Little is known about whether health insurance policies, particularly in developing countries, influence breast cancer prognosis. We aimed to examine the association between individual health insurance coverage plan among patients with invasive breast cancer in China and risks of breast cancer-specific mortality.
We included 7,436 women diagnosed with invasive breast cancer between January 1st, 2009, and December 31st, 2016, at West China Hospital, Sichuan University. The health insurance plan of each patient was classified into urban and rural schemes by insurance type, as well as low (0-69%) and high (70%-100%) reimbursement rate by the median. Cancer-specific mortality (i.e., death due to breast cancer) was the primary outcome, while overall mortality was the secondary outcome. Adjusting for multiple demographic and clinical covariates, we used Cox proportional hazards model, to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) of cancer-specific mortality, contrasting rates among patients with a rural scheme or low reimbursement rate to that of those with an urban scheme or high reimbursement rate, respectively.
During the median follow-up of 3.1 years, we identified 372 deaths, of which 326 (87.6%) were due to breast cancer. Compared with patients insured by an urban scheme, patients under rural scheme were at 35% increased rate of cancer-specific mortality (95% CI 5% to 72%) after adjusting for demographics, tumor characteristics and treatment modes. Patients at low reimbursement rate were at 42% increased rate of cancer-specific mortality (95% CI 11% to 81%) as compared to patients at high reimbursement rate. Importantly, every increase of 10% at reimbursement rate was associated with 7% (95% CI, 2% to 12%) reduction in rates of cancer-specific mortality. Greater risk reductions were observed particularly in patients insured by rural scheme (28%, 95% CI 12% to 41%).
Our findings suggest that under-insured breast cancer patients in China face increased risk of cancer-specific mortality.
We would like to thank all staff members working on the Breast Cancer Information Management System (BCIMS) for their contributions to data collection and management. We also thank Dr. Bo Fu, Ms. Yan Li, and Mr. Pei Liu at the University of Electronic Science and Technology of China for data cleaning and zip code mapping.
West China Hospital, Sichuan University, Chengdu, China.
National Natural Science Foundation of China (grant number 81872307), Swedish Research Council (grant number 2018-00648), Karolinska Institutet Research Foundation (grant number 2018-01585) and the Key Research and Development Project of Sichuan Province of China (Grant No. 2017SZ0005).
All authors have declared no conflicts of interest.