16 citations · 72 across the 18 of their papers we have counts for
18 papers
A Multi-Arm Two-Stage (MATS) Design for Proof-of-Concept and Dose Optimization in Early-Phase Oncology Trials
Zhenghao Jiang, Gu Mi, Ji Lin +2
The Project Optimus initiative by the FDA's Oncology Center of Excellence is widely viewed as a groundbreaking effort to change the of conventional dose-findi…
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…
On Bayesian Sequential Clinical Trial Designs
Tianjian Zhou, Yuan Ji
Clinical trials usually involve sequential patient entry. When designing a clinical trial, it is often desirable to include a provision for interim analyses of accumulating data wi…
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…
Incorporating External Data into the Analysis of Clinical Trials via Bayesian Additive Regression Trees
Tianjian Zhou, Yuan Ji
Most clinical trials involve the comparison of a new treatment to a control arm (e.g., the standard of care) and the estimation of a treatment effect. External data, including hist…
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…
PoD-BIN: A Probability of Decision Bayesian Interval Design for Time-to-Event Dose-Finding Trials with Multiple Toxicity Grades
Meizi Liu, Yuan Ji, Ji Lin
We consider a Bayesian framework based on "probability of decision" for dose-finding trial designs. The proposed PoD-BIN design evaluates the posterior predictive probabilities of…
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…
Hi3+3: A Model-Assisted Dose-Finding Design Borrowing Historical Data
Yunshan Duan, Sue-Jane Wang, Yuan Ji
Background -- In phase I clinical trials, historical data may be available through multi-regional programs, reformulation of the same drug, or previous trials for a drug under the…
Semiparametric Bayesian Inference for the Transmission Dynamics of COVID-19 with a State-Space Model
Tianjian Zhou, Yuan Ji
The outbreak of Coronavirus Disease 2019 (COVID-19) is an ongoing pandemic affecting over 200 countries and regions. Inference about the transmission dynamics of COVID-19 can provi…
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…
Statistical Frameworks for Oncology Dose-Finding Designs with Late-Onset Toxicities: A Review
Tianjian Zhou, Yuan Ji
In oncology dose-finding trials, due to staggered enrollment, it might be desirable to make dose-assignment decisions in real-time in the presence of pending toxicity outcomes, for…
Posterior Contraction Rate of Sparse Latent Feature Models with Application to Proteomics
Tong Li, Tianjian Zhou, Kam-Wah Tsui +2
The Indian buffet process (IBP) and phylogenetic Indian buffet process (pIBP) can be used as prior models to infer latent features in a data set. The theoretical properties of thes…
PoD-TPI: Probability-of-Decision Toxicity Probability Interval Design to Accelerate Phase I Trials
Tianjian Zhou, Wentian Guo, Yuan Ji
Cohort-based enrollment can slow down dose-finding trials since the outcomes of the previous cohort must be fully evaluated before the next cohort can be enrolled. This results in…
The i3+3 Design for Phase I Clinical Trials
Meizi Liu, Sue-Jane Wang, Yuan Ji
Purpose: The 3+3 design has been shown to be less likely to achieve the objectives of phase I dose-finding trials when compared with more advanced model-based designs. One major cr…
On the Interval-Based Dose-Finding Designs
Yuan Ji, Shengjie Yang
The landscape of dose-finding designs for phase I clinical trials is rapidly shifting in the recent years, noticeably marked by the emergence of interval-based designs. We categori…
A Bayesian Interval Dose-Finding Design Addressing Ockham's Razor: mTPI-2
Wentian Guo, Sue-Jane Wang, Shengjie Yang +2
There has been an increasing interest in using interval-based Bayesian designs for dose finding, one of which is the modified toxicity probability interval (mTPI) method. We show t…