Authors: Earle CC, Venditti LN, Neumann PJ, Gelber RD, Weinstein MC, Potosky AL, Weeks JC
Title: Who gets chemotherapy for metastatic lung cancer?
Journal: Chest 117(5):1239-46
Date: 2000 May
Abstract: STUDY OBJECTIVES: To determine the prevalence and factors associated with chemotherapy use in elderly patients presenting with advanced lung cancer. DESIGN: A retrospective cohort study using administrative data. SETTING AND PATIENTS: We analyzed the medical bills for the 6,308 Medicare patients > 65 years old with diagnosed stage IV non-small cell lung cancer (NSCLC) in the 11 SEER (survival, epidemiology, and end results) regions between 1991 and 1993. The main outcome measure, chemotherapy administration, was identified by the relevant medical billing codes. Patient sociodemographic and disease characteristics were obtained from the SEER database and census data. RESULTS: Almost 22% of patients received chemotherapy at some time for their metastatic NSCLC. As expected, younger patients and those with fewer comorbid conditions were more likely to receive chemotherapy. However, several nonmedical factors, such as nonblack race, higher socioeconomic status, treatment in a teaching hospital, and living in the Seattle/Puget Sound or Los Angeles SEER regions, also significantly increased a patient's likelihood of receiving chemotherapy. CONCLUSION: Compared to previous reports, the prevalence of chemotherapy use for advanced NSCLC appears to be increasing. However, despite uniform health insurance coverage, there is wide variation in the utilization of palliative chemotherapy among Medicare patients, and nonmedical factors are strong predictors of whether a patient receives chemotherapy. While it is impossible to know the appropriate rate of usage, nonmedical factors should only influence a patient's likelihood of receiving treatment if they reflect patient treatment preference. Research to further clarify the costs, benefits, and patient preferences for chemotherapy in this patient population is warranted in order to minimize the effect of nonmedical biases on management decisions.
Last Updated: 02 Mar 2015