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6 pages, 215 KiB

Open AccessEditorial

Breast Cancer Risk and Prevention: A Step Forward

by Sofia Vidali and Tommaso Susini

Cancers 2023, 15(23), 5559; https://doi.org/10.3390/cancers15235559 - 23 Nov 2023

Viewed by 2551

Abstract

Breast cancer (BC) is a leading topic in medical research as it is the most common cancer occurring in women worldwide; its incidence is progressively increasing in all age groups [...] Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

Research

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14 pages, 1909 KiB

Open AccessArticle

A Breast Cancer Polygenic Risk Score Is Feasible for Risk Stratification in the Norwegian Population

by Bayram Cevdet Akdeniz, Morten Mattingsdal, Mev Dominguez-Valentin, Oleksandr Frei, Alexey Shadrin, Mikk Puustusmaa, Regina Saar, Siim Sõber, Pål Møller, Ole A. Andreassen, Peeter Padrik and Eivind Hovig

Cancers 2023, 15(16), 4124; https://doi.org/10.3390/cancers15164124 - 16 Aug 2023

Cited by 1 | Viewed by 2167

Abstract

Background: Statistical associations of numerous single nucleotide polymorphisms with breast cancer (BC) have been identified in genome-wide association studies (GWAS). Recent evidence suggests that a Polygenic Risk Score (PRS) can be a useful risk stratification instrument for a BC screening strategy, and a [...] Read more.

Background: Statistical associations of numerous single nucleotide polymorphisms with breast cancer (BC) have been identified in genome-wide association studies (GWAS). Recent evidence suggests that a Polygenic Risk Score (PRS) can be a useful risk stratification instrument for a BC screening strategy, and a PRS test has been developed for clinical use. The performance of the PRS is yet unknown in the Norwegian population. Aim: To evaluate the performance of PRS models for BC in a Norwegian dataset. Methods: We investigated a sample of 1053 BC cases and 7094 controls from different regions of Norway. PRS values were calculated using four PRS models, and their performance was evaluated by the area under the curve (AUC) and the odds ratio (OR). The effect of the PRS on the age of onset of BC was determined by a Cox regression model, and the lifetime absolute risk of developing BC was calculated using the iCare tool. Results: The best performing PRS model included 3820 SNPs, which yielded an AUC = 0.625 and an OR = 1.567 per one standard deviation increase. The PRS values of the samples correlate with an increased risk of BC, with a hazard ratio of 1.494 per one standard deviation increase (95% confidence interval of 1.406–1.588). The individuals in the highest decile of the PRS have at least twice the risk of developing BC compared to the individuals with a median PRS. The results in this study with Norwegian samples are coherent with the findings in the study conducted using Estonian and UK Biobank samples. Conclusion: The previously validated PRS models have a similar observed accuracy in the Norwegian data as in the UK and Estonian populations. A PRS provides a meaningful association with the age of onset of BC and lifetime risk. Therefore, as suggested in Estonia, a PRS may also be integrated into the screening strategy for BC in Norway. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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15 pages, 10094 KiB

Open AccessArticle

Breast Lesions of Uncertain Malignant Potential (B3) and the Risk of Breast Cancer Development: A Long-Term Follow-Up Study

by Chiara Bellini, Jacopo Nori Cucchiari, Federica Di Naro, Diego De Benedetto, Giulia Bicchierai, Andrea Franconeri, Irene Renda, Simonetta Bianchi and Tommaso Susini

Cancers 2023, 15(13), 3521; https://doi.org/10.3390/cancers15133521 - 6 Jul 2023

Cited by 4 | Viewed by 4587

Abstract

Breast lesions of uncertain malignant potential (B3) are frequently diagnosed in the era of breast cancer (BC) screening and their management is controversial. They are generally removed surgically, but some international organizations and guidelines for breast research suggest follow-up care alone or, more [...] Read more.

Breast lesions of uncertain malignant potential (B3) are frequently diagnosed in the era of breast cancer (BC) screening and their management is controversial. They are generally removed surgically, but some international organizations and guidelines for breast research suggest follow-up care alone or, more recently, propose vacuum-assisted excision (VAE). The risk of upgrade to BC is known, but very little data exist on its role as risk factor for future BC development. We analyzed 966 B3 lesions diagnosed at our institution, 731 of which had long-term follow-up available. Surgical removal was performed in 91%, VAE in 3.8%, and follow-up in 5.2% of cases. The B3 lesions included flat epithelial atypia (FEA), atypical ductal hyperplasia (ADH), lobular intraepithelial neoplasia (LIN), atypical papillary lesions (PLs), radial scars (RSs), and others. Overall, immediate upgrade to BC (invasive or in situ) was 22.7%. After long-term follow-up, 9.2% of the patients were diagnosed with BC in the same or contralateral breast. The highest risk was associated with ADH diagnosis, with 39.8% of patients upgraded and 13.6% with a future BC diagnosis (p < 0.0001). These data support the idea that B3 lesions should be removed and provide evidence to suggest annual screening mammography for women after a B3 diagnosis because their BC risk is considerably increased. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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11 pages, 907 KiB

Open AccessArticle

Polygenic Risk Score Predicts Modified Risk in BRCA1 Pathogenic Variant c.4035del and c.5266dup Carriers in Breast Cancer Patients

by Egija Berga-Švītiņa, Jeļena Maksimenko, Edvīns Miklaševičs, Krista Fischer, Baiba Vilne and Reedik Mägi

Cancers 2023, 15(11), 2957; https://doi.org/10.3390/cancers15112957 - 28 May 2023

Cited by 1 | Viewed by 1878

Abstract

The aim of this study was to assess the power of the polygenic risk score (PRS) in estimating the overall genetic risk of women carrying germline BRCA1 pathogenic variants (PVs) c.4035del or c.5266dup to develop breast (BC) or ovarian cancer (OC) due to [...] Read more.

The aim of this study was to assess the power of the polygenic risk score (PRS) in estimating the overall genetic risk of women carrying germline BRCA1 pathogenic variants (PVs) c.4035del or c.5266dup to develop breast (BC) or ovarian cancer (OC) due to additional genetic variations. In this study, PRSs previously developed from two joint models using summary statistics of age-at-onset (BayesW model) and case–control data (BayesRR-RC model) from a genome-wide association analysis (GWAS) were applied to 406 germline BRCA1 PV (c.4035del or c.5266dup) carriers affected by BC or OC, compared with unaffected individuals. A binomial logistic regression model was used to assess the association of PRS with BC or OC development risk. We observed that the best-fitting BayesW PRS model effectively predicted the individual’s BC risk (OR = 1.37; 95% CI = 1.03–1.81, p = 0.02905 with AUC = 0.759). However, none of the applied PRS models was a good predictor of OC risk. The best-fitted PRS model (BayesW) contributed to assessing the risk of developing BC for germline BRCA1 PV (c.4035del or c.5266dup) carriers and may facilitate more precise and timely patient stratification and decision-making to improve the current BC treatment or even prevention strategies. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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16 pages, 2458 KiB

Open AccessArticle

Genome-Wide Association Study of Breast Density among Women of African Ancestry

by Shefali Setia Verma, Lindsay Guare, Sarah Ehsan, Aimilia Gastounioti, Gabrielle Scales, Marylyn D. Ritchie, Despina Kontos, Anne Marie McCarthy and Penn Medicine Biobank

Cancers 2023, 15(10), 2776; https://doi.org/10.3390/cancers15102776 - 16 May 2023

Viewed by 2226

Abstract

Breast density, the amount of fibroglandular versus fatty tissue in the breast, is a strong breast cancer risk factor. Understanding genetic factors associated with breast density may help in clarifying mechanisms by which breast density increases cancer risk. To date, 50 genetic loci [...] Read more.

Breast density, the amount of fibroglandular versus fatty tissue in the breast, is a strong breast cancer risk factor. Understanding genetic factors associated with breast density may help in clarifying mechanisms by which breast density increases cancer risk. To date, 50 genetic loci have been associated with breast density, however, these studies were performed among predominantly European ancestry populations. We utilized a cohort of women aged 40–85 years who underwent screening mammography and had genetic information available from the Penn Medicine BioBank to conduct a Genome-Wide Association Study (GWAS) of breast density among 1323 women of African ancestry. For each mammogram, the publicly available “LIBRA” software was used to quantify dense area and area percent density. We identified 34 significant loci associated with dense area and area percent density, with the strongest signals in GACAT3, CTNNA3, HSD17B6, UGDH, TAAR8, ARHGAP10, BOD1L2, and NR3C2. There was significant overlap between previously identified breast cancer SNPs and SNPs identified as associated with breast density. Our results highlight the importance of breast density GWAS among diverse populations, including African ancestry populations. They may provide novel insights into genetic factors associated with breast density and help in elucidating mechanisms by which density increases breast cancer risk. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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16 pages, 1823 KiB

Open AccessArticle

Will Absolute Risk Estimation for Time to Next Screen Work for an Asian Mammography Screening Population?

by Peh Joo Ho, Elaine Hsuen Lim, Nur Khaliesah Binte Mohamed Ri, Mikael Hartman, Fuh Yong Wong and Jingmei Li

Cancers 2023, 15(9), 2559; https://doi.org/10.3390/cancers15092559 - 29 Apr 2023

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Abstract

Personalized breast cancer risk profiling has the potential to promote shared decision-making and improve compliance with routine screening. We assessed the Gail model’s performance in predicting the short-term (2- and 5-year) and the long-term (10- and 15-year) absolute risks in 28,234 asymptomatic Asian [...] Read more.

Personalized breast cancer risk profiling has the potential to promote shared decision-making and improve compliance with routine screening. We assessed the Gail model’s performance in predicting the short-term (2- and 5-year) and the long-term (10- and 15-year) absolute risks in 28,234 asymptomatic Asian women. Absolute risks were calculated using different relative risk estimates and Breast cancer incidence and mortality rates (White, Asian-American, or the Singapore Asian population). Using linear models, we tested the association of absolute risk and age at breast cancer occurrence. Model discrimination was moderate (AUC range: 0.580–0.628). Calibration was better for longer-term prediction horizons (E/O_{long-term ranges}: 0.86–1.71; E/O_{short-term ranges}:1.24–3.36). Subgroup analyses show that the model underestimates risk in women with breast cancer family history, positive recall status, and prior breast biopsy, and overestimates risk in underweight women. The Gail model absolute risk does not predict the age of breast cancer occurrence. Breast cancer risk prediction tools performed better with population-specific parameters. Two-year absolute risk estimation is attractive for breast cancer screening programs, but the models tested are not suitable for identifying Asian women at increased risk within this short interval. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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12 pages, 1967 KiB

Open AccessArticle

Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk Prediction

by Hui Li, Kayla Robinson, Li Lan, Natalie Baughan, Chun-Wai Chan, Matthew Embury, Gary J. Whitman, Randa El-Zein, Isabelle Bedrosian and Maryellen L. Giger

Cancers 2023, 15(7), 2141; https://doi.org/10.3390/cancers15072141 - 4 Apr 2023

Cited by 7 | Viewed by 2160

Abstract

The identification of women at risk for sporadic breast cancer remains a clinical challenge. We hypothesize that the temporal analysis of annual screening mammograms, using a long short-term memory (LSTM) network, could accurately identify women at risk of future breast cancer. Women with [...] Read more.

The identification of women at risk for sporadic breast cancer remains a clinical challenge. We hypothesize that the temporal analysis of annual screening mammograms, using a long short-term memory (LSTM) network, could accurately identify women at risk of future breast cancer. Women with an imaging abnormality, which had been biopsy-confirmed to be cancer or benign, who also had antecedent imaging available were included in this case–control study. Sequences of antecedent mammograms were retrospectively collected under HIPAA-approved guidelines. Radiomic and deep-learning-based features were extracted on regions of interest placed posterior to the nipple in antecedent images. These features were input to LSTM recurrent networks to classify whether the future lesion would be malignant or benign. Classification performance was assessed using all available antecedent time-points and using a single antecedent time-point in the task of lesion classification. Classifiers incorporating multiple time-points with LSTM, based either on deep-learning-extracted features or on radiomic features, tended to perform statistically better than chance, whereas those using only a single time-point failed to show improved performance compared to chance, as judged by area under the receiver operating characteristic curves (AUC: 0.63 ± 0.05, 0.65 ± 0.05, 0.52 ± 0.06 and 0.54 ± 0.06, respectively). Lastly, similar classification performance was observed when using features extracted from the affected versus the contralateral breast in predicting future unilateral malignancy (AUC: 0.63 ± 0.05 vs. 0.59 ± 0.06 for deep-learning-extracted features; 0.65 ± 0.05 vs. 0.62 ± 0.06 for radiomic features). The results of this study suggest that the incorporation of temporal information into radiomic analyses may improve the overall classification performance through LSTM, as demonstrated by the improved discrimination of future lesions as malignant or benign. Further, our data suggest that a potential field effect, changes in the breast extending beyond the lesion itself, is present in both the affected and contralateral breasts in antecedent imaging, and, thus, the evaluation of either breast might inform on the future risk of breast cancer. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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10 pages, 251 KiB

Open AccessArticle

Circadian Disruption and Breast Cancer Risk: Evidence from a Case-Control Study in China

by Song Song, Lin Lei, Rui Zhang, Han Liu, Jia Du, Ni Li, Wanqing Chen, Ji Peng and Jiansong Ren

Cancers 2023, 15(2), 419; https://doi.org/10.3390/cancers15020419 - 8 Jan 2023

Cited by 7 | Viewed by 3186

Abstract

Studies had suggested an association between circadian disruptors (including night shift work, domestic light exposure at night, sleep duration, and circadian gene polymorphism) and breast cancer, while rare studies had been conducted in the Chinese population. This study was a case-control study conducted [...] Read more.

Studies had suggested an association between circadian disruptors (including night shift work, domestic light exposure at night, sleep duration, and circadian gene polymorphism) and breast cancer, while rare studies had been conducted in the Chinese population. This study was a case-control study conducted to explore the impact of circadian disruptors on the risk of breast cancer in China. Four hundred and sixty-four cases and 464 controls, admitted from the Department of Breast Surgery, Cancer Hospital, Chinese Academy of Medical Sciences, were included in this study. Adjusting age, BMI group, smoking, alcohol consumption, menopausal status, family history of breast cancer, duration of breastfeeding, age at menarche, number of pregnancies, age at first full-term pregnancy, use of estrogen and use of oral contraceptive, multivariate logistic regression analysis showed that the risk of breast cancer was higher in short sleep duration group (OR = 4.86, 95%CI: 1.73–17.33). Meanwhile, rs2292912 in CRY2, rs2253820 in PER1, rs2289591 in PER1 and rs3027188 in PER1 were positively associated with the risk of breast cancer. This study supported that the short duration of sleep and four SNPs in crucial circadian genes played a role in the development of breast cancer. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

16 pages, 1375 KiB

Open AccessArticle

Genetically Modified Circulating Levels of Advanced Glycation End-Products and Their Soluble Receptor (AGEs-RAGE Axis) with Risk and Mortality of Breast Cancer

by Yu Peng, Fubin Liu, Yating Qiao, Peng Wang, Han Du, Changyu Si, Xixuan Wang, Kexin Chen and Fangfang Song

Cancers 2022, 14(24), 6124; https://doi.org/10.3390/cancers14246124 - 12 Dec 2022

Cited by 9 | Viewed by 1745

Abstract

The interaction of advanced glycation end-products (AGEs) with their receptor (RAGE) elicits oxidative stress and inflammation, which is involved in the development of breast cancer. However, large-scale population-based evidence exploring genetically modified circulating levels of AGEs-RAGE axis with risk and mortality of breast [...] Read more.

The interaction of advanced glycation end-products (AGEs) with their receptor (RAGE) elicits oxidative stress and inflammation, which is involved in the development of breast cancer. However, large-scale population-based evidence exploring genetically modified circulating levels of AGEs-RAGE axis with risk and mortality of breast cancer is scarce. We recruited 1051 pairs of age-matched breast cancers and controls and measured plasma AGEs and sRAGE concentrations by enzyme-linked immunosorbent assay (ELISA). Multivariate logistic regression and Cox proportional hazard model were used to calculate the effects of plasma levels and genetic variants of the AGEs-RAGE axis and their combined effects on breast cancer risk and prognosis, respectively. Furthermore, linear regression was performed to assess the modifications in plasma AGEs/sRAGE levels by genetic predisposition. Higher levels of AGEs and AGEs/sRAGE-ratio were associated with an increased risk of breast cancer, but sRAGE levels were negatively associated with breast cancer risk, especially in women <60 years. We also observed a positive association between AGEs and the bad prognosis of breast cancer. Although we did not observe a significant contribution of genetic variants to breast cancer risk, rs2070600 and rs1800624 in the AGER gene were dose-dependently correlated with sRAGE levels. Further, compared to the haplotype CT at the lowest quartile of AGEs, haplotypes TT and TA were prominently associated with breast cancer risk in the highest quartile of AGEs. This study depicted a significant association between circulating levels of AGEs-RAGE axis and breast cancer risk and mortality and revealed the potential of plasma AGEs, especially coupled with AGER polymorphism as biomarkers of breast cancer. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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11 pages, 2119 KiB

Open AccessArticle

The Effect of Melatonin Intake on Survival of Patients with Breast Cancer—A Population-Based Registry Study

by Leda Pistiolis, Djino Khaki, Anikó Kovács and Roger Olofsson Bagge

Cancers 2022, 14(23), 5884; https://doi.org/10.3390/cancers14235884 - 29 Nov 2022

Cited by 2 | Viewed by 1766

Abstract

Previous research has demonstrated the antitumoral effects of melatonin on breast cancer in both in vitro and in vivo studies. The aim of the present study was to investigate whether melatonin has a favorable effect on the survival of patients diagnosed with early [...] Read more.

Previous research has demonstrated the antitumoral effects of melatonin on breast cancer in both in vitro and in vivo studies. The aim of the present study was to investigate whether melatonin has a favorable effect on the survival of patients diagnosed with early breast cancer. This retrospective registry-based study included all patients diagnosed with breast cancer in Sweden between 2005 and 2015. Data were linked to the Swedish Prescribed Drug Registry and the Swedish Cause of Death Registry. A multivariate Cox regression model, including patient age, tumor size, tumor grade, ER status, HER2 status, nodal status and defined daily doses (DDDs) of melatonin, was used to analyze breast-cancer-specific survival as well as overall survival. Of the 37,075 included patients, 926 (2.5%) were prescribed melatonin, with a median DDD of 30. Melatonin was found to have a protective effect on breast-cancer-specific survival (BCSS) in the univariate analysis (HR: 0.736, 95% CI: 0.548–0.989, p = 0.042), but when adjusting for known prognostic factors in the multivariate analysis, this beneficial effect disappeared (HR: 1.037, 95% CI: 0.648–1.659, p = 0.879). Melatonin was not proven to have a favorable effect on the survival of patients diagnosed with early breast cancer in this retrospective registry study. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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21 pages, 1726 KiB

Open AccessArticle

Promote Community Engagement in Participatory Research for Improving Breast Cancer Prevention: The P.I.N.K. Study Framework

by Michela Franchini, Stefania Pieroni, Francesca Denoth, Marco Scalese Urciuoli, Emanuela Colasante, Massimiliano Salvatori, Giada Anastasi, Cinzia Katia Frontignano, Elena Dogliotti, Sofia Vidali, Edgardo Montrucchio, Sabrina Molinaro, Tommaso Susini and Jacopo Nori Cucchiari

Cancers 2022, 14(23), 5801; https://doi.org/10.3390/cancers14235801 - 25 Nov 2022

Cited by 2 | Viewed by 2332

Abstract

Breast cancer (BC) has overtaken lung cancer as the most common cancer in the world and the projected incidence rates show a further increase. Early detection through population screening remains the cornerstone of BC control, but a progressive change from early diagnosis only-based [...] Read more.

Breast cancer (BC) has overtaken lung cancer as the most common cancer in the world and the projected incidence rates show a further increase. Early detection through population screening remains the cornerstone of BC control, but a progressive change from early diagnosis only-based to a personalized preventive and risk-reducing approach is widely debated. Risk-stratification models, which also include personal lifestyle risk factors, are under evaluation, although the documentation burden to gather population-based data is relevant and traditional data collection methods show some limitations. This paper provides the preliminary results from the analysis of clinical data provided by radiologists and lifestyle data collected using self-administered questionnaires from 5601 post-menopausal women. The weight of the combinations of women’s personal features and lifestyle habits on the BC risk were estimated by combining a model-driven and a data-driven approach to analysis. The weight of each factor on cancer occurrence was assessed using a logistic model. Additionally, communities of women sharing common features were identified and combined in risk profiles using social network analysis techniques. Our results suggest that preventive programs focused on increasing physical activity should be widely promoted, in particular among the oldest women. Additionally, current findings suggest that pregnancy, breast-feeding, salt limitation, and oral contraception use could have different effects on cancer risk, based on the overall woman’s risk profile. To overcome the limitations of our data, this work also introduces a mobile health tool, the Dress-PINK, designed to collect real patients’ data in an innovative way for improving women’s response rate, data accuracy, and completeness as well as the timeliness of data availability. Finally, the tool provides tailored prevention messages to promote critical consciousness, critical thinking, and increased health literacy among the general population. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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16 pages, 4180 KiB

Open AccessArticle

Deep Learning Models for Automated Assessment of Breast Density Using Multiple Mammographic Image Types

by Bastien Rigaud, Olena O. Weaver, Jennifer B. Dennison, Muhammad Awais, Brian M. Anderson, Ting-Yu D. Chiang, Wei T. Yang, Jessica W. T. Leung, Samir M. Hanash and Kristy K. Brock

Cancers 2022, 14(20), 5003; https://doi.org/10.3390/cancers14205003 - 13 Oct 2022

Cited by 6 | Viewed by 2380

Abstract

Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in [...] Read more.

Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investigate pre-trained EfficientNetB0 deep learning (DL) models for automated assessment of breast density using multiple mammographic types with and without clinical information to improve reliability and versatility of reporting. 120,000 for-processing and for-presentation full-field digital mammograms (FFDM), digital breast tomosynthesis (DBT), and synthesized 2D images from 5032 women were retrospectively analyzed. Each participant underwent up to 3 screening examinations and completed a questionnaire at each screening encounter. Pre-trained EfficientNetB0 DL models with or without clinical history were optimized. The DL models were evaluated using BI-RADS (fatty, scattered fibroglandular densities, heterogeneously dense, or extremely dense) versus binary (non-dense or dense) density classification. Pre-trained EfficientNetB0 model performances were compared using inter-observer and commercial software (Volpara) variabilities. Results show that the average Fleiss’ Kappa score between-observers ranged from 0.31–0.50 and 0.55–0.69 for the BI-RADS and binary classifications, respectively, showing higher uncertainty among experts. Volpara-observer agreement was 0.33 and 0.54 for BI-RADS and binary classifications, respectively, showing fair to moderate agreement. However, our proposed pre-trained EfficientNetB0 DL models-observer agreement was 0.61–0.66 and 0.70–0.75 for BI-RADS and binary classifications, respectively, showing moderate to substantial agreement. Overall results show that the best breast density estimation was achieved using for-presentation FFDM and DBT images without added clinical information. Pre-trained EfficientNetB0 model can automatically assess breast density from any images modality type, with the best results obtained from for-presentation FFDM and DBT, which are the most common image archived in clinical practice. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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11 pages, 268 KiB

Open AccessArticle

Effectiveness of Organized Mammography Screening for Different Breast Cancer Molecular Subtypes

by Lilu Ding, Marcel J. W. Greuter, Inge Truyen, Mathijs Goossens, Bert Van der Vegt, Harlinde De Schutter, Guido Van Hal and Geertruida H. de Bock

Cancers 2022, 14(19), 4831; https://doi.org/10.3390/cancers14194831 - 3 Oct 2022

Cited by 2 | Viewed by 1772

Abstract

Background: Screening program effectiveness is generally evaluated for breast cancer (BC) as one disease and without considering the regularity of participation, while this might have an impact on detection rate. Objectives: To evaluate the short-term effectiveness of a mammography screening program for the [...] Read more.

Background: Screening program effectiveness is generally evaluated for breast cancer (BC) as one disease and without considering the regularity of participation, while this might have an impact on detection rate. Objectives: To evaluate the short-term effectiveness of a mammography screening program for the major molecular subtypes of invasive BC. Methods: All women who participated in the screening program and were diagnosed with screen-detected or interval BC in Flanders were included in the study (2008–2018). Molecular subtypes considered were luminal and luminal-HER2-positive, human epidermal growth factor receptor 2-positive, and triple-negative BC (TNBC). The relationship between the BC stage at diagnosis (early (I–II) versus advanced (III–IV)) and the method of detection (screen-detected or interval) and the relationship between the method of detection and participation regularity (regular versus irregular) were evaluated by multi-variable logistic regression models. All models were performed for each molecular subtype and adjusted for age. Results: Among the 12,318 included women, BC of luminal and luminal-HER2-positive subtypes accounted for 70.9% and 11.3%, respectively. Screen-detected BC was more likely to be diagnosed at early stages than interval BC with varied effect sizes for luminal, luminal-HER2-positive, and TNBC with OR:2.82 (95% CI: 2.45–3.25), OR:2.39 (95% CI: 1.77–3.24), and OR:2.29 (95% CI: 1.34–4.05), respectively. Regular participation was related to a higher likelihood of screening detection than irregular participation for luminal, luminal-HER2-positive, and TNBC with OR:1.21 (95% CI: 1.09–1.34), OR: 1.79 (95% CI: 1.38–2.33), and OR: 1.62 (95% CI: 1.10–2.41), respectively. Conclusions: Regular screening as compared to irregular screening is effective for all breast cancers except for the HER2 subtype. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

18 pages, 1591 KiB

Open AccessArticle

Patterns of Care for Breast Radiotherapy in Italy: Breast IRRadiATA (Italian Repository of Radiotherapy dATA) Feasibility Study

by Antonella Ciabattoni, Fabiana Gregucci, Giuseppe D’Ermo, Alessandro Dolfi, Francesca Cucciarelli, Isabella Palumbo, Simona Borghesi, Alessandro Gava, Giovanna Maria Cesaro, Antonella Baldissera, Daniela Giammarino, Antonino Daidone, Francesca Maurizi, Marcello Mignogna, Lidia Mazzuoli, Vincenzo Ravo, Sara Falivene, Sara Pedretti, Edy Ippolito, Rosaria Barbarino, Daniela di Cristino, Alba Fiorentino, Cynthia Aristei, Sara Ramella, Rolando Maria D’Angelillo, Icro Meattini, Cinzia Iotti, Vittorio Donato and Silvia Chiara Formenti Show full author list Hide full author list

Cancers 2022, 14(16), 3927; https://doi.org/10.3390/cancers14163927 - 15 Aug 2022

Cited by 2 | Viewed by 2506

Abstract

Aim. Breast IRRADIATA (Italian Repository of RADIotherapy dATA) is a collaborative nationwide project supported by the Italian Society of Radiotherapy and Clinical Oncology (AIRO) and the Italian League Against Cancer (LILT). It focuses on breast cancer (BC) patients treated with radiotherapy (RT) and [...] Read more.

Aim. Breast IRRADIATA (Italian Repository of RADIotherapy dATA) is a collaborative nationwide project supported by the Italian Society of Radiotherapy and Clinical Oncology (AIRO) and the Italian League Against Cancer (LILT). It focuses on breast cancer (BC) patients treated with radiotherapy (RT) and was developed to create a national registry and define the patterns of care in Italy. A dedicated tool for data collection was created and pilot tested. The results of this feasibility study are reported here. Methods. To validate the applicability of a user-friendly data collection tool, a feasibility study involving 17 Italian Radiation Oncology Centers was conducted from July to October 2021, generating a data repository of 335 BC patients treated between January and March 2020, with a minimum follow-up time of 6 months. A snapshot of the clinical presentation, treatment modalities and radiotherapy toxicity in these patients was obtained. A Data Entry Survey and a Satisfaction Questionnaire were also sent to all participants. Results. All institutions completed the pilot study. Regarding the Data Entry survey, all questions achieved 100% of responses and no participant reported spending more than 10 min time for either the first data entry or for the updating of follow-up. Results from the Satisfaction Questionnaire revealed that the project was described as excellent by 14 centers (82.3%) and good by 3 (17.7%). Conclusion. Current knowledge for the treatment of high-prevalence diseases, such as BC, has evolved toward patient-centered medicine, evidence-based care and real-world evidence (RWE), which means evidence obtained from real-world data (RWD). To this aim, Breast IRRADIATA was developed as a simple tool to probe the current pattern of RT care in Italy. The pilot feasibility of IRRADIATA encourages a larger application of this tool nationwide and opens the way to the assessment of the pattern of care radiotherapy directed to other cancers. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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12 pages, 2032 KiB

Open AccessArticle

Impact of Breast Cancer Awareness Month on Public Interest in the United States between 2012 and 2021: A Google Trends Analysis

by Yoshito Nishimura and Jared D. Acoba

Cancers 2022, 14(10), 2534; https://doi.org/10.3390/cancers14102534 - 21 May 2022

Cited by 17 | Viewed by 2908

Abstract

Breast Cancer Awareness Month (BCAM) has a long history of over 30 years, established in 1985 to occur every October, and the National Breast Cancer Foundation now leads the operation. There have been no studies to evaluate the impact of the BCAM on [...] Read more.

Breast Cancer Awareness Month (BCAM) has a long history of over 30 years, established in 1985 to occur every October, and the National Breast Cancer Foundation now leads the operation. There have been no studies to evaluate the impact of the BCAM on public awareness of breast cancer. We analyzed the impact of BCAM on public awareness of breast cancer in the U.S. from 2012 to 2021 using the relative search volume (RSV) of Google Trends as a surrogate. We also analyzed the impact of Lung Cancer Awareness Month (LCAM) and Prostate Cancer Awareness Month (PCAM) on public awareness of lung and prostate cancer, respectively, to see differences in their effectiveness among the health observances for the top three most common cancers in the U.S. We performed a joinpoint regression analysis to identify statistically significant time points of a change in trend. There were joinpoints around BCAM for “Breast cancer” every year from 2012 to 2021, with a significant increase in the weekly RSVs from 21.9% to 46.7%. Except for 2013 and 2015 for “Lung cancer”, when significant increases in the RSV at 1.8% and 1.2% per week were observed around LCAM, no joinpoints were noted around LCAM or PCAM. These results imply that BCAM has successfully improved the public awareness of breast cancer in the U.S. compared to other representative health observances, likely due to the effective involvement of non-medical industries, influencers affected by breast cancer, and an awareness symbol. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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13 pages, 965 KiB

Open AccessArticle

ICOnnecta’t: Development and Initial Results of a Stepped Psychosocial eHealth Ecosystem to Facilitate Risk Assessment and Prevention of Early Emotional Distress in Breast Cancer Survivors’ Journey

by Joan C. Medina, Aida Flix-Valle, Ana Rodríguez-Ortega, Rosa Hernández-Ribas, María Lleras de Frutos and Cristian Ochoa-Arnedo

Cancers 2022, 14(4), 974; https://doi.org/10.3390/cancers14040974 - 15 Feb 2022

Cited by 9 | Viewed by 3106

Abstract

Psychosocial interventions prevent emotional distress and facilitate adaptation in breast cancer (BC). However, conventional care presents accessibility barriers that eHealth has the potential to overcome. ICOnnecta’t is a stepped digital ecosystem designed to build wellbeing and reduce psychosocial risks during the cancer journey [...] Read more.

Psychosocial interventions prevent emotional distress and facilitate adaptation in breast cancer (BC). However, conventional care presents accessibility barriers that eHealth has the potential to overcome. ICOnnecta’t is a stepped digital ecosystem designed to build wellbeing and reduce psychosocial risks during the cancer journey through a European-funded project. Women recently diagnosed with BC in a comprehensive cancer center were offered the ecosystem. ICOnnecta’t consists of four care levels, provided according to users’ distress: screening and monitoring, psychoeducation campus, peer-support community, and online-group psychotherapy. Descriptive analyses were conducted to assess the platform’s implementation, while multilevel linear models were used to study users’ psychosocial course after diagnosis. ICOnnecta’t showed acceptance, use and attrition rates of 57.62, 74.60, and 29.66%, respectively. Up to 76.19% of users reported being satisfied with the platform and 75.95% informed that it was easy to use. A total of 443 patients’ needs were detected and responsively managed, leading 94.33% of users to remain in the preventive steps. In general, strong social support led to a better psychosocial course. ICOnnecta’t has been successfully implemented. The results showed that it supported the development of a digital relation with healthcare services and opened new early support pathways. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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Review

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21 pages, 6983 KiB

Open AccessReview

Breast Cancer in Asia: Incidence, Mortality, Early Detection, Mammography Programs, and Risk-Based Screening Initiatives

by Yu Xian Lim, Zi Lin Lim, Peh Joo Ho and Jingmei Li

Cancers 2022, 14(17), 4218; https://doi.org/10.3390/cancers14174218 - 30 Aug 2022

Cited by 36 | Viewed by 10774

Abstract

Close to half (45.4%) of the 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined at the level of broad geographic regions, literature on more in-depth coverage of the individual countries and [...] Read more.

Close to half (45.4%) of the 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined at the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This narrative review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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Other

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19 pages, 2663 KiB

Open AccessSystematic Review

Oral Contraceptive Use and Breast Cancer Risk According to Molecular Subtypes Status: A Systematic Review and Meta-Analysis of Case-Control Studies

by Agnieszka Barańska, Joanna Dolar-Szczasny, Wiesław Kanadys, Wiktoria Kinik, Dorota Ceglarska, Urszula Religioni and Robert Rejdak

Cancers 2022, 14(3), 574; https://doi.org/10.3390/cancers14030574 - 23 Jan 2022

Cited by 12 | Viewed by 4889

Abstract

We conducted a systematic review and meta-analysis to investigate the effect of oral contraceptives (OCs) on risk of breast cancer (BrCa) by status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). We searched the MEDLINE (PubMed), [...] Read more.

We conducted a systematic review and meta-analysis to investigate the effect of oral contraceptives (OCs) on risk of breast cancer (BrCa) by status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). We searched the MEDLINE (PubMed), Embase and the Cochrane Library database and bibliographies of pertinent articles published up to 2020. Therein, we identified nineteen eligible case-control studies which provided data by breast cancer subtypes: ER-positive (ER+), ER-negative (ER−), HER2-positive (HER2+) and Triplet-negative (TN). Summary risk estimates (pooled OR [pOR]) and 95% confidence intervals (CIs) were calculated using fixed/random effects models. The summary meta-analysis showed that over-use of OCs led to significant increased risk of TNBrCa (OR = 1.37, 95% CI; 1.13 to 1.67, p = 0.002), as well as of ER−BrCa (OR = 1.20, 95% CI: 1.03 to 1.40, p = 0.019). There was also a significant reduction in the risk of ER+BrCa (OR = O.92, 95% CI: 0.86 to 0.99, p = 0.026,) and a slight reduction in the risk of HER2+BrCa (OR = 0.95, 95% CI; 0.79 to 1.14, p = 0.561) after taking OCs. Meta-analysis indicated that OC use has different impacts on risk of breast cancer subtypes defined by receptor status. The identified differences between individual subtypes of breast cancer may reflect different mechanisms of carcinogenesis. Full article

(This article belongs to the Special Issue Breast Cancer Risk and Prevention)

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