Lung Cancer-Specific Mortality Risk and Public Health Insurance

A Prospective Cohort Study in Chongqing, Southwest China

Bibliographic Data

ID22091020
AuthorsYuqi Wang (0009-0000-8683-4185, Chongqing University), Haike Lei (0000-0003-0284-2052, Chongqing University), Xiaosheng Li (0000-0001-8526-7094, Chongqing University), Wei Zhou (0000-0002-0849-1524, Chongqing University), Guixue Wang (0000-0002-9192-8757, Chongqing University), Anlong Sun (Chongqing University), Ying Wang (0000-0003-3126-1134, Chongqing University), Yongzhong Wu (0000-0001-8367-3347, Chongqing University, corresponding author), Bin Peng (0000-0001-5672-2086, Chongqing Public Health Medical Center, corresponding author)
Year2022
Volume10
Pages842844-842844
Publication date2022-04-29
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.842844
PMID35570974
OpenAlexW4225153254
LanguageEN
Citations received4
References cited25

Objective The incidence and mortality of lung cancer rank first among malignant tumors, and its long treatment cycle will bring serious economic burdens to lung cancer patients and their families. There are few studies on the prognosis of lung cancer and insurance policies. This article explores the relationship between the lung cancer-specific death and public health insurance, self-paying rate, and the joint effect of public health insurance and self-paying rate. Materials and Methods A prospective longitudinal cohort study was conducted in Chongqing, China from 2013 to 2019. The selected subjects were patients with C33–C34 coded according to the tenth edition of the International Classification of Diseases (ICD-10), aged 20 years or older. We conduct a subgroup analysis based on public health insurance types and self-paying rates. After following the inclusion and exclusion criteria, the chi-square test was used to describe the demographic and clinical characteristics of patients with different insurance types and different self-paying rates. Multivariate logistic regression was used to analyze the relationship between patients with different insurance types, self-paying rates, and lung cancer treatment methods. Finally, the Cox proportional hazard model and the competitive risk model are used to calculate the cumulative hazard ratio of all-cause death and lung cancer-specific death for different insurance types and different self-paying rate groups. Results A total of 12,464 patients with lung cancer were included in this study. During the follow-up period (median 13 months, interquartile range 5.6–25.2 months), 5,803 deaths were observed, of which 3,781 died of lung cancer. Compared with patients who received urban resident-based basic medical insurance (URBMI), patients who received urban employee-based basic medical insurance (UEBMI) had a 38.1% higher risk of lung cancer-specific death (Hazard Ratios (HRs) = 1.381, 95% confidence interval (CI): 1.293–1.476, P < 0.005), Compared with patients with insufficient self-paying rate, patients with a higher self-paying rate had a 40.2% lower risk of lung cancer-specific death (HRs = 0.598, 95% CI: 0.557–0.643, P < 0.005). Every 10% increase in self-paying rate of URBMI reduces the risk of lung cancer-specific death by 17.6%, while every 10% increase in self-paying rate of UEBMI reduces the risk of lung cancer-specific death by 18.0%. Conclusions The National Medical Security Administration should, under the condition of limited medical insurance funds, try to include the original self-paid anti-tumor drugs into the national medical insurance coverage. This can not only reduce the mortality rate of lung cancer patients, but also reduce the family burden of lung cancer patients. On the other hand, high-risk groups should increase their awareness of lung cancer screening and actively participate in the national cancer screening project led by the state

Cancer · Cohort · Confidence interval · Hazard ratio · Interquartile range · Lung cancer · Pathology · Proportional hazards model · Prospective cohort study · Public health · Demography · Economic and Financial Impacts of Cancer · Global Cancer Incidence and Screening · Healthcare Systems and Reforms · Medicine · Internal Medicine

Tools

Open DOIOpen Access