Chang Chih-Kuang, Chang Chi-Chang
Department of Cardiology, Jen-Ai Hospital, Dali District, Taichung, Taiwan.
School of Medical Informatics, Chung Shan Medical University, Information Technology Office of Chung Shan Medical University Hospital, Taichung, Taiwan.
Ther Clin Risk Manag. 2014 Dec 19;11:17-26. doi: 10.2147/TCRM.S67011. eCollection 2015.
In medical research, clinical practice must often be undertaken with imperfect information from limited resources. This study applied Bayesian imperfect information-value analysis to realistic situations to produce likelihood functions and posterior distributions, to a clinical decision-making problem for recurrent events. In this study, three kinds of failure models are considered, and our methods illustrated with an analysis of imperfect information from a trial of immunotherapy in the treatment of chronic granulomatous disease. In addition, we present evidence toward a better understanding of the differing behaviors along with concomitant variables. Based on the results of simulations, the imperfect information value of the concomitant variables was evaluated and different realistic situations were compared to see which could yield more accurate results for medical decision-making.
在医学研究中，临床实践常常必须在资源有限且信息不完整的情况下进行。本研究将贝叶斯不完全信息价值分析应用于实际情况，以生成似然函数和后验分布，用于复发性事件的临床决策问题。在本研究中，考虑了三种失败模型，并通过对慢性肉芽肿病免疫治疗试验中的不完全信息进行分析来说明我们的方法。此外，我们提供了证据，以便更好地理解不同行为以及伴随变量。基于模拟结果，评估了伴随变量的不完全信息价值，并比较了不同的实际情况，以确定哪种情况能为医疗决策产生更准确的结果。
