11 Trends in Breast Cancer Among Indian Women: Analysis of Global Burden of Diseases from 1990-2023

Background

Breast cancer is a commonly encountered malignancy among Indian women, with a growing clinical burden. Understanding its temporal and regional patterns is essential for optimizing screening, early detection, and equitable access to oncologic care. The aim of the study was thus to assess the temporal evolution and geographic heterogeneity of breast cancer burden among Indian women between 1990 and 2023 using the Global Burden of Disease (GBD) 2023 framework.

Materials and Methods

A secondary analysis of GBD 2023 data was performed for all 28 states and 8 union territories of India. Estimates for incidence, prevalence, mortality, and disability-adjusted life years (DALYs) were extracted from the Global Health Data Exchange. Age-standardized rates per 100,000 women and annual percentage change (APC) were computed to evaluate temporal trends. Spatial and temporal variations were visualized using Microsoft Excel.

Results

Between 1990 and 2023, breast cancer burden in India rose markedly across all indicators. The national age-standardized incidence rate was 28.7 (95% uncertainty interval, 22.3-36.4) per 100,000 women. Delhi (48.1) reported the highest incidence, whereas Sikkim (12.5) had the lowest. Jharkhand (APC, 5.7%) recorded the steepest temporal increases. Mortality rose from 33,151 (25,002-40,502) in 1991 to 101,621 (78,441-128,000) in 2023, and DALYs quadrupled nationally from 0.86 million to 3.32 million. Southern and Western states contributed the largest absolute burden, while Central and Eastern states showed the fastest relative growth.

Conclusions

India’s breast cancer burden has intensified over the past 3 decades, marked by rising incidence, mortality, and DALYs across all states. The transition of breast cancer to the leading cause of female cancer deaths highlights an urgent need to expand early detection, ensure timely treatment access, and monitor regional disparities through robust, data-driven cancer surveillance.