Impact of adding breast density to breast cancer risk models: A systematic review

Vilmun, Bolette Mikela; Vejborg, Ilse; Lynge, Elsebeth; Lillholm, Martin; Nielsen, Mads; Nielsen, Michael Bachmann; Carlsen, Jonathan Frederik

doi:10.1016/j.ejrad.2020.109019

Cited by 39 publications

(40 citation statements)

References 59 publications

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“…In the present nationwide Danish screening program with its "one-size-fits-all" biennial screening of women aged 50-69 years, the 2-year risk of breast cancer was 80 times higher in screen-positive than in screen-negative women [44]. In comparison, the ability of personalized screening models to discriminate between low and high risk women is 0.51-0.80, which is between none and moderate [45]. Another approach to personalized screening might be to target women based on the outcome of screening.…”

Section: Public Health Implicationsmentioning

confidence: 82%

Breast cancer mortality and overdiagnosis after implementation of population-based screening in Denmark

Lynge

Beau

Euler‐Chelpin

et al. 2020

Breast Cancer Res Treat

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Introduction Service breast cancer screening is difficult to evaluate because there is no unscreened control group. Due to a natural experiment, where 20% of women were offered screening in two regions up to 17 years before other women, Denmark is in a unique position. We utilized this opportunity to assess outcome of service screening. Materials and methods Screening was offered in Copenhagen from 1991 and Funen from 1993 to women aged 50-69 years. We used difference-indifferences methodology with a study group offered screening; a historical control group; a regional control group; and a regional-historical control group, comparing breast cancer mortality and incidence, including ductal carcinoma in situ, between study and historical control group adjusted for changes in other regions, and calculating ratios of rate ratios (RRR) with 95% confidence intervals (CI). Data came from Central Population Register; mammography screening databases; Cause of Death Register; and Danish Cancer Register. Results For breast cancer mortality, the study group accumulated 1,551,465 person-years and 911 deaths. Long-term breast cancer mortality in Copenhagen was 20% below expected in absence of screening; RRR 0.80 (95% CI 0.71-0.90), and in Funen 22% below; RRR 0.78 (95% CI 0.68-0.89). Combined, cumulative breast cancer incidence in women followed 8+ years post-screening was 2.3% above expected in absence of screening; RRR 1.023 (95% CI 0.97-1.08). Discussion Benefit-to-harm ratio of the two Danish screening programs was 2.6 saved breast cancer deaths per overdiagnosed case. Screening can affect only breast cancers diagnosed in screening age. Due to high breast cancer incidence after age 70, only one-third of breast cancer deaths after age 50 could potentially be affected by screening. Increasing upper age limit could be considered, but might affect benefit-to-harm ratio negatively.

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Section: Public Health Implicationsmentioning

confidence: 82%

Breast cancer mortality and overdiagnosis after implementation of population-based screening in Denmark

Lynge

Beau

Euler‐Chelpin

et al. 2020

Breast Cancer Res Treat

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“…Its significance is therefore inconclusive and would have to be carefully considered prior to incorporation into existing and established models of risk prediction, such as the Gail model or Tyrer-Cuzick. Integrating a clinical assessment tool into an existing model could both strengthen and personalise risk in asymptomatic, high-risk women, as illustrated by Vilmun et al 15 when reviewing the impact of adding breast density to breast cancer risk models. 78 In order to offer a personalised approach to risk screening, implementation of a stratification protocol offering varying screening regimes according to their elicited risk, following the interrogation of nipple smear cytology, would be required to be undertaken in various patient cohorts.…”

Section: Discussionmentioning

confidence: 99%

“…[12][13][14] This is primarily due to limited discrimination accuracy. 15 The Gail model, for example, tends to underestimate risk as it only takes into account first-degree relatives and does not consider age of onset of cancer. 11,16 The Claus model, although accounting for many of the genetic variations of risk, does not consider any non-hereditary risk factors and reflects women in the USA in the 1980s, mirroring a population with an outdated incidence of breast cancer 16 in both North America and Europe.…”

mentioning

confidence: 99%

“…17,18 Although the Tyrer-Cuzick model adjusts for many of these genetic factors, it focuses predominantly on penetrance of BRCA1/2 mutations rather than the plethora of non-BRCA mutations 14,19 and tends to over-estimate risk in women with atypical hyperplasia. 13 As has been suggested with breast density, 15 this begs the question as to whether adding further adjuncts such as nipple fluid cytological findings, if predictive findings are significant, could strengthen current risk assessment models and offer a personalised approach to risk screening in the future.…”

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confidence: 99%

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Diagnostic Accuracy of Nipple Aspirate Fluid Cytology in Asymptomatic Patients: A Meta-analysis and Systematic Review of the Literature

et al. 2020

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Purpose To calculate the diagnostic accuracy of nipple aspirate fluid (NAF) cytology. Background Evaluation of NAF cytology in asymptomatic patients conceptually offers a non-invasive method for either screening for breast cancer or else predicting or stratifying future cancer risk. Methods Studies were identified by performing electronic searches up to August 2019. A meta-analysis was conducted to attain an overall pooled sensitivity and specificity of NAF for breast cancer detection. Results A search through 938 studies yielded a total of 19 studies. Overall, 9308 patients were examined, with cytology results from 10,147 breasts [age (years), mean ± SD = 49.73 ± 4.09 years]. Diagnostic accuracy meta-analysis of NAF revealed a pooled specificity of 0.97 (95% CI 0.97–0.98), and sensitivity of 0.64 (95% CI 0.62–0.66). Conclusions The diagnostic accuracy of nipple smear cytology is limited by poor sensitivity. If nipple fluid assessment is to be used for diagnosis, then emerging technologies for fluid biomarker analysis must supersede the current diagnostic accuracy of NAF cytology.

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“…There is an estimated 4-5 fold greater risk of breast cancer in women within the highest breast density quintile compared with the lowest quintile (after adjustment for age, menopausal status and BMI) (6,7). Because of the major impact of MD on risk even for BRCA1/2 mutation carriers (8), MD has been successfully included in several models to assess breast cancer risk (9)(10)(11)(12)(13).…”

mentioning

confidence: 99%

Heritability of mammographic breast density

Evans¹,

Veen²,

Howell³

et al. 2020

Quant Imaging Med Surg

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Impact of adding breast density to breast cancer risk models: A systematic review

Cited by 39 publications

References 59 publications

Breast cancer mortality and overdiagnosis after implementation of population-based screening in Denmark

Breast cancer mortality and overdiagnosis after implementation of population-based screening in Denmark

Diagnostic Accuracy of Nipple Aspirate Fluid Cytology in Asymptomatic Patients: A Meta-analysis and Systematic Review of the Literature

Heritability of mammographic breast density

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