Mammographic density as a predictor of breast cancer survival

The Multiethnic Cohort

Gertraud Maskarinec, Ian S. Pagano, Melissa Little, Shannon M. Conroy, Song Yi Park, Laurence N. Kolonel

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

Introduction: Mammographic density, a strong predictor for breast cancer incidence, may also worsen prognosis in women with breast cancer. This prospective analysis explored the effect of prediagnostic mammographic density among 607 breast cancer cases diagnosed within the Hawaii component of the Multiethnic Cohort (MEC).Methods: Female MEC participants, aged ≥ 50 years at cohort entry, diagnosed with primary invasive breast cancer, and enrolled in a mammographic density case-control study were part of this analysis. At cohort entry, anthropometric and demographic information was collected by questionnaire. Tumor characteristics and vital status were available through linkage with the Hawaii Tumor Registry. Multiple digitized prediagnostic mammograms were assessed for mammographic density using a computer-assisted method. Cox proportional hazards regression was applied to examine the effect of mammographic density on breast cancer survival while adjusting for relevant covariates.Results: Of the 607 cases, 125 were diagnosed as in situ, 380 as localized, and 100 as regional/distant stage. After a mean follow-up time of 12.9 years, 27 deaths from breast cancer and 100 deaths from other causes had occurred; 71 second breast cancer primaries were diagnosed. In an overall model, mammographic density was not associated with breast cancer-specific survival (HR = 0.95 per 10%; 95%CI: 0.79-1.15), but the interaction with radiotherapy was highly significant (p = 0.006). In stratified models, percent density was associated with a reduced risk of dying from breast cancer (HR = 0.77; 95%CI: 0.60-0.99; p = 0.04) in women who had received radiation, but with an elevated risk (HR = 1.46; 95% CI: 1.00-2.14; p = 0.05) in patients who had not received radiation. High breast density predicted a borderline increase in risk for a second primary (HR = 1.72; 95% CI: 0.88-2.55; p = 0.15).Conclusions: Assessing mammographic density in women with breast cancer may identify women with a poorer prognosis and provide them with radiotherapy to improve outcomes.

Original languageEnglish (US)
Article numberR7
JournalBreast Cancer Research
Volume15
Issue number1
DOIs
StatePublished - Jan 22 2013

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Breast Neoplasms
Survival
Radiotherapy
Breast Density
Radiation
Second Primary Neoplasms
Registries
Case-Control Studies
Cause of Death
Neoplasms
Demography
Incidence

All Science Journal Classification (ASJC) codes

  • Cancer Research
  • Oncology
  • Medicine(all)

Cite this

Maskarinec, G., Pagano, I. S., Little, M., Conroy, S. M., Park, S. Y., & Kolonel, L. N. (2013). Mammographic density as a predictor of breast cancer survival: The Multiethnic Cohort. Breast Cancer Research, 15(1), [R7]. https://doi.org/10.1186/bcr3378

Mammographic density as a predictor of breast cancer survival : The Multiethnic Cohort. / Maskarinec, Gertraud; Pagano, Ian S.; Little, Melissa; Conroy, Shannon M.; Park, Song Yi; Kolonel, Laurence N.

In: Breast Cancer Research, Vol. 15, No. 1, R7, 22.01.2013.

Research output: Contribution to journalArticle

Maskarinec, G, Pagano, IS, Little, M, Conroy, SM, Park, SY & Kolonel, LN 2013, 'Mammographic density as a predictor of breast cancer survival: The Multiethnic Cohort', Breast Cancer Research, vol. 15, no. 1, R7. https://doi.org/10.1186/bcr3378
Maskarinec G, Pagano IS, Little M, Conroy SM, Park SY, Kolonel LN. Mammographic density as a predictor of breast cancer survival: The Multiethnic Cohort. Breast Cancer Research. 2013 Jan 22;15(1). R7. https://doi.org/10.1186/bcr3378
Maskarinec, Gertraud ; Pagano, Ian S. ; Little, Melissa ; Conroy, Shannon M. ; Park, Song Yi ; Kolonel, Laurence N. / Mammographic density as a predictor of breast cancer survival : The Multiethnic Cohort. In: Breast Cancer Research. 2013 ; Vol. 15, No. 1.
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abstract = "Introduction: Mammographic density, a strong predictor for breast cancer incidence, may also worsen prognosis in women with breast cancer. This prospective analysis explored the effect of prediagnostic mammographic density among 607 breast cancer cases diagnosed within the Hawaii component of the Multiethnic Cohort (MEC).Methods: Female MEC participants, aged ≥ 50 years at cohort entry, diagnosed with primary invasive breast cancer, and enrolled in a mammographic density case-control study were part of this analysis. At cohort entry, anthropometric and demographic information was collected by questionnaire. Tumor characteristics and vital status were available through linkage with the Hawaii Tumor Registry. Multiple digitized prediagnostic mammograms were assessed for mammographic density using a computer-assisted method. Cox proportional hazards regression was applied to examine the effect of mammographic density on breast cancer survival while adjusting for relevant covariates.Results: Of the 607 cases, 125 were diagnosed as in situ, 380 as localized, and 100 as regional/distant stage. After a mean follow-up time of 12.9 years, 27 deaths from breast cancer and 100 deaths from other causes had occurred; 71 second breast cancer primaries were diagnosed. In an overall model, mammographic density was not associated with breast cancer-specific survival (HR = 0.95 per 10{\%}; 95{\%}CI: 0.79-1.15), but the interaction with radiotherapy was highly significant (p = 0.006). In stratified models, percent density was associated with a reduced risk of dying from breast cancer (HR = 0.77; 95{\%}CI: 0.60-0.99; p = 0.04) in women who had received radiation, but with an elevated risk (HR = 1.46; 95{\%} CI: 1.00-2.14; p = 0.05) in patients who had not received radiation. High breast density predicted a borderline increase in risk for a second primary (HR = 1.72; 95{\%} CI: 0.88-2.55; p = 0.15).Conclusions: Assessing mammographic density in women with breast cancer may identify women with a poorer prognosis and provide them with radiotherapy to improve outcomes.",
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