Richeek Pradhan1, Sonal Singh2. 1. Department of Quantitative Health Sciences, University of Massachusetts Medical School, 55 Lake Ave North, Worcester, MA, 01655-0002, USA. 2. Department of Family Medicine and Community Health, Meyers Primary Care Institute, University of Massachusetts Medical School, 55 Lake Ave North, Worcester, MA, 01655-0002, USA. Sonal.Singh@umassmemorial.org.
Abstract
INTRODUCTION: Inconsistencies in data on serious adverse events (SAEs) and mortality in ClinicalTrials.gov and corresponding journal articles pose a challenge to research transparency. OBJECTIVE: The objective of this study was to compare data on SAEs and mortality from clinical trials reported in ClinicalTrials.gov and corresponding journal articles with US Food and Drug Administration (FDA) medical reviews. METHODS: We conducted a cross-sectional study of a randomly selected sample of new molecular entities approved during the study period 1 January 2013 to 31 December 2015. We extracted data on SAEs and mortality from 15 pivotal trials from ClinicalTrials.gov and corresponding journal articles (the two index resources), and FDA medical reviews (reference standard). We estimated the magnitude of deviations in rates of SAEs and mortality between the index resources and the reference standard. RESULTS: We found deviations in rates of SAEs (30% in ClinicalTrials.gov and 30% in corresponding journal articles) and mortality (72% in ClinicalTrials.gov and 53% in corresponding journal articles) when compared with the reference standard. The intra-class correlation coefficient between the three resources was 0.99 (95% confidence interval [CI] 0.98-0.99) for SAE rates and 0.99 (95% CI 0.97-0.99) for mortality rates. CONCLUSION: There are differences in data on rates of SAEs and mortality in randomized clinical trials in both ClinicalTrials.gov and journal articles compared with FDA reviews. Further efforts should focus on decreasing existing discrepancies to enhance the transparency and reproducibility of data reporting in clinical trials.
INTRODUCTION: Inconsistencies in data on serious adverse events (SAEs) and mortality in ClinicalTrials.gov and corresponding journal articles pose a challenge to research transparency. OBJECTIVE: The objective of this study was to compare data on SAEs and mortality from clinical trials reported in ClinicalTrials.gov and corresponding journal articles with US Food and Drug Administration (FDA) medical reviews. METHODS: We conducted a cross-sectional study of a randomly selected sample of new molecular entities approved during the study period 1 January 2013 to 31 December 2015. We extracted data on SAEs and mortality from 15 pivotal trials from ClinicalTrials.gov and corresponding journal articles (the two index resources), and FDA medical reviews (reference standard). We estimated the magnitude of deviations in rates of SAEs and mortality between the index resources and the reference standard. RESULTS: We found deviations in rates of SAEs (30% in ClinicalTrials.gov and 30% in corresponding journal articles) and mortality (72% in ClinicalTrials.gov and 53% in corresponding journal articles) when compared with the reference standard. The intra-class correlation coefficient between the three resources was 0.99 (95% confidence interval [CI] 0.98-0.99) for SAE rates and 0.99 (95% CI 0.97-0.99) for mortality rates. CONCLUSION: There are differences in data on rates of SAEs and mortality in randomized clinical trials in both ClinicalTrials.gov and journal articles compared with FDA reviews. Further efforts should focus on decreasing existing discrepancies to enhance the transparency and reproducibility of data reporting in clinical trials.
Authors: Daniel M Hartung; Deborah A Zarin; Jeanne-Marie Guise; Marian McDonagh; Robin Paynter; Mark Helfand Journal: Ann Intern Med Date: 2014-04-01 Impact factor: 25.391
Authors: Krista Y Chen; Erin M Borglund; Emma Charlotte Postema; Adam G Dunn; Florence T Bourgeois Journal: Clin Trials Date: 2022-04-28 Impact factor: 2.599
Authors: Richeek Pradhan; David C Hoaglin; Matthew Cornell; Weisong Liu; Victoria Wang; Hong Yu Journal: J Clin Epidemiol Date: 2018-09-23 Impact factor: 6.437