Persistent or increased breast density is associated with increased cancer risk

Researchers used mammography data from more than 1.7 million women aged 40 and older to identify distinct patterns of density change. This finding highlighted the importance of tracking density trajectories to enhance breast cancer risk prediction.

In a recent study published in BMJresearchers investigated the relationship between changes in breast density over time and breast cancer risk.

background

Breast density is an important factor in breast cancer risk because dense breasts increase the likelihood of cancer and make it difficult to detect tumors effectively. Breast density typically decreases with age, but certain patterns of increase are associated with increased cancer risk.

Current screening programs often rely on single-time point measurements of breast density, which can potentially miss significant changes over time. Such static measurements may not capture the dynamic nature of breast density, especially in populations with routine mammographic surveillance.

Although studies have demonstrated the predictive value of longitudinal density patterns, large-scale studies of density changes across multiple screens are limited. Understanding these patterns can provide valuable insights to improve risk prediction and early detection strategies.

Exploring how breast density trends relate to cancer outcomes is also essential for improving screening protocols and tailoring interventions.

About research

For the current study, researchers analyzed data from more than 1.7 million women aged 40 and older who underwent four consecutive mammograms every other year from 2009 to 2016 through South Korea's national laboratory. Breast cancer screening program.

Breast density was assessed using the Breast Imaging-Reporting and Data System or BI-RADS categories: fatty, scattered fibroglandular, heterogeneously dense, and extremely dense. Participants with previous cancer or missing data were excluded.

The researchers applied group-based trajectory modeling to identify five distinct patterns of density change. We also collected data on covariates such as age, body mass index (BMI), menopausal status, reproductive history, and lifestyle factors through questionnaires and medical records.

Cancer diagnoses, confirmed using medical records and insurance data, were tracked through 2021. Additionally, diagnosis codes and rare disease codes were incorporated into the analysis to increase the accuracy of breast cancer identification.

By employing longitudinal data and robust statistical methods, researchers aimed to develop a reliable method to identify the relationship between breast density patterns and breast cancer risk.

Main findings

This study identified five distinct breast density trajectories and their association with breast cancer risk. Researchers observed that women with persistently low breast density (fatty breasts) had the lowest breast density. breast cancer risk This group was then used as the reference group for the study. In contrast, women with initially low breast density but whose breast density increases over time were shown to have a 1.6 times higher risk of breast cancer.

Among trajectories involving women with denser breast tissue, the group that initially had dense, heterogeneous or very dense breast tissue but decreased over time showed a stable or slightly decreasing risk pattern.

However, all three groups had significantly increased cancer risk compared to the reference group with lower breast density. Women with persistently high breast density had a 3.07 times higher risk of breast cancer compared to the reference group. These associations persisted across age groups and were not influenced by changes in BMI or menopausal status.

Additionally, subgroup analyzes also revealed consistent patterns, regardless of change in BMI or transition to menopause. Women with persistently high or increasing breast density face higher risk in all scenarios. Additionally, sensitivity analyzes in less frequently screened women confirmed the robustness of these results and showed similar trajectories and risk patterns.

This result emphasized the importance of monitoring changes in breast density over time. The researchers concluded that static density assessments may not capture the increased risk associated with dynamic density patterns, especially for women with increasing or persistently high breast tissue density. has been demonstrated. These insights also highlighted the potential benefits of incorporating longitudinal density tracking into breast cancer screening and risk prediction models.

conclusion

Overall, this study demonstrated the importance of monitoring changes in breast density over time in predicting breast cancer risk. Persistent high or increasing breast tissue density is associated with significantly increased cancer risk, which also illustrates the limitations of static density measurements.

The results show that integrating longitudinal density assessment into screening protocols can help health systems improve risk prediction and early detection strategies. Furthermore, tailoring interventions to high-risk women based on dynamic density changes could significantly improve prevention efforts and clinical outcomes.