Weighted win loss approach for analyzing prioritized outcomes.

Pubmed ID: 28343373

Pubmed Central ID: PMC5490500

Journal: Statistics in medicine

Publication Date: July 10, 2017

Affiliation: Janssen Research and Development, Raritan, NJ 08869, U.S.A.

MeSH Terms: Humans, Survival Analysis, Randomized Controlled Trials as Topic, Clinical Trials as Topic, Data Interpretation, Statistical, Proportional Hazards Models, Treatment Outcome, Computer Simulation, Models, Statistical, Angiotensin-Converting Enzyme Inhibitors, Coronary Artery Disease, Endpoint Determination, Biostatistics, Acute Coronary Syndrome, Factor Xa Inhibitors, Rivaroxaban

Grants: P50 AG005138

Authors: Tian H, Luo X, Qiu J, Bai S

Cite As: Luo X, Qiu J, Bai S, Tian H. Weighted win loss approach for analyzing prioritized outcomes. Stat Med 2017 Jul 10;36(15):2452-2465. Epub 2017 Mar 26.

Studies:

Abstract

To analyze prioritized outcomes, Buyse (2010) and Pocock et al. (2012) proposed the win loss approach. In this paper, we first study the relationship between the win loss approach and the traditional survival analysis on the time to the first event. We then propose the weighted win loss statistics to improve the efficiency of the unweighted methods. A closed-form variance estimator of the weighted win loss statistics is derived to facilitate hypothesis testing and study design. We also calculated the contribution index to better interpret the results of the weighted win loss approach. Simulation studies and real data analysis demonstrated the characteristics of the proposed statistics. Copyright © 2017 John Wiley & Sons, Ltd.