruip, Maxime Maignan, Albert T.A. Mairuhu, Saskia Middeldorp, Mathilde Nijkeuter, Pierre-Marie Roy, Olivier Sanchez, Jeannot Schmidt, Marije ten Wolde, Frederikus A. Klok, Menno V. Huisman
Journal: New England Journal of Medicine (2019)

Pulmonary embolism is one of the leading causes of maternal death in the Western world. Because of the low specificity and sensitivity of the d-dimer test, all pregnant women with suspected pulmonary embolism undergo computed tomographic (CT) pulmonary angiography or ventilation-perfusion scanning, both of which involve radiation exposure to the mother and fetus. Whether a pregnancy-adapted algorithm could be used to safely avoid diagnostic imaging in pregnant women with suspected pulmonary embolism is unknown.In a prospective study involving pregnant women with suspected pulmonary embolism, we assessed three criteria from the YEARS algorithm (clinical signs of deep-vein thrombosis, hemoptysis, and pulmonary embolism as the most likely diagnosis) and measured the d-dimer level. Pulmonary embolism was ruled out if none of the three criteria were met and the d-dimer level was less than 1000 ng per milliliter or if one or more of the three criteria were met and the d-dimer level was less than 500 ng per milliliter. Adaptation of the YEARS algorithm for pregnant women involved compression ultrasonography for women with symptoms of deep-vein thrombosis; if the results were positive (i.e., a clot was present), CT pulmonary angiography was not performed. All patients in whom pulmonary embolism had not been ruled out underwent CT pulmonary angiography. The primary outcome was the incidence of venous thromboembolism at 3 months. The secondary outcome was the proportion of patients in whom CT pulmonary angiography was not indicated to safely rule out pulmonary embolism.A total of 510 women were screened, of whom 12 (2.4%) were excluded. Pulmonary embolism was diagnosed in 20 patients (4.0%) at baseline. During follow-up, popliteal deep-vein thrombosis was diagnosed in 1 patient (0.21%; 95% confidence interval [CI], 0.04 to 1.2); no patient had pulmonary embolism. CT pulmonary angiography was not indicated, and thus was avoided, in 195 patients (39%; 95% CI, 35 to 44). The efficiency of the algorithm was highest during the first trimester of pregnancy and lowest during the third trimester; CT pulmonary angiography was avoided in 65% of patients who began the study in the first trimester and in 32% who began the study in the third trimester.Pulmonary embolism was safely ruled out by the pregnancy-adapted YEARS diagnostic algorithm across all trimesters of pregnancy. CT pulmonary angiography was avoided in 32 to 65% of patients. (Funded by Leiden University Medical Center and 17 other participating hospitals; Artemis Netherlands Trial Register number, NL5726.).
Social Distance and Mobility — A 39-Year-Old Pregnant Migrant Farmworker
Authors: Laszlo Madaras, Scott Stonington, Claire H. Seda, Deliana Garcia, Ed Zuroweste
Journal: New England Journal of Medicine (2019)

Interview with Dr. Laszlo Madaras on caring for people who diverge from the typical patient imagined by health care institutions. (11:17)Download A 39-year-old pregnant migrant farmworker faces depression, heavy physical labor, exposure to pesticides and heat, uncertain nutritional and water intake…and frequent relocation for the work that provides her family's only income.
Abstract P247: Under-reporters of Caloric Intake Have Worst Cardiometabolic Risk Profile Among Children at Risk of Obesity
Authors: Karine Suissa, Andrea Benedetti, Melanie Henderson, Katherine Gray-Donald, Gilles Paradis
Journal: Circulation (2018)

Introduction: Misreporting of dietary data in nutritional epidemiology is a major concern for information bias, as they rely on subjects’ ability to accurately remember and report the foods they consumed. In children, underreporting is common and tends to occur differentially according to certain characteristics. We sought to describe characteristics of under-reporters (UR) within a cohort of children with a parental history of obesity, and to examine the bias introduced with underreporting in children. Methods: Data stem from the QUALITY cohort of 630 children, 8-10 years at recruitment with at least one obese parent. Three separate 24-hour dietary recalls were administered by a dietitian at baseline. Child and parent characteristics were obtained through direct measurement (blood pressure, blood lipids, anthropometrics) or questionnaires (socio-economic characteristics). Goldberg's cut-off method identified UR, by comparing a ratio of reported energy intake and basal metabolic rate to a calculated cut-off value. We used logistic regression to identify correlates of UR. We examined the bias resulting from underreporting by comparing the coefficients from the linear regression of BMI z-score after 2 years on glycemic load (GL) at baseline in all participants and in the adequate reporters (AR) subset, after excluding UR. Results: We identified 167 UR and 408 AR in the QUALITY cohort based on a calculated Goldberg's cut-off of 1.11. UR had a tendency to be older (9.9 vs. 9.5), had a higher BMI z-score (1.5 vs. 0.4) and had poorer cardiometabolic health indicators including higher SBP, DBP, triglycerides and LDL and lower HDL. UR had a lower family income (38,561 vs. 44,078 $CAN), parents were less educated (47.3% vs. 56.9% with a university education) and had a higher BMI compared to parents of AR. In logistic regression, age per year (OR: 1.48, 95%CI: 1.15-1.91), BMI z-score (OR: 2.04, 95% CI: 1.17-3.54), percent fat mass (OR: 1.06, 95%CI: 1.01-1.12) and family income (OR: 0.86 per 10,000$, 95%CI: 0.76-0.98) were the strongest correlates of underreporting. Linear regressions showed that the association between BMI and GL was null when all participants were included, but became significantly positive (ß=0.06 per 10 units, 95%CI: 0.05-0.07) after exclusion of the UR. Conclusion: In the QUALITY cohort, UR were different from AR. Underreporting is an important source of error in nutritional epidemiology that can bias measurement of nutritional exposures and the assessment of exposure outcome relationships. To prevent this bias, UR must be identified and an appropriate correction method must be used.
The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review
Authors: Alba Contreras, Ines Nieto, Carmen Valiente, Regina Espinosa, Carmelo Vazquez
Journal: Psychotherapy and Psychosomatics (2019)

&lt;b&gt;&lt;i&gt;Background:&lt;/i&gt;&lt;/b&gt; Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility. &lt;b&gt;&lt;i&gt;Methods:&lt;/i&gt;&lt;/b&gt; Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of “network analysis” with the terms “anxiety,” “affective disorders,” “depression,” “schizophrenia,” “psychosis,” “personality disorders,” “substance abuse” and “psychopathology.” &lt;b&gt;&lt;i&gt;Results:&lt;/i&gt;&lt;/b&gt; The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence. &lt;b&gt;&lt;i&gt;Conclusions:&lt;/i&gt;&lt;/b&gt; A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.