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Background: Literature suggests that Oncotype DX (ODX) is cost-effective. These studies, however, tend to ignore clinical characteristics and have not incorporated population-based data regarding the distribution of ODX results across different clinical risk groups. Accordingly, this study assessed the cost-effectiveness of ODX across strata of clinical risk groups using population-based ODX data. Methods: We created state-transition models to calculate costs and quality-adjusted life years (QALYs) gained over the lifetime for women with estrogen receptor (ER)–positive, HER2-negative, lymph node–negative breast cancer from a US payer perspective. Using the Connecticut Tumor Registry, we classified the 2,245 patients diagnosed in 2011 through 2013 into 3 clinical risk groups according to the PREDICT model, a risk calculator developed by the National Health Service in the United Kingdom. Within each risk group, we then determined the recurrence score (RS) distributions (<18, 18–30, and ≥31). Other input parameters were derived from the literature. Uncertainty was assessed using deterministic and probabilistic sensitivity analyses. Results: Approximately 82.5%, 11.9%, and 5.6% of our sample were in the PREDICT low-, intermediate-, and high-risk groups, respectively. When combining these 3 groups, ODX had an incremental cost-effectiveness ratio (ICER) of $62,200 per QALY for patients aged 60 years. The ICERs, however, differed across clinical risk groups, ranging from $124,600 per QALY in the low-risk group, to $28,700 per QALY in the intermediate-risk group, to $15,700 per QALY in the high-risk group. Results were sensitive to patient age: the ICER for patients aged 45 to 75 years ranged from $77,100 to $344,600 per QALY in the PREDICT low-risk group, and was lower than $100,000 per QALY in the intermediate- and high-risk groups. Conclusions: ODX is not cost-effective for women with clinical low-risk breast cancer, which constitutes most patients with ER-positive disease.

Background: Guidelines recommend annual mammography after curative-intent treatment for breast cancer. The goal of this study was to assess contemporary patterns of breast imaging after breast cancer treatment. Methods: Administrative claims data were used to identify privately insured and Medicare Advantage beneficiaries with nonmetastatic breast cancer who had residual breast tissue (not bilateral mastectomy) after breast surgery between January 2005 and May 2015. We calculated the proportion of patients who had a mammogram, MRI, both, or neither during each of 5 subsequent 13-month periods. Multinomial logistic regression was used to assess associations between patient characteristics, healthcare use, and breast imaging in the first and fifth years after surgery. Results: A total of 27,212 patients were followed for a median of 2.9 years (interquartile range, 1.8–4.6) after definitive breast cancer surgery. In year 1, 78% were screened using mammography alone, 1% using MRI alone, and 8% using both tests; 13% did not undergo either. By year 5, the proportion of the remaining cohort (n=4,790) who had no breast imaging was 19%. Older age was associated with an increased likelihood of mammography and a decreased likelihood of MRI during the first and fifth years. Black race, mastectomy, chemotherapy, and no MRI at baseline were all associated with a decreased likelihood of both types of imaging. Conclusions: Even in an insured cohort, a substantial proportion of breast cancer survivors do not undergo annual surveillance breast imaging, particularly as time passes. Understanding factors associated with imaging in cancer survivors may help improve adherence to survivorship care guidelines.