Socioeconomic status and survival outcomes in elderly cancer patients: A national health insurance service‐elderly sample cohort study

• Published in: Cancer medicine (Malden, MA) Vol. 8; no. 7; pp. 3604 - 3613
• Main Authors: Jang, Bum‐Sup, Chang, Ji Hyun
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.07.2019; John Wiley and Sons Inc; Wiley
• Subjects: Age Factors; Aged; Aged, 80 and over; Cancer; cancer mortality; Cancer Prevention; Cancer therapies; Cause of Death; Cohort analysis; Comorbidity; elderly; Esophagus; Expenditures; Family income; Female; Geriatrics; Gynecology; Health insurance; Households; Humans; income; Kaplan-Meier Estimate; Liver; Low income groups; Male; Medical aid; Medical diagnosis; Melanoma; Middle Aged; Mortality; Multivariate analysis; Neoplasms - diagnosis; Neoplasms - epidemiology; Neoplasms - mortality; Older people; Original Research; Patient Outcome Assessment; Patients; Per capita; Population studies; Proportional Hazards Models; Prostate; Public health; regional deprivation; Researchers; Risk Factors; Social Class; Social networks; Socioeconomic Factors; Socioeconomic status; Studies; Survival; income; Socioeconomic status; regional deprivation; elderly; cancer mortality
• ISSN: 2045-7634; 2045-7634
• DOI: 10.1002/cam4.2231

Background We hypothesized that lower socioeconomic status (SES) was associated with higher all‐cause mortality in patients newly diagnosed with cancer, particularly in the elderly population. Methods We collected study patients from the stratified random sample of Korean National Health Insurance Elderly Cohort (2002‐2015). The Cox's proportional hazards model was used to investigate the risk factors for mortality. Income level and composite deprivation index (CDI) 2010 were used to define the SES: low, intermediate, and high SES groups. The comorbidities were measured using Charlson Comorbidity Index score. After a wash‐out period (2002), the final study population was 108 626 (2003‐2015). Results In multivariate analysis, low SES was associated with poor overall survival (OS) (HR = 1.08, 95% CI: 1.05‐1.12, P < 0.001) and cancer‐specific survival (CSS) (HR = 1.11, 95% CI: 1.06‐1.16, P < 0.001) particularly for patients aged 70‐79 years. High SES was favorable prognostic factor of OS in patients aged 60‐69 years (HR = 0.85, 95% CI: 0.81‐0.89, P < 0.001), 70‐79 years (HR = 0.90, 95% CI: 0.87‐0.93, P < 0.001), and ≥80 years (HR = 0.91, 95% CI: 0.87‐0.96, P < 0.001). However, SES was not associated with CSS in advanced age patients (≥80 years). Patients with low SES manifesting colorectal, urinary, liver, gastric, melanoma, and esophageal cancers demonstrated worse OS, compared to patients with intermediate SES. Also, low SES patients with urinary, liver, or colorectal cancers or melanoma demonstrated worse CSS compared to those with intermediate SES. Conclusion Low SES at the time of cancer diagnosis is associated with increased risk of OS and CSS in elderly patients. Depending on cancer sites, different patterns of OS and CSS were observed according to SES. Further elucidation of the causes underlying these phenomena is needed along with appropriate support for elderly cancer patients with low SES. The socioeconomic status was associated with cancer‐specific survival as well as overall survival in elderly cancer patients (age 65 ≥ years). This study analyzed the data of 108 626 cancer patients in the national health care database, raising the issue about disparities among elderly cancer patients.