A multi-attribute model of prostate cancer patient's preferences for health states

Multi-attribute utility theory (MAUT) provides a way to model decisions involving trade-offs among different aspects or goals of a problem. We used MAUT to model prostate cancer patients' preferences for their own health state and we compared this model to patients' global judgments of health state utility. 57 patients with prostate cancer (mean age = 70) at two Chicago Veterans Administration health clinics were asked to evaluate health states described in terms of five health attributes affected by prostate cancer: pain, mood, sexual function, bladder and bowel function, and fatigue and energy. Each attribute had three levels that were used to form three clinically realistic health state descriptions (A = high, B = moderate, C = low). A fourth personalized health description (P) matched the patient's current health. We first measured patients' preferences using time trade-off (TTO) judgments for the three health states (A, B, and C) and for their own current health state (P). The TTO for the patient's own health state (P) was standardized by comparing it to TTO judgments for states A and C. We next constructed a multi-attribute model using the relative importance of the five attributes. The MAU scores were moderately correlated with the TTO preference judgments for the personalized state (Pearson r = 0.38, N = 57, p < 0.01). Thus, patients' preference judgments are moderately consistent and systematic. MAUT appears to be a potentially feasible method for evaluating preferences of prostate cancer patients and may prove helpful in assisting with patient decision making.