Guoqing Diao, Xun Jiang, Donglin Zeng, May Mo, H Amy Xia, Joseph G Ibrahim
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引用次数: 0
Abstract
With the availability of unprecedented human genomic biomarker data, incorporating such biomarker data has received a lot of attention in phase 3 clinical trials. One particular enrichment design proposed recently in the literature is to recruit more biomarker positive patients in an all-comer study if the treatment effect in the biomarker negative group is less promising than expected. The intuition is to improve the chance of success of the trial since the success rate in the all-comer population may be low. We propose an enrichment design that unifies the existing biomarker adaptive designs for phase 3 clinical trials. In addition, we propose a new test accounting for the correlations among the test statistics based on different groups of patients, including all-comers, biomarker positive patients only, and biomarker negative patients only. We investigate the theoretical properties of the design and demonstrate the new test accurately controls the type I error rate and gains power over existing methods through extensive simulations. A computer program is developed for power calculations given a set of design parameters, including the proportion of biomarker positive patients, the distribution of the failure time in each treatment and biomarker group, and the number of patients in the first stage and the second stage (i.e. the enrichment stage), among others.
期刊介绍:
The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers:
Drug, device, and biological research and development;
Drug screening and drug design;
Assessment of pharmacological activity;
Pharmaceutical formulation and scale-up;
Preclinical safety assessment;
Bioavailability, bioequivalence, and pharmacokinetics;
Phase, I, II, and III clinical development including complex innovative designs;
Premarket approval assessment of clinical safety;
Postmarketing surveillance;
Big data and artificial intelligence and applications.