Literature DB >> 20221802

Empirical receiver operating characteristic curve for two-sample comparison with cure fractions.

Xiaobing Zhao1, Xian Zhou.   

Abstract

Two-sample comparison of survival times with "cured patients" is of major interest and a challenging issue in many areas, particularly in cancer clinical research. Recently, several authors have proposed various procedures of comparison, including tests of no overall, no short-term and no long-term differences between two samples. In clinical practice, it is often of interest to detect the difference in treatment effects among noncured patients regardless of the difference between cure fractions. In this paper, we propose a statistical test to compare two samples with cured patients and possibly heterogeneous treatment effects based on a class of semi-parametric transformation models, and our main focus is on the survival times of noncured patients. The empirical and quantile processes are used to construct strong approximations for the empirical curves. The two-sample test is then constructed from general least squares estimators derived from these processes. Simulation results show that the proposed test perform well. As an example of application, a set of bladder cancer data is analyzed to illustrate the proposed methods.

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Year:  2010        PMID: 20221802     DOI: 10.1007/s10985-010-9159-8

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  13 in total

1.  Estimation in a Cox proportional hazards cure model.

Authors:  J P Sy; J M Taylor
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

2.  A semiparametric approach for the two-sample comparison of survival times with long-term survivors.

Authors:  P Broët; Y De Rycke; P Tubert-Bitter; J Lellouch; B Asselain; T Moreau
Journal:  Biometrics       Date:  2001-09       Impact factor: 2.571

3.  Principal stratification in causal inference.

Authors:  Constantine E Frangakis; Donald B Rubin
Journal:  Biometrics       Date:  2002-03       Impact factor: 2.571

4.  A score test for establishing non-inferiority with respect to short-term survival in two-sample comparisons with identical proportions of long-term survivors.

Authors:  P Broët; P Tubert-Bitter; Y De Rycke; T Moreau
Journal:  Stat Med       Date:  2003-03-30       Impact factor: 2.373

5.  A nonparametric comparison of conditional distributions with nonnegligible cure fractions.

Authors:  Yi Li; Jin Feng
Journal:  Lifetime Data Anal       Date:  2005-09       Impact factor: 1.588

6.  Bayesian dynamic models for survival data with a cure fraction.

Authors:  Sungduk Kim; Ming-Hui Chen; Dipak K Dey; Dani Gamerman
Journal:  Lifetime Data Anal       Date:  2007-03       Impact factor: 1.588

7.  Discrete-time survival models with long-term survivors.

Authors:  Xiaobing Zhao; Xian Zhou
Journal:  Stat Med       Date:  2008-04-15       Impact factor: 2.373

8.  Nonparametric estimation and testing in a cure model.

Authors:  E M Laska; M J Meisner
Journal:  Biometrics       Date:  1992-12       Impact factor: 2.571

9.  A linear rank test for use when the main interest is in differences in cure rates.

Authors:  R J Gray; A A Tsiatis
Journal:  Biometrics       Date:  1989-09       Impact factor: 2.571

10.  The use of mixture models for the analysis of survival data with long-term survivors.

Authors:  V T Farewell
Journal:  Biometrics       Date:  1982-12       Impact factor: 2.571

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