Medication use and mammographic breast density

Aspirin Metabolites and Mammographic Breast Density in Premenopausal Women

BACKGROUND

Studies investigating the associations of self-reported aspirin use and mammographic breast density (MBD) have reported conflicting results. Therefore, we investigated the associations of aspirin metabolites with MBD in premenopausal women.

METHODS

We performed this study on 705 premenopausal women who had a fasting blood draw for metabolomic profiling. We performed covariate-adjusted linear regression models to calculate the least square means of volumetric measures of MBD [volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV)] by quartiles of aspirin metabolites [salicyluric glucuronide, 2-hydroxyhippurate (salicylurate), salicylate, and 2,6-dihydroxybenzoic acid].

RESULTS

Approximately 13% of participants reported taking aspirin in the past 12 months. Aspirin users had higher levels of 2-hydroxyhippurate (salicylurate), salicylate, and salicyluric glucuronide (peak area) than nonusers, but only the mean peak area of salicyluric glucuronide was increased by both dose (1-2 tablets per day = 1,140,663.7 and ≥3 tablets per day = 1,380,476.0) and frequency (days per week: 1 day = 888,129.3, 2-3 days = 1,199,897.9, and ≥4 days = 1,654,637.0). Aspirin metabolites were not monotonically associated with VPD, DV, or NDV.

CONCLUSIONS

Given the null results, additional research investigating the associations of aspirin metabolites in breast tissue and MBD is necessary. Impact: Elucidating the determinants of MBD, a strong risk factor for breast cancer, can play an important role in breast cancer prevention. Future studies should determine the associations of nonaspirin NSAID metabolites with MBD.

A systematic review and meta-analysis of correlation of automated breast density measurement

INTRODUCTION

Breast cancer is the most common cancer in women and a leading cause of mortality. This systematic review and meta-analysis aims to evaluate the correlation between breast density measurements obtained from various software and visual assessments by radiologists using full-field digital mammography (FFDM).

METHODS

Following the PRISMA 2020 guidelines, five databases (Pubmed, Google Scholar, Science Direct, Cochrane Library, and MEDLINE) were searched for studies correlating volumetric breast density with breast cancer risk. The Newcastle-Ottawa Scale and the Joanna Briggs Institute Checklist were used to assess the quality of the included studies. Meta-analysis of correlation was applied to aggregate correlation coefficients using a random-effects model using MedCalc Statistical Software version 19.2.6.

RESULTS

The review included 22 studies with a total of 58,491 women. The pooled correlation coefficient for volumetric breast density amongst Volpara™ and Quantra™ was found to be 0.755 (95% CI 0.496-0.890, p < 0.001), indicating a high positive correlation, albeit with a significant heterogeneity (I2 = 99.89%, p < 0.0001). Subgroup analyses based on study origin, quality, and methodology were performed but did not reveal the heterogeneity cause. Egger's and Begg's tests showed no significant publication bias.

CONCLUSION

Volumetric breast density is strongly correlated with breast cancer risk, underscoring the importance of accurate breast density assessment in screening programs. Automated volumetric measurement tools like Volpara™ and Quantra™ provide reliable assessments, potentially improving breast cancer risk prediction and management.

IMPLICATIONS FOR PRACTICE

Implementing fully automated breast density assessment tools could enhance consistency in clinical practice, minimizing observer variability and improving screening accuracy. These tools should be further validated against standardized criteria to ensure reliability in diverse clinical settings.

Breast Density: Current Knowledge, Assessment Methods, and Clinical Implications

Breast density is an accepted independent risk factor for the future development of breast cancer, and greater breast density has the potential to mask malignancies on mammography, thus lowering the sensitivity of screening mammography. The risk associated with dense breast tissue has been shown to be modifiable with changes in breast density. Numerous studies have sought to identify factors that influence breast density, including age, genetic, racial/ethnic, prepubertal, adolescent, lifestyle, environmental, hormonal, and reproductive history factors. Qualitative, semiquantitative, and quantitative methods of breast density assessment have been developed, but to date there is no consensus assessment method or reference standard for breast density. Breast density has been incorporated into breast cancer risk models, and there is growing consciousness of the clinical implications of dense breast tissue in both the medical community and public arena. Efforts to improve breast cancer screening sensitivity for women with dense breasts have led to increased attention to supplemental screening methods in recent years, prompting the American College of Radiology to publish Appropriateness Criteria for supplemental screening based on breast density.