Literature DB >> 3203130

Efficiency of balanced treatment allocation for survival analysis.

L A Kalish1, D P Harrington.   

Abstract

We assess the efficiency of balanced treatment allocation methods in clinical trials for comparing treatments with respect to survival. We compare optimal designs for each of three standard survival analysis techniques (maximum partial likelihood estimation, log-rank test, exponential regression) with balanced designs, over a range of hypothetical trials. Although balanced designs are not optimal, we find them to be very efficient. In view of the high efficiency demonstrated in this and in a previous paper (Begg and Kalish, 1984, Biometrics 40, 409-420), and practical difficulties in implementing an optimal design, we recommend the use of balanced allocation methods in practice.

Mesh:

Year:  1988        PMID: 3203130

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  3 in total

1.  An asymptotic analysis of the logrank test.

Authors:  R L Strawderman
Journal:  Lifetime Data Anal       Date:  1997       Impact factor: 1.588

2.  Adaptive Optimal Designs for Dose-Finding Studies with Time-to-Event Outcomes.

Authors:  Yevgen Ryeznik; Oleksandr Sverdlov; Andrew C Hooker
Journal:  AAPS J       Date:  2017-12-28       Impact factor: 4.009

3.  Optimal treatment allocation for placebo-treatment comparisons in trials with discrete-time survival endpoints.

Authors:  Mirjam Moerbeek; Weng-Kee Wong
Journal:  Stat Med       Date:  2015-06-28       Impact factor: 2.373

  3 in total

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