BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4//
BEGIN:VEVENT
UID:20250725T185800EDT-9670afcwhN@132.216.98.100
DTSTAMP:20250725T225800Z
DESCRIPTION:Title\; Dose-Finding Design in Phase I/II trial via Bayesian Ut
 ility.\n\nAbstract: Haolun Shi is an Assistant Professor in the Department
  of Statistics and Actuarial Science at Simon Fraser University. Specializ
 ed in biostatistics and clinical trial design\, he earned his Ph.D. from t
 he University of Hong Kong. His research focuses on developing adaptive cl
 inical trials\, efficient parametric and non-parametric statistical infere
 nces\, and Bayesian testing procedures. He is also interested in functiona
 l data analysis and statistics in sports. He published extensively in stat
 istical journals indexed in the Science Citation Index.\n	Molecularly targe
 ted agents and immunotherapy have revolutionized modern cancer treatment. 
 Unlike chemotherapy\, the maximum tolerated dose of the targeted therapies
  may not pose significant clinical benefit over the lower doses. By simult
 aneously considering both binary toxicity and efficacy endpoints\, phase I
 /II trials can identify a better dose for subsequent phase II trials than 
 traditional phase I trials in terms of efficacy-toxicity tradeoff. Existin
 g phase I/II dose-finding methods are model-based or need to pre-specify m
 any design parameters\, which makes them difficult to implement in practic
 e. To strengthen and simplify the current practice of phase I/II trials\, 
 we propose a utility-based toxicity probability interval (uTPI) design for
  finding the optimal biological dose (OBD) where binary toxicity and effic
 acy endpoints are observed. The uTPI design is model-assisted in nature\, 
 simply modeling the utility outcomes observed at the current dose level ba
 sed on a quasibinomial likelihood. Toxicity probability intervals are used
  to screen out overly toxic dose levels\, and then the dose escalation/de-
 escalation decisions are made adaptively by comparing the posterior utilit
 y distributions of the adjacent levels of the current dose. The uTPI desig
 n is flexible in accommodating various utility functions while only needs 
 minimum design parameters. A prominent feature of the uTPI design is that 
 it has a simple decision structure such that a concise dose-assignment dec
 ision table can be calculated before the start of trial and be used throug
 hout the trial\, which greatly simplifies practical implementation of the 
 design. Extensive simulation studies demonstrate that the proposed uTPI de
 sign yields desirable as well as robust performance under various scenario
 s. This talk is based on the joint work with Ruitao Lin and Ying Yuan at M
 D Anderson Cancer Center.\n\n \n\nSeminar Epidemiology\, Biostatistics\, &
  Occupational Health\n	Via Zoom: https://mcgill.zoom.us/j/85978187693?pwd=W
 WtJZUpnb0JXK3o5SStnOFcxK3FFUT09\n
DTSTART:20211006T193000Z
DTEND:20211006T203000Z
SUMMARY:Haolun Shi (Simon Fraser University)
URL:/mathstat/channels/event/haolun-shi-simon-fraser-u
 niversity-333854
END:VEVENT
END:VCALENDAR