title: Pilot study of a utilities-based treatment decision intervention for prostate cancer patients.
abstract: This pilot study evaluates a shared decision-making approach to individual decision making in localized prostate cancer care. The approach is based on a decision analytic model that incorporates patient utilities, ie, patient preferences among possible health states that might occur with prostate cancer treatments. Data on comorbidities, histologic grade of the biopsy, and age were obtained for 13 patients with newly diagnosed localized prostate cancer who received care in a Veterans Administration medical center. Using a standard gamble technique, interviewers obtained patient utilities for 5 distinct health states related to prostate cancer treatment. Utilities and patient clinical and pathologic characteristics were incorporated into the decision analytic model, and the derived quality-adjusted life expectancies were shared with the treating urologist before the first patient-physician discussion about treatment options. The results of the pilot study raised 2 major concerns. First, 4 patients had utility scores of 1.0 for all of the possible health states, and 7 patients had inconsistent utilities in which they rated both impotence and incontinence as a better health state than having just one of these problems. Second, the model recommended radiation therapy to individuals with a broad range of clinical characteristics, pathologic findings, and utility scores. Many of the patients who were recommended radiation therapy by the model received discordant recommendations from the treating urologist. Future refinements of both the utility assessment exercise and decision analytic model may be needed before the feasibility of the model in the clinical setting can be determined.
authors.affiliation: San Francisco VA Medical Center, Department of Psychiatry, University of California at San Francisco, CA, USA.
authors.forename: Sara J
authors.initials: SJ
authors.lastname: Knight
authors.forename: Derek P
authors.initials: DP
authors.lastname: Nathan
authors.forename: Amy K
authors.initials: AK
authors.lastname: Siston
authors.forename: Michael W
authors.initials: MW
authors.lastname: Kattan
authors.forename: Arthur S
authors.initials: AS
authors.lastname: Elstein
authors.forename: Kathleen M
authors.initials: KM
authors.lastname: Collela
authors.forename: Michael S
authors.initials: MS
authors.lastname: Wolf
authors.forename: Nicholas S
authors.initials: NS
authors.lastname: Slimack
authors.forename: Charles L
authors.initials: CL
authors.lastname: Bennett
authors.forename: Robert M
authors.initials: RM
authors.lastname: Golub
mesh_terms: D000368:Aged; D003661:Decision Support Techniques; D018572:Disease-Free Survival; D006801:Humans; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D009367:Neoplasm Staging; D019370:Observation; D010358:Patient Participation; D018579:Patient Selection; D010865:Pilot Projects; D011336:Probability; D011379:Prognosis; D011468:Prostatectomy / Q000379:methods; D011471:Prostatic Neoplasms / Q000401:mortality / Q000473:pathology* / Q000628:therapy*; D019057:Quality-Adjusted Life Years; D011878:Radiotherapy / Q000379:methods; D012307:Risk Factors; D012680:Sensitivity and Specificity; D015996:Survival Rate; D016896:Treatment Outcome