Literature DB >> 28804182

Change-Plane Analysis for Subgroup Detection and Sample Size Calculation.

Ailin Fan1, Rui Song1, Wenbin Lu1.   

Abstract

We propose a systematic method for testing and identifying a subgroup with an enhanced treatment effect. We adopts a change-plane technique to first test the existence of a subgroup, and then identify the subgroup if the null hypothesis on non-existence of such a subgroup is rejected. A semiparametric model is considered for the response with an unspecified baseline function and an interaction between a subgroup indicator and treatment. A doubly-robust test statistic is constructed based on this model, and asymptotic distributions of the test statistic under both null and local alternative hypotheses are derived. Moreover, a sample size calculation method for subgroup detection is developed based on the proposed statistic. The finite sample performance of the proposed test is evaluated via simulations. Finally, the proposed methods for subgroup identification and sample size calculation are applied to a data from an AIDS study.

Entities:  

Keywords:  Change-plane analysis; Doubly robust test; Sample size calculation; Semiparametric model; Subgroup analysis

Year:  2017        PMID: 28804182      PMCID: PMC5553128          DOI: 10.1080/01621459.2016.1166115

Source DB:  PubMed          Journal:  J Am Stat Assoc        ISSN: 0162-1459            Impact factor:   5.033


  17 in total

1.  Subgroup analyses in randomized trials: risks of subgroup-specific analyses; power and sample size for the interaction test.

Authors:  Sara T Brookes; Elise Whitely; Matthias Egger; George Davey Smith; Paul A Mulheran; Tim J Peters
Journal:  J Clin Epidemiol       Date:  2004-03       Impact factor: 6.437

2.  The Cox proportional hazards model with change point: an epidemiologic application.

Authors:  K Y Liang; S G Self; X H Liu
Journal:  Biometrics       Date:  1990-09       Impact factor: 2.571

3.  Treating individuals 2. Subgroup analysis in randomised controlled trials: importance, indications, and interpretation.

Authors:  Peter M Rothwell
Journal:  Lancet       Date:  2005 Jan 8-14       Impact factor: 79.321

4.  Analysis of randomized comparative clinical trial data for personalized treatment selections.

Authors:  Tianxi Cai; Lu Tian; Peggy H Wong; L J Wei
Journal:  Biostatistics       Date:  2010-09-28       Impact factor: 5.899

5.  Subgroup identification from randomized clinical trial data.

Authors:  Jared C Foster; Jeremy M G Taylor; Stephen J Ruberg
Journal:  Stat Med       Date:  2011-08-04       Impact factor: 2.373

6.  Subgroup analysis and other (mis)uses of baseline data in clinical trials.

Authors:  S F Assmann; S J Pocock; L E Enos; L E Kasten
Journal:  Lancet       Date:  2000-03-25       Impact factor: 79.321

7.  Variable selection for optimal treatment decision.

Authors:  Wenbin Lu; Hao Helen Zhang; Donglin Zeng
Journal:  Stat Methods Med Res       Date:  2011-11-23       Impact factor: 3.021

8.  Recursive subsetting to identify patients in the STAR*D: a method to enhance the accuracy of early prediction of treatment outcome and to inform personalized care.

Authors:  Anthony Y C Kuk; Jialiang Li; A John Rush
Journal:  J Clin Psychiatry       Date:  2010-11       Impact factor: 4.384

9.  Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials.

Authors:  S Yusuf; J Wittes; J Probstfield; H A Tyroler
Journal:  JAMA       Date:  1991-07-03       Impact factor: 56.272

10.  A trial comparing nucleoside monotherapy with combination therapy in HIV-infected adults with CD4 cell counts from 200 to 500 per cubic millimeter. AIDS Clinical Trials Group Study 175 Study Team.

Authors:  S M Hammer; D A Katzenstein; M D Hughes; H Gundacker; R T Schooley; R H Haubrich; W K Henry; M M Lederman; J P Phair; M Niu; M S Hirsch; T C Merigan
Journal:  N Engl J Med       Date:  1996-10-10       Impact factor: 91.245

View more
  4 in total

1.  Subgroup detection and sample size calculation with proportional hazards regression for survival data.

Authors:  Suhyun Kang; Wenbin Lu; Rui Song
Journal:  Stat Med       Date:  2017-08-08       Impact factor: 2.373

2.  Threshold-based subgroup testing in logistic regression models in two-phase sampling designs.

Authors:  Ying Huang; Juhee Cho; Youyi Fong
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2020-11-28       Impact factor: 1.864

3.  Addressing patient heterogeneity in disease predictive model development.

Authors:  Xu Gao; Weining Shen; Jing Ning; Ziding Feng; Jianhua Hu
Journal:  Biometrics       Date:  2021-08-01       Impact factor: 1.701

4.  Multithreshold change plane model: Estimation theory and applications in subgroup identification.

Authors:  Jialiang Li; Yaguang Li; Baisuo Jin; Michael R Kosorok
Journal:  Stat Med       Date:  2021-04-11       Impact factor: 2.497

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.