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Efficiency Considerations for Group Sequential Designs with Adaptive Unblinded Sample Size Re-assessment

Author

Listed:
  • Lingyun Liu

    (Cytel Corporation)

  • Sam Hsiao

    (Cytel Corporation)

  • Cyrus R. Mehta

    (Cytel Corporation
    Harvard T.H. Chan School of Public Health)

Abstract

Clinical trials with adaptive sample size re-assessment, based on an analysis of the unblinded interim results (ubSSR), have gained in popularity due to uncertainty regarding the value of $$\delta $$ δ at which to power the trial at the start of the study. While the statistical methodology for controlling the type-1 error of such designs is well established, there remain concerns that conventional group sequential designs with no ubSSR can accomplish the same goals with greater efficiency. The precise manner in which this efficiency comparison can be objectified has been difficult to quantify, however. In this paper, we present a methodology for making this comparison in a standard, well-accepted manner by plotting the unconditional power curves of the two approaches while holding constant their expected sample size, at each value of $$\delta $$ δ in the range of interest. It is seen that under reasonable decision rules for increasing sample size (conservative promising zones, and no more than a 50% increase in sample size) there is little or no loss of efficiency for the adaptive designs in terms of unconditional power. The two approaches, however, have very different conditional power profiles. More generally, a methodology has been provided for comparing any design with ubSSR relative to a comparable group sequential design with no ubSSR, so one can determine whether the efficiency loss, if any, of the ubSSR design is offset by the advantages it confers for re-powering the study at the time of the interim analysis.

Suggested Citation

  • Lingyun Liu & Sam Hsiao & Cyrus R. Mehta, 2018. "Efficiency Considerations for Group Sequential Designs with Adaptive Unblinded Sample Size Re-assessment," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(2), pages 405-419, August.
  • Handle: RePEc:spr:stabio:v:10:y:2018:i:2:d:10.1007_s12561-017-9188-x
    DOI: 10.1007/s12561-017-9188-x
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    References listed on IDEAS

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    1. Walter Lehmacher & Gernot Wassmer, 1999. "Adaptive Sample Size Calculations in Group Sequential Trials," Biometrics, The International Biometric Society, vol. 55(4), pages 1286-1290, December.
    2. Qing Liu & George Y. H. Chi, 2001. "On Sample Size and Inference for Two‐Stage Adaptive Designs," Biometrics, The International Biometric Society, vol. 57(1), pages 172-177, March.
    3. Anastasios A. Tsiatis, 2003. "On the inefficiency of the adaptive design for monitoring clinical trials," Biometrika, Biometrika Trust, vol. 90(2), pages 367-378, June.
    4. Lu Chi & H. M. James Hung & Sue-Jane Wang, 1999. "Modification of Sample Size in Group Sequential Clinical Trials," Biometrics, The International Biometric Society, vol. 55(3), pages 853-857, September.
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