Use of pragmatic randomized trials in multiple sclerosis: A systematic overview.

BACKGROUND: Pragmatic trials are increasingly recognized for providing real-world evidence on treatment choices. OBJECTIVE: The objective of this study is to investigate the use and characteristics of pragmatic trials in multiple sclerosis (MS). METHODS: Systematic literature search and analysis of pragmatic trials on any intervention published up to 2022. The assessment of pragmatism with PRECIS-2 (PRagmatic Explanatory Continuum Indicator Summary-2) is performed. RESULTS: We identified 48 pragmatic trials published 1967-2022 that included a median of 82 participants (interquartile range (IQR) = 42-160) to assess typically supportive care interventions (n = 41; 85%). Only seven trials assessed drugs (15%). Only three trials (6%) included >500 participants. Trials were mostly from the United Kingdom (n = 18; 38%), Italy (n = 6; 13%), the United States and Denmark (each n = 5; 10%). Primary outcomes were diverse, for example, quality-of-life, physical functioning, or disease activity. Only 1 trial (2%) used routinely collected data for outcome ascertainment. No trial was very pragmatic in all design aspects, but 14 trials (29%) were widely pragmatic (i.e. PRECIS-2 score ⩾ 4/5 in all domains). CONCLUSION: Only few and mostly small pragmatic trials exist in MS which rarely assess drugs. Despite the widely available routine data infrastructures, very few trials utilize them. There is an urgent need to leverage the potential of this pioneering study design to provide useful randomized real-world evidence.

U.S. Food and Drug Administration Reasoning in Approval Decisions When Efficacy Evidence Is Borderline, 2013-2018.

BACKGROUND: The U.S. Food and Drug Administration (FDA) has substantial flexibility in its approval criteria in the context of life-threatening disease and unmet therapeutic need. OBJECTIVE: To understand the FDA's evidentiary standards when flexible criteria are employed. DESIGN: Case series. SETTING: Applications submitted between 2013 and 2018 that went through multiple review cycles because the evidence for clinical efficacy was initially deemed insufficient. MEASUREMENTS: Information was obtained from the approval package (available on Drugs@FDA), including advisory committee minutes, FDA reviews, and complete response letters. RESULTS: Of 912 applications reviewed, 117 went through multiple review cycles; only 22 of these faced additional review primarily because of issues related to clinical efficacy. Concerns about the end point, the clinical meaningfulness of the observed effect, and inconsistent results were common bases for initial rejection. In 7 of the 22 cases, the approval did not require new evidence but rather new interpretations of the original evidence. No FDA decisions cited reasoning used in previous decisions. LIMITATION: The conclusions rely on the authors' interpretation of the FDA statements and on a series of "close calls." CONCLUSION: The FDA has no mechanism to find or tradition to cite similar cases when weighing evidence for approvals, resulting in standalone, bespoke decisions. These decisions show highly variable criteria for "substantial evidence" when flexible evidential criteria are used, highlighted by the recent approval of aducanumab. A precedential tradition and suitable information system are required for the FDA to improve institutional memory and build upon past decisions. These would increase the FDA's decisional transparency, consistency, and predictability, which are critical to preserving the FDA's most valuable asset, the public's trust. PRIMARY FUNDING SOURCE: U.S. Food and Drug Administration.

Validity of observational evidence on putative risk and protective factors: appraisal of 3744 meta-analyses on 57 topics.

BACKGROUND: The validity of observational studies and their meta-analyses is contested. Here, we aimed to appraise thousands of meta-analyses of observational studies using a pre-specified set of quantitative criteria that assess the significance, amount, consistency, and bias of the evidence. We also aimed to compare results from meta-analyses of observational studies against meta-analyses of randomized controlled trials (RCTs) and Mendelian randomization (MR) studies. METHODS: We retrieved from PubMed (last update, November 19, 2020) umbrella reviews including meta-analyses of observational studies assessing putative risk or protective factors, regardless of the nature of the exposure and health outcome. We extracted information on 7 quantitative criteria that reflect the level of statistical support, the amount of data, the consistency across different studies, and hints pointing to potential bias. These criteria were level of statistical significance (pre-categorized according to 10-6, 0.001, and 0.05 p-value thresholds), sample size, statistical significance for the largest study, 95% prediction intervals, between-study heterogeneity, and the results of tests for small study effects and for excess significance. RESULTS: 3744 associations (in 57 umbrella reviews) assessed by a median number of 7 (interquartile range 4 to 11) observational studies were eligible. Most associations were statistically significant at P < 0.05 (61.1%, 2289/3744). Only 2.6% of associations had P < 10-6, ≥1000 cases (or ≥20,000 participants for continuous factors), P < 0.05 in the largest study, 95% prediction interval excluding the null, and no large between-study heterogeneity, small study effects, or excess significance. Across the 57 topics, large heterogeneity was observed in the proportion of associations fulfilling various quantitative criteria. The quantitative criteria were mostly independent from one another. Across 62 associations assessed in both RCTs and in observational studies, 37.1% had effect estimates in opposite directions and 43.5% had effect estimates differing beyond chance in the two designs. Across 94 comparisons assessed in both MR and observational studies, such discrepancies occurred in 30.8% and 54.7%, respectively. CONCLUSIONS: Acknowledging that no gold-standard exists to judge whether an observational association is genuine, statistically significant results are common in observational studies, but they are rarely convincing or corroborated by randomized evidence.

Association between convalescent plasma treatment and mortality in COVID-19: a collaborative systematic review and meta-analysis of randomized clinical trials.

BACKGROUND: Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, https://doi.org/10.17605/OSF.IO/GEHFX ). METHODS: In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the Hartung-Knapp-Sidik-Jonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. RESULTS: A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. CONCLUSIONS: Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care.

Association of Convalescent Plasma Treatment With Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis.

Importance: Convalescent plasma is a proposed treatment for COVID-19. Objective: To assess clinical outcomes with convalescent plasma treatment vs placebo or standard of care in peer-reviewed and preprint publications or press releases of randomized clinical trials (RCTs). Data Sources: PubMed, the Cochrane COVID-19 trial registry, and the Living Overview of Evidence platform were searched until January 29, 2021. Study Selection: The RCTs selected compared any type of convalescent plasma vs placebo or standard of care for patients with confirmed or suspected COVID-19 in any treatment setting. Data Extraction and Synthesis: Two reviewers independently extracted data on relevant clinical outcomes, trial characteristics, and patient characteristics and used the Cochrane Risk of Bias Assessment Tool. The primary analysis included peer-reviewed publications of RCTs only, whereas the secondary analysis included all publicly available RCT data (peer-reviewed publications, preprints, and press releases). Inverse variance-weighted meta-analyses were conducted to summarize the treatment effects. The certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation. Main Outcomes and Measures: All-cause mortality, length of hospital stay, clinical improvement, clinical deterioration, mechanical ventilation use, and serious adverse events. Results: A total of 1060 patients from 4 peer-reviewed RCTs and 10 722 patients from 6 other publicly available RCTs were included. The summary risk ratio (RR) for all-cause mortality with convalescent plasma in the 4 peer-reviewed RCTs was 0.93 (95% CI, 0.63 to 1.38), the absolute risk difference was -1.21% (95% CI, -5.29% to 2.88%), and there was low certainty of the evidence due to imprecision. Across all 10 RCTs, the summary RR was 1.02 (95% CI, 0.92 to 1.12) and there was moderate certainty of the evidence due to inclusion of unpublished data. Among the peer-reviewed RCTs, the summary hazard ratio was 1.17 (95% CI, 0.07 to 20.34) for length of hospital stay, the summary RR was 0.76 (95% CI, 0.20 to 2.87) for mechanical ventilation use (the absolute risk difference for mechanical ventilation use was -2.56% [95% CI, -13.16% to 8.05%]), and there was low certainty of the evidence due to imprecision for both outcomes. Limited data on clinical improvement, clinical deterioration, and serious adverse events showed no significant differences. Conclusions and Relevance: Treatment with convalescent plasma compared with placebo or standard of care was not significantly associated with a decrease in all-cause mortality or with any benefit for other clinical outcomes. The certainty of the evidence was low to moderate for all-cause mortality and low for other outcomes.

The benefit-risk balance for biological agents in juvenile idiopathic arthritis: a meta-analysis of randomized clinical trials.

OBJECTIVE: To assess the net benefit of biological agents (BA) used in JIA. METHODS: We systematically searched databases up to March 2019 for randomized controlled trials (RCT) performed in JIA disease. Separate random-effects meta-analyses were conducted for efficacy (ACR paediatric score 30%, ACRpedi30) and serious adverse events for safety. In order to standardize the baseline risk, we performed a meta-analysis of baseline risk in the control group (for both efficacy and safety meta-analysis). The net benefit was determined as the risk difference of efficacy subtracted by the risk difference of safety. RESULTS: We included 19 trials: 11 parallel RCTs (754 patients) and 8 withdrawal RCTs (704 patients). The net benefit ranged from 2.4% (adalimumab) to 17.6% (etanercept), and from 2.4% (etanercept) to 36.7%, (abatacept) in parallel and withdrawal trials assessing non-systemic JIA, respectively. In the systemic JIA category, the net benefit ranged from 22.8% (rilonacept) to 70.3% (canakinumab), and from 32.3% (canakinumab) to 58.2% (tocilizumab) in parallel and withdrawal trials, respectively. CONCLUSION: The results suggest that a greater number of patients experienced therapeutic success without serious adverse events in the systemic onset JIA category compared with the BAs for non-systemic JIA categories. Baseline risk, design of trial and JIA categories impact the measure of net benefit of BAs in JIA patients.

Real-world evidence: How pragmatic are randomized controlled trials labeled as pragmatic?

INTRODUCTION: Pragmatic randomized controlled trials (RCTs) mimic usual clinical practice and they are critical to inform decision-making by patients, clinicians and policy-makers in real-world settings. Pragmatic RCTs assess effectiveness of available medicines, while explanatory RCTs assess efficacy of investigational medicines. Explanatory and pragmatic are the extremes of a continuum. This debate article seeks to evaluate and provide recommendation on how to characterize pragmatic RCTs in light of the current landscape of RCTs. It is supported by findings from a PubMed search conducted in August 2017, which retrieved 615 RCTs self-labeled in their titles as "pragmatic" or "naturalistic". We focused on 89 of these trials that assessed medicines (drugs or biologics). DISCUSSION: 36% of these 89 trials were placebo-controlled, performed before licensing of the medicine, or done in a single-center. In our opinion, such RCTs overtly deviate from usual care and pragmatism. It follows, that the use of the term 'pragmatic' to describe them, conveys a misleading message to patients and clinicians. Furthermore, many other trials among the 615 coined as 'pragmatic' and assessing other types of intervention are plausibly not very pragmatic; however, this is impossible for a reader to tell without access to the full protocol and insider knowledge of the trial conduct. The degree of pragmatism should be evaluated by the trial investigators themselves using the PRECIS-2 tool, a tool that comprises 9 domains, each scored from 1 (very explanatory) to 5 (very pragmatic). CONCLUSIONS: To allow for a more appropriate characterization of the degree of pragmatism in clinical research, submissions of RCTs to funders, research ethics committees and to peer-reviewed journals should include a PRECIS-2 tool assessment done by the trial investigators. Clarity and accuracy on the extent to which a RCT is pragmatic will help understand how much it is relevant to real-world practice.

Use of available clinical evidence to extrapolate drug effects from adults to children.

The extrapolation of the benefit risk ratio from adults to children is performed during drug development and often implicitly used by many paediatricians when prescribing off-label drugs in children. This is due to the specific constraints of paediatric clinical research leading to a lack of safety and efficacy data in children. Extrapolation frameworks for drug development have been proposed by several regulatory agencies. Using a meta-epidemiological approach, we explored the similarities and differences of the benefit, the benefit risk ratio and the perceived placebo effect between adults and children from meta-analyses including randomized double-blinded placebo-controlled trials evaluating a drug intervention in an indication in adults and children with separate data for both populations. We also explored the use of the effect model using adult data to predict the treatment effect in children and to calibrate future paediatric clinical trials. Our research highlights the importance of using all available evidence and quantitative methods before extrapolating the benefit risk ratio from adults to children and carrying out new studies in the context of the existing evidence. More generally, this should be applied to any research to avoid a waste of time and resources invested.

Is the perceived placebo effect comparable between adults and children? A meta-regression analysis.

BACKGROUND: A potential larger perceived placebo effect in children compared with adults could influence the detection of the treatment effect and the extrapolation of the treatment benefit from adults to children. This study aims to explore this potential difference, using a meta-epidemiological approach. METHODS: A systematic review of the literature was done to identify trials included in meta-analyses evaluating a drug intervention with separate data for adults and children. The standardized mean change and the proportion of responders (binary outcomes) were used to calculate the perceived placebo effect. A meta-regression analysis was conducted to test for the difference between adults and children of the perceived placebo effect. RESULTS: For binary outcomes, the perceived placebo effect was significantly more favorable in children compared with adults (ß = 0.13; P = 0.001). Parallel group trials (ß = -1.83; P < 0.001), subjective outcomes (ß = -0.76; P < 0.001), and the disease type significantly influenced the perceived placebo effect. CONCLUSION: The perceived placebo effect is different between adults and children for binary outcomes. This difference seems to be influenced by the design, the disease, and outcomes. Calibration of new studies for children should consider cautiously the placebo effect in children.

Trends in the number and the quality of trial protocols involving children submitted to a French Institutional Review Board.

BACKGROUND: There is a great need for high quality clinical research for children. The European Pediatric Regulation aimed to improve the quality of clinical trials in order to increase the availability of treatments for children. The main purpose of this study was to assess the evolution of both the number and the quality of pediatric trial protocols that were submitted to a French Institutional Review Board (IRB00009118) before and after the initiation of the EU Pediatric Regulation. METHODS: All protocols submitted to the IRB00009118 between 2003 and 2014 and conducting research on subjects under eighteen years of age were eligible. The quality of randomized clinical trials was assessed according to the guidelines developed by the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network and ranked using the Jadad score. RESULTS: Out of 622 protocols submitted to the Institutional Review Board (IRB), 21% (133/622) included children. Among these 133 pediatric protocols, the number of submitted pediatric protocols doubled between the two studied periods. From 2003 to 2008, 47 protocols including 21 institutionally sponsored were submitted to the IRB and from 2009 until 2014, 86 protocols including 48 institutionally sponsored were submitted. No significant trend was observed on the quality of RCTs. The overall median score of RCTs on the Jadad scale was high (3.5), 70.0% of protocols had a Jadad score ≥ 3, and 30.0% had a score < 3. CONCLUSION: Following the EU Pediatric Regulation, the number of pediatric protocols submitted to the IRB00009118 tends to increase, but no change was noticed regarding their quality.

Benchmarking Human-AI Collaboration for Common Evidence Appraisal Tools.

BACKGROUND: It is unknown whether large language models (LLMs) may facilitate time- and resource-intensive text-related processes in evidence appraisal. OBJECTIVES: To quantify the agreement of LLMs with human consensus in appraisal of scientific reporting (PRISMA) and methodological rigor (AMSTAR) of systematic reviews and design of clinical trials (PRECIS-2). To identify areas, where human-AI collaboration would outperform the traditional consensus process of human raters in efficiency. DESIGN: Five LLMs (Claude-3-Opus, Claude-2, GPT-4, GPT-3.5, Mixtral-8x22B) assessed 112 systematic reviews applying the PRISMA and AMSTAR criteria, and 56 randomized controlled trials applying PRECIS-2. We quantified agreement between human consensus and (1) individual human raters; (2) individual LLMs; (3) combined LLMs approach; (4) human-AI collaboration. Ratings were marked as deferred (undecided) in case of inconsistency between combined LLMs or between the human rater and the LLM. RESULTS: Individual human rater accuracy was 89% for PRISMA and AMSTAR, and 75% for PRECIS-2. Individual LLM accuracy was ranging from 63% (GPT-3.5) to 70% (Claude-3-Opus) for PRISMA, 53% (GPT-3.5) to 74% (Claude-3-Opus) for AMSTAR, and 38% (GPT-4) to 55% (GPT-3.5) for PRECIS-2. Combined LLM ratings led to accuracies of 75-88% for PRISMA (4-74% deferred), 74-89% for AMSTAR (6-84% deferred), and 64-79% for PRECIS-2 (29-88% deferred). Human-AI collaboration resulted in the best accuracies from 89-96% for PRISMA (25/35% deferred), 91-95% for AMSTAR (27/30% deferred), and 80-86% for PRECIS-2 (76/71% deferred). CONCLUSIONS: Current LLMs alone appraised evidence worse than humans. Human-AI collaboration may reduce workload for the second human rater for the assessment of reporting (PRISMA) and methodological rigor (AMSTAR) but not for complex tasks such as PRECIS-2.

Definitions of digital biomarkers: a systematic mapping of the biomedical literature.

BACKGROUND: Technological devices such as smartphones, wearables and virtual assistants enable health data collection, serving as digital alternatives to conventional biomarkers. We aimed to provide a systematic overview of emerging literature on 'digital biomarkers,' covering definitions, features and citations in biomedical research. METHODS: We analysed all articles in PubMed that used 'digital biomarker(s)' in title or abstract, considering any study involving humans and any review, editorial, perspective or opinion-based articles up to 8 March 2023. We systematically extracted characteristics of publications and research studies, and any definitions and features of 'digital biomarkers' mentioned. We described the most influential literature on digital biomarkers and their definitions using thematic categorisations of definitions considering the Food and Drug Administration Biomarkers, EndpointS and other Tools framework (ie, data type, data collection method, purpose of biomarker), analysing structural similarity of definitions by performing text and citation analyses. RESULTS: We identified 415 articles using 'digital biomarker' between 2014 and 2023 (median 2021). The majority (283 articles; 68%) were primary research. Notably, 287 articles (69%) did not provide a definition of digital biomarkers. Among the 128 articles with definitions, there were 127 different ones. Of these, 78 considered data collection, 56 data type, 50 purpose and 23 included all three components. Those 128 articles with a definition had a median of 6 citations, with the top 10 each presenting distinct definitions. CONCLUSIONS: The definitions of digital biomarkers vary significantly, indicating a lack of consensus in this emerging field. Our overview highlights key defining characteristics, which could guide the development of a more harmonised accepted definition.

[Registration of national health registry-based research]. / Registrering av forskning baserad på nationella hälsoregister.

In medical research as a whole, frequent inaccurate or biased findings are of international concern. One measure against reporting biases is study registration before the start of data collection (preregistration), preferably together with the statistical analysis plan. This meta-research study systematically evaluated registration of Swedish observational research based on national health registries. In a random sample of registry-based observational studies published 2010-2022, very few were preregistered with a publicly available analysis plan (<1 procent). Ideas from the meta-research literature can be leveraged to strengthen the brand of Swedish registry-based observational studies and counteract reporting bias.

Clinical trial evidence of quality-of-life effects of disease-modifying therapies for multiple sclerosis: a systematic analysis.

BACKGROUND: Increasingly, patients, clinicians, and regulators call for more evidence on the impact of innovative medicines on quality of life (QoL). We assessed the effects of disease-modifying therapies (DMTs) on QoL in people with multiple sclerosis (PwMS). METHODS: Randomized trials assessing approved DMTs in PwMS with results for at least one outcome referred to as "quality of life" were searched in PubMed and ClinicalTrials.gov. RESULTS: We identified 38 trials published between 1999 and 2023 with a median of 531 participants (interquartile range (IQR) 202 to 941; total 23,225). The evaluated DMTs were mostly interferon-beta (n = 10; 26%), fingolimod (n = 7; 18%), natalizumab (n = 5; 13%), and glatiramer acetate (n = 4; 11%). The 38 trials used 18 different QoL instruments, with up to 11 QoL subscale measures per trial (median 2; IQR 1-3). QoL was never the single primary outcome. We identified quantitative QoL results in 24 trials (63%), and narrative statements in 15 trials (39%). In 16 trials (42%), at least one of the multiple QoL results was statistically significant. The effect sizes of the significant quantitative QoL results were large (median Cohen's d 1.02; IQR 0.3-1.7; median Hedges' g 1.01; IQR 0.3-1.69) and ranged between d 0.14 and 2.91. CONCLUSIONS: Certain DMTs have the potential to positively impact QoL of PwMS, and the assessment and reporting of QoL is suboptimal with a multitude of diverse instruments being used. There is an urgent need that design and reporting of clinical trials reflect the critical importance of QoL for PwMS.

Characteristics, Progression, and Output of Randomized Platform Trials: A Systematic Review.

Importance: Platform trials have become increasingly common, and evidence is needed to determine how this trial design is actually applied in current research practice. Objective: To determine the characteristics, progression, and output of randomized platform trials. Evidence Review: In this systematic review of randomized platform trials, Medline, Embase, Scopus, trial registries, gray literature, and preprint servers were searched, and citation tracking was performed in July 2022. Investigators were contacted in February 2023 to confirm data accuracy and to provide updated information on the status of platform trial arms. Randomized platform trials were eligible if they explicitly planned to add or drop arms. Data were extracted in duplicate from protocols, publications, websites, and registry entries. For each platform trial, design features such as the use of a common control arm, use of nonconcurrent control data, statistical framework, adjustment for multiplicity, and use of additional adaptive design features were collected. Progression and output of each platform trial were determined by the recruitment status of individual arms, the number of arms added or dropped, and the availability of results for each intervention arm. Findings: The search identified 127 randomized platform trials with a total of 823 arms; most trials were conducted in the field of oncology (57 [44.9%]) and COVID-19 (45 [35.4%]). After a more than twofold increase in the initiation of new platform trials at the beginning of the COVID-19 pandemic, the number of platform trials has since declined. Platform trial features were often not reported (not reported: nonconcurrent control, 61 of 127 [48.0%]; multiplicity adjustment for arms, 98 of 127 [77.2%]; statistical framework, 37 of 127 [29.1%]). Adaptive design features were only used by half the studies (63 of 127 [49.6%]). Results were available for 65.2% of closed arms (230 of 353). Premature closure of platform trial arms due to recruitment problems was infrequent (5 of 353 [1.4%]). Conclusions and Relevance: This systematic review found that platform trials were initiated most frequently during the COVID-19 pandemic and declined thereafter. The reporting of platform features and the availability of results were insufficient. Premature arm closure for poor recruitment was rare.

MultiSCRIPT-Cycle 1-a pragmatic trial embedded within the Swiss Multiple Sclerosis Cohort (SMSC) on neurofilament light chain monitoring to inform personalized treatment decisions in multiple sclerosis: a study protocol for a randomized clinical trial.

BACKGROUND: Treatment decisions for persons with relapsing-remitting multiple sclerosis (RRMS) rely on clinical and radiological disease activity, the benefit-harm profile of drug therapy, and preferences of patients and physicians. However, there is limited evidence to support evidence-based personalized decision-making on how to adapt disease-modifying therapy treatments targeting no evidence of disease activity, while achieving better patient-relevant outcomes, fewer adverse events, and improved care. Serum neurofilament light chain (sNfL) is a sensitive measure of disease activity that captures and prognosticates disease worsening in RRMS. sNfL might therefore be instrumental for a patient-tailored treatment adaptation. We aim to assess whether 6-monthly sNfL monitoring in addition to usual care improves patient-relevant outcomes compared to usual care alone. METHODS: Pragmatic multicenter, 1:1 randomized, platform trial embedded in the Swiss Multiple Sclerosis Cohort (SMSC). All patients with RRMS in the SMSC for ≥ 1 year are eligible. We plan to include 915 patients with RRMS, randomly allocated to two groups with different care strategies, one of them new (group A) and one of them usual care (group B). In group A, 6-monthly monitoring of sNfL will together with information on relapses, disability, and magnetic resonance imaging (MRI) inform personalized treatment decisions (e.g., escalation or de-escalation) supported by pre-specified algorithms. In group B, patients will receive usual care with their usual 6- or 12-monthly visits. Two primary outcomes will be used: (1) evidence of disease activity (EDA3: occurrence of relapses, disability worsening, or MRI activity) and (2) quality of life (MQoL-54) using 24-month follow-up. The new treatment strategy with sNfL will be considered superior to usual care if either more patients have no EDA3, or their health-related quality of life increases. Data collection will be embedded within the SMSC using established trial-level quality procedures. DISCUSSION: MultiSCRIPT aims to be a platform where research and care are optimally combined to generate evidence to inform personalized decision-making in usual care. This approach aims to foster better personalized treatment and care strategies, at low cost and with rapid translation to clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT06095271. Registered on October 23, 2023.

Meta-research on pragmatism of randomized trials: rationale and design of the PragMeta database.

BACKGROUND: Pragmatic trials provide decision-oriented, real-world evidence that is highly applicable and generalizable. The interest in real-world evidence is fueled by the assumption that effects in the "real-world" are different to effects obtained under artificial, controlled, research conditions as often used for traditional explanatory trials. However, it is unknown which features of pragmatism, generalizability, and applicability would be responsible for such differences. There is a need to provide empirical evidence and promote meta-research to answer these fundamental questions on the pragmatism of randomized trials and real-world evidence. Here, we describe the rationale and design of the PragMeta database which pursues this goal ( www.PragMeta.org ). METHODS: PragMeta is a non-commercial, open data platform and infrastructure to facilitate research on pragmatic trials. It collects and shares data from published randomized trials that either have a specific design feature or other characteristic related to pragmatism or they form clusters of trials addressing the same research question but having different aspects of pragmatism. This lays the foundation to determine the relationship of various features of pragmatism, generalizability, and applicability with intervention effects or other trial characteristics. The database contains trial data actively collected for PragMeta but also allows to import and link existing datasets of trials collected for other purposes, forming a large-scale meta-database. PragMeta captures data on (1) trial and design characteristics (e.g., sample size, population, intervention/comparison, outcome, longitudinal structure, blinding), (2) effects estimates, and (3) various determinants of pragmatism (e.g., the use of routinely collected data) and ratings from established tools used to determine pragmatism (e.g., the PRagmatic-Explanatory Continuum Indicator Summary 2; PRECIS-2). PragMeta is continuously provided online, inviting the meta-research community to collaborate, contribute, and/or use the database. As of April 2023, PragMeta contains data from > 700 trials, mostly with assessments on pragmatism. CONCLUSIONS: PragMeta will inform a better understanding of pragmatism and the generation and interpretation of real-world evidence.

Robustness of reported postacute health outcomes in children with SARS-CoV-2 infection: a systematic review.

OBJECTIVE: To systematically assess the robustness of reported postacute SARS-CoV-2 infection health outcomes in children. METHODS: A search on PubMed and Web of Science was conducted to identify studies published up to 22 January 2022 that reported on postacute SARS-CoV-2 infection health outcomes in children (<18 years) with follow-up of ≥2 months since detection of infection or ≥1 month since recovery from acute illness. We assessed the consideration of confounding bias and causality, as well as the risk of bias. RESULTS: 21 studies including 81 896 children reported up to 97 symptoms with follow-up periods of 2.0-11.5 months. Fifteen studies had no control group. The reported proportion of children with post-COVID syndrome was between 0% and 66.5% in children with SARS-CoV-2 infection (n=16 986) and between 2.0% and 53.3% in children without SARS-CoV-2 infection (n=64 910). Only two studies made a clear causal interpretation of an association between SARS-CoV-2 infection and the main outcome of 'post-COVID syndrome' and provided recommendations regarding prevention measures. The robustness of all 21 studies was seriously limited due to an overall critical risk of bias. CONCLUSIONS: The robustness of reported postacute SARS-CoV-2 infection health outcomes in children is seriously limited, at least in all the published articles we could identify. None of the studies provided evidence with reasonable certainty on whether SARS-CoV-2 infection has an impact on postacute health outcomes, let alone to what extent. Children and their families urgently need much more reliable and methodologically robust evidence to address their concerns and improve care.

Effects of remdesivir in patients hospitalised with COVID-19: a systematic review and individual patient data meta-analysis of randomised controlled trials.

BACKGROUND: Interpretation of the evidence from randomised controlled trials (RCTs) of remdesivir in patients treated in hospital for COVID-19 is conflicting. We aimed to assess the benefits and harms of remdesivir compared with placebo or usual care in these patients, and whether treatment effects differed between prespecified patient subgroups. METHODS: For this systematic review and meta-analysis, we searched PubMed, Embase, the Cochrane COVID-19 trial registry, ClinicalTrials.gov, the International Clinical Trials Registry Platform, and preprint servers from Jan 1, 2020, until April 11, 2022, for RCTs of remdesivir in adult patients hospitalised with COVID-19, and contacted the authors of eligible trials to request individual patient data. The primary outcome was all-cause mortality at day 28 after randomisation. We used multivariable hierarchical regression-adjusting for respiratory support, age, and enrollment period-to investigate effect modifiers. This study was registered with PROSPERO, CRD42021257134. FINDINGS: Our search identified 857 records, yielding nine RCTs eligible for inclusion. Of these nine eligible RCTs, individual data were provided for eight, covering 10 480 patients hospitalised with COVID-19 (99% of such patients included in such RCTs worldwide) recruited between Feb 6, 2020, and April 1, 2021. Within 28 days of randomisation, 662 (12·5%) of 5317 patients assigned to remdesivir and 706 (14·1%) of 5005 patients assigned to no remdesivir died (adjusted odds ratio [aOR] 0·88, 95% CI 0·78-1·00, p=0·045). We found evidence for a credible subgroup effect according to respiratory support at baseline (pinteraction=0·019). Of patients who were ventilated-including those who received high-flow oxygen-253 (30·0%) of 844 patients assigned to remdesivir died compared with 241 (28·5%) of 846 patients assigned to no remdesivir (aOR 1·10 [0·88-1·38]; low-certainty evidence). Of patients who received no oxygen or low-flow oxygen, 409 (9·1%) of 4473 patients assigned to remdesivir died compared with 465 (11·2%) of 4159 patients assigned to no remdesivir (0·80 [0·70-0·93]; high-certainty evidence). No credible subgroup effect was found for time to start of remdesivir after symptom onset, age, presence of comorbidities, enrolment period, or corticosteroid use. Remdesivir did not increase the frequency of severe or serious adverse events. INTERPRETATION: This individual patient data meta-analysis showed that remdesivir reduced mortality in patients hospitalised with COVID-19 who required no or conventional oxygen support, but was underpowered to evaluate patients who were ventilated when receiving remdesivir. The effect size of remdesivir in patients with more respiratory support or acquired immunity and the cost-effectiveness of remdesivir remain to be further elucidated. FUNDING: EU-RESPONSE.