1032 - The Impact of National Cancer Systems on Lung Cancer Mortality
Presenter(s)
E. C. Dee1, J. Willmann2,3, E. J. G. Feliciano4, J. F. Wu5, C. D. U. Ang6, F. Y. Y. Moraes7, D. R. Gomez1, C. Faivre-Finn8, N. Y. Lee1, M. Guckenberger2, and P. Iyengar1; 1Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 2Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland, 3Memorial Sloan Kettering Cancer Center, New York, NY, 4NYC Health + Hospitals/Elmhurst, Queens, NY, 5Medical College of Wisconsin, Milwaukee, WI, 6University of Santo Tomas Hospital, Manila, Philippines, 7Queen's University Global Oncology Program, Kingston, ON, Canada, 8The Christie NHS Foundation Trust and The University of Manchester, Manchester, United Kingdom
Purpose/Objective(s):
Lung cancer is the leading cause of cancer mortality worldwide, highlighting the need to identify factors that improve outcomes. Radiotherapy (RT) is essential in lung cancer treatment, but disparities in RT access may drive outcome variations. This study explores the relationship between RT center density (number of RT centers per 1,000 population) and lung cancer outcomes, aiming to inform health system planning and guide investments in RT infrastructure to reduce the global burden of lung cancer.Materials/Methods:
We used publicly available global health system data from the World Health Organization (WHO), the World Bank, the Directory of Radiotherapy Centres (DIRAC), the United Nations Development Programme (UNDP), and the International Agency for Research on Cancer (IARC) to evaluate predictors of improved global lung cancer outcomes (defined as lung cancer mortality-to-incidence ratio from the IARC’s GLOBOCAN data). The number of radiotherapy centers per country was taken from Directory of Radiotherapy Centres (DIRAC). Population data from 2023 (World Bank) were used to derive number of radiotherapy centers per 1000 population. Additionally, the following variables were selected, which were hypothesized to have a potential impact on lung cancer outcomes: health spending as a percent of GDP, physicians per 1000 population, nurses and midwives per 1000 population, surgical workforce per 1000 population, Universal Health Coverage Service Coverage Index (UHC index), availability of pathology services, Human development index (HDI) and gender inequality index (GII). The association between lung MIR and each health system metric was evaluated using univariable linear regression models. Multivariable models were built using forward selection, upon correcting for multicollinearity using variance inflation factor (VIF) analysis.Results:
In total, 185 countries’ data were included based on the availability of cancer incidence and mortality data. On univariable analysis, each metric was significantly associated with MIR of lung cancer (P<0.001 for all). The final model with eight metrics had an R2 of 0.70 (N=123 countries had complete data). VIF for all eight metrics was <10. On multivariable analysis, the following variables were independently associated with lower (improved) MIR for lung cancer: 1) radiotherapy centers per 1000 population, 2) health spending as % of GDP, 3) physicians per 1000 population, 4) nurses/midwives per 1000 population, and 5) UHC index.Conclusion:
Using global data and adjusting for health spending and workforce variables, our analysis highlights the impact of radiotherapy availability on lung cancer outcomes. These findings emphasize radiotherapy access as a key factor, alongside health spending and workforce capacity, in improving lung cancer care outcomes.