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Med Care. 2006 Dec;44(12):1137-41.

The influence of patient race and social vulnerability on urologist treatment recommendations in localized prostate carcinoma.

Author information

1
General Internal Medicine, University of Colorado Health Sciences Center, Denver, CO 80262, USA. tom.denberg@uchsc.edu

Abstract

BACKGROUND:

In localized prostate carcinoma (PCa), many studies have found that black subjects receive radical prostatectomy (RP) less often than white subjects. Such disparities involve barriers to health care, comorbid illnesses, tumor characteristics, and patient preferences. It is unclear whether differences in urologist treatment recommendations also might play a role.

METHODS:

Using a randomized, 2 x 2 factorial design, we presented 2000 urologists with a clinical vignette and asked them to recommend treatment of a healthy 70-year-old patient with low-risk, clinically localized PCa. Options included either RP, external beam radiotherapy, brachytherapy, cryotherapy, observation, or hormonal therapy. There were 2 variables within 4 otherwise-identical versions of the vignette: 1) patient race (black vs. white) and 2) social vulnerability (middle-income and married vs. low-income and widowed). We used multivariable logistic regression to model the effects of patient race, social vulnerability, and their interaction on recommendations for RP versus radiotherapy.

RESULTS:

The response rate was 66.1% (n = 1313). Race and social vulnerability interacted (P = 0.05) such that the highly vulnerable black patient received an RP recommendation 14.4% less often than his less vulnerable counterpart; the difference between the 2 white patients was 4.2%.

DISCUSSION:

Race interacts with social vulnerability to influence urologist recommendations for RP. Because PCa tends to be more lethal in blacks, urologists may view such patients as good candidates for RP. However, black race may amplify perceptions of social vulnerability, heightening urologists' concerns about poor surgical outcomes and follow-up. These findings affirm the importance of modeling interactions between race/ethnicity and other social variables in health disparities research.

[Indexed for MEDLINE]

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