Abstract 4867: Longitudinal latent class analysis to further understand trajectory of density over time and risk of breast cancer
Authors: Colditz Graham A. , Bennett Debbie L. , Jiang Shu 
Published: March 2024

Abstract
Background: It is clinically important to refine strategies to manage women with dense breasts as they represent approximately 50% of all women screened. Change in breast density is related to risk of breast cancer.1 We also must understand this change in density over time in women with dense and non-dense breasts. While population level data have been reported to estimate decrease in density with age, this has largely used digitized film images.2 Expanding use of digital mammography and repeated screening generates a large library of images for each woman, offering the potential to use more of the image data.
Methods: We use longitudinal latent class analysis to cluster women and estimate their change in density over time. To evaluate the groups of women with different patterns of change in density we fit latent class models to our previously published data.1 This includes 289 pathology confirmed cases of breast cancer and 658 controls among women followed from November 3, 2008 to October 31, 2020.
Results: Among women with dense breasts, there are 107 who developed breast cancer during follow-up and 267 control women who remained free from breast cancer. In the women without dense breasts, 173 cases and 383 controls were evaluated and showed similar age and BMI within the controls as seen in women with dense breasts. Prevalence of family history and history of benign breast biopsy did not differ between the two groups. We observe this latent class and trajectory of density phenomenal separately for dense and non-dense groups in our data. We show that the data define 2 classes, those who have decrease in density over time and those who have increase over time. The odds ratio (OR) for cancer comparing decline vs. incline is 4.9 in women with dense breasts (BI-RADS C, D) and 6.17 on women with non-dense breasts (BI-RADS A, B).
Discussion: To refine our understanding of patterns of change in breast density over time in relation to breast cancer risk we fit latent class models. Longitudinal change matters as reflected in the 2-class model. This is independent of starting density and confirms that a one-time measure of density is not enough to define level of risk for subsequent breast cancer. Further work is needed to better define the drivers and inhibitors of decline in breast density over time given this change over time as women age is a universal phenomenon.2
1. Jiang S, Bennett DL, Rosner BA, Colditz GA. Longitudinal Analysis of Change in Mammographic Density in Each Breast and Its Association With Breast Cancer Risk. JAMA Oncol 2023;9(6):808-814. (In English). DOI: 10.1001/jamaoncol.2023.0434.
2. Burton A, Maskarinec G, Perez-Gomez B, et al. Mammographic density and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide. PLoS Med 2017;14(6):e1002335. DOI: 10.1371/journal.pmed.1002335.
Citation Format: Graham A. Colditz, Debbie L. Bennett, Shu Jiang. Longitudinal latent class analysis to further understand trajectory of density over time and risk of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4867.