Dataset Information

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

ABSTRACT:

Background

Immunotherapy 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.

Methods

We 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.

Results

A 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) (30ConclusionOur 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.

SUBMITTER: Wang Y

PROVIDER: S-EPMC9301013 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

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

Wang Yuhong Y Chen Chen C Du Wei W Zhou Yixin Y He Lina L Hong Shaodong S Zhang Li L

Frontiers in immunology 20220707

<h4>Background</h4>Immunotherapy 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.<h4>Methods</h4>We evaluated the harm reporting quality of IO trials. The PubMed, Embase, Cochrane Library, and Web of Science databases w ...[more]

PMID: 35874673

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Project description:BackgroundMore and more immune-oncology trials have been conducted for treating various cancers, yet it is unclear what the reporting quality of immune-oncology trials is,and characteristics associated with higher reporting quality.ObjectiveThis study aims to evaluate the reporting quality of immune-oncology trials.MethodsThe PubMed and Cochrane library were searched to identify all English publications of clinical trials assessing immunotherapy for cancer. Reporting quality of immune-oncology trials was evaluated by a quality score with 11 points derived from the Trial Reporting in Immuno-Oncology (TRIO) statement, which contained two parts: an efficacy score of 6 points and toxicity score of 5 point. Linear regression was used to identify characteristics associated with higher scores.ResultsOf the 10,169 studies screened, 298 immune-oncology trial reports were enrolled. The mean quality score, efficacy score, and toxicity score were 6.46, 3.61, and 2.85, respectively. The most common well-reported items were response evaluation criteria (96.0%) and toxicity grade (98.7%), followed by Kaplan-Meier survival analyses (80.5%). Treatment details beyond progression (12.8%) and toxicity onset time and duration (7.7%) were poorly reported. Multivariate regression revealed that higher impact factor (IF) (IF >20 vs. IF <5, p < 0.001), specific tumor type (p = 0.018 for lung, p = 0.021 for urinary system, vs. pan cancer), and a certain kind of immune checkpoint blocking agent (p < 0.001 for anti-PD-1 or multiagents, vs. anti-CTLA-4) were independent predictors of higher-quality score. Similar independent predictive characteristics were revealed for high-efficacy score. Only IF >20 had a significant high-toxicity score (p < 0.001).ConclusionImmune-oncology trial reports presented an unsatisfied quality score, especially in the reporting of treatment details beyond progression and toxicity onset time and duration. High IF journals have better reporting quality. Future improvement of trial reporting was warranted to the benefit-risk assessment of immunotherapy.

Project description:IntroductionAdverse event (AE) under-reporting has been a recurrent issue raised during health authorities Good Clinical Practices (GCP) inspections and audits. Moreover, safety under-reporting poses a risk to patient safety and data integrity. The current clinical Quality Assurance (QA) practices used to detect AE under-reporting rely heavily on investigator site and study audits. Yet several sponsors and institutions have had repeated findings related to safety reporting, and this has led to delays in regulatory submissions. Recent developments in data management and IT systems allow data scientists to apply techniques such as machine learning to detect AE under-reporting in an automated fashion.ObjectiveIn this project, we developed a predictive model that enables Roche/Genentech Quality Program Leads oversight of AE reporting at the program, study, site, and patient level. This project was part of a broader effort at Roche/Genentech Product Development Quality to apply advanced analytics to augment and complement traditional clinical QA approaches.MethodWe used a curated data set from 104 completed Roche/Genentech sponsored clinical studies to train a machine learning model to predict the expected number of AEs. Our final model used 54 features built on patient (e.g., demographics, vitals) and study attributes (e.g., molecule class, disease area).ResultsIn order to evaluate model performance, we tested how well it would detect simulated test cases based on data not used for model training. For relevant simulation scenarios of 25%, 50%, and 75% under-reporting on the site level, our model scored an area under the curve (AUC) of the receiver operating characteristic (ROC) curve of 0.62, 0.79, and 0.92, respectively.ConclusionThe model has been deployed to evaluate safety reporting performance in a set of ongoing studies in the form of a QA/dashboard cockpit available to Roche Quality Program Leads. Applicability and production performance will be assessed over the next 12-24 months in which we will develop a validation strategy to fully integrate our model into Roche QA processes.

Project description:Introduction: With the widespread application of Immune checkpoint inhibitors (ICIs), it is important to explore the association between ICIs and cardiac arrhythmias and to characterize the clinical features of ICI-associated cardiac arrhythmias in real-world studies. Objective: The purpose of this study was to characterize the main features of ICI-related cardiac arrhythmias. Methods: From January 2017 to June 2021, data in the Food and Drug Administration Adverse Event Reporting System (FAERS) database were retrieved to conduct the disproportionality analysis. For the ICI-related cardiac arrhythmia detection, signals were detected by reporting odds ratio (ROR) and information component (IC), calculated using two-by-two contingency tables The clinical characteristics of patients reported with ICI-related cardiac arrhythmias were compared between fatal and non-fatal groups, and the time to onset (TTO) following different ICI regimens was further investigated. Multivariate logistic regression was used to evaluate the association between concurrent cardiotoxicities and ICI-associated arrhythmias. Results: We identified a total of 1957 ICI-associated cardiac arrhythmias reports which appeared to influence more men (64.44%) than women (30.76%), with a median age of 68 [interquartile range (IQR) 60-75] years. Cardiac arrhythmias were reported most often in patients with lung, pleura, thymus and heart cancers (38.02% of 1957 patients). Compared with the full database, ICIs were detected with pharmacovigilance of cardiac arrhythmias (ROR025 = 1.16, IC025 = 0.19). Anti-PD-1 and anti-PD-L1 monotherapies were found to be related to higher reporting of arrhythmias, corresponding to ROR025 = 1.03, IC025 = 0.06 and ROR025 = 1.27, IC025 = 0.29, respectively, with the exception of anti-CTLA-4 monotherapies (ROR025 = 0.57, IC025 = -1.21). The spectrum of arrhythmias induced by ICIs differed among therapeutic regimens. There was no significant difference in the onset time between monotherapy and combination regimen. Moreover, reports of ICI-associated arrhythmias were associated with other concurrent cardiotoxicity, including cardiac failure [ROR 2.61 (2.20-3.09)], coronary artery disorders [ROR 2.28 (1.83-2.85)], myocardial disorders [ROR 5.25 (4.44-6.22)], pericardial disorders [ROR 2.76 (2.09-3.64)] and cardiac valve disorders [ROR 3.21 (1.34-7.68)]. Conclusion: ICI monotherapy and combination therapy can lead to cardiac arrhythmias that can result in serious outcomes and tend to occur early. Our findings underscore the importance of early recognition and management of ICI-related cardiac arrhythmias.

Dataset Information

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

Background

Methods

Results

Publications

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

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