Adverse Event Reporting Quality in Cancer Clinical Trials Evaluating Immune Checkpoint Inhibitor Therapy: A Systematic Review release_2uadhsxkunaprcvmztqbdu5nt4

Abstract

BackgroundImmunotherapy has become one of the most important breakthroughs in cancer treatment. Consequently, there have been more immuno-oncology (IO) clinical trials for various cancers in recent decades. However, the quality of such trials in reporting adverse events (AE), especially immune-related AE (irAE), has not been comprehensively evaluated.MethodsWe evaluated the harm reporting quality of IO trials. The PubMed, Embase, Cochrane Library, and Web of Science databases were searched to identify all head-to-head phase II and III clinical trials assessing cancer immunotherapy published between January 1, 2010, and December 31, 2021. Publications were assessed using a 16-point harm reporting quality score (HRQS) derived from the 2004 Consolidated Standards of Reporting Trials (CONSORT) extension. The characteristics associated with improved reporting quality were identified with linear regression.ResultsA total of 123 publications were included. The mean HRQS was 11.1 (range, 5-14). The most common poorly reported items were harms addressed in the title (2%), AE collection methodology (3%), the statistical approach for analyzing harms (11%), and the irAE onset patterns and management (adequately reported in 14% and 33% of publications, respectively). The harm information was well described in the publications' Results and Discussion sections (89-99%). The multivariable regression model revealed that higher impact factor (IF) (30<IF<60 vs. IF<30, P=0.021) and phase III clinical trial (phase III vs. phase II, P=0.023) were independent predictors of higher quality score.ConclusionOur findings show that AE reporting in IO randomized trials is suboptimal. Efforts should be made to improve harm reporting and to standardize reporting practices. Improvements in AE reporting would permit more balanced assessment of interventions and would enhance evidence-based IO practice.
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