Retrieved-Dropout-Based multiple imputation for time-to-event data in cardiovascular outcome trials. Issue 2 (4th March 2023)

• Record Type: Journal Article
• Authors: He, Jiwei; Crackel, Roberto; Koh, William; Chen, Ling-Wan; Li, Feng; Zhang, Jialu; Rothmann, Mark
• Is Part Of: Journal of biopharmaceutical statistics. Volume 33:Issue 2(2023)
• Page Start: 234
• Page End: 252
• Publication Date: 2023-03-04
• Subjects: Missing data -- multiple imputation -- treatment policy estimand -- retrieved dropout -- cardiovascular outcome trial; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2022.2118763
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Recently, retrieved-dropout-based multiple imputation has been used in some therapeutic areas to address the treatment policy estimand, mostly for continuous endpoints. In this approach, data from subjects who discontinued study treatment but remained in study were used to construct a model for multiple imputation for the missing data of subjects in the same treatment arm who discontinued study. We extend this approach to time-to-event endpoints and provide a practical guide for its implementation. We use a cardiovascular outcome trial dataset to illustrate the method and compare the results with those from Cox proportional hazard and reference-based multiple imputation methods.