HSR&D Citation Abstract
Search | Search by Center | Search by Source | Keywords in Title
Understanding why rheumatoid arthritis patient treatment preferences differ by race.
Constantinescu F, Goucher S, Weinstein A, Smith W, Fraenkel L. Understanding why rheumatoid arthritis patient treatment preferences differ by race. Arthritis Rheum. 2009 Apr 15; 61(4):413-8.
OBJECTIVE: Rheumatoid arthritis (RA) patient preferences may account for some of the variability in treatment between racial groups. How and why treatment preferences differ by race is not well understood. We sought to determine whether African American and white RA patients differ in how they evaluate the specific risks and benefits related to medications. METHODS: A total of 136 RA patients completed a conjoint analysis interactive computer survey to determine how they valued the specific risks and benefits related to treatment characteristics. The importance that respondents assigned to each characteristic and the ratio of the importance that patients attached to overall benefit versus overall risk were calculated. Subjects having a risk ratio < 1 were classified as being risk averse. RESULTS: The mean age of the study sample was 55 years (range 22-84). Forty-nine percent were African American and 51% were white. African American subjects assigned the greatest importance to the theoretical risk of cancer, whereas white subjects were most concerned with the likelihood of remission and halting radiographic progression. Fifty-two percent of African American subjects were found to be risk averse compared with 12% of the white subjects (P < 0.0001). Race remained strongly associated with risk aversion (adjusted odds ratio [95% confidence interval] 8.4 [3.1, -23.1]) after adjusting for relevant covariates. CONCLUSION: African American patients attach greater importance to the risks of toxicity and less importance to the likelihood of benefit than their white counterparts. Effective risk communication and improved understanding of expected benefits may help decrease unwanted variability in health care.