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Patient decisions about breast cancer chemoprevention: a systematic review and meta-analysis
Mary E Ropka1, Jess Keim, John T Philbrick
1Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. mer2e@virginia.edu
Purpose:
Women at high risk of breast cancer face the complex decision of whether to take tamoxifen or raloxifene for breast cancer chemoprevention. We investigated what is known about decisions of women regarding chemoprevention.
Methods:
Using MEDLINE, CINAHL, and PSYCINFO, plus reviewing reference lists of relevant articles, in December 2009 we identified 13 studies that addressed patient decisions about breast cancer chemoprevention, were published in 1995 or later, were peer-reviewed primary clinical studies, and reported rates at which participants showed interest in (hypothetical uptake) or accepted (real uptake) chemoprevention medications.
Results:
Nine studies provided information about hypothetical breast cancer chemoprevention decisions (mean uptake rate, 24.7%) and five provided information about real decisions (mean uptake rate, 14.8%). The range of rates was wide, and each of the hypothetical uptake studies assessed interest differently. A logistic regression model found significant correlation with uptake of decision type (hypothetical versus real, odds ratio [OR] = 1.65; 95% CI, 1.26 to 2.16), educational or decision support intervention (provided v not, OR = 0.21; 95% CI, 0.17 to 0.27), and cohort risk for breast cancer (high-risk v general population, OR = 0.65; 95% CI, 0.56 to 0.75). Perceived vulnerability to breast cancer was consistently correlated with increased uptake, and concern for adverse effects was correlated with reduced uptake. All studies used a correlational/descriptive design, and most studies used convenience sampling strategies.
Conclusion:
Breast cancer chemoprevention uptake rates are low and variation is wide. Hypothetical uptake rates are higher than real uptake, and interventions markedly reduce uptake. Research is needed that uses reproducible sampling methods and examines decision support strategies that lead to quality decisions.
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