Literature DB >> 26336199

Application of the Wei-Lachin multivariate one-directional test to multiple event-time outcomes.

John M Lachin1, Ionut Bebu2.   

Abstract

BACKGROUND/AIMS: Cardiovascular outcome trials, among others, aim to assess the beneficial effects of a treatment on multiple event-time outcomes, such as the time to a myocardial infarction and the time to a stroke. The traditional approach is to conduct a simple analysis of a composite outcome defined as the time to the first component event using a logrank test or the Cox Proportional Hazards regression model. This ignores information from other component events after the first. The composite outcome analysis also treats all initial outcome events as equally important, for example, non-fatal myocardial infarction is as important as cardiovascular death.
METHODS: Herein, we describe the application of the Wei-Lachin multivariate one-sided (or one-directional) test to the analysis of multiple event-time outcomes. The test is based on the unweighted mean of the treatment group coefficients from individual Cox proportional hazards models fit to the outcomes, where the covariance of the set of coefficients is obtained from a partitioning of the information sandwich estimate. A weighted test is also described, weighing the outcomes by a scoring of their clinical importance. These and other methods are compared with application to the Prevention of Events with Angiotensin-Converting Enzyme Inhibition cardiovascular outcome study.
RESULTS: The Wei-Lachin test provides an inference with strong control of the type 1 error probability on the difference between groups for the set of outcomes considered. However, it does not provide an inference on the individual components specifically with control of the overall type 1 error probability. By direct computation of relative efficiency and by simulation, we show that the power of the Wei-Lachin one-directional test can be greater than that of the traditional composite outcome analysis based on the time to the first observed component event.
CONCLUSION: The Wei-Lachin multivariate one-directional test may be more powerful than the traditional analysis of a composite outcome defined as the time to the first component outcomes experienced by each subject.
© The Author(s) 2015.

Entities:  

Keywords:  Composite outcome; Wei–Lachin test; event-time data; multivariate one-directional test

Mesh:

Year:  2015        PMID: 26336199      PMCID: PMC4562325          DOI: 10.1177/1740774515601027

Source DB:  PubMed          Journal:  Clin Trials        ISSN: 1740-7745            Impact factor:   2.486


  10 in total

1.  Some large-sample distribution-free estimators and tests for multivariate partially incomplete data from two populations.

Authors:  J M Lachin
Journal:  Stat Med       Date:  1992-06-30       Impact factor: 2.373

2.  Impact of weighted composite compared to traditional composite endpoints for the design of randomized controlled trials.

Authors:  Jeffrey A Bakal; Cynthia M Westerhout; Paul W Armstrong
Journal:  Stat Methods Med Res       Date:  2012-01-24       Impact factor: 3.021

Review 3.  Advanced multiplicity adjustment methods in clinical trials.

Authors:  Mohamed Alosh; Frank Bretz; Mohammad Huque
Journal:  Stat Med       Date:  2013-09-16       Impact factor: 2.373

4.  Treatment selections using risk-benefit profiles based on data from comparative randomized clinical trials with multiple endpoints.

Authors:  Brian Claggett; Lu Tian; Davide Castagno; Lee-Jen Wei
Journal:  Biostatistics       Date:  2014-08-12       Impact factor: 5.899

5.  The analysis of failure times in the presence of competing risks.

Authors:  R L Prentice; J D Kalbfleisch; A V Peterson; N Flournoy; V T Farewell; N E Breslow
Journal:  Biometrics       Date:  1978-12       Impact factor: 2.571

6.  Cox regression analysis of multivariate failure time data: the marginal approach.

Authors:  D Y Lin
Journal:  Stat Med       Date:  1994-11-15       Impact factor: 2.373

7.  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

8.  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

9.  Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification.

Authors:  J M Lachin; M A Foulkes
Journal:  Biometrics       Date:  1986-09       Impact factor: 2.571

10.  Applications of the Wei-Lachin multivariate one-sided test for multiple outcomes on possibly different scales.

Authors:  John M Lachin
Journal:  PLoS One       Date:  2014-10-17       Impact factor: 3.240

  10 in total
  9 in total

1.  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

2.  Properties of composite time to first event versus joint marginal analyses of multiple outcomes.

Authors:  Ionut Bebu; John M Lachin
Journal:  Stat Med       Date:  2018-06-28       Impact factor: 2.373

3.  An optimal Wilcoxon-Mann-Whitney test of mortality and a continuous outcome.

Authors:  Roland A Matsouaka; Aneesh B Singhal; Rebecca A Betensky
Journal:  Stat Methods Med Res       Date:  2016-12-29       Impact factor: 3.021

4.  Safety and efficacy of Cerebrolysin in acute brain injury and neurorecovery: CAPTAIN I-a randomized, placebo-controlled, double-blind, Asian-Pacific trial.

Authors:  W Poon; C Matula; P E Vos; D F Muresanu; N von Steinbüchel; K von Wild; V Hömberg; E Wang; T M C Lee; S Strilciuc; J C Vester
Journal:  Neurol Sci       Date:  2019-09-07       Impact factor: 3.307

5.  Current Drug Treatment of Acute Ischemic Stroke: Challenges and Opportunities.

Authors:  Dafin F Muresanu; Stefan Strilciuc; Adina Stan
Journal:  CNS Drugs       Date:  2019-09       Impact factor: 5.749

6.  Introducing a new estimator and test for the weighted all-cause hazard ratio.

Authors:  Ann-Kathrin Ozga; Geraldine Rauch
Journal:  BMC Med Res Methodol       Date:  2019-06-11       Impact factor: 4.615

7.  Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches.

Authors:  Ann-Kathrin Ozga; Geraldine Rauch
Journal:  BMC Med Res Methodol       Date:  2022-02-05       Impact factor: 4.615

8.  A class of two-sample nonparametric statistics for binary and time-to-event outcomes.

Authors:  Marta Bofill Roig; Guadalupe Gómez Melis
Journal:  Stat Methods Med Res       Date:  2021-12-06       Impact factor: 3.021

9.  Win Ratio -An Intuitive and Easy-To-Interpret Composite Outcome in Medical Studies.

Authors:  Hongyue Wang; Jing Peng; Juila Z Zheng; Bokai Wang; Xiang Lu; Chongshu Chen; Xin M Tu; Changyong Feng
Journal:  Shanghai Arch Psychiatry       Date:  2017-02-25
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.