×

Nonparametric group sequential methods for evaluating survival benefit from multiple short-term follow-up windows. (English) Zbl 1436.62652

Summary: This article takes a fresh look at group sequential methods applied to two-sample tests of censored survival data and proposes an alternative method of defining and evaluating treatment benefit. Our method re-purposes traditional censored event time data into a sequence of short-term outcomes taken from (potentially overlapping) follow-up windows. A new two-sample restricted means test based on this restructured follow-up data is proposed along with group sequential methods for its use in the clinical trial setting. This method compares favorably with existing methods for group sequential monitoring of time-to-event outcomes, including methods for monitoring the restricted means test and the logrank test. Our method performs particularly well in cases where there is a delayed treatment effect and/or a subset of cured patients. As part of developing group sequential methods for these analyses, we consider asymmetric error spending approaches that differentially limit the chances of stopping incorrectly for perceived efficacy versus perceived harm attributed to the investigational arm of the trial. Recommendations for how to choose proper group sequential stopping boundaries are given, with supporting simulations and an example from the AIDS Clinical Trial Group.

MSC:

62P10 Applications of statistics to biology and medical sciences; meta analysis
62N05 Reliability and life testing
62G07 Density estimation
62L12 Sequential estimation
62N01 Censored data models

References:

[1] Breslow, N. (1970). A generalized Kruskal‐Wallis test for comparing k samples subject to unequal patterns of censorship. Biometrika57, 579-594. · Zbl 0215.26403
[2] DeMets, D. L. and Lan, K. K. G. (1994). Interim analysis: The alpha spending function approach. Stat Med13, 1341-1352.
[3] DeMets, D. L. and Ware, J. H. (1982). Asymmetric group sequential boundaries for monitoring clinical trials. Biometrika69, 661-663.
[4] Fischl, M., Parker, L., Petinelli, C., et al. (1990). A randomized controlled trial of a reduced daily dose of zidovudine in patients with the aquired immunodeficiency syndrome. N Engl J Med323, 1009-1014.
[5] Friedman, L. M., Furberg, C. D., De Mets, D. L., Reboussin, D. M., and Granger, C. B. (2015). Foundamentals of Clinical Trials. Springer.
[6] Gehan, E. A. (1965). A generalized Wilcoxon test for comparing arbitrarily singly‐censored samples. Biometrika, 52452, 203-223. · Zbl 0133.41901
[7] Harrington, D. P. (2012). Design for Clinical Trials. Springer.
[8] Harrington, D. P. and Fleming, T. R. (1982). A class of rank test procedures for censored survival data. Biometrika69, 553-566. · Zbl 0532.62026
[9] Jennison, C. and Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall. · Zbl 0934.62078
[10] Lan, K. K. G. and De Mets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika70, 659-663. · Zbl 0543.62059
[11] Li, Z. (1999). A group sequential test for survival trials: An alternative to rank‐based procedures. Biometrics55, 277-283. · Zbl 1059.62583
[12] Mantel, N. (1963). Chi‐square tests with one degree of freedom; extensions of the Mantel-Haenszel procedure. J Am Stat Assoc58, 690-700. · Zbl 0114.11601
[13] Mantel, N. (1966). Evaluation of survival data and two new rank‐order statistics arising in its consideration. Cancer Chemother Rep50, 163-170.
[14] Murray, S. and Tsiatis, A. A. (1999). Sequential methods for comparing years of life saved in the two‐sample censored data problem. Biometrics55, 1085-1092. · Zbl 1059.62683
[15] O’Brien, P. and Fleming, T. (1979). A multiple testing procedure for clinical trials. Biometrics35, 549-556.
[16] Pampallona, S. and Tsiatis, A. A. (1994). Group sequential designs for one‐sided and two‐sided hypothesis testing with provision for early stopping in favor of the null hypothesis. J Stat Plan Inference42, 19-35. · Zbl 0805.62078
[17] Pepe, M. S. and Fleming, T. R. (1989). Weighted Kaplan‐Meier statistics: A class of distance tests for censored survival data. Biometrics45, 497-507. · Zbl 0715.62087
[18] Peto, R. and Peto, J. (1972). Asymptotically efficient rank invariant test procedures. J R Stat Soc Ser A135, 185-207.
[19] Pocock, S. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika64, 191-199.
[20] Prentice, R. L. (1978). Linear rank tests with right censored data. Biometrika65, 167-179. · Zbl 0377.62024
[21] Proschan, M. A., Lan, K. K. G., and Wittes, J. T. (2006). Statistical Monitoring of Chinical Trials: A Unified Approach. Springer. · Zbl 1121.62098
[22] Tayob, N. and Murray, S. (2016). Nonparametric restricted mean analysis across multiple follow‐up intervals. Stat Probabil Lett109, 152-158. · Zbl 1383.62090
[23] Tayob, N. and Murray, S. (2017). Statistical consequences of a successful lung allocation system -Recovering information and reducing bias in models for urgency. Stat Med36, 2435-2451.
[24] Tsiatis, A. A. (1981). The asymptotic joint distribution of the efficient scores test for the proportional hazards model calculated over time. Biometrika68, 311-315. · Zbl 0461.62021
[25] Tsiatis, A. A. (1982). Repeated significance testing for a general class of statistics used in censored survival analysis. J Am Stat Assoc77, 855-861. · Zbl 0511.62045
[26] Ware, J. H., Muller, J., and Braunwald, E. (1985). The futility index. An approach to the cost‐effective termination of randomized clinical trials. Am J Med78, 635-643.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.