Dee Edward Christopher, Wu James Fan, Feliciano Erin Jay G, Ting Frederic Ivan L, Willmann Jonas, Ho Frances Dominique V, Jain Bhav, Jain Urvish, Chen Jenny, Moraes Fabio Ynoe, Lee Nancy Y, Iyengar Puneeth, Nguyen Paul L
Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
Division of Hematology and Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee.
JAMA Oncol. 2025 Apr 10. doi: 10.1001/jamaoncol.2025.0473.
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.
DESIGN, SETTING, AND PARTICIPANTS: 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.
预计到2040年全球将有大约2990万癌症病例和1530万例死亡,因此有必要加强癌症防治体系。深入了解可用于改善癌症控制的卫生系统因素,可能会为卫生系统规划提供指导。
评估全球癌症治疗效果改善的预测因素。
设计、背景和参与者:这项泛癌症生态研究使用了最新可得的国家卫生系统指标和癌症统计数据,涵盖了185个国家的全球收入水平范围。年龄标准化死亡率与发病率之比的估计值来自2022年全球癌症负担数据(GLOBOCAN 2022),涉及所有年龄段的癌症患者。分析于2024年11月27日进行。
收集了以下数据:卫生支出占国内生产总值(GDP)的百分比、每千人口的医生数量、每千人口的护士和助产士数量、每千人口的外科手术人员数量、人均GDP、全民健康覆盖(UHC)服务覆盖指数、病理服务的可及性(可得性)、人类发展指数、性别不平等指数(GII)、每千人口的放疗中心数量,以及自付费用占当前卫生支出的百分比。使用单变量线性回归(α = 0.0045)评估死亡率与发病率之比(MIR)与每个指标之间的关联,这些回归用于构建多变量模型(α = 0.05)。方差膨胀因子用于排除具有显著多重共线性的变量。R² 衡量拟合优度。
在单变量分析中,所有指标均与癌症的MIR显著相关(所有P < 0.001),包括UHC指数(β,-0.0076 [95%置信区间,-0.0083至-0.0068])、人均GDP(β,-5.10×10⁻⁶ [95%置信区间,-5.75×10⁻⁶至-4.46×10⁻⁶])、临床和劳动力能力、放疗能力(β,-88.25 [95%置信区间,-100.43至-76.06])以及性别不平等指数(β,0.63 [95%置信区间,0.57 - 0.70])。在纳入单变量分析中有显著意义的指标并校正多重共线性后,在多变量分析中,更高的UHC指数和人均GDP与更低(改善)的癌症MIR独立相关。多变量模型的R²为0.87。在按性别分层的多变量分析中,更高的UHC指数和更高的人均GDP与所有癌症的MIR改善独立相关。女性多变量模型的R²为0.87,男性为0.85。
本研究发现,在单变量分析中,与全民医疗保健进展、更多医疗保健支出和人均GDP、更强的临床劳动力和能力以及更大的性别平等相关的全球卫生系统指标,与人群水平上泛癌症治疗效果的改善相关。在具有良好解释力的多变量模型中,UHC程度和人均GDP与癌症治疗效果的改善独立相关。这些探索性发现值得进一步验证,并可能指导卫生系统规划和优先事项确定。