Socioeconomic Disparities in Lung Cancer Treatment and Outcomes Persist Within a Single Academic Medical Center

Abstract

Background Socioeconomic disparities in treatment and outcomes of non-small cell lung cancer (NSCLC) are well established. To explore whether these differences are secondary to individual or institutional characteristics, we examined treatment selection and outcome in a diverse population treated at a single medical center. Patient and Methods We performed a retrospective analysis of consecutive patients diagnosed with NSCLC stages I-III from 2000-2005 at the University of Texas Southwestern Medical Center. Treatment selection was dichotomized as “standard” (surgery for stage I-II; surgery and/or radiation therapy for stage III) or “other.” Associations between patient characteristics (including socioeconomic status) and treatment selection were examined using logistic regression; associations between characteristics and overall survival were examined using Cox regression models and Kaplan-Meier survival analysis. Results A total of 450 patients were included. Twenty-eight percent of patients had private insurance, 43% had Medicare, and 29% had an indigent care plan. The likelihood of receiving “standard” therapy was significantly associated with insurance type [indigent plan versus private insurance OR 0.13 (95% CI 0.04-0.43) for stage I-II; OR 0.38 (95% CI 0.14-1.00) for stage III]. For patients with stage I-II NSCLC, survival was associated with age, gender, insurance type (indigent plan versus private insurance HR 1.98; 95% CI 1.16-3.37), stage, and treatment selection. In stage III NSCLC, survival was associated with treatment selection. Conclusion Within a single academic medical center, socioeconomically disadvantaged patients with stage I-III NSCLC are less likely to receive “standard” therapy. Socioeconomically disadvantaged patients with stage I-II NSCLC have inferior survival independent of therapy.

Elimination of socioeconomic and racial disparities related to lung cancer: Closing the gap at a high volume community cancer center

“…In their study, they argue that insurance type is a better classification method for SES because it is specific to the patient, regardless of zip code, and because other studies show it to be a better representation of wealth than by using indicators of income alone [4, 24]. Therefore, we chose to investigate survival differences in patients with different insurance types as an independent variable of wealth.…”

“…Lung cancer in particular, which remains the leading cause of cancer related death in the United States, is a major focus for measuring disparities as discussed in several studies [4–6]. For instance, it has been documented that African-Americans, Hispanics and those with low socioeconomic status have higher incidence and mortality rates of lung cancer when compared to non-Hispanic whites and those with high socioeconomic status [7].…”

Effects of Delayed Surgical Resection on Short-Term and Long-Term Outcomes in Clinical Stage I Non-Small Cell Lung Cancer

“…Previous studies have documented how disparities in receiving care according to practice guidelines can persist at academic centers. [25] Prospective tracking of patients from the time of initial suspicion of lung cancer could help define which intervals in the surgical evaluation process are associated with delays in an institution specific manner. With an anticipated increase in early stage lung cancer diagnoses through expanded screening coverage, ensuring timely surgical care for the patients will become even more pressing.…”

Disparities in overall and urothelial carcinoma specific mortality associated with healthcare insurance status

“…Insurance plans that are based on income level cutoffs, such as Medicaid and Massachusetts Free Care, were characterized as lower SES-associated plans. We grouped patients who had purchased supplemental Medigap or Medicare Advantage plans as high SES-associated plans and those who had not purchased supplemental coverage as lower SES-associated plans [11][12][13][14]. Median zip code income and local poverty level was determined by search of the individual zip code of residence in the 2000 US census [15,16] and used to confirm the association of SES measures with the insurance plan groups.…”

“…SES [1,11,12]. The strength of this measure is that particularly for lower SES-associated health insurance plans, an individual review of income is performed on each patient to justify the taxpayer subsidy that often accompanies inclusion in the plan.…”