Predictors of utilities for health states in early stage prostate cancer

Department of Urology, University of California-Los Angeles, Los Angeles, CA 90095-1738, USA.
The Journal of Urology (Impact Factor: 4.47). 10/2001; 166(3):942-6. DOI: 10.1097/00005392-200109000-00031
Source: PubMed


When faced with treatment choices for early stage prostate cancer, patients must balance the survival benefit of a treatment with its morbidity. Little is known about how patients balance these trade-offs. To further our understanding of patient decision making we assessed patient utilities for prostate cancer treatment related morbidities. We determined whether patient utilities were predicted by sociodemographic characteristics or baseline genitourinary function.
We evaluated 401 men undergoing prostate needle biopsy for suspicion of prostate cancer at university, Veterans Affairs and public hospitals. Study design included a prospective cross-sectional cohort with correlation and multivariate analysis. Subjects were studied with 2 established health related quality of life instruments. Patient utilities were assessed with an interactive software application.
On multivariate analysis utility for current general health was a significant predictor of utilities for treatment related morbidities. Surprisingly baseline urinary, sexual and bowel function scores did not correlate well with respective utilities for potential incontinence, impotence or radiation proctitis. In other words, men with good and imperfect baseline function were equally willing to risk impairment to preserve life.
Men who perceived that general health was better appear to place higher value on quantity of life, while those who already are suffering from poor general health place higher value on quality of life. Ethnicity appears to modify some effects of other variables on patient preference. Utility assessment provides a quantitative tool to aid physicians in counseling patients when making treatment decisions for localized prostate cancer.

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    • "Some factors have been shown to be associated with subjective preferences for treatment. For instance, age [6-8], ethnicity[7], marital status[9], education[9], current general health [7], and baseline sexual and urological functions[6-8,10] have been shown to be associated with prostate cancer utilities in previous studies. However, the findings remain inconsistent in predicting prostate cancer treatment utilities. "
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    ABSTRACT: Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction. Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals' preferences for health states given similar treatments and clinical risks. Using latent class mixture model (LCA), we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states) and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups. The sample (N=244) included men with prostate cancer (n=188) and men at-risk for disease (n=56). The sample was predominantly white (77%), with mean age of 60 years (SD+/-9.5). Most (85.9%) were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC), substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of <.001. The three identified clusters were named high-traders (n=31), low-traders (n=116), and no-traders (n=97). High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment. Low-traders were less likely to trade survival time and accepted risks of treatment. The no-traders were likely to make no trade-offs in any direction favouring the status quo. There was significant difference among the clusters in the importance of sexual activity (Pearson's chi2=16.55, P=0.002; Goodman and Kruskal tau=0.039, P<0.001). In multinomial logistic regression, the level of importance assigned to sexual activity remained an independent predictor of class membership. Age and prostate cancer/at-risk status were not significant factors in the multinomial model. Most existing utility work is undertaken focusing on how people choose on average. Distinct clusters of prostate cancer treatment utilities in our sample point to the need for further understanding of subgroups and need for tailored assessment and interventions.
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