Please use this identifier to cite or link to this item: https://doi.org/10.1002/cam4.4297
Title: Breast cancer risk stratification for mammographic screening: A nation-wide screening cohort of 24,431 women in Singapore
Authors: Ho, Peh Joo
Wong, Fuh Yong 
Chay, Wen Yee 
Lim, Elaine Hsuen
Lim, Zi Lin
Chia, Kee Seng 
Hartman, Mikael 
Li, Jingmei 
Keywords: Science & Technology
Life Sciences & Biomedicine
Oncology
breast cancer
Gail model
mammogram recall status
mammographic density
mammography screening
COST-EFFECTIVENESS
DENSITY
PARTICIPATION
INTERVENTIONS
BENEFITS
PROGRAM
Issue Date: 28-Oct-2021
Publisher: WILEY
Citation: Ho, Peh Joo, Wong, Fuh Yong, Chay, Wen Yee, Lim, Elaine Hsuen, Lim, Zi Lin, Chia, Kee Seng, Hartman, Mikael, Li, Jingmei (2021-10-28). Breast cancer risk stratification for mammographic screening: A nation-wide screening cohort of 24,431 women in Singapore. CANCER MEDICINE. ScholarBank@NUS Repository. https://doi.org/10.1002/cam4.4297
Abstract: Background: Breast cancer incidence is increasing in Asia. However, few women in Singapore attend routine mammography screening. We aim to identify women at high risk of breast cancer who will benefit most from regular screening using the Gail model and information from their first screen (recall status and mammographic density). Methods: In 24,431 Asian women (50–69 years) who attended screening between 1994 and 1997, 117 developed breast cancer within 5 years of screening. Cox proportional hazard models were used to study the associations between risk classifiers (Gail model 5-year absolute risk, recall status, mammographic density), and breast cancer occurrence. The efficacy of risk stratification was evaluated by considering sensitivity, specificity, and the proportion of cancers identified. Results: Adjusting for information from first screen attenuated the hazard ratios (HR) associated with 5-year absolute risk (continuous, unadjusted HR [95% confidence interval]: 2.3 [1.8–3.1], adjusted HR: 1.9 [1.4–2.6]), but improved the discriminatory ability of the model (unadjusted AUC: 0.615 [0.559–0.670], adjusted AUC: 0.703 [0.653–0.753]). The sensitivity and specificity of the adjusted model were 0.709 and 0.622, respectively. Thirty-eight percent of all breast cancers were detected in 12% of the study population considered high risk (top five percentile of the Gail model 5-year absolute risk [absolute risk ≥1.43%], were recalled, and/or mammographic density ≥50%). Conclusion: The Gail model is able to stratify women based on their individual breast cancer risk in this population. Including information from the first screen can improve prediction in the 5 years after screening. Risk stratification has the potential to pick up more cancers.
Source Title: CANCER MEDICINE
URI: https://scholarbank.nus.edu.sg/handle/10635/208236
ISSN: 20457634
DOI: 10.1002/cam4.4297
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