Validation of the Snehita BRISK Model: Incidence Patterns and Impact of Risk?Stratified Communication in a Community Cohort

Background

Breast cancer incidence is rising steadily in India, yet uptake of early detection services remains low, particularly in low?resource settings where routine screening is not widely available. Risk?stratified approaches offer a pragmatic pathway to improve early detection by identifying women who would benefit most from timely clinical evaluation. The Snehita BRISK model is a locally developed breast cancer risk assessment tool designed to reflect the reproductive, demographic, and lifestyle characteristics of women in the Indian subcontinent. Although widely used in community programmes, its predictive performance and real?world behavioural impact required systematic validation using longitudinal cohort data.

Objective

To validate the Snehita BRISK model by examining breast cancer incidence across risk strata in a large community cohort and assessing whether risk?stratified communication increases uptake of early detection services among higher?risk women.

Methods

A retrospective cohort analysis was conducted among 9,751 women enrolled in the Snehita Women’s Health Foundation early detection programme between 2015 and 2019, contributing approximately 30,000 woman?years of follow?up. Baseline risk scores were recalculated, and women were stratified into normal, moderate, and high?risk categories using both original and newly derived age?specific cut?offs. A cross?sectional follow?up survey was conducted via telephone to update current health status, screening practices, and risk perceptions. Women classified as high?risk or overdue for follow?up were invited for clinical breast examination (CBE) and radiological breast evaluation (RBE) as needed. Incidence rates were compared across risk strata, and behavioural response to risk?stratified communication was assessed by measuring uptake of CBE/RBE among contacted women.

Results

Updated follow?up information was obtained for 9,751 women, and 2,750 attended in?person review and CBE. Among these, 1,239 clinical findings were documented, and 61 women underwent mammography. Four early?stage breast cancers were detected during the follow?up period, all among women classified as moderate or high risk. Incidence rates were higher in the upper risk strata, supporting the discriminatory ability of the model. Re?stratification using age?specific cut?offs improved alignment between predicted risk and observed incidence. Risk?stratified communication had a measurable behavioural impact: high?risk women demonstrated substantially higher uptake of CBE and RBE compared with women in lower?risk categories. The model also facilitated targeted invitations, enabling efficient use of limited diagnostic resources.

Conclusions/Implications

The Snehita BRISK model shows promising validity in distinguishing breast cancer risk levels within a large community cohort, with higher incidence observed among women classified as moderate and high risk. Age?specific cut?offs further enhance stratification accuracy. Importantly, risk?stratified communication motivated higher?risk women to seek early detection services, demonstrating the model’s practical utility in real?world settings. These findings support the use of the Snehita BRISK model as a cost?effective tool for guiding risk?based early detection strategies in low?resource environments. Its integration into community programmes and state?level initiatives, such as the Kerala pilot, highlights its potential for scalable public health impact across the Indian subcontinent. 

Resume Lizbeth Paul