Methodologic evaluation of adaptive conjoint analysis to assess patient preferences: an application in oncology

Abstract

Background: Adaptive conjoint analysis (ACA) is an individually tailored preferences elicitation technique that mimics actual decision-making processes by asking participants to make trade-offs between the various dimensions that underlie decision problems. ACA is increasingly applied in patient preferences assessments but formal evaluation of its validity and reliability is lacking.

Objective: To investigate ACA's validity and reliability in elicitation of treatment outcome preferences.

Methods: Sixty-eight disease-free rectal cancer patients, treated with surgery with or without preoperative radiotherapy were asked to complete exercises to assess their preferences for radiotherapy [using the treatment trade-off method (TTM)] and for key outcomes associated with radiotherapy (using ACA). We assessed (i) rank ordering of ACA-derived outcome-probability utilities, (ii) compensatory decision making, (iii) ACA test-retest reliability, and (iv) concordance of ACA- and TTM-based preferences.

Results: All participants completed the TTM and 66 completed the ACA questionnaire, in 15 min on average. Outcome utilities were rank ordered in agreement with probabilities from best to worst in most participants, except for sexual dysfunction. Most participants were willing to trade survival and their most important outcome. Mean importance ratings were similar at retest. ACA- and TTM-based preferences differed. TTM-based preferences were related to past treatment, ACA-based preferences were not.

Conclusions: ACA assesses group-level preferences reliably over time and captures individual preferences independently from treatment experience in treated cancer patients. ACA seems a valid treatment outcome preference elicitation method in a context in which trade-offs between cure and quality of life need to be considered.

Figure 1

Adaptive conjoint analysis questionnaire.