collaborators

6 papers

stat.ME2026

A seamless dose-optimization design for monotherapy and combination therapy

Kentaro Takeda, Masahiro Kojima

The emergence of molecular-targeted agents and immune-oncology therapies has fundamentally transformed oncology drug development, necessitating evolution beyond traditional dose-fi…

stat.ME2026

A Globally Calibrated Bayesian Optimal Phase II Design for Adaptive Enrichment Trials

Masahiro Kojima, Hisato Sunami, Masaaki Kuriki

Adaptive enrichment allows development of an experimental treatment to continue when its activity is insufficient in an all-comer population but remains promising in a prespecified…

stat.ME2026

Fast Power Evaluation under Biased-Coin Minimization: Sampling and Randomization Calibration

Masahiro Kojima

Design-stage power and sample-size evaluation under biased-coin minimization can be computationally intensive when a prespecified randomization test is reproduced within every simu…

stat.ME2026

Covariate-Adaptive Sample Size Re-estimation for Population-Standardized Historical Control Designs in Single-Arm Trials

Keisuke Hanada, Masahiro Kojima

Externally controlled single-arm trials are increasingly considered when randomized controls are infeasible, but baseline imbalance between the active-arm trial and historical cont…

stat.ME2026

Hybrid Non-informative and Informative Prior Model-assisted Designs for Mid-trial Dose Insertion

Kana Yamada, Hisato Sunami, Kentaro Takeda +2

In oncology phase I trials, model-assisted designs have been increasingly adopted because they enable adaptive yet operationally simple dose adjustment based on accumulating safety…

stat.ME2025

Sample size re-estimation in blinded hybrid-control design using inverse probability weighting

Masahiro Kojima, Shunichiro Orihara, Keisuke Hanada +1

With the increasing availability of data from historical studies and real-world data sources, hybrid control designs that incorporate external data into the evaluation of current s…