Event-specific win ratios for inference with terminal and non-terminal events.
Song YangJames F TroendleDaewoo PakEric LeiferPublished in: Statistics in medicine (2021)
For semi-competing risks data involving a non-terminal event and a terminal event we derive the asymptotic distributions of the event-specific win ratios under proportional hazards (PH) assumptions for the relevant cause-specific hazard functions of the non-terminal and terminal event, respectively. The win ratios converge to the respective hazard ratios under the PH assumptions and therefore are censoring-free, whether or not the censoring distributions in the two treatment arms are the same. With the asymptotic bivariate normal distributions of the win ratios, confidence intervals and testing procedures are obtained. Through extensive simulation studies and data analysis, we identified proper transformations of the win ratios that yield good control of the type one error rate for various testing procedures while maintaining competitive power. The confidence intervals also have good coverage probabilities. Furthermore, a test for the PH assumptions and a test of equal hazard ratios are developed. The new procedures are illustrated in the clinical trial Aldosterone Antagonist Therapy for Adults With Heart Failure and Preserved Systolic Function, which evaluated the effects of spironolactone in patients with heart failure and a preserved left ventricular ejection fraction.
Keyphrases
- heart failure
- left ventricular
- data analysis
- ejection fraction
- clinical trial
- aortic stenosis
- randomized controlled trial
- blood pressure
- healthcare
- acute myocardial infarction
- atrial fibrillation
- risk assessment
- single cell
- open label
- mitral valve
- study protocol
- coronary artery disease
- big data
- left atrial
- double blind
- monte carlo
- percutaneous coronary intervention
- smoking cessation
- virtual reality