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On the relative conservativeness of Bayesian logistic regression method in oncology dose-finding studies.
Yang, Cheng-Han; Cheng, Guanghui; Lin, Ruitao.
Affiliation
  • Yang CH; Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
  • Cheng G; Guangzhou Institute of International Finance, Guangzhou University, Guangzhou, Guangdong, China.
  • Lin R; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Pharm Stat ; 23(4): 585-594, 2024.
Article in En | MEDLINE | ID: mdl-38317370
ABSTRACT
The Bayesian logistic regression method (BLRM) is a widely adopted and flexible design for finding the maximum tolerated dose in oncology phase I studies. However, the BLRM design has been criticized in the literature for being overly conservative due to the use of the overdose control rule. Recently, a discussion paper titled "Improving the performance of Bayesian logistic regression model with overall control in oncology dose-finding studies" in Statistics in Medicine has proposed an overall control rule to address the "excessive conservativeness" of the standard BLRM design. In this short communication, we discuss the relative conservativeness of the standard BLRM design and also suggest a dose-switching rule to further enhance its performance.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bayes Theorem / Clinical Trials, Phase I as Topic / Maximum Tolerated Dose / Dose-Response Relationship, Drug / Antineoplastic Agents Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Pharm Stat Journal subject: FARMACOLOGIA Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bayes Theorem / Clinical Trials, Phase I as Topic / Maximum Tolerated Dose / Dose-Response Relationship, Drug / Antineoplastic Agents Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Pharm Stat Journal subject: FARMACOLOGIA Year: 2024 Document type: Article Affiliation country: Country of publication: