What Explains the Survival Gap? Decomposing Cross-National Inequality in Breast Cancer Mortality-to-Incidence Ratios Using Open Global Data Repositories - Siti Mardhiah El-Khairah Siti Mardhiah; Melsi Pita Sari Melsi Pita (Frontiers on Healthcare Research, 2026)
Background: Women diagnosed with breast cancer in low-resource countries are several times more likely to die from the disease than those in high-income countries, despite lower incidence. The mortality-to-incidence ratio (MIR) captures this survival gap, but previous studies have mainly described its association with national wealth rather than quantified the contribution of specific health-system factors. We aimed to measure inequality in breast cancer MIR across the human development gradient and identify key determinants using freely accessible and redistributable data sources. Methods: We conducted a cross-sectional ecological analysis of 185 countries and territories. Breast cancer incidence and mortality rates for 2022 were obtained from the IARC Global Cancer Observatory. Explanatory variables were derived from UNDP, WHO, and IAEA databases. Associations were assessed using beta regression with a logit link. Inequality was measured using the Erreygers-corrected concentration index and decomposed by determinant contributions. A counterfactual analysis estimated potentially avertable deaths if all countries achieved MIR levels observed in the highest human development quintile. Results: MIR ranged from 0.14 to 0.63 (median 0.31). The concentration index was −0.284 (95% CI −0.331 to −0.237), indicating higher MIR among less developed countries. Radiotherapy machine density contributed 31.2% of inequality, followed by UHC service coverage (22.6%), population-based mammography programmes (14.8%), and health expenditure per capita (11.3%). Approximately 214,600 deaths annually (32.2% of global breast cancer deaths) were potentially avertable. Conclusion: Global inequality in breast cancer survival is strongly associated with measurable health-system capacity gaps, particularly treatment infrastructure. Publicly available data enable reproducible analyses to guide targeted improvements in cancer care equity