Characterization of accelerated approval status, trial endpoints and results, and recommendations in guidelines for oncology drug treatments from the National Comprehensive Cancer Network: cross sectional study.

Objectives: To evaluate National Comprehensive Cancer Network (NCCN) guideline recommendations for oncology drug treatments that have been granted accelerated approval, and to determine whether recommendations are updated based on the results of confirmatory trials after approval and based on status updates from the US Food and Drug Administration (FDA). Design: Cross sectional study. Setting: US FDA and NCCN guidelines. Population: Oncology therapeutic indications (ie, specific oncological conditions for which the drug is recommended) that have been granted accelerated approval in 2009-18. Main outcome measures: NCCN guideline reporting of accelerated approval status and postapproval confirmatory trials, and guideline recommendation alignment with postapproval confirmatory trial results and FDA status updates. Results: 39 oncology drug treatments were granted accelerated approval for 62 oncological indications. Although all indications were recommended in NCCN guidelines, accelerated approval status was reported for 10 (16%) indications. At least one postapproval confirmatory trial was identified for all 62 indications, 33 (53%) of which confirmed benefit; among these indications, NCCN guidelines maintained the previous recommendation or strengthened the category of evidence for 27 (82%). Postapproval confirmatory trials failed to confirm benefit for 12 (19%) indications; among these indications, NCCN guidelines removed the previous recommendation or weakened the category of evidence for five (42%). NCCN guidelines reflected the FDA's decision to convert 30 (83%) of 36 indications from accelerated to traditional approval, of which 20 (67%) had guideline updates before the FDA's conversion decision. NCCN guidelines reflected the FDA's decision to withdraw seven (58%) of 12 indications from the market, of which four (57%) had guidelines updates before the FDA's withdrawal decision. Conclusions: NCCN guidelines always recommend drug treatments that have been granted accelerated approval for oncological indications, but do not provide information about their accelerated approval status, including surrogate endpoint use and status of postapproval confirmatory trials. NCCN guidelines consistently provide information on postapproval trial results confirming clinical benefit, but not on postapproval trials failing to confirm clinical benefit. NCCN guidelines more frequently update recommendation for indications converted to traditional approval than for those approvals that were withdrawn.

Associations Between Surrogate Markers and Clinical Outcomes for Nononcologic Chronic Disease Treatments.

Importance: Surrogate markers are increasingly used as primary end points in clinical trials supporting drug approvals. Objective: To systematically summarize the evidence from meta-analyses, systematic reviews and meta-analyses, and pooled analyses (hereafter, meta-analyses) of clinical trials examining the strength of association between treatment effects measured using surrogate markers and clinical outcomes in nononcologic chronic diseases. Data sources: The Food and Drug Administration (FDA) Adult Surrogate Endpoint Table and MEDLINE from inception to March 19, 2023. Study Selection: Three reviewers selected meta-analyses of clinical trials; meta-analyses of observational studies were excluded. Data Extraction and Synthesis: Two reviewers extracted correlation coefficients, coefficients of determination, slopes, effect estimates, or results from meta-regression analyses between surrogate markers and clinical outcomes. Main Outcomes and Measures: Correlation coefficient or coefficient of determination, when reported, was classified as high strength (r ≥ 0.85 or R2 ≥ 0.72); primary findings were otherwise summarized. Results: Thirty-seven surrogate markers listed in FDA's table and used as primary end points in clinical trials across 32 unique nononcologic chronic diseases were included. For 22 (59%) surrogate markers (21 chronic diseases), no eligible meta-analysis was identified. For 15 (41%) surrogate markers (14 chronic diseases), at least 1 meta-analysis was identified, 54 in total (median per surrogate marker, 2.5; IQR, 1.3-6.0); among these, median number of trials and patients meta-analyzed was 18.5 (IQR, 12.0-43.0) and 90 056 (IQR, 20 109-170 014), respectively. The 54 meta-analyses reported 109 unique surrogate marker-clinical outcome pairs: 59 (54%) reported at least 1 r or R2, 10 (17%) of which reported at least 1 classified as high strength, whereas 50 (46%) reported slopes, effect estimates, or results of meta-regression analyses only, 26 (52%) of which reported at least 1 statistically significant result. Conclusions and Relevance: Most surrogate markers used as primary end points in clinical trials to support FDA approval of drugs treating nononcologic chronic diseases lacked high-strength evidence of associations with clinical outcomes from published meta-analyses.

Grilling the data: application of specification curve analysis to red meat and all-cause mortality.

OBJECTIVES: To present an application of specification curve analysis-a novel analytic method that involves defining and implementing all plausible and valid analytic approaches for addressing a research question-to nutritional epidemiology. STUDY DESIGN AND SETTING: We reviewed all observational studies addressing the effect of red meat on all-cause mortality, sourced from a published systematic review, and documented variations in analytic methods (eg, choice of model, covariates, etc.). We enumerated all defensible combinations of analytic choices to produce a comprehensive list of all the ways in which the data may reasonably be analyzed. We applied specification curve analysis to data from National Health and Nutrition Examination Survey 2007 to 2014 to investigate the effect of unprocessed red meat on all-cause mortality. The specification curve analysis used a random sample of all reasonable analytic specifications we sourced from primary studies. RESULTS: Among 15 publications reporting on 24 cohorts included in the systematic review on red meat and all-cause mortality, we identified 70 unique analytic methods, each including different analytic models, covariates, and operationalizations of red meat (eg, continuous vs quantiles). We applied specification curve analysis to National Health and Nutrition Examination Survey, including 10,661 participants. Our specification curve analysis included 1208 unique analytic specifications, of which 435 (36.0%) yielded a hazard ratio equal to or more than 1 for the effect of red meat on all-cause mortality and 773 (64.0%) less than 1. The specification curve analysis yielded a median hazard ratio of 0.94 (interquartile range: 0.83-1.05). Forty-eight specifications (3.97%) were statistically significant, 40 of which indicated unprocessed red meat to reduce all-cause mortality and eight of which indicated red meat to increase mortality. CONCLUSION: We show that the application of specification curve analysis to nutritional epidemiology is feasible and presents an innovative solution to analytic flexibility.

Autoimmune diseases and risk of non-Hodgkin lymphoma: A Mendelian randomisation study.

Objective: To examine whether genetically predicted susceptibility to ten autoimmune diseases (Behçet's disease, coeliac disease, dermatitis herpetiformis, lupus, psoriasis, rheumatoid arthritis, sarcoidosis, Sjögren's syndrome, systemic sclerosis, and type 1 diabetes) is associated with risk of non-Hodgkin lymphoma (NHL). Design: Two sample Mendelian randomization (MR) study. Setting: Genome wide association studies (GWASs) of ten autoimmune diseases, NHL, and four NHL subtypes (i.e., follicular lymphoma, mature T/natural killer-cell lymphomas, non-follicular lymphoma, and other and unspecified types of NHL). Analysis: We used data from the largest publicly available GWASs of European ancestry for each autoimmune disease, NHL, and NHL subtypes. For each autoimmune disease, we extracted single nucleotide polymorphisms (SNPs) strongly associated (P < 5×10-8) with that disease and that were independent of one another (R2 < 1×10-3) as genetic instruments. SNPs within the human leukocyte antigen region were not considered due to potential pleiotropy. Our primary MR analysis was the inverse-variance weighted analysis. Additionally, we conducted MR-Egger, weighted mode, and weighted median regression to address potential bias due to pleiotropy, and robust adjusted profile scores to address weak instrument bias. We carried out sensitivity analysis limited to the non-immune pathway for nominally significant findings. To account for multiple testing, we set the thresholds for statistical significance at P < 5×10-3. Participants: The number of cases and controls identified in the relevant GWASs were 437 and 3,325 for Behçet's disease, 4,918 and 5,684 for coeliac disease, 435 and 341,188 for dermatitis herpetiformis, 4,576 and 8,039 for lupus, 11,988 and 275,335 for psoriasis, 22,350 and 74,823 for rheumatoid arthritis, 3,597 and 337,121 for sarcoidosis, 2,735 and 332,115 for Sjögren's syndrome, 9,095 and 17,584 for systemic sclerosis, 18,942 and 501,638 for type 1 diabetes, 2,400 and 410,350 for NHL; and 296 to 2,340 cases and 271,463 controls for NHL subtypes. Exposures: Genetic variants predicting ten autoimmune diseases: Behçet's disease, coeliac disease, dermatitis herpetiformis, lupus, psoriasis, rheumatoid arthritis, sarcoidosis, Sjögren's syndrome, systemic sclerosis, and type 1 diabetes. Main outcome measures: Estimated associations between genetically predicted susceptibility to ten autoimmune diseases and the risk of NHL. Results: The variance of each autoimmune disease explained by the SNPs ranged from 0.3% to 3.1%. Negative associations between type 1 diabetes and sarcoidosis and the risk of NHL were observed (odds ratio [OR] 0.95, 95% confidence interval [CI]: 0.92 to 0.98, P = 5×10-3, and OR 0.92, 95% CI: 0.85 to 0.99, P = 2.8×10-2, respectively). These findings were supported by the sensitivity analyses accounting for potential pleiotropy and weak instrument bias. No significant associations were found between the other eight autoimmune diseases and NHL risk. Of the NHL subtypes, type 1 diabetes was most strongly associated with follicular lymphoma (OR 0.91, 95% CI: 0.86 to 0.96, P = 1×10-3), while sarcoidosis was most strongly associated with other and unspecified NHL (OR 0.86, 95% CI: 0.75 to 0.97, P = 1.8×10-2). Conclusions: These findings suggest that genetically predicted susceptibility to type 1 diabetes, and to some extent sarcoidosis, might reduce the risk of NHL. However, future studies with different datasets, approaches, and populations are warranted to further examine the potential associations between these autoimmune diseases and the risk of NHL.

Systematic review and meta-analysis of the genetics of peripheral arterial disease.

Background: Peripheral artery disease (PAD) impacts more than 200 million people worldwide. The understanding of the genetics of the disease and its clinical implications continue to evolve. This systematic review provides a comprehensive summary of all DNA variants that have been studied in association with the diagnosis and progression of PAD, with a meta-analysis of the ones replicated in the literature. Methods: A systematic review of all studies examining DNA variants associated with the diagnosis and progression of PAD was performed. Candidate gene and genome-wide association studies (GWAS) were included. A meta-analysis of 13 variants derived from earlier smaller candidate gene studies of the diagnosis of PAD was performed. The literature on the progression of PAD was limited, and a meta-analysis was not feasible because of the heterogeneity in the criteria used to characterize it. Results: A total of 231 DNA variants in 112 papers were studied for the association with the diagnosis of PAD. There were significant variations in the definition of PAD and the selection of controls in the various studies. GWAS have established 19 variants associated with the diagnosis of PAD that were replicated in several large patient cohorts. Only variants in intercellular adhesion molecule-1 (rs5498), IL-6 (rs1800795), and hepatic lipase (rs2070895) showed significant association with the diagnosis of PAD. However, these variants were not noted in the published GWAS. Conclusions: Genetic research in the diagnosis of PAD has significant heterogeneity, but recent GWAS have demonstrated variants consistently associated with the disease. More research focusing on the progression of PAD is needed to identify patients at risk of adverse events and develop strategies that would improve their outcomes.

Published research on the human health implications of climate change between 2012 and 2021: cross sectional study.

Objective: To better understand the state of research on the effects of climate change on human health, including exposures, health conditions, populations, areas of the world studied, funding sources, and publication characteristics, with a focus on topics that are relevant for populations at risk. Design: Cross sectional study. Data sources: The National Institute of Environmental Health Sciences climate change and human health literature portal, a curated bibliographical database of global peer reviewed research and grey literature was searched. The database combines searches of multiple search engines including PubMed, Web of Science, and Google Scholar, and includes added-value expert tagging of climate change exposures and health impacts. Eligibility criteria: Inclusion criteria were peer reviewed, original research articles that investigated the health effects of climate change and were published in English from 2012 to 2021. After identification, a 10% random sample was selected to manually perform a detailed characterisation of research topics and publication information. Results: 10 325 original research articles were published between 2012 and 2021, and the number of articles increased by 23% annually. In a random sample of 1014 articles, several gaps were found in research topics that are particularly relevant to populations at risk, such as those in the global south (134 countries established through the United Nations Office for South-South Cooperation) (n=444; 43.8%), adults aged 65 years or older (n=195; 19.2%), and on topics related to human conflict and migration (n=25; 2.5%) and food and water quality and security (n=148; 14.6%). Additionally, fewer first authors were from the global south (n=349; 34.4%), which may partly explain why research focusing on these countries is disproportionally less. Conclusions: Although the body of research on the health effects of climate change has grown substantially over the past decade, including those with a focus on the global south, a disproportionate focus continues to be on countries in the global north and less at risk populations. Governments are the largest source of funding for such research, and governments, particularly in the global north, need to re-orient their climate and health research funding to support researchers in the global south and to be more inclusive of issues that are relevant to the global south.

Evidence of subgroup differences in meta-analyses evaluating medications for alcohol use disorder: An umbrella review.

Randomized controlled trials (RCTs) evaluating medications for alcohol use disorder (AUD) often examine heterogeneity of treatment effects through subgroup analyses that contrast effect estimates in groups of patients across individual demographic, clinical, and study design-related characteristics. However, these analyses are often not prespecified or adequately powered, highlighting the potential role of subgroup analyses in meta-analysis. Here, we conducted an umbrella review (i.e., a systematic review of meta-analyses) to determine the range and characteristics of reported subgroup analyses in meta-analyses of AUD medications. We searched PubMed to identify meta-analyses of RCTs evaluating medications for the management of AUD, alcohol abuse, or alcohol dependence in adults. We sought studies that measured drinking-related outcomes; quality of life, function, and rates of mortality; adverse events; and dropout. We considered meta-analyses that reported the results from formal subgroup analyses (comparing the summary effects across subgroup levels); summary effect estimates stratified across subgroup levels; and meta-regression, regression, or correlation-based subgroup analyses. We analyzed nine meta-analyses that included 61 formal subgroup analyses (median = 6 per meta-analysis), of which 33 (54%) were based on baseline participant-level and 28 (46%) were based on trial-level characteristics. Of the 58 subgroup analyses with either a p-value from a subgroup test or a statement by the authors that the subgroup analyses were not statistically significant, eight (14%) were statistically significant at the p < 0.05 level. Twelve meta-analyses reported the results of 102 meta-regression analyses, of which 25 (25%) identified statistically significant predictors of the relevant outcome of interest; nine (9%) were based on baseline participant-level and 93 (91%) were based on trial characteristics. Subgroup analyses across meta-analyses of AUD medications often focus on study-level characteristics, which may not be as clinically informative as subgroup analyses based on participant-level characteristics. Opportunities exist for future meta-analyses to standardize their subgroup methodology, focus on more clinically informative participant-level characteristics, and use predictive approaches to account for multiple relevant variables.

Pivotal Trial Demographic Representation and Clinical Development Times for Oncology Therapeutics.

This study evaluates whether FDA-approved novel cancer therapeutics supported by pivotal trials with adequate representation of minoritized groups were associated with slower clinical development times than those with inadequate representation.

Association of health benefits and harms of Christmas dessert ingredients in recipes from The Great British Bake Off: umbrella review of umbrella reviews of meta-analyses of observational studies.

OBJECTIVE: To determine the health benefits and harms of various ingredients in Christmas desserts from The Great British Bake Off. DESIGN: Umbrella review of umbrella reviews of meta-analyses of observational studies. DATA SOURCES: The Great British Bake Off website, Embase, Medline, and Scopus. INCLUSION CRITERIA: Umbrella reviews of meta-analyses of observational studies evaluating the associations between Christmas dessert ingredients and the risk of death or disease. MAIN OUTCOME MEASURES: Proportion of protective and harmful summary associations between ingredient groups from The Great British Bake Off Christmas dessert recipes and the risk of death or disease. RESULTS: 48 recipes for Christmas desserts (ie, cakes, biscuits, pastries, and puddings and desserts) were provided on The Great British Bake Off website with 178 unique ingredients that were collapsed into 17 overarching ingredient groups. A literature search identified 7008 titles and abstracts, of which 46 eligible umbrella reviews reported 363 unique summary associations between the ingredient groups and risk of death or disease. Of these summary associations, 149 (41%) were significant, including 110 (74%) that estimated that the ingredient groups reduced the risk of death or disease and 39 (26%) that increased the risk. The most common ingredient groups associated with a reduced risk of death or disease were fruit (44/110, 40%), coffee (17/110, 16%), and nuts (14/110, 13%), whereas alcohol (20/39, 51%) and sugar (5/39, 13%) were the most common ingredient groups associated with increased risk of death or disease. CONCLUSIONS: Recipes for Christmas desserts from The Great British Bake Off often use ingredient groups that are associated with reductions, rather than increases, in the risk of death or disease. This Christmas, if concerns about the limitations of observational nutrition research are set aside, you can have your cake and eat it too.

Feasibility of Emulating Clinical Trials Supporting US FDA Supplemental Indication Approvals of Drugs and Biologics.

This cross-sectional study evaluates the supporting clinical trials for supplemental new drug applications and supplemental biologics license applications from 2017 to 2019.

Assessing the use of observational methods and real-world data to emulate ongoing randomized controlled trials.

BACKGROUND/AIMS: There has been growing interest in better understanding the potential of observational research methods in medical product evaluation and regulatory decision-making. Previously, we used linked claims and electronic health record data to emulate two ongoing randomized controlled trials, characterizing the populations and results of each randomized controlled trial prior to publication of its results. Here, our objective was to compare the populations and results from the emulated trials with those of the now-published randomized controlled trials. METHODS: This study compared participants' demographic and clinical characteristics and study results between the emulated trials, which used structured data from OptumLabs Data Warehouse, and the published PRONOUNCE and GRADE trials. First, we examined the feasibility of implementing the baseline participant characteristics included in the published PRONOUNCE and GRADE trials' using real-world data and classified each variable as ascertainable, partially ascertainable, or not ascertainable. Second, we compared the emulated trials and published randomized controlled trials for baseline patient characteristics (concordance determined using standardized mean differences <0.20) and results of the primary and secondary endpoints (concordance determined by direction of effect estimates and statistical significance). RESULTS: The PRONOUNCE trial enrolled 544 participants, and the emulated trial included 2226 propensity score-matched participants. In the PRONOUNCE trial publication, one of the 32 baseline participant characteristics was listed as an exclusion criterion on ClinicalTrials.gov but was ultimately not used. Among the remaining 31 characteristics, 9 (29.0%) were ascertainable, 11 (35.5%) were partially ascertainable, and 10 (32.2%) were not ascertainable using structured data from OptumLabs. For one additional variable, the PRONOUNCE trial did not provide sufficient detail to allow its ascertainment. Of the nine variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 6 (66.7%). The primary endpoint of time from randomization to the first major adverse cardiovascular event and secondary endpoints of nonfatal myocardial infarction and stroke were concordant between the emulated trial and published randomized controlled trial. The GRADE trial enrolled 5047 participants, and the emulated trial included 7540 participants. In the GRADE trial publication, 8 of 34 (23.5%) baseline participant characteristics were ascertainable, 14 (41.2%) were partially ascertainable, and 11 (32.4%) were not ascertainable using structured data from OptumLabs. For one variable, the GRADE trial did not provide sufficient detail to allow for ascertainment. Of the eight variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 4 (50.0%). The primary endpoint of time to hemoglobin A1c ≥7.0% was mostly concordant between the emulated trial and the published randomized controlled trial. CONCLUSION: Despite challenges, observational methods and real-world data can be leveraged in certain important situations for a more timely evaluation of drug effectiveness and safety in more diverse and representative patient populations.

Comparative effectiveness of second line glucose lowering drug treatments using real world data: emulation of a target trial.

Objective: To build on the recently completed GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) randomised trial examining the comparative effectiveness of second line glucose lowering drugs in achieving and maintaining glycaemic control in adults with type 2 diabetes. Design: Emulation of a target trial. Setting: Medical and pharmacy claims data from the OptumLabs Data Warehouse, a de-identified US national dataset of beneficiaries of commercially insured and Medicare Advantage plans, 29 March 2013 to 30 June 2021. Participants: Adults (≥18 years) with type 2 diabetes who first started taking glimepiride, sitagliptin, liraglutide, insulin glargine, or canagliflozin between 29 March 2013 and 30 June 2021. Participants were treatment naive or were receiving metformin monotherapy at the time of starting the study drug. Main outcome measures: The main outcomes were time to primary and secondary metabolic failure of the assigned treatment, calculated as days to haemoglobin A1c levels of ≥7.0% and >7.5%, respectively. Secondary metabolic, cardiovascular, and microvascular outcomes were analysed as specified in the GRADE statistical analysis plan. Propensity scores were estimated with the gradient boosting method, and inverse propensity score weighting was used to emulate randomisation to the treatment groups, which were then compared with Cox proportional hazards regression. Results: The study cohort included participants starting treatment with glimepiride (n=20 511), liraglutide (n=5569), sitagliptin (n=13 039), insulin glargine (n=7262), and canagliflozin (n=5290). The insulin glargine arm was excluded because of insufficient control of confounding. Median times to primary metabolic failure were 439 (95% confidence interval 400 to 489) days in the canagliflozin arm, 439 (426 to 453) days in the glimepiride arm, 624 (567 to 731) days in the liraglutide arm, and 461 (442 to 482) days in the sitagliptin arm. Median time to secondary metabolic failure was also longest in the liraglutide arm. Adults receiving liraglutide had the lowest one year cumulative incidence rate of primary metabolic failure (0.37, 95% confidence interval 0.35 to 0.40) followed by sitagliptin (0.44, 0.43 to 0.45), glimepiride (0.45, 0.44 to 0.45), and canagliflozin (0.46, 0.44 to 0.48). Similarly, the one year cumulative incidence rate of secondary metabolic failure was 0.27 (0.25 to 0.29) in the canagliflozin arm, 0.28 (0.27 to 0.29) in the glimepiride arm, 0.23 (0.21 to 0.26) in the liraglutide arm, and 0.28 (0.27 to 0.29) in the sitagliptin arm. No differences were observed between the study arms in the rates of microvascular and macrovascular complications. Conclusions: In this target trial emulation of an expanded GRADE study framework, liraglutide was more effective in achieving and maintaining glycaemic control as a second line glucose lowering drug than canagliflozin, sitagliptin, or glimepiride.

Use of Expedited Regulatory Programs and Clinical Development Times for FDA-Approved Novel Therapeutics.

This cross-sectional study evaluates the duration between application to US Food and Drug Administration (FDA) and approval for new drugs and biologics in the US from 2015 to 2022.

Consistency between trials presented at conferences, their subsequent publications and press releases.

OBJECTIVE: This study examined the extent to which trials presented at major international medical conferences in 2016 consistently reported their study design, end points and results across conference abstracts, published article abstracts and press releases. DESIGN: Cross-sectional analysis of clinical trials presented at 12 major medical conferences in the USA in 2016. Conferences were identified from a list of the largest clinical research meetings aggregated by the Healthcare Convention and Exhibitors Association and were included if their abstracts were publicly available. From these conferences, all late-breaker clinical trials were included, as well as a random selection of all other clinical trials, such that the total sample included up to 25 trial abstracts per conference. MAIN OUTCOME MEASURES: First, it was determined if trials were registered and reported results in an International Committee of Medical Journal Editors-approved clinical trial registry. Second, it was determined if trial results were published in a peer-reviewed journal. Finally, information on trial media coverage and press releases was collected using LexisNexis. For all published trials, the consistency of reporting of the following characteristics was examined, through comparison of the trials' conference and publication abstracts: primary efficacy endpoint definition, safety endpoint identification, sample size, follow-up period, primary end point effect size and characterisation of trial results. For all published abstracts with press releases, the characterisation of trial results across conference abstracts, press releases and publications was compared. Authors determined consistency of reporting when identical information was presented across abstracts and press releases. Primary analyses were descriptive; secondary analyses included χ2 tests and multiple logistic regression. RESULTS: Among 240 clinical trials presented at 12 major medical conferences, 208 (86.7%) were registered, 95 (39.6%) reported summary results in a registry and 177 (73.8%) were published; 82 (34.2%) were covered by the media and 68 (28.3%) had press releases. Among the 177 published trials, 171 (96.6%) reported the definition of primary efficacy endpoints consistently across conference and publication abstracts, whereas 96/128 (75.0%) consistently identified safety endpoints. There were 107/172 (62.2%) trials with consistent sample sizes across conference and publication abstracts, 101/137 (73.7%) that reported their follow-up periods consistently, 92/175 (52.6%) that described their effect sizes consistently and 157/175 (89.7%) that characterised their results consistently. Among the trials that were published and had press releases, 32/32 (100%) characterised their results consistently across conference abstracts, press releases and publication abstracts. No trial characteristics were associated with reporting primary efficacy end points consistently. CONCLUSIONS: For clinical trials presented at major medical conferences, primary efficacy endpoint definitions were consistently reported and results were consistently characterised across conference abstracts, registry entries and publication abstracts; consistency rates were lower for sample sizes, follow-up periods, and effect size estimates. REGISTRATION: This study was registered at the Open Science Framework (https://doi.org/10.17605/OSF.IO/VGXZY).

Comparison of Clinical Study Results Reported in medRxiv Preprints vs Peer-reviewed Journal Articles.

Importance: Preprints have been widely adopted to enhance the timely dissemination of research across many scientific fields. Concerns remain that early, public access to preliminary medical research has the potential to propagate misleading or faulty research that has been conducted or interpreted in error. Objective: To evaluate the concordance among study characteristics, results, and interpretations described in preprints of clinical studies posted to medRxiv that are subsequently published in peer-reviewed journals (preprint-journal article pairs). Design, Setting, and Participants: This cross-sectional study assessed all preprints describing clinical studies that were initially posted to medRxiv in September 2020 and subsequently published in a peer-reviewed journal as of September 15, 2022. Main Outcomes and Measures: For preprint-journal article pairs describing clinical trials, observational studies, and meta-analyses that measured health-related outcomes, the sample size, primary end points, corresponding results, and overarching conclusions were abstracted and compared. Sample size and results from primary end points were considered concordant if they had exact numerical equivalence. Results: Among 1399 preprints first posted on medRxiv in September 2020, a total of 1077 (77.0%) had been published as of September 15, 2022, a median of 6 months (IQR, 3-8 months) after preprint posting. Of the 547 preprint-journal article pairs describing clinical trials, observational studies, or meta-analyses, 293 (53.6%) were related to COVID-19. Of the 535 pairs reporting sample sizes in both sources, 462 (86.4%) were concordant; 43 (58.9%) of the 73 pairs with discordant sample sizes had larger samples in the journal publication. There were 534 pairs (97.6%) with concordant and 13 pairs (2.4%) with discordant primary end points. Of the 535 pairs with numerical results for the primary end points, 434 (81.1%) had concordant primary end point results; 66 of the 101 discordant pairs (65.3%) had effect estimates that were in the same direction and were statistically consistent. Overall, 526 pairs (96.2%) had concordant study interpretations, including 82 of the 101 pairs (81.2%) with discordant primary end point results. Conclusions and Relevance: Most clinical studies posted as preprints on medRxiv and subsequently published in peer-reviewed journals had concordant study characteristics, results, and final interpretations. With more than three-fourths of preprints published in journals within 24 months, these results may suggest that many preprints report findings that are consistent with the final peer-reviewed publications.

Characteristics of Retracted Research Articles About COVID-19 vs Other Topics.

This cross-sectional study compares the author and journal characteristics of retracted articles on COVID-19 with retracted articles from other topics.

Emulating the GRADE trial using real world data: retrospective comparative effectiveness study.

OBJECTIVE: To emulate the GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) trial using real world data before its publication. GRADE directly compared second line glucose lowering drugs for their ability to lower glycated hemoglobin A1c (HbA1c). DESIGN: Observational study. SETTING: OptumLabs® Data Warehouse (OLDW), a nationwide claims database in the US, 25 January 2010 to 30 June 2019. PARTICIPANTS: Adults with type 2 diabetes and HbA1c 6.8-8.5% while using metformin monotherapy, identified according to the GRADE trial specifications, who also used glimepiride, liraglutide, sitagliptin, or insulin glargine. MAIN OUTCOME MEASURES: The primary outcome was time to HbA1c ≥7.0%. Secondary outcomes were time to HbA1c >7.5%, incident microvascular complications, incident macrovascular complications, adverse events, all cause hospital admissions, and all cause mortality. Propensity scores were estimated using the gradient boosting machine method, and inverse propensity score weighting was used to emulate randomization of the treatment groups, which were then compared using Cox proportional hazards regression. RESULTS: 8252 people were identified (19.7% of adults starting the study drugs in OLDW) who met eligibility criteria for the GRADE trial (glimepiride arm=4318, liraglutide arm=690, sitagliptin arm=2993, glargine arm=251). The glargine arm was excluded from analyses owing to small sample size. Median times to HbA1c ≥7.0% were 442 days (95% confidence interval 394 to 480 days) for glimepiride, 764 (741 to not calculable) days for liraglutide, and 427 (380 to 483) days for sitagliptin. Liraglutide was associated with lower risk of reaching HbA1c ≥7.0% compared with glimepiride (hazard ratio 0.57, 95% confidence interval 0.43 to 0.75) and sitagliptin (0.55, 0.41 to 0.73). Results were consistent for the secondary outcome of time to HbA1c >7.5%. No significant differences were observed among treatment groups for the remaining secondary outcomes. CONCLUSIONS: In this emulation of the GRADE trial, liraglutide was statistically significantly more effective at maintaining glycemic control than glimepiride or sitagliptin when added to metformin monotherapy. Generating timely evidence on medical treatments using real world data as a complement to prospective trials is of value.

Characterization and corroboration of safety signals identified from the US Food and Drug Administration Adverse Event Reporting System, 2008-19: cross sectional study.

OBJECTIVE: To characterize potential drug safety signals identified from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS), from 2008 to 2019, to determine how often these signals resulted in regulatory action by the FDA and whether these actions were corroborated by published research findings or public assessments by the Sentinel Initiative. DESIGN: Cross sectional study. SETTING: USA. POPULATION: Safety signals identified from the FAERS and publicly reported by the FDA between 2008 and 2019; and review of the relevant literature published before and after safety signals were reported in 2014-15. Literature searches were performed in November 2019, Sentinel Initiative assessments were searched in December 2021, and data analysis was finalized in December 2021. MAIN OUTCOME MEASURES: Safety signals and resulting regulatory actions; number and characteristics of published studies, including corroboration of regulatory action as evidenced by significant associations (or no associations) between the drug related to the signal and the adverse event. RESULTS: From 2008 to 2019, 603 potential safety signals identified from the FAERS were reported by the FDA (median 48 annually, interquartile range 41-61), of which 413 (68.5%) were resolved as of December 2021 (372 of 399 (93.2%) signals ≥3 years old were resolved). Among the resolved safety signals, 91 (22.0%) led to no regulatory action and 322 (78.0%) resulted in regulatory action, including 319 (77.2%) changes to drug labeling and 59 (14.3%) drug safety communications or other public communications from the FDA. For a subset of 82 potential safety signals reported in 2014-15, a literature search identified 1712 relevant publications; 1201 (70.2%) were case reports or case series. Among these 82 safety signals, 76 (92.7%) were resolved, of which relevant published research was identified for 57 (75.0%) signals and relevant Sentinel Initiative assessments for four (5.3%) signals. Regulatory actions by the FDA were corroborated by at least one relevant published research study for 17 of the 57 (29.8%) resolved safety signals; none of the relevant Sentinel Initiative assessments corroborated FDA regulatory action. CONCLUSIONS: Most potential safety signals identified from the FAERS led to regulatory action by the FDA. Only a third of regulatory actions were corroborated by published research, however, and none by public assessments from the Sentinel Initiative. These findings suggest that either the FDA is taking regulatory actions based on evidence not made publicly available or more comprehensive safety evaluations might be needed when potential safety signals are identified.