Dataset Information

High mammographic breast density predicts locoregional recurrence after modified radical mastectomy for invasive breast cancer: a case-control study.

ABSTRACT:

Background

We aimed to evaluate the influence of mammographic breast density at diagnosis on the risk of cancer recurrence and survival outcomes in patients with invasive breast cancer after modified radical mastectomy.

Methods

This case-control study included 121 case-control pairs of women diagnosed with invasive breast cancer between 2004 and 2009, and who had undergone modified radical mastectomy and had mammographic breast density measured before or at diagnosis. Women with known locoregional recurrence or distant metastasis were matched by pathological disease stage, age, and year of diagnosis to women without recurrence. Locoregional recurrence was defined as recurrence in the ipsilateral chest wall, or axillary, internal mammary, or supraclavicular nodes. The median follow-up duration was 84.0 months for case patients and 92.9 months for control patients.

Results

Patients with heterogeneously dense (50-75% density) and extremely dense (>75% density) breasts had an increased risk of locoregional recurrence (hazard ratios 3.1 and 5.7, 95% confidence intervals 1.1-9.8 and 1.2-34.9, p = 0.043 and 0.048, respectively) than did women with less dense breasts. Positive margins after surgery also increased the risk of locoregional recurrence (hazard ratio 3.3, 95% confidence interval 1.3-8.3, p = 0.010). Multivariate analysis that included dense breasts (>50% density), positive margin, no adjuvant radiotherapy, and no adjuvant chemotherapy revealed that dense breasts were significant factors for predicting locoregional recurrence risk (hazard ratio 3.6, 95% confidence interval 1.2-11.1, p = 0.025).

Conclusions

Our results demonstrate that dense breast tissue (>50% density) increased the risk of locoregional recurrence after modified radical mastectomy in patients with invasive breast cancer. Additional prospective studies are necessary to validate these findings.

Trial registration

The study is retrospectively registered with ClinicalTrials.gov, number NCT02771665 , on May 11, 2016.

SUBMITTER: Huang YS

PROVIDER: S-EPMC5134100 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High mammographic breast density predicts locoregional recurrence after modified radical mastectomy for invasive breast cancer: a case-control study.

Huang Yu-Sen YS Chen Jenny Ling-Yu JL Huang Chiun-Sheng CS Kuo Sung-Hsin SH Jaw Fu-Shan FS Tseng Yao-Hui YH Ko Wei-Chun WC Chang Yeun-Chung YC

Breast cancer research : BCR 20161201 1

<h4>Background</h4>We aimed to evaluate the influence of mammographic breast density at diagnosis on the risk of cancer recurrence and survival outcomes in patients with invasive breast cancer after modified radical mastectomy.<h4>Methods</h4>This case-control study included 121 case-control pairs of women diagnosed with invasive breast cancer between 2004 and 2009, and who had undergone modified radical mastectomy and had mammographic breast density measured before or at diagnosis. Women with k ...[more]

PMID: 27906044

Similar Datasets

Project description:BackgroundDespite the common use of conventional electrocautery in modified radical mastectomy for breast cancer, the harmonic scalpel is recently emerging as a dominant surgical instrument for dissection and haemostasis, which is thought to reduce the morbidity, such as seroma and blood loss. But the results of published trials are inconsistent. So we made the meta-analysis to assess the intraoperative and postoperative endpoints among women undergoing modified radical mastectomy with harmonic scalpel or electrocautery.MethodsA comprehensive literature search of case-control studies from PubMed, MEDLINE, EMBASE and Cochrane Library databases involving modified radical mastectomy with harmonic scalpel or electrocautery was performed. We carried out a meta-analysis of primary endpoints including postoperative drainage, seroma development, intraoperative blood loss and secondly endpoints including operative time and wound complications. We used odds ratios (ORs) with 95% confidence intervals (CIs) to evaluate the effect size for categorical outcomes and standardised mean differences (SMDs) for continuous outcomes.ResultsA total of 11 studies with 702 patients were included for this meta-analysis. There was significant difference in total postoperative drainage (SMD: -0.74 [95%CI: -1.31, -0.16]; P< 0.01), seroma development[OR: 0.49 (0.34, 0.70); P < 0.01], intraoperative blood loss(SMD: -1.14 [95%CI: -1.81,-0.47]; P < 0.01) and wound complications [OR: 0.38 (0.24, 0.59); P < 0.01] between harmonic scalpel dissection and standard electrocautery in modified radical mastectomy for breast cancer. No difference was found as for operative time between harmonic scalpel dissection and standard electrocautery (SMD: 0.04 [95%CI: -0.41, 0.50]; P = 0.85).ConclusionCompared to standard electrocautery, harmonic scalpel dissection presents significant advantages in decreasing postoperative drainage, seroma development, intraoperative blood loss and wound complications in modified radical mastectomy for breast cancer, without increasing operative time. Harmonic scalpel can be recommended as a preferential surgical instrument in modified radical mastectomy.

Project description:INTRODUCTION:While Cumulus - a semi-automated method for measuring breast density - is utilised extensively in research, it is labour-intensive and unsuitable for screening programmes that require an efficient and valid measure on which to base screening recommendations. We develop an automated method to measure breast density (AutoDensity) and compare it to Cumulus in terms of association with breast cancer risk and breast cancer screening outcomes. METHODS:AutoDensity automatically identifies the breast area in the mammogram and classifies breast density in a similar way to Cumulus, through a fast, stand-alone Windows or Linux program. Our sample comprised 985 women with screen-detected cancers, 367 women with interval cancers and 4,975 controls (women who did not have cancer), sampled from first and subsequent screening rounds of a film mammography screening programme. To test the validity of AutoDensity, we compared the effect estimates using AutoDensity with those using Cumulus from logistic regression models that tested the association between breast density and breast cancer risk, risk of small and large screen-detected cancers and interval cancers, and screening programme sensitivity (the proportion of cancers that are screen-detected). As a secondary analysis, we report on correlation between AutoDensity and Cumulus measures. RESULTS:AutoDensity performed similarly to Cumulus in all associations tested. For example, using AutoDensity, the odds ratios for women in the highest decile of breast density compared to women in the lowest quintile for invasive breast cancer, interval cancers, large and small screen-detected cancers were 3.2 (95% CI 2.5 to 4.1), 4.7 (95% CI 3.0 to 7.4), 6.4 (95% CI 3.7 to 11.1) and 2.2 (95% CI 1.6 to 3.0) respectively. For Cumulus the corresponding odds ratios were: 2.4 (95% CI 1.9 to 3.1), 4.1 (95% CI 2.6 to 6.3), 6.6 (95% CI 3.7 to 11.7) and 1.3 (95% CI 0.9 to 1.8). Correlation between Cumulus and AutoDensity measures was 0.63 (P < 0.001). CONCLUSIONS:Based on the similarity of the effect estimates for AutoDensity and Cumulus inmodels of breast density and breast cancer risk and screening outcomes, we conclude that AutoDensity is a valid automated method for measuring breast density from digitised film mammograms.

Dataset Information

High mammographic breast density predicts locoregional recurrence after modified radical mastectomy for invasive breast cancer: a case-control study.

Background

Methods

Results

Conclusions

Trial registration

Publications

High mammographic breast density predicts locoregional recurrence after modified radical mastectomy for invasive breast cancer: a case-control study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets