Background: The purpose of this study was to examine the extent to which patterns of intensive end-of-life care explain geographic variation in end-of-life care expenditures among cancer decedents. Methods: Using the SEER-Medicare database, we identified 90,465 decedents who were diagnosed with cancer in 2004–2011. Measures of intensive end-of-life care included chemotherapy received within 14 days of death; more than 1 emergency department visit, more than 1 hospitalization, or 1 or more intensive care unit (ICU) admissions within 30 days of death; in-hospital death; and hospice enrollment less than 3 days before death. Using hierarchical generalized linear models, we estimated risk-adjusted expenditures in the last month of life for each hospital referral region and identified key contributors to variation in expenditures. Results: The mean expenditure per cancer decedent in the last month of life was $10,800, ranging from $8,300 to $15,400 in the lowest and highest expenditure quintile areas, respectively. There was considerable variation in the percentage of decedents receiving intensive end-of-life care intervention, with 41.7% of decedents receiving intensive care in the lowest quintile of expenditures versus 57.9% in the highest quintile. Regional patterns of late chemotherapy or late hospice use explained only approximately 1% of the expenditure difference between the highest and lowest quintile areas. In contrast, the proportion of decedents who had ICU admissions within 30 days of death was a major driver of variation, explaining 37.6% of the expenditure difference. Conclusions: Promoting appropriate end-of-life care has the potential to reduce geographic variation in end-of-life care expenditures.
Shi-Yi Wang, Jane Hall, Craig E. Pollack, Kerin Adelson, Amy J. Davidoff, Jessica B. Long and Cary P. Gross
Shi-Yi Wang, Tiange Chen, Weixiong Dang, Sarah S. Mougalian, Suzanne B. Evans and Cary P. Gross
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.
Brigette A. Davis, Jenerius A. Aminawung, Maysa M. Abu-Khalaf, Suzanne B. Evans, Kevin Su, Rajni Mehta, Shi-Yi Wang and Cary P. Gross
Background: Racial disparities have been reported in breast cancer care, yet little is known about disparities in access to gene expression profiling (GEP) tests. Given the impact of GEP test results, such as those of Oncotype DX (ODx), on treatment decision-making for hormone receptor–positive (HR+) breast cancer, it is particularly important to assess disparities in its use. Methods: We conducted a retrospective population-based study of 8,784 patients diagnosed with breast cancer in Connecticut during 2011 through 2013. We assessed the association between race, ethnicity, and ODx receipt among women with HR+ breast cancer for whom NCCN does and does not recommend ODx testing, using bivariate and multivariate logistic analyses. Results: We identified 5,294 women who met study inclusion criteria: 83.8% were white, 6.3% black, and 7.4% Hispanic. Overall, 50.9% (n=4,131) of women in the guideline-recommended group received ODx testing compared with 18.5% (n=1,163) in the nonrecommended group. More white women received the ODx test compared with black and Hispanic women in the recommended and nonrecommended groups (51.4% vs 44.6% and 47.7%; and 21.2% vs 9.0% and 9.7%, respectively). After adjusting for tumor and clinical characteristics, we observed significantly lower ODx use among black (odds ratio [OR], 0.64; 95% CI, 0.47–0.88) and Hispanic women (OR, 0.59; 95% CI, 0.45–0.77) compared with white women in the recommended group and in the guideline-discordant group (blacks: OR, 0.39; 95% CI, 0.20–0.78, and Hispanics: OR, 0.44; 95% CI, 0.23–0.85). Conclusions: In this population-based study, we identified racial disparities in ODx testing. Disparities in access to innovative cancer care technologies may further exacerbate existing disparities in breast cancer outcomes.