In silico study of medical decision-making for rare diseases: heterogeneity of decision-makers in a population improves overall benefit
- Published
- Accepted
- Subject Areas
- Bioinformatics, Clinical Trials, Public Health, Ethical Issues, Statistics
- Keywords
- heterogeneity, rare disease, decision-making, self-decision
- Copyright
- © 2018 Wang et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. In silico study of medical decision-making for rare diseases: heterogeneity of decision-makers in a population improves overall benefit. PeerJ Preprints 6:e27170v1 https://doi.org/10.7287/peerj.preprints.27170v1
Abstract
Background: Medical decision-making is difficult when information is limited due to 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.
Methods: 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.
Results: The heterogeneity of decision-makers in a population improved the overall benefit of treatment under some conditions.
Discussion: 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. It would be further suggested to investigate the effects of heterogeneity of decision-making in other fashions, such as genetic heterogeneity and phenotypic heterogeneity.
Author Comment
This is a submission to PeerJ for review.