Follow up after sample size re-estimation in a breast cancer randomized trial for disease-free survival

Erinn M Hade, Gregory S Young, Richard R Love, Erinn M Hade, Gregory S Young, Richard R Love

Abstract

Background: While the clinical trials and statistical methodology literature on sample size re-estimation (SSRE) is robust, evaluation of SSRE procedures following the completion of a clinical trial has been sparsely reported. In blinded sample size re-estimation, only nuisance parameters are re-estimated, and the blinding of the current trial treatment effect is preserved. Blinded re-estimation procedures are well-accepted by regulatory agencies and funders. We review our experience of sample size re-estimation in a large international, National Institutes of Health funded clinical trial for adjuvant breast cancer treatment, and evaluate our blinded sample size re-estimation procedure for this time-to-event trial. We evaluated the SSRE procedure by examining assumptions made during the re-estimation process, estimates resulting from re-estimation, and the impact on final trial results with and without the addition of participants, following sample size re-estimation.

Methods: We compared the control group failure probabilities estimated at the time of SSRE to estimates used in the original planning, to the final un-blinded control group failure probability estimates for those included in the SSRE procedure (SSRE cohort), and to the final total control group failure probability estimates. The impact of re-estimation on the final comparison between randomized treatment groups is evaluated for those in the originally planned cohort (n = 340) and for the combination of those recruited in the originally planned cohort and those added after re-estimation (n = 509).

Results: Very little difference is observed between the originally planned cohort and all randomized patients in the control group failure probabilities over time or in the overall hazard ratio estimating treatment effect (originally planned cohort HR 1.25 (0.86, 1.79); all randomized cohort HR 1.24 95% CI (0.91, 1.68)). At the time of blinded SSRE, the estimated control group failure probabilities at 3 years (0.24) and 5 years (0.40) were similar to those for the SSRE cohort once un-blinded (3 years, 0.22 (0.16, 0.30); 5 years, 0.33 (0.26, 0.41)).

Conclusions: We found that our re-estimation procedure performed reasonably well in estimating the control group failure probabilities at the time of re-estimation. Particularly for time-to-event outcomes, pre-planned blinded SSRE procedures may be the best option to aid in maintaining power.

Trial registration: ClinicalTrials.gov, NCT00201851 . Registered on 9 September 2005. Retrospectively registered.

Keywords: Blinded sample size re-estimation; Breast cancer; Control group failure; Time to event.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Hazard rate for recurrence or death for all randomized patients (a) and for the initial group of randomized patients (b). a All patients, n = 499, average follow up 4.2 years. b Initial group of randomized patients, n = 334, average follow up 4.6 years. Black line indicates the scheduled/luteal-phase-surgery group; gray line indicates the immediate/follicular-phase-surgery group. Dashed lines are pointwise 95% confidence intervals
Fig. 2
Fig. 2
Hazard rate for recurrence or death for the sample size re-estimation (SSRE) cohort at the time of re-estimation (a) and through the final follow up (b). a At SSRE, n = 278, average follow up 1.2 years. b At final follow up, average follow up 4.2 years. Black line indicates the scheduled/luteal-phase-surgery group; gray line is for the immediate/follicular-phase-surgery group. Dashed lines are pointwise 95% confidence intervals
Fig. 3
Fig. 3
Hazard rate for recurrence or death for randomized patients at each major site of accrual at site A (a) and site B (b). a Site A, n = 170, average follow up 4.76 years. b Site B, n = 215, average follow up 4.0 years. Black line indicates the scheduled/luteal-phase-surgery group; gray line indicates the immediate/follicular-phase-surgery group. Dashed lines are pointwise 95% confidence intervals

References

    1. McClure LA, Szychowski JM, Benavente O, Hart RG, Coffey CS. A post hoc evaluation of a sample size re-estimation in the Secondary Prevention of Small Subcortical Strokes study. Clin Trials. 2016;13(5):537–544. doi: 10.1177/1740774516643689.
    1. Pritchett YL, Menon S, Marchenko O, Antonijevic Z, Miller E, Sanchez-Kam M, et al. Sample size re-estimation designs in confirmatory clinical trials-current state, statistical considerations, and practical guidance. Stat Biopharm Res. 2015;7(4):309–321. doi: 10.1080/19466315.2015.1098564.
    1. Gould AL. Sample size re-estimation: recent developments and practical considerations. Stat Med. 2001;20(17–18):2625–2643. doi: 10.1002/sim.733.
    1. Gould AL. Planning and revising the sample-size for a trial. Stat Med. 1995;14(9–10):1039–1051. doi: 10.1002/sim.4780140922.
    1. Wittes J, Brittain E. The role of internal pilot-studies in increasing the efficiency of clinical trials. Stat Med. 1990;9(1–2):65–72. doi: 10.1002/sim.4780090113.
    1. Bauer P, Kohne K. Evaluation of experiments with adaptive interim analyses. Biometrics. 1994;50(4):1029–1041. doi: 10.2307/2533441.
    1. Wassmer G. A comparison of two methods for adaptive interim analyses in clinical trials. Biometrics. 1998;54(2):696–705. doi: 10.2307/3109775.
    1. Shen Y, Cai JW. Sample size reestimation for clinical trials with censored survival data. J Am Stat Assoc. 2003;98(462):418–426. doi: 10.1198/016214503000206.
    1. Jennison C, Turnbull BW. Mid-course sample size modification in clinical trials based on the observed treatment effect. Stat Med. 2003;22(6):971–993. doi: 10.1002/sim.1457.
    1. Jennison C, Turnbull BW. Efficient group sequential designs when there are several effect sizes under consideration. Stat Med. 2006;25(6):917–932. doi: 10.1002/sim.2251.
    1. Jennison C, Turnbull BW. Adaptive and nonadaptive group sequential tests. Biometrika. 2006;93(1):1–21. doi: 10.1093/biomet/93.1.1.
    1. Muller HH, Schafer H. A general statistical principle for changing a design any time during the course of a trial. Stat Med. 2004;23(16):2497–2508. doi: 10.1002/sim.1852.
    1. Hade EM, Jarjoura D, Lai W. Sample size re-estimation in a breast cancer trial. Clin Trials. 2010;7(3):219–226. doi: 10.1177/1740774510367525.
    1. Friede T, Kieser M. Sample size recalculation in internal pilot study designs: a review. Biom J. 2006;48(4):537–555. doi: 10.1002/bimj.200510238.
    1. Proschan MA. Sample size re-estimation in clinical trials. Biom J. 2009;51(2):348–357. doi: 10.1002/bimj.200800266.
    1. Guidance for industry . adaptive design clinical trials for drugs and biologics (draft) 2010.
    1. Love RR, Laudico AV, Van Dinh N, Allred DC, Uy GB, Quang le H, et al. Timing of adjuvant surgical oophorectomy in the menstrual cycle and disease-free and overall survival in premenopausal women with operable breast cancer. J Natl Cancer Inst. 2015;107(6):djv064. doi: 10.1093/jnci/djv064.
    1. Love RR, Duc NB, Dinh NV, Shen TZ, Havighurst TC, Allred DC, et al. Mastectomy and oophorectomy by menstrual cycle phase in women with operable breast cancer. J Natl Cancer Inst. 2002;94(9):662–669. doi: 10.1093/jnci/94.9.662.
    1. Love RR, Van Dinh N, Quy TT, Linh ND, Tung ND, T-z S, et al. Survival After adjuvant oophorectomy and tamoxifen in operable breast cancer in premenopausal women. J Clin Oncol. 2008;26(2):253–257. doi: 10.1200/JCO.2007.11.6061.
    1. Love RR, Young GS, Hade EM, Jarjoura D. Effects on survival of menstrual cycle phase of adjuvant surgical oophorectomy in premenopausal women with breast cancer. Breast Cancer Res Treat. 2011;126(2):479–485. doi: 10.1007/s10549-011-1370-0.
    1. Cooper LS, Gillett CE, Patel NK, Barnes DM, Fentiman IS. Survival of premenopausal breast carcinoma patients in relation to menstrual cycle timing of surgery and estrogen receptor/progesterone receptor status of the primary tumor. Cancer. 1999;86(10):2053–2058. doi: 10.1002/(SICI)1097-0142(19991115)86:10<2053::AID-CNCR24>;2-H.
    1. Hade E, Young G, Jarjoura D, Love R. Follow up after sample size re-estimation in a breast cancer trial for time to recurrence. Trials. 2013;14(1):O107. doi: 10.1186/1745-6215-14-S1-O107.
    1. Kaplan E. L., Meier Paul. Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association. 1958;53(282):457. doi: 10.1080/01621459.1958.10501452.
    1. Silverman B. Density estimation for statistics and data analysis. New York: Chapman and Hall; 1986.
    1. Pritchett Y, Jemiai Y, Chang Y, Bhan I, Agarwal R, Zoccali C, et al. The use of group sequential, information-based sample size re-estimation in the design of the PRIMO study of chronic kidney disease. Clin Trials. 2011;8(2):165–174. doi: 10.1177/1740774511399128.
    1. FDA . Guidance for industry: adaptive design clinical trials for drugs and biologics. 2015.
    1. Freidlin B, Korn EL. Sample size adjustment designs with time-to-event outcomes: a caution. Clin Trials. 2017;14(6):597–604. doi: 10.1177/1740774517724746.

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