A personalized decision aid for prostate cancer shared decision making

Abstract

Background A shared decision-making model is preferred for engaging prostate cancer patients in treatment decisions. However, the process of assessing an individual’s preferences and values is challenging and not formalized. The purpose of this study is to develop an automated decision aid for patient-centric treatment decision-making using decision analysis, preference thresholds and value elicitations to maximize the compatibility between a patient’s treatment expectations and outcome. Methods A template for patient-centric medical decision-making was constructed. The inputs included prostate cancer risk group, pre-treatment health state, treatment alternatives (primarily focused on radiation in this model), side effects (erectile dysfunction, urinary incontinence, nocturia and bowel incontinence), and treatment success (5-year freedom from biochemical failure). A linear additive value function was used to combine the values for each attribute (side effects, success and the alternatives) into a value for all prospects. The patient-reported toxicity probabilities were derived from phase II and III trials. The probabilities are conditioned on the starting state for each of the side effects. Toxicity matrices for erectile dysfunction, urinary incontinence, nocturia and bowel incontinence were created for the treatment alternatives. Toxicity probability thresholds were obtained by identifying the patient’s maximum acceptable threshold for each of the side effects. Results are represented as a visual. R and Rstudio were used to perform analyses, and R Shiny for application creation. Results We developed a web-based decision aid. Based on preliminary use of the application, every treatment alternative could be the best choice for a decision maker with a particular set of preferences. This result implies that no treatment has determinist dominance over the remaining treatments and that a preference-based approach can help patients through their decision-making process, potentially affecting compliance with treatment, tolerance of side effects and satisfaction with the decision. Conclusions We present a unique patient-centric prostate cancer treatment decision aid that systematically assesses and incorporates a patient’s preferences and values to rank treatment options by likelihood of achieving the preferred outcome. This application enables the practice and study of personalized medicine. This model can be expanded to include additional inputs, such as genomics, as well as competing, concurrent or sequential therapies.

A pooled long-term follow-up after radiotherapy for prostate cancer with and without a rectal hydrogel spacer: impact of hydrogel on decline in sexual quality of life

“…The impact of prostate cancer treatment on sexual function has a substantial influence upon men’s decisions in regard to treatment and upon both their QOL and regret following treatment ( 19 – 21 ). In men that do have adequate erectile function who are treated with RT, we still lack clear comprehensive data for all potential organs at risk, which lead to sexual decline after RT ( 7 , 22 ).…”

Prediction models of incontinence and sexual function one year after radical prostatectomy based on data from 20 164 prostate cancer patients

“…In this way, the results presented here can be applied directly in oncological care, e.g. in joint physician-patient discussions [32]. For future initiatives, however, the inclusion of longer timeframes (such as prediction of functional impairments after 24 months) would be desirable to strengthen the possible care implications even more (e.g.…”

Taking shared decision making for prostate cancer to the next level: Requirements for a Dutch treatment decision aid with personalized risks on side effects

“…To date, none of the PDAs for prostate cancer treatment were personalized in terms of outcome probabilities ( Vromans et al, 2019 ). Only recently, Bagshaw et al (2021) developed a personalized PDA with toxicity tables for the most common side effects, relating pre-treatment health state to the probability of a certain post-treatment health state for different radiation modalities. This PDA, in which men can also incorporate preference thresholds, assign value and evaluate alternative treatments, is currently evaluated in practice.…”