Adaptive phase I/II clinical trials for drug combination assessment in oncology using the outcomes of each cycle. (25th August 2017)

• Record Type: Journal Article
• Authors: Yada, Shinjo; Hamada, Chikuma
• Is Part Of: Pharmaceutical statistics. Volume 16:Number 6(2017)
• Page Start: 433
• Page End: 444
• Publication Date: 2017-08-25
• Subjects: drug combinations -- overall response -- seamless phase I/II; Pharmacy -- Statistical methods -- Periodicals; Pharmacy -- Statistics -- Periodicals; 615.10727
• DOI: 10.1002/pst.1822
• Languages: English
• ISSNs: 1539-1604

Abstract

Abstract : Many new anticancer agents can be combined with existing drugs, as combining a number of drugs may be expected to have a better therapeutic effect than monotherapy owing to synergistic effects. Furthermore, to drive drug development and to reduce the associated cost, there has been a growing tendency to combine these as phase I/II trials. With respect to phase I/II oncology trials for the assessment of dose combinations, in the existing methodologies in which efficacy based on tumor response and safety based on toxicity are modeled as binary outcomes, it is not possible to enroll and treat the next cohort of patients unless the best overall response has been determined in the current cohort. Thus, the trial duration might be potentially extended to an unacceptable degree. In this study, we proposed a method that randomizes the next cohort of patients in the phase II part to the dose combination based on the estimated response rate using all the available observed data upon determination of the overall response in the current cohort. We compared the proposed method to the existing method using simulation studies. These demonstrated that the percentage of optimal dose combinations selected in the proposed method is not less than that in the existing method and that the trial duration in the proposed method is shortened compared to that in the existing method. The proposed method meets both ethical and financial requirements, and we believe it has the potential to contribute to expedite drug development.