Breast Cancer Recurrence Test Less Cost-Effective Than Expected
A commonly used gene expression profile test for predicting breast cancer recurrence proves to be less cost-effective in a real-world setting, according to research published in the Journal of Clinical Oncology (online January 8, 2018; doi:10.1200/JCO.2017.74.5034).
Gene expression profile testing is used to support chemotherapy decision making for patients with early-stage, estrogen receptor-positive (ER+), human epidermal growth factor 2-negative (HER2-) breast cancer. The most commonly used gene expression profile test, Oncotype DX, has demonstrated cost-effectiveness in clinical trials, but real-world evidence on its cost implications are lacking.
Young Chandler, DrPH, MS, MPH, assistant professor of oncology, Georgetown University School of Medicine, and colleagues evaluated the cost-effectiveness of Oncotype DX in community practice. Test-eligible patients were predefined as 40 to 79 years of age. Researchers used a simulation model to compare 25-year societal incremental costs and quality-adjusted life-years (QALYs) of community Oncotype DX use from 2005 to 2012 versus usual care in the pre-testing era (2000 to 2004). Inputs into the model included test and chemotherapy data from an integrated health care system and national and published data on Oncotype DX accuracy, chemotherapy effectiveness, utilities, survival and recurrence, and Medicare and patient costs.
Researchers acknowledged that 24% of test-eligible patients had Oncotype DX testing, and that testing was higher in younger patients or those with stage I disease.
Results of the evaluation yielded a cost-effectiveness ratio for testing (versus usual care) of $188,125 per QALY. The cost-effectiveness ratio decreased to $58,431 per QALY after considerations of test effects on worry versus reassurance.
Researchers also noted that with perfect test accuracy, the cost-effectiveness ratio was $28,947 per QALY, while under ideal conditions the ratio was $39,496 per QALY.
Dr Chandler and colleagues concluded that gene expression profile testing is likely to have a high cost-effectiveness ratio on the basis of community practice patterns. “The differences in cost-effectiveness ratios on the basis of community versus ideal conditions underscore the importance of considering real-world implementation when assessing the new technology,” they wrote.—Zachary Bessette