High out-of-pocket costs may impact anticancer treatment uptake. The Low-Income Subsidy (LIS) program can reduce patient out-of-pocket cost for Medicare Part D-covered treatments. We examined whether the LIS increased uptake and reduced time to initiate orally administered anticancer drugs in patients with advanced non-small cell lung cancer (NSCLC). Methods: Using Surveillance, Epidemiology and End Results (SEER)-Medicare data, we identified older adults (aged 65 years and older) diagnosed with advanced NSCLC from 2007 through 2013 and categorized them as full LIS, partial LIS, or non-LIS. We used propensity-score weighted (IPTW) Cox proportional hazards regression to assess the likelihood of and time to initiate Part D treatments. Part B medication uptake was our negative control because supplemental insurance reduces out-of-pocket costs for those drugs. All statistical tests were two-sided. Results: Among 19 746 advanced NSCLC patients, approximately 10% initiated Part D treatments. Patients with partial or no LIS were less likely to initiate Part D treatments than were those with full subsidies (partial LIS vs full LIS HRIPTW = 0.77, 95% confidence interval = 0.62 to 0.97; non-LIS vs full LIS HRIPTW = 0.87, 95% confidence interval = 0.79 to 0.95). Time to initiate Part D treatments was also slightly shorter among full-LIS patients (full LIS mean [SD] = 10.8 [0.04] months; partial LIS mean [SD] = 11.3 [0.08] months; and non-LIS mean [SD] = 11.1 [0.03] months, P <. 001). Conversely, patients with partial or no LIS had shorter time to initiation of Part B drugs. Conclusions: Patients receiving the full LIS had higher orally administered anticancer treatment uptake than patients without LIS. Notably, patients with partial LIS had the lowest treatment uptake, likely because of their low incomes combined with high expected out-of-pocket spending. High out-of-pocket costs for Part D medications may be a barrier to treatment use for patients without full LIS.
Bibliographical noteFunding Information:
This was an unfunded project. The database infrastructure used for this project was funded by the CER Strategic Initiative of UNC’s Clinical &Translational Science Award (UL1TR001111) and the UNC School of Medicine. Additional funding for the SEER-Medicare data was provided by the UNC Lineberger Comprehensive Cancer Center’s University Cancer Research Fund via the State of North Carolina.
The collection of cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885 and the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201000140C, awarded to the Cancer Prevention Institute of California; contract HHSN261201000035C, awarded to the University of Southern California; and contract HHSN261201000034C, awarded to the Public Health Institute; as well as the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement U58DP003862-01 awarded to the California Department of Public Health. The ideas and opinions expressed herein are those of the authors, and endorsement by the State of California Department of Public Health, the National Cancer Institute, and the Centers for Disease Control and Prevention or their contractors and subcontractors is not intended nor should be inferred.
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