# Medical decision analysis for personalized oncology at the patient bedside

## TL;DR

This paper promotes using medical decision analysis to help doctors make personalized cancer treatment choices by combining probabilities and values at the patient's bedside.

## Contribution

The paper introduces practical templates for applying medical decision analysis to common cancer treatment decisions.

## Key findings

- Medical decision analysis can help with trade-offs in curable cancer and treatment timing.
- It supports decisions on active surveillance and advanced cancer treatment.
- Its value increases with decision complexity and can enhance medical education.

## Abstract

Medical decision analysis is a method to make rational clinical decisions under uncertainty, enabling a mathematical combination of probabilities and utilities (i.e. values assigned to outcomes under risk). Decision analysis is commonly used in health economics, but it is underexploited in the clinic. With a view to fostering the use of medical decision analysis at the cancer patient bedside, this paper provides basic templates for some typical clinical decisions in cancer treatment, namely affecting: the quantity/quality of life trade-offs in curable cancer; adjuvant/neoadjuvant treatments; cytoreductive treatments; active surveillance / watchful waiting choices; treatment of advanced cancer; cancer follow-up. The clinical use of medical decision analysis is challenged by several difficulties, which are briefly recalled. Contrary to clinical research, medical decision analysis does not build new evidence: it simply provides physicians with a method to personalize clinical decisions on the basis of available evidence. Its added value in clinical practice correlates with the complexity of a decision. However, it also has a great potential in medical education, in order to empower clinicians with skills improving their ability to rationally shape medical decisions and share them properly with their patients.