Methods for Employing Information About Uncertainty of Ascertainment of Events in Clinical Trials
- PDF / 1,124,616 Bytes
- 15 Pages / 595.276 x 790.866 pts Page_size
- 97 Downloads / 157 Views
ORIGINAL RESEARCH
Methods for Employing Information About Uncertainty of Ascertainment of Events in Clinical Trials Yiming Chen1,2 · John Lawrence, PhD3 · H. M. James Hung, PhD3 · Norman Stockbridge, MD, PhD4 Received: 24 April 2020 / Accepted: 19 August 2020 © The Drug Information Association, Inc 2020
Abstract Background Uncertain ascertainment of events in clinical trials has been noted for decades. To correct possible bias, Clinical Endpoint Committees (CECs) have been employed as a critical element of trials to ensure consistent and high-quality endpoint evaluation, especially for cardiovascular endpoints. However, the efficiency and usefulness of adjudication have been debated. Methods The multiple imputation (MI) method was proposed to incorporate endpoint event uncertainty. In a simulation conducted to explain this methodology, the dichotomous outcome was imputed each time with subject-specific event probabilities. As the final step, the desired analysis was conducted based on all imputed data. This proposed method was further applied to real trial data from PARADIGM-HF. Results Compared with the conventional Cox model with adjudicated events only, the Cox MI method had higher power, even with a small number of uncertain events. It yielded more robust inferences regarding treatment effects and required a smaller sample size to achieve the same power. Conclusions Instead of using dichotomous endpoint data, the MI method enables incorporation of event uncertainty and eliminates the need for categorizing endpoint events. In future trials, assigning a probability of event occurrence for each event may be preferable to a CEC assigning a dichotomous outcome. Considerable resources could be saved if endpoint events can be identified more simply and in a manner that maintains study power. Keywords Adjudication · Multiple imputation · Dichotomous endpoint · Event uncertainty
Introduction
Disclaimer This article reflects the views of the authors and should not be construed to represent the views or policies of the U.S. Food and Drug Administration. * John Lawrence [email protected] 1
Department of Epidemiology and Biostatistics, University of Maryland, College Park, USA
2
ORISE, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, USA
3
Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA
4
Division of Cardiology and Nephrology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, USA
Substantial efforts have been made to standardize definitions for cardiovascular (CV) and stroke outcomes in the past 10 years [1]. Multiple factors complicate the diagnosis of CV endpoints, such as the heterogeneity of patients’ clinical presentation and the accuracy and completeness of the information available to the investigators. Endpoint evaluation is crucial because the outcome of clinical trials is typically driven by events. With the po
Data Loading...
