16 citations · 38 across the 11 of their papers we have counts for
12 papers
Transformer-Based Reinforcement Learning for Phase I Dose Allocation
Shijie Yuan
Phase I dose-finding trials must learn from sparse toxicity observations while limiting exposure to overly toxic doses. We develop a single reinforcement-learning policy for trials…
Robust Power and Sample Size Calculations in Quasi-likelihood Models: Methods and Practice
Shijie Yuan, Amy Cochran, Paul Rathouz
Accurate power and sample size (PSS) calculations are essential for designing studies that use quasi-likelihood (QL) models, which extend generalized linear models (GLMs) to settin…
Monitoring Adverse Events Through Bayesian Nonparametric Clustering Across Studies
Shijie Yuan, Kevin Roberts, Noirrit Kiran Chandra +2
We introduce a Bayesian nonparametric inference approach for aggregate adverse event (AE) monitoring across studies. The proposed model seamlessly integrates external data from his…
SIMBA -- A Bayesian Decision Framework for the Identification of Optimal Biomarker Subgroups for Cancer Basket Clinical Trials
Shijie Yuan, Jiaxin Liu, Zhihua Gong +4
We consider basket trials in which a biomarker-targeting drug may be efficacious for patients across different disease indications. Patients are enrolled if their cells exhibit som…
The Modified Combo i3+3 Design for Novel-Novel Combination Dose-Finding Trials in Oncology
Jiaxin Liu, Shijie Yuan, Qiqi Deng +1
We consider a modified Ci3+3 (MCi3+3) design for dual-agent dose-finding trials in which both agents are tested on multiple doses. This usually happens when the agents are novel th…
Pharmacometrics-Enabled DOse OPtimization (PEDOOP) for Seamless Phase I-II Trials in Oncology
Shijie Yuan, Zhanbo Huang, Jiaxin Liu +1
We consider a dose-optimization design for first-in-human oncology trial that aims to identify a suitable dose for late-phase drug development. The proposed approach, called the Ph…
The Backfill i3+3 Design for Dose-Finding Trials in Oncology
Jiaxin Liu, Shijie Yuan, B. Nebiyou Bekele +1
We consider a formal statistical design that allows simultaneous enrollment of a main cohort and a backfill cohort of patients in a dose-finding trial. The goal is to accumulate mo…
A Unified Decision Framework for Phase I Dose-Finding Designs
Yunshan Duan, Shijie Yuan, Yuan Ji +1
The purpose of a phase I dose-finding clinical trial is to investigate the toxicity profiles of various doses for a new drug and identify the maximum tolerated dose. Over the past…
BaySize: Bayesian Sample Size Planning for Phase I Dose-Finding Trials
Xiaolei Lin, Jiaying Lyu, Shijie Yuan +2
We propose BaySize, a sample size calculator for phase I clinical trials using Bayesian models. BaySize applies the concept of effect size in dose finding, assuming the MTD is defi…
The Ci3+3 Design for Dual-Agent Combination Dose-Finding Clinical Trials
Shijie Yuan, Tianjian Zhou, Yawen Lin +1
We propose a rule-based statistical design for combination dose-finding trials with two agents. The Ci3+3 design is an extension of the i3+3 design with simple decision rules compa…
Lessons Learned from the Bayesian Design and Analysis for the BNT162b2 COVID-19 Vaccine Phase 3 Trial
Yuan Ji, Shijie Yuan
The phase III BNT162b2 mRNA COVID-19 vaccine trial is based on a Bayesian design and analysis, and the main evidence of vaccine efficacy is presented in Bayesian statistics. Confus…
MUCE: Bayesian Hierarchical Modeling for the Design and Analysis of Phase 1b Multiple Expansion Cohort Trials
Jiaying Lyu, Tianjian Zhou, Shijie Yuan +2
We propose a multiple cohort expansion (MUCE) approach as a design or analysis method for phase 1b multiple expansion cohort trials, which are novel first-in-human studies conducte…