
Performance of TyrerCuzick Model for Breast Cancer Risk Assessment among Pakistan’s Females
Author(s) -
Rufina Soomro,
Rabia Niaz
Publication year - 2021
Publication title -
journal of advances in medicine and medical research
Language(s) - English
Resource type - Journals
ISSN - 2456-8899
DOI - 10.9734/jammr/2021/v33i2331188
Subject(s) - family history , breast cancer , medicine , risk assessment , incidence (geometry) , demography , mammographic density , risk factors for breast cancer , obstetrics , gynecology , mammography , cancer , physics , computer security , sociology , computer science , optics
Background: Breast cancer incidence is highest in Pakistan among Asian countries. The known risk factors are family history, hormonal exposure, benign proliferative diseases, and high mammographic density which are included in the TyrerCuzick model. The model needs validation studies to implement in prediction, screening, and prevention strategies among different populations. This study aims to validate the TyrerCuzick model for Pakistan's females.
Methods and Materials: A total of 317 biopsy-proven breast cancer patients from the breast surgery clinic at Liaquat National Hospital were included. The 10 years risk score is calculated by applying the TyrerCuzick model software. Subcategories of low risk 8% were identified. Further risk group stratification is done to find the association with individual factors i.e., age group, menopausal status, family history, and mammographic density.
Results: The mean TyrerCuzick score was low to moderate i.e. 2.23±1.66. The score was distributed as low risk 174(54.9%), moderate risk 137(43.2%), and high risk 6(1.9%). Low risk was observed among 116(81.7%) of less than 50 years old, 105(78.9%) premenopausal, 113(59.8%) with no family history, and 120 patients (59.7%) with low mammographic density. Most of the moderate risk was found in 113(64.6%) of more than 50 years old, 109(60.2%) with postmenopausal, 24(61.5%) with family history, 58(50%) with high mammographic density respectively.
Conclusion: The TyrerCuzick model can predict risk for developing breast cancer among Pakistan’s femalesclose to accurate among older age, postmenopausal, family history of breast cancer, and high mammographic density.