Literature DB >> 28343373

Weighted win loss approach for analyzing prioritized outcomes.

Xiaodong Luo1, Junshan Qiu2, Steven Bai2, Hong Tian3.   

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. Copyright © 2017 John Wiley & Sons, Ltd.

Entities:  

Keywords:  clinical trials; composite end points; contribution index; prioritized outcomes; variance estimation; weighted win ratio

Mesh:

Substances:

Year:  2017        PMID: 28343373      PMCID: PMC5490500          DOI: 10.1002/sim.7284

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  9 in total

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Authors:  Jessica L Mega; Eugene Braunwald; Stephen D Wiviott; Jean-Pierre Bassand; Deepak L Bhatt; Christoph Bode; Paul Burton; Marc Cohen; Nancy Cook-Bruns; Keith A A Fox; Shinya Goto; Sabina A Murphy; Alexei N Plotnikov; David Schneider; Xiang Sun; Freek W A Verheugt; C Michael Gibson
Journal:  N Engl J Med       Date:  2011-11-13       Impact factor: 91.245

2.  Generalized pairwise comparisons of prioritized outcomes in the two-sample problem.

Authors:  Marc Buyse
Journal:  Stat Med       Date:  2010-12-30       Impact factor: 2.373

3.  Large sample inference for a win ratio analysis of a composite outcome based on prioritized components.

Authors:  Ionut Bebu; John M Lachin
Journal:  Biostatistics       Date:  2015-09-08       Impact factor: 5.899

4.  An alternative approach to confidence interval estimation for the win ratio statistic.

Authors:  Xiaodong Luo; Hong Tian; Surya Mohanty; Wei Yann Tsai
Journal:  Biometrics       Date:  2014-08-25       Impact factor: 2.571

5.  The win ratio approach to analyzing composite outcomes: An application to the EVOLVE trial.

Authors:  Safa Abdalla; Maria E Montez-Rath; Patrick S Parfrey; Glenn M Chertow
Journal:  Contemp Clin Trials       Date:  2016-04-11       Impact factor: 2.226

6.  The win ratio: a new approach to the analysis of composite endpoints in clinical trials based on clinical priorities.

Authors:  Stuart J Pocock; Cono A Ariti; Timothy J Collier; Duolao Wang
Journal:  Eur Heart J       Date:  2011-09-06       Impact factor: 29.983

7.  Angiotensin-converting-enzyme inhibition in stable coronary artery disease.

Authors:  Eugene Braunwald; Michael J Domanski; Sarah E Fowler; Nancy L Geller; Bernard J Gersh; Judith Hsia; Marc A Pfeffer; Madeline M Rice; Yves D Rosenberg; Jean L Rouleau
Journal:  N Engl J Med       Date:  2004-11-07       Impact factor: 91.245

8.  A win ratio approach to comparing continuous non-normal outcomes in clinical trials.

Authors:  Duolao Wang; Stuart Pocock
Journal:  Pharm Stat       Date:  2016-03-11       Impact factor: 1.894

9.  Rethinking composite end points in clinical trials: insights from patients and trialists.

Authors:  Joshua M Stolker; John A Spertus; David J Cohen; Philip G Jones; Kaushik K Jain; Emily Bamberger; Brady B Lonergan; Paul S Chan
Journal:  Circulation       Date:  2014-09-08       Impact factor: 29.690

  9 in total
  5 in total

1.  The inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic: an unbiased estimator in the presence of independent censoring.

Authors:  Gaohong Dong; Lu Mao; Bo Huang; Margaret Gamalo-Siebers; Jiuzhou Wang; GuangLei Yu; David C Hoaglin
Journal:  J Biopharm Stat       Date:  2020-06-17       Impact factor: 1.051

2.  Statistical models for composite endpoints of death and non-fatal events: a review.

Authors:  Lu Mao; KyungMann Kim
Journal:  Stat Biopharm Res       Date:  2021-07-06       Impact factor: 1.586

3.  On recurrent-event win ratio.

Authors:  Lu Mao; KyungMann Kim; Yi Li
Journal:  Stat Methods Med Res       Date:  2022-03-29       Impact factor: 2.494

4.  A class of proportional win-fractions regression models for composite outcomes.

Authors:  Lu Mao; Tuo Wang
Journal:  Biometrics       Date:  2020-10-10       Impact factor: 1.701

Review 5.  Choosing primary endpoints for clinical trials of health care interventions.

Authors:  Charlie McLeod; Richard Norman; Edward Litton; Benjamin R Saville; Steve Webb; Thomas L Snelling
Journal:  Contemp Clin Trials Commun       Date:  2019-11-12
  5 in total

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