학술논문
Causal relationships between breast cancer risk factors based on mammographic features
Document Type
article
Author
Zhoufeng Ye; Tuong L. Nguyen; Gillian S. Dite; Robert J. MacInnis; Daniel F. Schmidt; Enes Makalic; Osamah M. Al-Qershi; Minh Bui; Vivienne F. C. Esser; James G. Dowty; Ho N. Trinh; Christopher F. Evans; Maxine Tan; Joohon Sung; Mark A. Jenkins; Graham G. Giles; Melissa C. Southey; John L. Hopper; Shuai Li
Source
Breast Cancer Research, Vol 25, Iss 1, Pp 1-13 (2023)
Subject
Language
English
ISSN
1465-542X
Abstract
Abstract Background Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. Methods We used digitised mammograms for 371 monozygotic twin pairs, aged 40–70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. Results The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22–0.81; all P