An Approach for Sample Size Determination in Clinical Trials of Rare Diseases based on Bayesian Decision Theory
10.11783/j.issn.1002－3674.2025.02.001
- VernacularTitle:基于贝叶斯决策理论的罕见病临床试验样本含量估算方法
- Author:
Nana CHEN
1
;
Zhiwei RONG
1
;
Yan HOU
1
Author Information
1. 北京大学公共卫生学院生物统计系(100191)
- Publication Type:Journal Article
- Keywords:
Rare diseases;
Sample size;
Decision theory;
Benefit function;
Clinical trials
- From:
Chinese Journal of Health Statistics
2025;42(2):162-165
- CountryChina
- Language:Chinese
-
Abstract:
Objective Traditional methods for sample size estimation in clinical trial do not consider the patient size applicable to the results during the estimation process,and use point estimation for unknown true values of parameters,which has certain limitations in rare disease clinical trials.This article introduces a sample size estimation method based on Bayesian decision theory.Methods This article proposes a Tripartite Balanced Benefit Function(TBBF)and constructs a benefit function model based on the characteristics of acute and chronic diseases.The sample size in clinical trial is determined by maximizing expected benefits.Results The case analysis of hemophilia B demonstrated the application process of the model,and the sample size obtained by maximizing expected benefits is feasible in practical situations.This method has the advantage of being suitable for estimating sample sizes in small sample clinical trials.Conclusion TBBF fully utilizes prior information,incorporates patient size into the estimation process,and makes the quantitative form of different stakeholders'interests clearer,making the decision-making process more scientific and interpretable.
