Regional discrepancies between diagnosis and treatment start of breast cancer: a comparative analysis of DATASUS data in different Brazilian regions

Abstract

Objective: This study aimed to analyze data available in the Department of Informatics of the Unified Health System
(DATASUS) regarding the number of breast cancer diagnoses compared to the starting time of treatments in different Brazilian regions. Methods: This is an observational, descriptive, and analytical study using secondary data from
DATASUS platform, covering the period from 2019 to 2024, including women of all ages diagnosed with malignant breast
neoplasia, excluding those with incomplete records. The work is compliant with ethical guidelines and ensures participant privacy protection. Results: Analysis of the proportion of patients who started treatment within 30 days of diagnosis revealed significant regional variations. The South and Southeast regions had the highest percentages of early treatment, with values often exceeding 25% of diagnosed cases. However, the North and Northeast recorded the lowest rates
of starting treatment within this period, with values below 20% in most of the years evaluated. Analysis of the percentage of patients who started treatment after 60 days of diagnosis revealed that the North and Northeast regions had the
highest rates of delay in starting treatment, often above 50% of diagnosed cases. The Southeast and South, despite also
registering delays, presented relatively lower percentages. Conclusion: Despite the implementation of the 60 Day Law,
data indicate that the time between diagnosis and treatment start is still a challenge. The lack of statistical significance in
the comparison between regions does not rule out the importance of the differences identified, since delays in treatment
can compromise clinical outcomes and impact patients’ quality of life. Public policies aimed at equity in access to early
diagnosis and treatment of breast cancer need to be reinforced, especially in more vulnerable regions. Measures such as
strengthening primary care, expanding the cancer care network, and optimizing queue management can be fundamental to reducing these inequalities.