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. 2013 Mar;69(1):52-61.
doi: 10.1111/j.1541-0420.2012.01818.x. Epub 2013 Feb 5.

Latent subgroup analysis of a randomized clinical trial through a semiparametric accelerated failure time mixture model

L Altstein  1 , G Li
Affiliations

Latent subgroup analysis of a randomized clinical trial through a semiparametric accelerated failure time mixture model

L Altstein et al. Biometrics. 2013 Mar.

Abstract

This article studies a semiparametric accelerated failure time mixture model for estimation of a biological treatment effect on a latent subgroup of interest with a time-to-event outcome in randomized clinical trials. Latency is induced because membership is observable in one arm of the trial and unidentified in the other. This method is useful in randomized clinical trials with all-or-none noncompliance when patients in the control arm have no access to active treatment and in, for example, oncology trials when a biopsy used to identify the latent subgroup is performed only on subjects randomized to active treatment. We derive a computational method to estimate model parameters by iterating between an expectation step and a weighted Buckley-James optimization step. The bootstrap method is used for variance estimation, and the performance of our method is corroborated in simulation. We illustrate our method through an analysis of a multicenter selective lymphadenectomy trial for melanoma.

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Figures

Figure 1
Figure 1
Estimated and Observed Survival Curves in the Two-Sample Analysis of MSLT-I
Figure 2
Figure 2
Plot of log(−log(Survival of node + in treatment)) −log(−log(Survival of node + in control)) for DFS (Left Panel) and DDFS (Right Panel) in MSLT-I
Figure 3
Figure 3
Sensitivity of the Hazard Smoother on DFS in Node-Positive Subgroup
See this image and copyright information in PMC

References

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    1. Altstein L, Li G, Elashoff R. A method to estimate treatment efficacy among latent subgroups of a randomized clinical trial. Statistics in Medicine. 2011;30(7):709–717. - PMC - PubMed
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