Data Management Techniques Applied to the Scandinavian Simvastatin Survival Study (4S) Mega-Trial

Abstract

Event-based clinical trials involving large numbers of patients, usually treated over several years, are commonly referred to as mega-trials. Unlike the majority of clinical trials where the study stops when the last patient entered into the trial completes a predefined treatment duration (or discontinues), mega-trials terminate when the requisite number of clinical endpoints has been reached. The uncertainty about the actual stop date combined with the multinational nature of such a trial and the very large volume of data generated over a long period requires extensive, flexible, and sometimes inventive techniques to ensure consistent, timely, and effective data management. This article describes the evolution of the data management techniques used during the conduct of the Scandinavian Simvastatin Survival Study (4S) in 4444 patients to investigate the effect on mortality of treatment with simvastatin (Zocor(R)) compared to placebo. The distributed data processing system established for the study, the creation and execution of the original data management plan (DMP), and the rationale for modifying this plan mid-way through the study in response to actual trial experience will be described. The rationale for developing a revised data management strategy will be presented and how a joint data review approach involving data management, clinical, and field monitoring staff was successful in achieving a clean file for analysis within four months of the decision to stop the study will be described. Critical to this success was the development of a package of electronic screening queries to facilitate data review and the introduction of a shared database application to manage the large number of review questions.