Dataset Information

Mammographic density reduction is a prognostic marker of response to adjuvant tamoxifen therapy in postmenopausal patients with breast cancer.

ABSTRACT:

Purpose

Tamoxifen treatment is associated with a reduction in mammographic density and an improved survival. However, the extent to which change in mammographic density during adjuvant tamoxifen therapy can be used to measure response to treatment is unknown.

Patients and methods

Overall, 974 postmenopausal patients with breast cancer who had both a baseline and a follow-up mammogram were eligible for analysis. On the basis of treatment information abstracted from medical records, 474 patients received tamoxifen treatment and 500 did not. Mammographic density was measured by using an automated thresholding method and expressed as absolute dense area. Change in mammographic density was calculated as percentage change from baseline. Survival analysis was performed by using delayed-entry Cox proportional hazards regression models, with death as a result of breast cancer as the end point. Analyses were adjusted for a range of patient and tumor characteristics.

Results

During a 15-year follow-up, 121 patients (12.4%) died from breast cancer. Women treated with tamoxifen who experienced a relative density reduction of more than 20% between baseline and first follow-up mammogram had a reduced risk of death as a result of breast cancer of 50% (hazard ratio, 0.50; 95% CI, 0.27 to 0.93) compared with women with stable mammographic density. In the no-tamoxifen group, there was no statistically significant association between mammographic density change and survival. The survival advantage was not observed when absolute dense areas at baseline or follow-up were evaluated separately.

Conclusion

A decrease in mammographic density after breast cancer diagnosis appears to serve as a prognostic marker for improved long-term survival in patients receiving adjuvant tamoxifen, and these data should be externally validated.

SUBMITTER: Li J

PROVIDER: S-EPMC3677838 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Mammographic breast density (MBD) is a risk factor for breast cancer, but its molecular basis is poorly understood. Growth factors stimulate cellular and epithelial proliferation and could influence MBD via these mechanisms. Studies investigating the associations of circulating growth factors with MBD have, however, yielded conflicting results especially in postmenopausal women. We, therefore, investigated the associations of plasma growth factor gene expression [insulin-like growth factor (IGF)-1, IGF-binding protein 3, FGF-1, FGF-12, TGFβ1 and bone morphogenetic protein (BMP)-2] with MBD in postmenopausal women. We used NanoString nCounter platform to quantify plasma growth factor gene expression and Volpara to evaluate volumetric MBD measures. We investigated the associations of growth factor gene expression with MBD using both multiple linear regression (fold change) and multinomial logistic regression models, adjusted for potential confounders. The mean age of the 368 women enrolled was 58 years (range, 50-64). In analyses using linear regression models, one unit increase in IGF-1 gene expression was associated with a 35% higher volumetric percent density (VPD, 1.35; 95% confidence interval (CI), 1.13-1.60; P = 0.001). There were suggestions that TGFβ1 gene expression was positively associated with VPD while BMP-2 gene expression was inversely associated with VPD, but these were not statistically significant. In analyses using multinomial logistic regression, TGFβ1 gene expression was 33% higher (OR = 1.33; 95% CI, 1.13-1.56; P = 0.0008) in women with extremely dense breasts than those with almost entirely fatty breasts. There were no associations between growth factor gene expression and dense volume or nondense volume. Our study provides insights into the associations of growth factors with MBD in postmenopausal women and requires confirmation in other study populations.Prevention relevanceMammographic breast density is a strong risk factor for breast cancer. Understanding its underlying biological mechanisms could have utility in breast cancer prevention.