Wang Juan, Yamada Ryo
Unit of Statistical Genetics, Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
PeerJ. 2018 Sep 25;6:e5677. doi: 10.7717/peerj.5677. eCollection 2018.
Medical decision-making is difficult when information is limited due to its rareness. For example, there are two treatment options for patients affected by a rare disease with high lethality. The information about both treatment effects is unavailable or very limited. Patients are inclined to accept one of the interventions rather than waiting for death, but they are reluctant to be assigned the inferior one. While a single patient selects one treatment that seems better based on the limited information, he or she loses the chance to select the other treatment, which may be the better option. This is the so-called dilemma between exploitation (enjoying the benefits of using current knowledge) and exploration (taking the risk to obtain new knowledge). In clinical settings, the statistical advice for individual patients seems to be the maximum expected success rate or something equivalent and patients' selections tend to be homogeneous, which does not solve the dilemma. In this study, our aim is to investigate the effects of the heterogeneity of decision-makers in the decision process.
Here, we proposed a decision strategy that introduced the heterogeneity of decision-makers by considering patients' self-decisions where the patients' heterogeneous attitudes towards the treatment are integrated into the probabilistic utility function based on the Beta Bayesian posterior. Based on the context of two-armed bandit treatment options with limited information, we compared the overall success rate of treatment between our heterogeneous decision strategy and a homogeneous decision strategy that is defined to select the treatment with the largest posterior mean.
The heterogeneity of decision-makers in a population improved the overall benefit of treatment under some conditions.
In clinical settings, there exists heterogeneity of decision-making among patients. Our study investigated a targeting strategy by respecting the self-decision of all individuals and found that the heterogeneity of decision-making can improve the overall benefit under some conditions. In addition, this outperformance may suggest that heterogeneity of decision-making is of importance to human beings. Besides the ethical merit, our findings provide meaningful ideas for better strategies towards decision-making dilemmas in clinical settings for rare diseases or cases where only limited information is available. Furthermore, it is suggested to investigate the effects of heterogeneity of decision-making in other fashions, such as genetic heterogeneity and phenotypic heterogeneity.
当因信息稀缺而导致信息有限时,医学决策会变得困难。例如,对于患有高致死率罕见疾病的患者有两种治疗方案。关于两种治疗效果的信息都不可得或非常有限。患者倾向于接受其中一种干预措施而非坐等死亡,但他们又不愿被分配到较差的那种。当单个患者基于有限信息选择一种看似更好的治疗方法时,他或她就失去了选择另一种治疗方法的机会,而另一种治疗方法可能才是更好的选择。这就是所谓的利用(享受运用现有知识的益处)与探索(冒险获取新知识)之间的困境。在临床环境中,针对个体患者的统计建议似乎是最大预期成功率或类似的东西,并且患者的选择往往趋于一致,这并不能解决困境。在本研究中,我们的目的是调查决策过程中决策者异质性的影响。
在此,我们提出了一种决策策略,该策略通过考虑患者的自我决策来引入决策者的异质性,其中患者对治疗的异质态度基于贝塔贝叶斯后验被整合到概率效用函数中。基于信息有限的双臂博弈治疗方案的背景,我们比较了我们的异质决策策略与定义为选择后验均值最大的治疗方法的同质决策策略之间的总体治疗成功率。
在某些条件下,人群中决策者的异质性提高了治疗的总体益处。
在临床环境中,患者之间存在决策异质性。我们的研究通过尊重所有个体的自我决策来研究一种靶向策略,发现决策异质性在某些条件下可以提高总体益处。此外,这种优势可能表明决策异质性对人类很重要。除了伦理价值外,我们的研究结果为针对罕见疾病或信息有限的临床环境中的决策困境制定更好的策略提供了有意义的思路。此外,建议以其他方式研究决策异质性的影响,例如基因异质性和表型异质性。