Spatial distribution of the time between diagnosis and treatment of breast cancer among women in Brazil

Female breast cancer presents high incidence and mortality rates and is considered a significant public health problem. The timeliness of oncological treatment is a fundamental factor in the prognosis and survival of patients. The objective of this study was to analyze the spatial distribution pattern of the percentage of women who initiated breast cancer treatment within 60 days and its association with socioeconomic indicators and the availability of health services in Brazil. An ecological study was conducted using 133 Intermediate Regions of Urban Articulation (IRUA), based on records from the period 2013–2019. Data on the percentage of treatment initiation within 60 days were obtained from the Hospital Cancer Registry Integrator (IHCR). Socioeconomic variables were collected from the Atlas of Human Development in Brazil and the Institute for Applied Economic Research (IPEA). Data on the availability and density of health professionals and services were obtained from the National Registry of Health Establishments (NRHE) and the Hospital Information System (HIS). The Global Moran’s Index and the Local Indicator of Spatial Association (LISA) were used to verify the existence of territorial clusters. Multivariate analysis employed models with global spatial effects. The percentage of breast cancer cases that initiated treatment within 60 days was 48.9% (95% CI: 48.6% − 49.1%), with the highest adherence observed in the IRUA of Cascavel (85%) and the lowest in the IRUA of Rio de Janeiro (16.6%). In the final Spatial Lag Model, positive associations were observed with the density of Family and Community Physicians (β = 0.35; p = 0.007) and the proportion of surgical procedures (β = 0.30; p = 0.001). The analysis indicates that compliance with the 60-day law is related to the structure and organization of health services, highlighting the importance of primary health care as the coordinator of care and the role of surgical capacity in the spatial distribution pattern.