National Cancer System Characteristics and Global Pan-Cancer Outcomes.

Abstract

Approximately 29.9 million cancer cases and 15.3 million deaths are anticipated by 2040 globally, necessitating cancer system strengthening. A greater understanding of health system factors that can be leveraged to improve cancer control may guide health system planning. To evaluate predictors of improved cancer outcomes globally. This pan-cancer ecological study used the most recent available national health system metrics and cancer statistics, spanning the breadth of global income levels across 185 countries. Estimates of age-standardized mortality to incidence ratios were derived from GLOBOCAN 2022 for patients with cancer of all ages. The analysis took place on November 27, 2024. Health spending as a percent of gross domestic product (GDP), physicians per 1000 population, nurses and midwives per 1000 population, surgical workforce per 1000 population, GDP per capita, Universal Health Coverage (UHC) service coverage index, availability of pathology services, human development index, gender inequality index (GII), radiotherapy centers per 1000 population, and out-of-pocket expenditure as percentage of current health expenditure were collected. The association between the mortality to incidence ratio (MIR) and each metric was evaluated using univariable linear regressions (α = .0045), which were used to construct multivariable models (α = .05). Variation inflation factor allowed exclusion of variables with significant multicollinearity. R2 measured goodness of fit. On univariable analysis, all metrics were significantly associated with MIR of cancer (P < .001 for all), including UHC index (β, -0.0076 [95% CI, -0.0083 to -0.0068]), GDP per capita (β, -5.10 × 10-6 [95% CI, -5.75 × 10-6 to -4.46 × 10-6]), clinical and workforce capacity, radiotherapy capacity (β, -88.25 [95% CI, -100.43 to -76.06]), and gender inequality index (β, 0.63 [95% CI, 0.57-0.70]). After including metrics significant on univariable analysis and correcting for multicollinearity, on multivariable analysis, greater UHC index and GDP per capita were independently associated with lower (improved) MIR for cancer. The multivariable model had R2 of 0.87. On multivariable analysis stratified by sex, greater UHC index and greater GDP per capita were independently associated with improved MIR for all cancers. R2 for the multivariable models was 0.87 for females and 0.85 for males. This study found that global health system metrics related to progress toward universal health care, greater health care spending and GDP per capita, strengthened clinical workforce and capacity, and increased gender equity were associated with improved pan-cancer outcomes at a population level on univariable analysis. The degree of UHC and GDP per capita were independently associated with improved cancer outcomes in multivariable models with good explanatory power. These exploratory findings merit further validation and may guide health system planning and prioritization.