Sample size computation in phase II designs combining the A'Hern design and the Sargent and Goldberg design. Issue 2 (3rd March 2020)

• Record Type: Journal Article
• Authors: Neven, Anouk; Mauer, Murielle; Hasan, Baktiar; Sylvester, Richard; Collette, Laurence
• Is Part Of: Journal of biopharmaceutical statistics. Volume 30:Issue 2(2020)
• Page Start: 305
• Page End: 321
• Publication Date: 2020-03-03
• Subjects: Randomized phase II -- A'Hern design -- screening design -- pick-the-winner design -- flexible design -- sample size computation; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2019.1641817
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: This work focuses on the modification of two classical phase II trials designs, the A'Hern design, a single-arm single-stage design, and the Sargent and Goldberg design introduced in the context of flexible screening designs. In the first part of the paper, we have proposed a drift-adjusted A'Hern design, a hybrid design combining the A'Hern design and the Sargent and Goldberg design. Indeed, classical single-arm phase II designs such as the A'Hern design are still widely used in oncology. Conducting randomized comparative phase II trials may be challenging in many settings due to the increased sample size and this despite larger type 1 errors. Randomized non-comparative phase II designs first introduced by Herson and Carter include a simultaneous randomized standard-treatment reference arm to detect any drift in the reference arm assumption, but the trial is analyzed against historical controls as if it were a single-arm study. However, not incorporating at all an internal control arm in the trial design has been criticized in the literature. Our new design takes into account the observed response rate in a non-comparative reference arm to reduce the trial's risk of a false-positive conclusion. In the second part, we have proposed an alternative strategy to determining the sample size of the screened selection design. The latter, introduced in recent years by Yap et al. and Wu et al., extended the Sargent and Goldberg design to include a comparison to a historical control. However, their sample size computations may have potential weaknesses, which motivated us to revisit the existing approaches. A detailed simulation study has been carried out to evaluate the operating characteristics of the drift-adjusted A'Hern design and the different sample size strategies of the screened selection designs.