Cancers

Research

13 pages, 1120 KiB

Open AccessArticle

Prevalence of Cancer Predisposition Germline Variants in Male Breast Cancer Patients: Results of the German Consortium for Hereditary Breast and Ovarian Cancer

by Muriel Rolfes, Julika Borde, Kathrin Möllenhoff, Mohamad Kayali, Corinna Ernst, Andrea Gehrig, Christian Sutter, Juliane Ramser, Dieter Niederacher, Judit Horváth, Norbert Arnold, Alfons Meindl, Bernd Auber, Andreas Rump, Shan Wang-Gohrke, Julia Ritter, Julia Hentschel, Holger Thiele, Janine Altmüller, Peter Nürnberg, Kerstin Rhiem, Christoph Engel, Barbara Wappenschmidt, Rita K. Schmutzler, Eric Hahnen and Jan Hauke Show full author list Hide full author list

Cancers 2022, 14(13), 3292; https://doi.org/10.3390/cancers14133292 - 5 Jul 2022

Cited by 14 | Viewed by 8075

Abstract

Male breast cancer (mBC) is associated with a high prevalence of pathogenic variants (PVs) in the BRCA2 gene; however, data regarding other BC predisposition genes are limited. In this retrospective multicenter study, we investigated the prevalence of PVs in BRCA1/2 and 23 non- [...] Read more.

Male breast cancer (mBC) is associated with a high prevalence of pathogenic variants (PVs) in the BRCA2 gene; however, data regarding other BC predisposition genes are limited. In this retrospective multicenter study, we investigated the prevalence of PVs in BRCA1/2 and 23 non-BRCA1/2 genes using a sample of 614 patients with mBC, recruited through the centers of the German Consortium for Hereditary Breast and Ovarian Cancer. A high proportion of patients with mBC carried PVs in BRCA2 (23.0%, 142/614) and BRCA1 (4.6%, 28/614). The prevalence of BRCA1/2 PVs was 11.0% in patients with mBC without a family history of breast and/or ovarian cancer. Patients with BRCA1/2 PVs did not show an earlier disease onset than those without. The predominant clinical presentation of tumor phenotypes was estrogen receptor (ER)-positive, progesterone receptor (PR)-positive, and HER2-negative (77.7%); further, 10.2% of the tumors were triple-positive, and 1.2% were triple-negative. No association was found between ER/PR/HER2 status and BRCA1/2 PV occurrence. Comparing the prevalence of protein-truncating variants (PTVs) between patients with mBC and control data (ExAC, n = 27,173) revealed significant associations of PTVs in both BRCA1 and BRCA2 with mBC (BRCA1: OR = 17.04, 95% CI = 10.54–26.82, p < 10⁻⁵; BRCA2: OR = 77.71, 95% CI = 58.71–102.33, p < 10⁻⁵). A case-control investigation of 23 non-BRCA1/2 genes in 340 BRCA1/2-negative patients and ExAC controls revealed significant associations of PTVs in CHEK2, PALB2, and ATM with mBC (CHEK2: OR = 3.78, 95% CI = 1.59–7.71, p = 0.002; PALB2: OR = 14.77, 95% CI = 5.02–36.02, p < 10⁻⁵; ATM: OR = 3.36, 95% CI = 0.89–8.96, p = 0.04). Overall, our findings support the benefit of multi-gene panel testing in patients with mBC irrespective of their family history, age at disease onset, and tumor phenotype. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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21 pages, 1430 KiB

Open AccessArticle

Validation of Breast Cancer Risk Models by Race/Ethnicity, Family History and Molecular Subtypes

by Anne Marie McCarthy, Yi Liu, Sarah Ehsan, Zoe Guan, Jane Liang, Theodore Huang, Kevin Hughes, Alan Semine, Despina Kontos, Emily Conant, Constance Lehman, Katrina Armstrong, Danielle Braun, Giovanni Parmigiani and Jinbo Chen

Cancers 2022, 14(1), 45; https://doi.org/10.3390/cancers14010045 - 23 Dec 2021

Cited by 19 | Viewed by 3496

Abstract

(1) Background: The purpose of this study is to compare the performance of four breast cancer risk prediction models by race, molecular subtype, family history of breast cancer, age, and BMI. (2) Methods: Using a cohort of women aged 40–84 without prior history [...] Read more.

(1) Background: The purpose of this study is to compare the performance of four breast cancer risk prediction models by race, molecular subtype, family history of breast cancer, age, and BMI. (2) Methods: Using a cohort of women aged 40–84 without prior history of breast cancer who underwent screening mammography from 2006 to 2015, we generated breast cancer risk estimates using the Breast Cancer Risk Assessment tool (BCRAT), BRCAPRO, Breast Cancer Surveillance Consortium (BCSC) and combined BRCAPRO+BCRAT models. Model calibration and discrimination were compared using observed-to-expected ratios (O/E) and the area under the receiver operator curve (AUC) among patients with at least five years of follow-up. (3) Results: We observed comparable discrimination and calibration across models. There was no significant difference in model performance between Black and White women. Model discrimination was poorer for HER2+ and triple-negative subtypes compared with ER/PR+HER2−. The BRCAPRO+BCRAT model displayed improved calibration and discrimination compared to BRCAPRO among women with a family history of breast cancer. Across models, discriminatory accuracy was greater among obese than non-obese women. When defining high risk as a 5-year risk of 1.67% or greater, models demonstrated discordance in 2.9% to 19.7% of patients. (4) Conclusions: Our results can inform the implementation of risk assessment and risk-based screening among women undergoing screening mammography. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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16 pages, 2107 KiB

Open AccessArticle

The Impact of Lifestyle Interventions in High-Risk Early Breast Cancer Patients: A Modeling Approach from a Single Institution Experience

by Mirco Pistelli, Valentina Natalucci, Laura Scortichini, Veronica Agostinelli, Edoardo Lenci, Sonia Crocetti, Filippo Merloni, Lucia Bastianelli, Marina Taus, Daniele Fumelli, Gloria Giulietti, Claudia Cola, Marianna Capecci, Roberta Serrani, Maria Gabriella Ceravolo, Maurizio Ricci, Albano Nicolai, Elena Barbieri, Giulia Nicolai, Zelmira Ballatore, Agnese Savini and Rossana Berardi Show full author list Hide full author list

Cancers 2021, 13(21), 5539; https://doi.org/10.3390/cancers13215539 - 4 Nov 2021

Cited by 10 | Viewed by 3053

Abstract

A healthy lifestyle plays a strategic role in the prevention of BC. The aim of our prospective study is to evaluate the effects of a lifestyle interventions program based on special exercise and nutrition education on weight, psycho-physical well-being, blood lipid and hormonal [...] Read more.

A healthy lifestyle plays a strategic role in the prevention of BC. The aim of our prospective study is to evaluate the effects of a lifestyle interventions program based on special exercise and nutrition education on weight, psycho-physical well-being, blood lipid and hormonal profile among BC patients who underwent primary surgery. From January 2014 to March 2017, a multidisciplinary group of oncologists, dieticians, physiatrists and an exercise specialist evaluated 98 adult BC female patients at baseline and at different time points. The patients had at least one of the following risk factors: BMI ≥ 25 kg/m², high testosterone levels, high serum insulin levels or diagnosis of MS. Statistically significant differences are shown in terms of BMI variation with the lifestyle interventions program, as well as in waist circumference and blood glucose, insulin and testosterone levels. Moreover, a statistically significant difference was reported in variations of total Hospital Anxiety and Depression Scale (HADS) score, in the anxiety HADS score and improvement in joint pain. Our results suggested that promoting a healthy lifestyle in clinical practice reduces risk factors involved in BC recurrence and ensures psycho-physical well-being. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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16 pages, 1908 KiB

Open AccessArticle

Incorporating Robustness to Imaging Physics into Radiomic Feature Selection for Breast Cancer Risk Estimation

by Raymond J. Acciavatti, Eric A. Cohen, Omid Haji Maghsoudi, Aimilia Gastounioti, Lauren Pantalone, Meng-Kang Hsieh, Emily F. Conant, Christopher G. Scott, Stacey J. Winham, Karla Kerlikowske, Celine Vachon, Andrew D. A. Maidment and Despina Kontos

Cancers 2021, 13(21), 5497; https://doi.org/10.3390/cancers13215497 - 1 Nov 2021

Cited by 4 | Viewed by 2774

Abstract

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects [...] Read more.

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects of imaging physics, we analyzed the feature variation across imaging acquisition settings (kV, mAs) using an anthropomorphic phantom. We also analyzed the intra-woman variation (IWV), a measure of how much a feature varies between breasts with similar parenchymal patterns—a woman’s left and right breasts. From 341 features, we identified “robust” features that minimized the effects of imaging physics and IWV. We also investigated whether robust features offered better case-control classification in an independent data set of 575 images, all with an overall BI-RADS^® assessment of 1 (negative) or 2 (benign); 115 images (cases) were of women who developed cancer at least one year after that screening image, matched to 460 controls. We modeled cancer occurrence via logistic regression, using cross-validated area under the receiver-operating-characteristic curve (AUC) to measure model performance. Models using features from the most-robust quartile of features yielded an AUC = 0.59, versus 0.54 for the least-robust, with p < 0.005 for the difference among the quartiles. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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11 pages, 1135 KiB

Open AccessArticle

Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models

by Sherly X. Li, Roger L. Milne, Tú Nguyen-Dumont, Dallas R. English, Graham G. Giles, Melissa C. Southey, Antonis C. Antoniou, Andrew Lee, Ingrid Winship, John L. Hopper, Mary Beth Terry and Robert J. MacInnis

Cancers 2021, 13(20), 5194; https://doi.org/10.3390/cancers13205194 - 16 Oct 2021

Cited by 7 | Viewed by 2400

Abstract

Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle [...] Read more.

Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50–65 years and unaffected at commencement of follow-up two (conducted in 2003–2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50–54, 55–59, 60–65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56–0.62) and IBIS (0.57, 95% CI 0.54–0.61) than the other models (p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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14 pages, 2202 KiB

Open AccessArticle

Data on Utility in Cost–Utility Analyses of Genetic Screen-and-Treat Strategies for Breast and Ovarian Cancer

by Julia Simões Corrêa Galendi, Vera Vennedey, Hannah Kentenich, Stephanie Stock and Dirk Müller

Cancers 2021, 13(19), 4879; https://doi.org/10.3390/cancers13194879 - 29 Sep 2021

Cited by 2 | Viewed by 2366

Abstract

Genetic screen-and-treat strategies for the risk-reduction of breast cancer (BC) and ovarian cancer (OC) are often evaluated by cost–utility analyses (CUAs). This analysis compares data on health preferences (i.e., utility values) in CUAs of targeted genetic testing for BC and OC. Based on [...] Read more.

Genetic screen-and-treat strategies for the risk-reduction of breast cancer (BC) and ovarian cancer (OC) are often evaluated by cost–utility analyses (CUAs). This analysis compares data on health preferences (i.e., utility values) in CUAs of targeted genetic testing for BC and OC. Based on utilities applied in fourteen CUAs, data on utility including related assumptions were extracted for the health states: (i) genetic test, (ii) risk-reducing surgeries, (iii) BC/OC and (iv) post cancer. In addition, information about the sources of utility and the impact on the cost-effectiveness was extracted. Utility for CUAs relied on heterogeneous data and assumptions for all health states. The utility values ranged from 0.68 to 0.97 for risk-reducing surgeries, 0.6 to 0.85 for BC and 0.5 to 0.82 for OC. In two out of nine studies, considering the impact of the test result strongly affected the cost–effectiveness ratio. While in general utilities seem not to affect the cost–utility ratio, in future modeling studies the impact of a positive/negative test on utility should be considered mandatory. Women’s health preferences, which may have changed as a result of improved oncologic care and genetic counselling, should be re-evaluated. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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12 pages, 699 KiB

Open AccessArticle

Combination of a 15-SNP Polygenic Risk Score and Classical Risk Factors for the Prediction of Breast Cancer Risk in Cypriot Women

by Kristia Yiangou, Kyriacos Kyriacou, Eleni Kakouri, Yiola Marcou, Mihalis I. Panayiotidis, Maria A. Loizidou, Andreas Hadjisavvas and Kyriaki Michailidou

Cancers 2021, 13(18), 4568; https://doi.org/10.3390/cancers13184568 - 11 Sep 2021

Cited by 7 | Viewed by 2647

Abstract

The PRS combines multiplicatively the effects of common low-risk single nucleotide polymorphisms (SNPs) and has the potential to be used for the estimation of an individual’s risk for a trait or disease. PRS has been successfully implemented for the prediction of breast cancer [...] Read more.

The PRS combines multiplicatively the effects of common low-risk single nucleotide polymorphisms (SNPs) and has the potential to be used for the estimation of an individual’s risk for a trait or disease. PRS has been successfully implemented for the prediction of breast cancer risk. The combination of PRS with classical breast cancer risk factors provides a more comprehensive risk estimation and could, thus, improve risk stratification and personalized preventative strategies. In this study, we assessed the predictive performance of the combined effect of PRS₁₅ with classical breast-cancer risk factors in Cypriot women using 1109 cases and 1177 controls from the MASTOS study. The PRS₁₅ was significantly associated with an increased breast cancer risk in Cypriot women OR (95% CI) 1.66 (1.25–2.19). The integrated risk model obtained an AUC (95% CI) 0.70 (0.67–0.72) and had the ability to stratify women according to their disease status at the extreme deciles. These results provide evidence that the combination of PRS with classical risk factors may be used in the future for the stratification of Cypriot women based on their disease risk, and support its potential clinical utility for targeted preventative actions and population screening. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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18 pages, 1176 KiB

Open AccessArticle

TUMOSPEC: A Nation-Wide Study of Hereditary Breast and Ovarian Cancer Families with a Predicted Pathogenic Variant Identified through Multigene Panel Testing

by Fabienne Lesueur, Séverine Eon-Marchais, Sarah Bonnet-Boissinot, Juana Beauvallet, Marie-Gabrielle Dondon, Lisa Golmard, Etienne Rouleau, Céline Garrec, Mathilde Martinez, Christine Toulas, Tan Dat Nguyen, Fanny Brayotel, Louise Crivelli, Christine M. Maugard, Virginie Bubien, Nicolas Sevenet, Paul Gesta, Stéphanie Chieze-Valero, Sophie Nambot, Vincent Goussot, Véronique Mari, Cornel Popovici, Fabienne Prieur, Marie-Emmanuelle Morin-Meschin, Julie Tinat, Alain Lortholary, Hélène Dreyfus, Marie Bidart, Marie-Agnès Collonge-Rame, Monique Mozelle-Nivoix, Laurence Gladieff, Sophie Giraud, Nadia Boutry-Kryza, Jean Chiesa, Philippe Denizeau, Yves-Jean Bignon, Nancy Uhrhammer, Odile Cohen-Haguenauer, Paul Vilquin, Audrey Mailliez, Isabelle Coupier, Jean-Marc Rey, Elodie Lacaze, Odile Béra, Chrystelle Colas, Florence Coulet, Capucine Delnatte, Claude Houdayer, Christine Lasset, Jérôme Lemonnier, Michel Longy, Catherine Noguès, Dominique Stoppa-Lyonnet, Dominique Vaur, Nadine Andrieu and Olivier Caron Show full author list Hide full author list

Cancers 2021, 13(15), 3659; https://doi.org/10.3390/cancers13153659 - 21 Jul 2021

Cited by 5 | Viewed by 3128

Abstract

Assessment of age-dependent cancer risk for carriers of a predicted pathogenic variant (PPV) is often hampered by biases in data collection, with a frequent under-representation of cancer-free PPV carriers. TUMOSPEC was designed to estimate the cumulative risk of cancer for carriers of a [...] Read more.

Assessment of age-dependent cancer risk for carriers of a predicted pathogenic variant (PPV) is often hampered by biases in data collection, with a frequent under-representation of cancer-free PPV carriers. TUMOSPEC was designed to estimate the cumulative risk of cancer for carriers of a PPV in a gene that is usually tested in a hereditary breast and ovarian cancer context. Index cases are enrolled consecutively among patients who undergo genetic testing as part of their care plan in France. First- and second-degree relatives and cousins of PPV carriers are invited to participate whether they are affected by cancer or not, and genotyped for the familial PPV. Clinical, family and epidemiological data are collected, and all data including sequencing data are centralized at the coordinating centre. The three-year feasibility study included 4431 prospective index cases, with 19.1% of them carrying a PPV. When invited by the coordinating centre, 65.3% of the relatives of index cases (5.7 relatives per family, on average) accepted the invitation to participate. The study logistics were well adapted to clinical and laboratory constraints, and collaboration between partners (clinicians, biologists, coordinating centre and participants) was smooth. Hence, TUMOSPEC is being pursued, with the aim of optimizing clinical management guidelines specific to each gene. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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12 pages, 6447 KiB

Open AccessArticle

Genomic Risk Prediction for Breast Cancer in Older Women

by Paul Lacaze, Andrew Bakshi, Moeen Riaz, Suzanne G. Orchard, Jane Tiller, Johannes T. Neumann, Prudence R. Carr, Amit D. Joshi, Yin Cao, Erica T. Warner, Alisa Manning, Tú Nguyen-Dumont, Melissa C. Southey, Roger L. Milne, Leslie Ford, Robert Sebra, Eric Schadt, Lucy Gately, Peter Gibbs, Bryony A. Thompson, Finlay A. Macrae, Paul James, Ingrid Winship, Catriona McLean, John R. Zalcberg, Robyn L. Woods, Andrew T. Chan, Anne M. Murray and John J. McNeil Show full author list Hide full author list

Cancers 2021, 13(14), 3533; https://doi.org/10.3390/cancers13143533 - 14 Jul 2021

Cited by 5 | Viewed by 3316

Abstract

Genomic risk prediction models for breast cancer (BC) have been predominantly developed with data from women aged 40–69 years. Prospective studies of older women aged ≥70 years have been limited. We assessed the effect of a 313-variant polygenic risk score (PRS) for BC [...] Read more.

Genomic risk prediction models for breast cancer (BC) have been predominantly developed with data from women aged 40–69 years. Prospective studies of older women aged ≥70 years have been limited. We assessed the effect of a 313-variant polygenic risk score (PRS) for BC in 6339 older women aged ≥70 years (mean age 75 years) enrolled into the ASPREE trial, a randomized double-blind placebo-controlled clinical trial investigating the effect of daily 100 mg aspirin on disability-free survival. We evaluated incident BC diagnoses over a median follow-up time of 4.7 years. A multivariable Cox regression model including conventional BC risk factors was applied to prospective data, and re-evaluated after adding the PRS. We also assessed the association of rare pathogenic variants (PVs) in BC susceptibility genes (BRCA1/BRCA2/PALB2/CHEK2/ATM). The PRS, as a continuous variable, was an independent predictor of incident BC (hazard ratio (HR) per standard deviation (SD) = 1.4, 95% confidence interval (CI) 1.3–1.6) and hormone receptor (ER/PR)-positive disease (HR = 1.5 (CI 1.2–1.9)). Women in the top quintile of the PRS distribution had over two-fold higher risk of BC than women in the lowest quintile (HR = 2.2 (CI 1.2–3.9)). The concordance index of the model without the PRS was 0.62 (95% CI 0.56–0.68), which improved after addition of the PRS to 0.65 (95% CI 0.59–0.71). Among 41 (0.6%) carriers of PVs in BC susceptibility genes, we observed no incident BC diagnoses. Our study demonstrates that a PRS predicts incident BC risk in women aged 70 years and older, suggesting potential clinical utility extends to this older age group. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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13 pages, 1022 KiB

Open AccessArticle

BRENDA-Score, a Highly Significant, Internally and Externally Validated Prognostic Marker for Metastatic Recurrence: Analysis of 10,449 Primary Breast Cancer Patients

by Manfred Wischnewsky, Lukas Schwentner, Joachim Diessner, Amelie de Gregorio, Ralf Joukhadar, Dayan Davut, Jessica Salmen, Inga Bekes, Matthias Kiesel, Max Müller-Reiter, Maria Blettner, Regine Wolters, Wolfgang Janni, Rolf Kreienberg, Achim Wöckel and Florian Ebner

Cancers 2021, 13(13), 3121; https://doi.org/10.3390/cancers13133121 - 22 Jun 2021

Cited by 3 | Viewed by 2013

Abstract

Background Current research in breast cancer focuses on individualization of local and systemic therapies with adequate escalation or de-escalation strategies. As a result, about two-thirds of breast cancer patients can be cured, but up to one-third eventually develop metastatic disease, which is considered [...] Read more.

Background Current research in breast cancer focuses on individualization of local and systemic therapies with adequate escalation or de-escalation strategies. As a result, about two-thirds of breast cancer patients can be cured, but up to one-third eventually develop metastatic disease, which is considered incurable with currently available treatment options. This underscores the importance to develop a metastatic recurrence score to escalate or de-escalate treatment strategies. Patients and methods Data from 10,499 patients were available from 17 clinical cancer registries (BRENDA-project. In total, 8566 were used to develop the BRENDA-Index. This index was calculated from the regression coefficients of a Cox regression model for metastasis-free survival (MFS). Based on this index, patients were categorized into very high, high, intermediate, low, and very low risk groups forming the BRENDA-Score. Bootstrapping was used for internal validation and an independent dataset of 1883 patients for external validation. The predictive accuracy was checked by Harrell’s c-index. In addition, the BRENDA-Score was analyzed as a marker for overall survival (OS) and compared to the Nottingham prognostic score (NPS). Results: Intrinsic subtypes, tumour size, grading, and nodal status were identified as statistically significant prognostic factors in the multivariate analysis. The five prognostic groups of the BRENDA-Score showed highly significant (p < 0.001) differences regarding MFS:low risk: hazard ratio (HR) = 2.4, 95%CI (1.7–3.3); intermediate risk: HR = 5.0, 95%CI.(3.6–6.9); high risk: HR = 10.3, 95%CI (7.4–14.3) and very high risk: HR = 18.1, 95%CI (13.2–24.9). The external validation showed congruent results. A multivariate Cox regression model for OS with BRENDA-Score and NPS as covariates showed that of these two scores only the BRENDA-Score is significant (BRENDA-Score p < 0.001; NPS p = 0.447). Therefore, the BRENDA-Score is also a good prognostic marker for OS. Conclusion: The BRENDA-Score is an internally and externally validated robust predictive tool for metastatic recurrence in breast cancer patients. It is based on routine parameters easily accessible in daily clinical care. In addition, the BRENDA-Score is a good prognostic marker for overall survival. Highlights: The BRENDA-Score is a highly significant predictive tool for metastatic recurrence of breast cancer patients. The BRENDA-Score is stable for at least the first five years after primary diagnosis, i.e., the sensitivities and specificities of this predicting system is rather similar to the NPI with AUCs between 0.76 and 0.81 the BRENDA-Score is a good prognostic marker for overall survival. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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13 pages, 713 KiB

Open AccessArticle

Use of Low-Dose Tamoxifen to Increase Mammographic Screening Sensitivity in Premenopausal Women

by Mikael Eriksson, Kamila Czene, Emily F. Conant and Per Hall

Cancers 2021, 13(2), 302; https://doi.org/10.3390/cancers13020302 - 15 Jan 2021

Cited by 7 | Viewed by 2512

Abstract

Increased breast density decreases mammographic sensitivity due to masking of cancers by dense tissue. Tamoxifen exposure reduces mammographic density and, therefore, should improve screening sensitivity. We modelled how low-dose tamoxifen exposure could be used to increase mammographic sensitivity. Mammographic sensitivity was calculated using [...] Read more.

Increased breast density decreases mammographic sensitivity due to masking of cancers by dense tissue. Tamoxifen exposure reduces mammographic density and, therefore, should improve screening sensitivity. We modelled how low-dose tamoxifen exposure could be used to increase mammographic sensitivity. Mammographic sensitivity was calculated using the KARMA prospective screening cohort. Two models were fitted to estimate screening sensitivity and detected tumor size based on baseline mammographic density. BI-RADS-dependent sensitivity was estimated. The results of the 2.5 mg tamoxifen arm of the KARISMA trial were used to define expected changes in mammographic density after six months exposure and to predict changes in mammographic screening sensitivity and detected tumor size. Rates of interval cancers and detection of invasive tumors were estimated for women with mammographic density relative decreases by 10–50%. In all, 517 cancers in premenopausal women were diagnosed in KARMA: 287 (56%) screen-detected and 230 (44%) interval cancers. Screening sensitivities prior to tamoxifen, were 76%, 69%, 53%, and 46% for BI-RADS density categories A, B, C, and D, respectively. After exposure to tamoxifen, modelled screening sensitivities were estimated to increase by 0% (p = 0.35), 2% (p < 0.01), 5% (p < 0.01), and 5% (p < 0.01), respectively. An estimated relative density decrease by ≥20% resulted in an estimated reduction of interval cancers by 24% (p < 0.01) and reduction in tumors >20 mm at detection by 4% (p < 0.01). Low-dose tamoxifen has the potential to increase mammographic screening sensitivity and thereby reduce the proportion of interval cancers and larger screen-detected cancers. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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Review

Jump to: Research, Other

30 pages, 518 KiB

Open AccessReview

A Review of Breast Cancer Risk Factors in Adolescents and Young Adults

by Una Mary McVeigh, John William Tepper and Terri Patricia McVeigh

Cancers 2021, 13(21), 5552; https://doi.org/10.3390/cancers13215552 - 5 Nov 2021

Cited by 12 | Viewed by 3810

Abstract

Cancer in adolescents and young adults (AYAs) deserves special consideration for several reasons. AYA cancers encompass paediatric malignancies that present at an older age than expected, or early-onset of cancers that are typically observed in adults. However, disease diagnosed in the AYA population [...] Read more.

Cancer in adolescents and young adults (AYAs) deserves special consideration for several reasons. AYA cancers encompass paediatric malignancies that present at an older age than expected, or early-onset of cancers that are typically observed in adults. However, disease diagnosed in the AYA population is distinct to those same cancers which are diagnosed in a paediatric or older adult setting. Worse disease-free and overall survival outcomes are observed in the AYA setting, and the incidence of AYA cancers is increasing. Knowledge of an individual’s underlying cancer predisposition can influence their clinical care and may facilitate early tumour surveillance strategies and cascade testing of at-risk relatives. This information can further influence reproductive decision making. In this review we discuss the risk factors contributing to AYA breast cancer, such as heritable predisposition, environmental, and lifestyle factors. We also describe a number of risk models which incorporate genetic factors that aid clinicians in quantifying an individual’s lifetime risk of disease. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

23 pages, 849 KiB

Open AccessReview

Breast Cancer Risk Assessment and Primary Prevention Advice in Primary Care: A Systematic Review of Provider Attitudes and Routine Behaviours

by Sarah Bellhouse, Rhiannon E. Hawkes, Sacha J. Howell, Louise Gorman and David P. French

Cancers 2021, 13(16), 4150; https://doi.org/10.3390/cancers13164150 - 18 Aug 2021

Cited by 25 | Viewed by 4874

Abstract

Implementing risk-stratified breast cancer screening is being considered internationally. It has been suggested that primary care will need to take a role in delivering this service, including risk assessment and provision of primary prevention advice. This systematic review aimed to assess the acceptability [...] Read more.

Implementing risk-stratified breast cancer screening is being considered internationally. It has been suggested that primary care will need to take a role in delivering this service, including risk assessment and provision of primary prevention advice. This systematic review aimed to assess the acceptability of these tasks to primary care providers. Five databases were searched up to July–August 2020, yielding 29 eligible studies, of which 27 were narratively synthesised. The review was pre-registered (PROSPERO: CRD42020197676). Primary care providers report frequently collecting breast cancer family history information, but rarely using quantitative tools integrating additional risk factors. Primary care providers reported high levels of discomfort and low confidence with respect to risk-reducing medications although very few reported doubts about the evidence base underpinning their use. Insufficient education/training and perceived discomfort conducting both tasks were notable barriers. Primary care providers are more likely to accept an increased role in breast cancer risk assessment than advising on risk-reducing medications. To realise the benefits of risk-based screening and prevention at a population level, primary care will need to proactively assess breast cancer risk and advise on risk-reducing medications. To facilitate this, adaptations to infrastructure such as integrated tools are necessary in addition to provision of education. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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Other

Jump to: Research, Review

14 pages, 851 KiB

Open AccessSystematic Review

Oral Contraceptive Use and Breast Cancer Risk Assessment: A Systematic Review and Meta-Analysis of Case-Control Studies, 2009–2020

by Agnieszka Barańska, Agata Błaszczuk, Wiesław Kanadys, Maria Malm, Katarzyna Drop and Małgorzata Polz-Dacewicz

Cancers 2021, 13(22), 5654; https://doi.org/10.3390/cancers13225654 - 12 Nov 2021

Cited by 23 | Viewed by 8262

Abstract

To perform a meta-analysis of case-control studies that addressed the association between oral contraceptive pills (OC) use and breast cancer (BrCa), PubMED (MEDLINE), Embase, and the Cochrane Library were searched to identify case-control studies of OC and BrCa published between 2009 and 2020. [...] Read more.

To perform a meta-analysis of case-control studies that addressed the association between oral contraceptive pills (OC) use and breast cancer (BrCa), PubMED (MEDLINE), Embase, and the Cochrane Library were searched to identify case-control studies of OC and BrCa published between 2009 and 2020. We used the DerSimonian–Laird method to compute pooled odds ratios (ORs) and confidence intervals (CIs), and the Mantel–Haenszel test to assess the association between OC use and cancer. Forty-two studies were identified that met the inclusion criteria and we included a total of 110,580 women (30,778 into the BrCa group and 79,802 into the control group, of which 15,722 and 38,334 were using OC, respectively). The conducted meta-analysis showed that the use of OC was associated with a significantly increased risk of BrCa in general, OR = 1.15, 95% CI: 1.01 to 1.31, p = 0.0358. Regarding other risk factors for BrCa, we found that increased risk was associated significantly with early menarche, nulliparous, non-breastfeeding, older age at first parity, postmenopause, obesity, smoking, and family history of BrCa. Despite our conclusion that birth control pills increase the cancer risk being supported by extensive previous studies and meta-analyzes, further confirmation is required. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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Open AccessSystematic Review

Type 2 Diabetes Mellitus and Clinicopathological Tumor Characteristics in Women Diagnosed with Breast Cancer: A Systematic Review and Meta-Analysis

by Fan Zhang, Jing de Haan-Du, Grigory Sidorenkov, Gijs W. D. Landman, Mathilde Jalving, Qingying Zhang and Geertruida H. de Bock

Cancers 2021, 13(19), 4992; https://doi.org/10.3390/cancers13194992 - 5 Oct 2021

Cited by 11 | Viewed by 2664

Abstract

Poor prognosis caused by type 2 diabetes mellitus (T2DM) in women with breast cancer is conferred, while the association between T2DM and breast tumor aggressiveness is still a matter of debate. This study aimed to clarify the differences in breast cancer characteristics, including [...] Read more.

Poor prognosis caused by type 2 diabetes mellitus (T2DM) in women with breast cancer is conferred, while the association between T2DM and breast tumor aggressiveness is still a matter of debate. This study aimed to clarify the differences in breast cancer characteristics, including stage, size, lymph node status, grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (Her2), between patients with and without pre-existing T2DM. PubMed, Embase, and Web of Science were searched for studies from 1 January 2010 to 2 July 2021. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were pooled by using a random effects model. T2DM was significantly associated with tumor stages III/IV versus cancers in situ and stages I/II (pooled ORs (pOR), 95% CI: 1.19; 1.04–1.36, p = 0.012), tumor size >20 versus ≤20 mm (pOR, 95% CI: 1.18; 1.04–1.35, p = 0.013), and lymph node invasion versus no involvement (pOR, 95% CI: 1.26; 1.05–1.51, p = 0.013). These findings suggest that women with T2DM are at a higher risk of late-stage tumors, large tumor sizes, and invasive lymph nodes at breast cancer diagnosis. Full article

(This article belongs to the Special Issue Risk Assessment for Breast Cancer)

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