dataesr/scientific-paragraphs-categorization huggingface dataset:
We abstracted data on document characteristics (e. g. , authors, year of publication, country), PRM content, and barriers to or facilitators of their implementation. As a result of the last stepscharting the data (step 4) and collating, summarising, and reporting the results (step 5) -we coded the data from the articles, reports and websites in relation to our question, thus, defining three broad categories:(i) the type of PROMs and PREMs used, generic or specific to cancer; (ii) the national or international initiatives using PRMs; in this case, we referred to four types of initiatives related to HCOs assessment  [5]  (iii)The types of barriers to implementing PRMs as QIs: Instead of being only thematic, we enriched our frame with a perspective scale  [26]. Finally, we did not analyse the methodological qualities of our studies, which were heterogeneous.
Though not implemented yet, performance-based payment is at the core of different projects  [4]. PROMs are mainly used in research data collections and in outcome benchmarking between and within state and national jurisdictions  [4, 40, 41]. For example, the Palliative Care Outcomes Collaboration (PCOC) includes PROMs to benchmark the outcomes of palliative care services  [2, 19]. Another example is the Prostate Cancer Outcomes Registry-Australia and New Zealand, which tracks the treatment and outcomes of men with prostate cancer  [42]. In New Zealand, PROMs are used for benchmarking and comparison issues and PREMs for performance-based payment and public diffusion  [4]. For performance-based payment, incentive systems are currently being developed  [5]. Sweden is a leading country for PRO collection.
Translating PRMs into improvement actions The actionable nature of QIs reflects the ability to move from a measurement-based assessment time to an improvement time. Even if PREMs turn out to be more exploitable than the PROMs  [20] , in most cases, the transformation of a measure into improvement actions represents a challenge. In some cases, no effective treatments are available concerning the improvements outlined during the PRMs assessment  [35]. An inter-HCO comparison based on QIs-PRMs related also introduces a supplementary level of complexity as a question arises on the merits of the aggregated analysis produced. When a patient transmits data related to PRMs, the relationship with the healthcare professional is essential to providing an appropriate response  [9]. At an aggregate level, based on feedback from a sample of patients, such an individual analysis is more complex to deduce because the aggregated expression of an average or a median does not reflect each patient's situation  [1].
The second finding is that different barriers exist at the different steps of the design and implementation of the QIs-PRMs related to health policy purposes. They are related to the definition of a standard set of QIs, the data collection process, scientific soundness, and the ability to translate these QIs into quality improvements. Regardless of the clinical condition, the generic aspect of these barriers suggests that they are probably similar in clinical conditions other than oncology. Many of them are also shared whatever the objectives of PRMs' use pursued (i. e. ,clinical trial, professional practices, patient self-management or healthcare policy purpose). However, the lack of a standardised methodology for developing PRObased QIs jeopardises the significance of results even more when healthcare policy purposes are targeted.
These two findings combined lead to a paradox. The dissemination of PRMs within the framework of health policies is widely supported in various countries although major issues have to be resolved. To support the development of PRMs, it is crucial to define a methodological framework to advance the design of validated QIs related to PRMs, and also to ensure an effective implementation. In this way, various recommendations can be issued  [63, 64] : -Involve professionals from the outset by defining and communicating the objectives of data collection; the understanding, engagement, and support from clinicians are prerequisites toward the setting of PRMs; -Select measures that are valid and easy for the patient to implement (i. e. , methodologically reliable, internally consistent, sensitive to change, easy to understand, and easily administered); -Pay attention to discriminatory power between populations and to confounding factors (e.
g. the PRMs can be risk-stratified based on severity so that clinicians can manage patients with the greatest needs while monitoring other patients who may require assistance at some point), and also in case of litigation (e. g. Risk stratification of PMRs can be very useful in comparing the poor performance of a healthcare organization against a national average). Recent initiatives also provide insights. For instance, the remote monitoring system Capri highlights the role of Nurse Navigators in processing the information generated by PRMs. Their work involves advising patients in terms of self-management, directing them to various ambulatory healthcare professionals and contacting oncologists when required, thereby alleviating the burden of data collection for the latter  [66]. These initiatives highlight that a PRM's platform without organization to treat the data can lead to unsustainable and critical situations.
Since 2017, all data is public control (2014) Routine application caregivers Approximately 40% of at regional and national national registers include levels. PREMs Since 2018, all PROMs are National Prostate Cancer collected electronically Registry (NPCR) Same for breast cancer Germany PREMs: The Patient 15 questions in the categories Inter-HCO Mandatory (2014) Experience Questionnaire of medical care, nursing care, comparison collection [5,39,45] (PEQ) hospital stay, and global Focus Klinikliste: Routine application PROM and PREM tool hospital assessment and how hospital rankings for Public reporting translated from the Danish patients would recommend 15 medical (including PEQ National Cancer Patient hospitals indications, including results) Questionnaire All hospitals breast and colon Cancer registry All cancer patients cancer Spain Health Barometer Survey Annual evaluation of National Benchmark Mandatory (2008) PREM satisfaction for outpatient and collection (unclear) [x] BiblioPRO inpatient services [xliv] Database of PRO tools in Spanish Norway PCO Norway National collection, patients Benchmark: inter- Not mandatory Performance-based [48] PROM prostate diagnosed with prostate HCO comparisons National Collection payment according (2017) National online survey: cancer complete 3 to inter-HCO [5,10] Patient Experiences questionnaires: EQ-5D-DL, comparisons Questionnaire (PEQ) EORTC-QLQ-C30 and EPIC- (2013) Hospital-based Patient 26.
23 questions (2001) General Practice Survey about moments of the care [5] (DANPEP) trajectory ICHOM PROMs Sets of standardised European and global Mandatory [4,52,53] indicators, including 5 for benchmarking in collection for HCOs (2012) cancer (notably prostate). progress (e. g. : involved in the [5] Works with national TrueNTH Global project organizations (Bowel Cancer Registry (PROM EPIC Australia, Database of South 26) Australia (CADOSA), the Department of Veterans' Affairs, Ramsay Health Care, Royal Melbourne Hospital, the Victorian Prostate Cancer Registry…) OECD PROMs and PREMs 19-country Mandatory for [2,4] benchmark for HCOs involved in (2018) ambulatory care the project (PREM) PaRIS initiatives: PROMs /PREMs development for an international benchmark.
Materials and methods EANS skull base section panelists were enrolled and 11 completed the survey: the goal was to provide a consensus statement of the endoscopic endonasal approach for pituitary adenoma surgery. The survey consisted of 44 questions covering demographics data (i. e. , academic/ non-academic center, case load, years of experience), surgical techniques (i. e. , use of neuronavigation, preoperative imaging), and followup management.
In conclusion, bowel cleansing with mannitol was safe as the concentrations of H 2 and CH 4 were the same as those found in patients prepared with 2 L PEG-Asc. In both groups, the concentrations of gases were influenced more by the degree of cleansing achieved and the insufflation and washing maneuvers performed than by the preparation used for bowel cleansing. The trial protocol was registered with Clini calTr ials. gov (https://clini caltr ials. gov/ ct2/show/NCT04 759885) and with EudraCT (eudract_number: 2019-002856-18).
Finally, to further evaluate the factors affecting residual concentrations of intestinal gases in all patients, regardless of treatment group and separately for H 2 and CH 4 , a multivariable regression analysis was conducted using as independent variables the preparation used for bowel cleansing, the degree of cleanliness obtained (BBPS score), and the oxygen concentration measured (indicating the degree of insufflation and washing performed during colonoscopy). All inferential analyses were performed using SAS release 9. 4 (SAS Institute).
MS/MS targeted molecular networking approach for the discovery of DME communesins chemodiversity In order to selectively highlight communesins in samples (especially minor ones), an automated workflow was then developed, taking advantage of both molecular networking approach and characteristic fragmentation pattern of communesins. After a peak picking step applied to all LC-HRMS/MS data obtained on fractions enriched in communesins, a R script was devised for DME communesin detection. It calculated a score for each feature detected after the peak picking step, based on the presence of fragments within the MS/MS spectra. 4f] These scores were thus mapped into a molecular network obtained using MetGem software  [7]  (Figure  1 ). Such an approach allowed to instantly highlight a cluster corresponding to DME communesins.
This allowed to determine a relative probability about the nature of R 2 , which could be visualized by applying a different color to each fragment score (for -H, -CH 3 or -CHO, respectively), displayed as pie charts for each node (Figure  2 ). Consequently, most nodes of our DME communesin cluster could have their R 2 substituent deduced, except for some nodes with low or weak fragmentation or with a R 2 substituent potentially different from -H, -CH 3 or -CHO (blue nodes on Figure  2 ). The results obtained for the seven known DME communesins confirmed the accuracy of our approach. Thus, the DME communesin cluster was then composed mostly of analogues methylated at R 2 position whereas the two other Figure  1. Molecular networks obtained using MetGem software  [6]  with the DME communesin score calculated as node size.
Fungal strain: The studied fungal strain was isolated from a sediment sample collected in a shellfish farming area of the Loire estuary (Le Croisic, France). It was identified as Penicillium expansum Link by sequencing the internal transcribed spacers (ITS 1 and 2) and the beta-tubulin regions (GenBanK accession number JN794527 and JN794529, respectively). The strain is conserved in the laboratory fungal collection under the reference number MMS42 (UR2160 ISOMer, Nantes Université, France).
The aqueous phases were collected and alkalized until pH 10 by a NaOH concentrated solution. The obtained mixture was extracted three times by CH 2 Cl 2 (200 mL each time). The CH 2 Cl 2 phases were collected and dried giving the alkaloid fraction. HPLC-HRESIMS analysis: HPLC-HRESIMS/MS analyses were carried out on a UFLC-MS (IT-TOF) Shimadzu instrument (combining Ion trap and Time of Flight analyzers, Shimadzu, Japan). olecular networking: HPLC-HRMS/MS profiles were converted from *. raw data to *. mzXML format using MSconvert software. These raw data were processed by using MZmine2 software as detailed in supplementary information. Export from MZmine2 generated a *. mgf file with 459 peaks with associated HRMS/MS data and a *. csv file with the integration values for each peak in each sample.
Automated detection of communesin patterns was performed on the *. mgf file by using a in-house developed R script, using the CluMSID package (version 1. 6. 0)  [15] searching for characteristic fragments of both DME and DMV communesins (see Supporting Information). The script allowed to calculate specific scores for each peak, based on their probability to correspond to DME or DMV communesins, as well as for the probability for R 2 to be either -H, -CH 3 or -CHO. These scores were implemented directly in the previously generated *. csv file. Molecular network was then built using MetGem (see Supporting Information for details), which allowed to visualize spectral similarities between the peaks by using both the cosine score (GNPS-like) and the t-SNE algorithm. [7] Search for known compounds was carried out by using libraries of available experimental or in silico MS/MS spectra.
Acknowledgements The semisynthetic work was supported by a  CNRS GDR MediatEC  grant. Authors acknowledge the  Vietnam International Education Development program  for a Ph. D. grant. We sincerely thank  J. C. Jullian  and  B. Séon-Meniel  from  BioCIS laboratory (Université Paris-Saclay ) for helping in NMR experiments. The authors also thank  J. -H. Renault  from  ICMR  ( Université de Reims Champagne-Ardenne ) for the conformational study.
Introduction: Baricitinib, an orally available small-molecule inhibitor of Janus kinase (JAK)1 and JAK2, is indicated to treat active moderateto-severe rheumatoid arthritis (RA). Objective: This systematic review described the real-world clinical characteristics of baricitinibtreated patients with RA, prescription patterns, effectiveness, drug persistence, patient-reported outcomes (PROs; physical function, pain, health-related quality of life [HRQoL]), patient global assessment (PGA), and safety of baricitinib. Methods: A PRISMA systematic review of realworld studies was conducted to identify relevant literature published between January 2016 and September 2022 using MEDLINEÒ, EMBASEÒ, and evidence-based medicine review databases. Websites or online repositories of the American College of Rheumatology and the European Alliance of Associations for Rheumatology were searched manually to include relevant abstracts from conferences held between January 2016 and November 2022.
Results: A total of 11,472 records were identified by searching online databases. Seventy studies were included in the study, of which 40 were abstracts. Most patients were older (51-71 years), female, and with mean RA duration of 4-19 years. Baricitinib was mostly used after the failure of one or more bDMARDs, and 4 mg dosing was prevalent in patients with RA (range 22-100%). Clinical effectiveness of baricitinib was reported in real-world settings regardless of prior biologic/targeted synthetic disease-modifying antirheumatic drug (DMARD) use and concomitant conventional synthetic DMARD use. Achievement of Clinical Disease Activity Index (CDAI) remission was reported in 8. 7-60% of patients at week 12 and CDAI low disease activity (LDA) in 20. 2-81. 6% at week 24. The proportion of patients attaining Simple Disease Activity Index (SDAI) remission was reported in 12% at week 4 to 45.
Data Sources and Search Strategy This SLR was performed according to guidance issued by the Centre for Reviews and Dissemination and the Cochrane Collaboration  [12, 13]. An English language search of the MEDLINE Ò , EMBASE Ò , and evidence-based medicine reviews databases was conducted to identify relevant literature (full-text and abstracts) published between January 2016 and September 2021. The literature search was updated following the same strategy (September 2021-2022) to ensure that new evidence is incorporated into the findings. The OVIDÒ platform was used to perform the searches using a combination of free text and controlled vocabulary terms for the disease and study designs. Validated search filters of the Scottish Intercollegiate Guidelines Network  [14]  were modified and adapted for the searches.
Search Results Initial literature search was conducted between January 2016 and September 22, 2021. A total of 9188 records were identified by searching online databases. After removing duplicates, 7407 potentially relevant records were identified and screened based on titles and abstracts. Of 7407 studies, 102 full-text articles were selected. Of these, 36 were included based on the inclusion criteria. In addition, 69 studies from additional sources (56 abstracts from ACR and the EULAR, published between 2016 and 2021, and 13 studies suggested by peer reviewers) were included. Of the final 105 studies (41 full-text articles and 64 conference abstracts), 41 studies (17 full-text articles and 24 abstracts) on baricitinib were included in the study (Fig. 1 ). The updated search resulted in 2284 records.
Lines of Baricitinib Therapy Baricitinib was used in all treatment lines, but differences in frequency were observed depending on the geography  [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51]. In Italy, baricitinib was used very rarely in the first (0. 3-2. 7%; N = 47,711-41,290)  [32]  and in the second line of treatment (1. 5-4. 3%)  [33]. In the OPAL dataset from Australia (N = 45,317), higher use of baricitinib was reported in the second to the sixth line of treatment  [51]. In Sweden, baricitinib (n = 1420) was more frequently used as second-or third-line treatment, while tofacitinib was used as in later lines of therapy  [35]. Similarly, in nationwide registries DANBIO and DERMBIO (n = 5104), only 3. 3% of baricitinib patients were bio-naı ¨ve  [38]. Slightly higher percentage of patients (17%) were bio-naı ¨ve in Switzerland (2017-2020; n = 273)  [49, 58].
3%), followed by tofacitinib (86. 4%) and golimumab (69. 0%) in a study of small sample size (n = 31)  [73]. Another small study reported adherence (medication possession ratio [MPR]) and persistence of tofacitinib and baricitinib in RA patients in a real-life setting. Between 2017 and 2021, 40 (29. 4%) and 38 (27. 9%) patients treated with tofacitinib and baricitinib discontinued the treatment. Mean treatment persistence was 363 days (95% confidence interval [CI]: 2-1. 282) in the tofacitinib group and 406 days (95% CI 8-1. 300) in the baricitinib group. There were no statistical differences in treatment survival (hazard ratio [HR] = 1. 01 [95% CI 0. 59-1. 71]; P = 0. 97)  [75]. In a retrospective observational study (N = 5455) conducted using the Australian Medicare Database (from January 2006 till October 2021), persistence rates on first-line JAK inhibitors were 70% for baricitinib and 57% for tofacitinib; persistence rates dropped to 63% for baricitinib and 47% for tofacitinib in the second-line setting.
In a study that used the Japanese Adverse Drug Event Report (JADER) database (2014-2020), the proportion of patients with infections was more in patients treated with baricitinib (49. 2%) than in those treated with tofacitinib (37%). In addition, solid tumors were more frequent in patients treated with abatacept or baricitinib, and more frequencies of MACE were noted in patients treated with baricitinib and golimumab. Cases of VTE were more frequent in patients treated with baricitinib and tofacitinib compared to those treated with other DMARDs  [72]. The same observations were made in a single-center retrospective study (2017-2020) in which the incidence of infection and serious infection was numerically higher in the baricitinib group than in the tofacitinib group but with no statistical signification.
The incidence rates of overall malignancy were 0. 85 and 0. 80 per 100 patient-years for tofacitinib and baricitinib, respectively. In this study, breast cancer was also reported as an IME in patients taking baricitinib with odds ratio of 4. 54 (95% CI 2. 04-10. 14). However, among the spontaneous AE reports, 86. 2% of patients taking tofacitinib and 91. 9% of patients taking upadacitinib were reported from North America, whereas only 59. 7% of patients taking baricitinib were from North America and 30. 7% from Europe  [95]. A multi-database study, across 14 post-marketing data sources in Europe, the USA, and Japan, of patients in routine care using disease registries and claims databases suggested increased risk of VTE with baricitinib versus TNF inhibitors (incident rate ratio [IRR] = 1.
On the other hand, the risk of MACEs and VTEs did not significantly differ between initiating a JAK inhibitor and adalimumab in a nationwide population-based cohort study (N = 15,835) of the French national health data system. This study assessed the risk of MACEs and VTEs among patients initiating tofacitinib or baricitinib (79. 5% received 4 mg daily) versus adalimumab. Also, risk of MACEs (both myocardial infarction and stroke) and VTEs was not significant between baricitinib and tofacitinib groups  [42]. Overall, HZ and respiratory infections, gastrointestinal issues, and elevated blood lipids were observed with the use of baricitinib in the real-world setting. Treatment with baricitinib is also associated with the risk of VTE and MACE; however, this treatment had a similar risk with TNF inhibitors.
Treatment with baricitinib was observed to rapidly improve pain and the patient's perception of the disease. Pain reduction with baricitinib was observed to be only partially attributable to the reduction of inflammatory markers. Improvements in PROs in real-world settings are similar to those observed in RCTs  [92, 105]. Baricitinib 2 or 4 mg/day provided significant improvement versus placebo in PROs across different domains of RA, including physical function, morning joint stiffness, fatigue, pain, and HRQoL, suggesting that baricitinib can be a potentially valuable addition to the RA treatment options for patients struggling with this common and disabling condition  [93]. Data from two phase 3 studies, RA-BUILD (NCT01721057; csDMARD-IR patients) and RA-BEACON (NCT01721044; bDMARD-IR patients), showed that baricitinibtreated patients with RA achieved MCID improvement in PROs (pain, physical function, fatigue, HRQoL, and PGA data) at weeks 4 and 12 and maintained those improvements over time.
In addition, substantial PRO responses were achieved quickly  [106]. Lack of efficacy and AEs were common reasons of treatment discontinuation in baricitinib. HZV and respiratory infections, gastrointestinal symptoms, and hyperlipidemia were observed with the use of baricitinib in the real-world setting. However, the infection rates were not different than those observed in RCTs. Despite the large number of patients who are older and have more comorbidities than those enrolled in RCTs, no new safety concerns were identified. Baricitinib maintained a safety profile similar to that previously reported, with incidence rates of safety events of special interest (including deaths, malignancies, MACE, and VTE) remaining stable  [107] [108] [109] [110]. From this SLR, several gaps in the availability of data were identified.
None of the studies measured adherence or persistence specifically for baricitinib. Similarly, switching and dose changes during treatment were not reported frequently. Dose tapering of oral GCCs and the decrease in the proportion of patients receiving it concomitantly with baricitinib were mostly conducted in patients from Italy. Several high-quality studies included in this review were conducted with patients from Japan. Most of the data on baricitinib versus other JAK inhibitors regarding relative efficacy and tolerance were reported in these studies, limiting its interpretation for other populations. In addition, ORAL Surveillance (NCT02092467), an FDA-mandated, post-authorization, phase IIIb/ IV randomized, open-label, non-inferiority study, evaluated the safety and efficacy of tofacitinib as compared with a TNF inhibitor in patients with RA who were 50 years of age or older and had at least one additional cardiovascular risk factor.