Feasibility of personalized screening and prevention recommendations in the general population through breast cancer risk assessment: results from a dedicated risk clinic

Abstract

Purpose A personalized approach to prevention and early detection based on known risk factors should contribute to early diagnosis and treatment of breast cancer. We initiated a risk assessment clinic for all women wishing to undergo an individual breast cancer risk assessment. Methods Women underwent a complete breast cancer assessment including a questionnaire, mammogram with evaluation of breast density, collection of saliva sample, consultation with a radiologist, and a breast cancer specialist. Women aged 40 or older, with 0 or 1 first-degree relative with breast cancer diagnosed after the age of 40 were eligible for risk assessment using MammoRisk, a machine learning-based tool that provides an individual 5-year estimated risk of developing breast cancer based on the patient's clinical data and breast density, with or without polygenic risk scores (PRSs). DNA was extracted from saliva samples for genotyping of 76 single-nucleotide polymorphisms. The individual risk was communicated to the patient, with individualized screening and prevention recommendations. Results A total of 290 women underwent breast cancer assessment, among which 196 women (68%) were eligible for risk assessment using MammoRisk (median age 52, range 40-72). When PRS was added to MammoRisk, 40% (n = 78) of patients were assigned a different risk category, with 28% (n = 55) of patients changing from intermediate to moderate or high risk. Conclusion Individual risk assessment is feasible in the general population. Screening recommendations could be given based on individual risk. The use of PRS changed the risk score and screening recommendations in 40% of women.

Feasibility and Acceptability of Personalized Breast Cancer Screening (DECIDO Study): A Single-Arm Proof-of-Concept Trial

“…For the same threshold, the integrated model reclassified 15% of UK women (5% from above to below and 10% in the opposite direction), identifying an additional 16% of the future cases. Saghatchian et al [ 51 ] reported the feasibility of giving screening recommendations based on individual risk in the general population. The use of PRS changed the risk score and monitoring and prevention recommendations in 40% of women, 28% of which classified from intermediate to moderate or high risk.…”

The Prognostic Quality of Risk Prediction Models to Assess the Individual Breast Cancer Risk in Women: An Overview of Reviews

“…A systematic review published in July 2022 [69] also emphasised that there are currently no endorsed risk prediction models for breast cancer tailored to diverse ethnic populations. Furthermore, we did not assess a machine learningbased software tool, the Mammo-Risk ™ model (Predilife, Villejuif, France) [70], as it was published in 2022. Te model was developed in the BCSC cohort [71,72] to estimate the risk of developing breast cancer within the next fve years based on the following four risk factors: age, family history of breast cancer, history of breast biopsies, and breast density with or without a polygenic risk score.…”

“…Table 3 presents an overview of the discriminatory accuracy of the identifed empirical and genetic breast cancer risk prediction models and shows that almost all identifed model versions had a limited discriminatory accuracy with AUC values <0. 70 One study did not report on the population. Te discriminatory accuracy of these original models ranged from AUC values of 0.53 [38] to 0.785 [45], whereby the latter applied to the prediction of ER-positive, HER2negative, invasive, and noninvasive carcinoma in a Japanese population considering a polygenic risk score.…”

A Clinical Risk Model for Personalized Screening and Prevention of Breast Cancer

“…The lifestyle/familial-expanded AI risk model showed an advantage over the imaging-only AI risk model for identifying ER-positive breast cancers across the 1–10-year follow-up. Women therefore could have an advantage in having their risk assessed using the lifestyle/familial-expanded model when considering prophylactic endocrine therapy to reduce their risk of developing breast cancer [ 38 ].…”