The benefits and harms of breast cancer screening: an independent review

A shortcut weighted fusion pyramid network for microcalcification detection in breast mammograms

BACKGROUND: High-precision detection for individual and clustered microcalcifications in mammograms is important for the early diagnosis of breast cancer. Large-scale differences between the two types and low-contrast images are major difficulties faced by radiologists when performing diagnoses. OBJECTIVE: Deep learning-based methods can provide end-to-end solutions for efficient detection. However, multicenter data bias, the low resolution of network inputs, and scale differences between microcalcifications lead to low detection rates. Aiming to overcome the aforementioned limitations, we propose a pyramid feature network for microcalcification detection in mammograms, MicroDMa, with adaptive image adjustment and shortcut connections. METHODS: First, mammograms from multiple centers are represented as histograms and cropped by adaptive image adjustment, which mitigates the impact of dataset bias. Second, the proposed shortcut connection pyramid network ensures that the feature map contains more information for multiscale objects, while a shortcut path that jumps over layers enhances the efficiency of feature propagation from bottom to top. Third, the weights of each feature map at different scales in the fusion are trainable; thus, the network can automatically learn the contributions of all feature maps in the fusion stage. RESULT: Experiments were conducted on our in-house dataset and the public dataset INbreast. When the average number of positives per image is one on the in-house dataset, the recall rates of MicroDMa are the 96.8% for individual microcalcification and 98.9% for clustered microcalcification, which are higher than 69.1% and 91.2% achieved by recent deep learning model. Free-response receiver operating characteristic curve of MicroDMa is also higher than other methods when models are performed on INbreast. CONCLUSION: MicroDMa network is better than other methods and it can effectively help radiologists detect and identify two types of microcalcifications in clinical applications.

Considerations for Evaluating the Introduction of New Cancer Screening Technology: Use of Interval Cancers to Assess Potential Benefits and Harms

This framework focuses on the importance of the consideration of the downstream intermediate and long-term health outcomes when a change to a screening program is introduced. The authors present a methodology for utilising the relationship between screen-detected and interval cancer rates to infer the benefits and harms associated with a change to the program. A review of the previous use of these measures in the literature is presented. The framework presents other aspects to consider when utilizing this methodology, and builds upon an existing framework that helps researchers, clinicians, and policy makers to consider the impacts of changes to screening programs on health outcomes. It is hoped that this research will inform future evaluative studies to assess the benefits and harms of changes to screening programs.

Women's preference to apply shared decision-making in breast cancer screening: a discrete choice experiment

OBJECTIVE

To analyse women's stated preferences for establishing the relative importance of each attribute of shared decision-making (SDM) and their willingness to pay (WTP) for more participatory care in breast cancer screening programmes (BCSP).

DESIGN

A discrete choice experiment was designed with 12 questions (choice tasks). It included three attributes: 'How the information is obtained', regarding benefits and harms; whether there is a 'Dialogue for scheduled mammography' between the healthcare professional and the woman; and, 'Who makes the decision', regarding participation in BCSP. Data were obtained using a survey that included 12 choice tasks, 1 question on WTP and 7 socioeconomic-related questions. The analysis was performed using conditional mixed-effect logit regression and stratification according to WTP.

SETTING

Data collection related to BCSP was conducted between June and November 2021 in Catalonia, Spain.

PARTICIPANTS

Sixty-five women aged between 50 and 60.

MAIN OUTCOME MEASURES

Women's perceived utility of each attribute, trade-off on these attributes and WTP for SDM in BCSP.

RESULT

The only significant attribute was 'Who makes the decision'. The decision made alone (coefficient=2.879; 95% CI=2.297 to 3.461) and the decision made together with a healthcare professional (2.375; 95% CI=1.573 to 3.177) were the options preferred by women. The former contributes 21% more utility than the latter. Moreover, 52.3% of the women stated a WTP of €10 or more for SDM. Women's preferences regarding attributes did not influence their WTP.

CONCLUSIONS

The participant women refused a current paternalistic model and preferred either SDM or informed decision-making in BCSP.

Depiction of breast cancers on digital mammograms by artificial intelligence-based computer-assisted diagnosis according to cancer characteristics

OBJECTIVE

To evaluate how breast cancers are depicted by artificial intelligence-based computer-assisted diagnosis (AI-CAD) according to clinical, radiological, and pathological factors.

MATERIALS AND METHODS

From January 2017 to December 2017, 896 patients diagnosed with 930 breast cancers were enrolled in this retrospective study. Commercial AI-CAD was applied to digital mammograms and abnormality scores were obtained. We evaluated the abnormality score according to clinical, radiological, and pathological characteristics. False-negative results were defined by abnormality scores less than 10.

RESULTS

The median abnormality score of 930 breasts was 87.4 (range 0-99). The false-negative rate of AI-CAD was 19.4% (180/930). Cancers with an abnormality score of more than 90 showed a high proportion of palpable lesions, BI-RADS 4c and 5 lesions, cancers presenting as mass with or without microcalcifications and invasive cancers compared with low-scored cancers (all p < 0.001). False-negative cancers were more likely to develop in asymptomatic patients and extremely dense breasts and to be diagnosed as occult breast cancers and DCIS compared to detected cancers.

CONCLUSION

Breast cancers depicted with high abnormality scores by AI-CAD are associated with higher BI-RADS category, invasive pathology, and higher cancer stage.

KEY POINTS

• High-scored cancers by AI-CAD included a high proportion of BI-RADS 4c and 5 lesions, masses with or without microcalcifications, and cancers with invasive pathology. • Among invasive cancers, cancers with higher T and N stage and HER2-enriched subtype were depicted with higher abnormality scores by AI-CAD. • Cancers missed by AI-CAD tended to be in asymptomatic patients and extremely dense breasts and to be diagnosed as occult breast cancers by radiologists.

Differences in Cancer Screening Responses to State Medicaid Expansions by Race and Ethnicity, 2011‒2019

Objectives. To estimate whether state Medicaid expansions' relationships to breast, cervical, and colorectal cancer screening differ by race/ethnicity. Methods. Analyses conducted in 2021 used 2011-2016 and 2018-2019 Behavioral Risk Factor Surveillance System data on adults aged 40 to 64 years with household incomes below 400% of the federal poverty guideline (FPG; n = 537 250). Triple-difference analyses compared cancer screening in Medicaid expansion versus nonexpansion states, before versus after expansion, among people with incomes above versus below the eligibility cutoff (138% FPG). Race/ethnicity and ethnicity-by-language interaction terms tested for effect modification. Results. Associations between Medicaid expansions and cancer screening were significant for past-2-year mammograms and past-5-year colorectal screening. Effect modification analyses showed elevated mammography among non-Hispanic Asian women (+9.0 percentage points; 95% confidence interval [CI] = 3.2, 14.8) and Hispanic women (+6.0 percentage points; 95% CI = 2.0, 10.1), and Papanicolaou tests among Hispanic women (+4.2 percentage points; 95% CI = 0.1, 8.2). Findings were not limited to English- or Spanish-speaking respondents and were robust to insurance status controls. Conclusions. Medicaid expansions yielded statistically significant increases in income-eligible Asian and Hispanic women's mammography and Hispanic women's Pap testing relative to non-Hispanic White women. Neither language proficiency nor insurance status explained these findings. (Am J Public Health. 2022;112(11):1630-1639. https://doi.org/10.2105/AJPH.2022.307027).

Effectiveness of Mammography Screening on Breast Cancer Mortality – A Study Protocol for Emulation of Target Trials Using German Health Claims Data

Background

The efficacy of mammography screening in reducing breast cancer mortality has been demonstrated in randomized trials. However, treatment options - and hence prognosis – for advanced tumor stages as well as mammography techniques have considerably improved since completion of these trials. Consequently, the effectiveness of mammography screening under current conditions is unclear and controversial. The German mammography screening program (MSP), an organized population-based screening program, was gradually introduced between 2005 and 2008 and achieved nation-wide coverage in 2009.

Objective

We describe in detail a study protocol for investigating the effectiveness of the German MSP in reducing breast cancer mortality in women aged 50 to 69 years based on health claims data. Specifically, the proposed study aims at estimating per-protocol effects of several screening strategies on cumulative breast cancer mortality. The first analysis will be conducted once 10-year follow-up data are available.

Methods and Analysis

We will use claims data from five statutory health insurance providers in Germany, covering approximately 37.6 million individuals. To estimate the effectiveness of the MSP, hypothetical target trials will be emulated across time, an approach that has been demonstrated to minimize design-related biases. Specifically, the primary contrast will be in terms of the cumulative breast cancer mortality comparing the screening strategies of “never screen” versus “regular screening as intended by the MSP”.

Ethics and Dissemination

In Germany, the utilization of data from health insurances for scientific research is regulated by the Code of Social Law. All involved health insurance providers as well as the responsible authorities approved the use of the health claims data for this study. The Ethics Committee of the University of Bremen determined that studies based on claims data are exempt from institutional review. The findings of the proposed study will be published in peer-reviewed journals.

Healthcare professionals' views following implementation of risk stratification into a national breast cancer screening programme

Background

It is crucial to determine feasibility of risk-stratified screening to facilitate successful implementation. We introduced risk-stratification (BC-Predict) into the NHS Breast Screening Programme (NHSBSP) at three screening sites in north-west England from 2019 to 2021. The present study investigated the views of healthcare professionals (HCPs) on acceptability, barriers, and facilitators of the BC-Predict intervention and on the wider implementation of risk-based screening after BC-Predict was implemented in their screening site.

Methods

Fourteen semi-structured interviews were conducted with HCPs working across the breast screening pathway at three NHSBSP sites that implemented BC-Predict. Thematic analysis interpreted the data.

Results

Three pre-decided themes were produced. (1) Acceptability of risk-based screening: risk-stratification was perceived as a beneficial step for both services and women. HCPs across the pathway reported low burden of running the BC-Predict trial on routine tasks, but with some residual concerns; (2) Barriers to implementation: comprised capacity constraints of services including the inadequacy of current IT systems to manage women with different risk profiles and, (3) Facilitators to implementation: included the continuation of stakeholder consultation across the pathway to inform implementation and need for dedicated risk screening admin staff, a push for mammography staff recruitment and guidance for screening services. Telephone helplines, integrating primary care, and supporting access for all language needs was emphasised.

Conclusion

Risk-stratified breast screening was viewed as a progressive step providing it does not worsen inequalities for women. Implementation of risk-stratified breast screening requires staff to be reassured that there will be systems in place to support implementation and that it will not further burden their workload. Next steps require a comprehensive assessment of the resource needed for risk-stratification versus current resource availability, upgrades to screening IT and building screening infrastructure. The role of primary care needs to be determined. Simplification and clarification of risk-based screening pathways is needed to support HCPs agency and facilitate implementation. Forthcoming evidence from ongoing randomised controlled trials assessing effectiveness of breast cancer risk-stratification will also determine implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10134-0.

Effectiveness of Organized Mammography Screening for Different Breast Cancer Molecular Subtypes

Simple Summary

We evaluated the short-term effectiveness of a mammography screening program in all women who participated in the screening program and were diagnosed with screen-detected or interval breast cancer (BC) in Flanders (2008–2018). The evaluation was performed for the major molecular subtypes of invasive BC separately and considering the regularity of participation. We found that screen-detected BC was more likely to be diagnosed at early stages than interval BC of luminal, luminal-HER2-positive, and triple-negative BC (TNBC) type, but not for the human epidermal growth factor receptor 2-positive (HER2 positive) subtype. In addition, regular participation was related to a higher likelihood of screening detection than irregular participation for luminal, luminal-HER2-positive, and TNBC, but not for the HER2 positive subtype, either. Our results indicate that regular screening as compared to irregular screening is effective for all breast cancers except for the HER2 subtype.

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 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.

Implementing Risk-Stratified Breast Screening in England: An Agenda Setting Meeting

It is now possible to accurately assess breast cancer risk at routine NHS Breast Screening Programme (NHSBSP) appointments, provide risk feedback and offer risk management strategies to women at higher risk. These strategies include National Institute for Health and Care Excellence (NICE) approved additional breast screening and risk-reducing medication. However, the NHSBSP invites nearly all women three-yearly, regardless of risk. In March 2022, a one-day agenda setting meeting took place in Manchester to discuss the feasibility and desirability of implementation of risk-stratified screening in the NHSBSP. Fifty-eight individuals participated (38 face-to-face, 20 virtual) with relevant expertise from academic, clinical and/or policy-making perspectives. Key findings were presented from the PROCAS2 NIHR programme grant regarding feasibility of risk-stratified screening in the NHSBSP. Participants discussed key uncertainties in seven groups, followed by a plenary session. Discussions were audio-recorded and thematically analysed to produce descriptive themes. Five themes were developed: (i) risk and health economic modelling; (ii) health inequalities and communication with women; (iii); extending screening intervals for low-risk women; (iv) integration with existing NHSBSP; and (v) potential new service models. Most attendees expected some form of risk-stratified breast screening to be implemented in England and collectively identified key issues to be resolved to facilitate this.

Rational Approach to Finding Genes Encoding Molecular Biomarkers: Focus on Breast Cancer

Early detection of cancer facilitates treatment and improves patient survival. We hypothesized that molecular biomarkers of cancer could be rationally predicted based on even partial knowledge of transcriptional regulation, functional pathways and gene co-expression networks. To test our data mining approach, we focused on breast cancer, as one of the best-studied models of this disease. We were particularly interested to check whether such a ‘guilt by association’ approach would lead to pan-cancer markers generally known in the field or whether molecular subtype-specific ‘seed’ markers will yield subtype-specific extended sets of breast cancer markers. The key challenge of this investigation was to utilize a small number of well-characterized, largely intracellular, breast cancer-related proteins to uncover similarly regulated and functionally related genes and proteins with the view to predicting a much-expanded range of disease markers, especially that of extracellular molecular markers, potentially suitable for the early non-invasive detection of the disease. We selected 23 previously characterized proteins specific to three major molecular subtypes of breast cancer and analyzed their established transcription factor networks, their known metabolic and functional pathways and the existing experimentally derived protein co-expression data. Having started with largely intracellular and transmembrane marker ‘seeds’ we predicted the existence of as many as 150 novel biomarker genes to be associated with the selected three major molecular sub-types of breast cancer all coding for extracellularly targeted or secreted proteins and therefore being potentially most suitable for molecular diagnosis of the disease. Of the 150 such predicted protein markers, 114 were predicted to be linked through the combination of regulatory networks to basal breast cancer, 48 to luminal and 7 to Her2-positive breast cancer. The reported approach to mining molecular markers is not limited to breast cancer and therefore offers a widely applicable strategy of biomarker mining.

Breast cancer patient characterisation and visualisation using deep learning and fisher information networks

Breast cancer is the most commonly diagnosed female malignancy globally, with better survival rates if diagnosed early. Mammography is the gold standard in screening programmes for breast cancer, but despite technological advances, high error rates are still reported. Machine learning techniques, and in particular deep learning (DL), have been successfully used for breast cancer detection and classification. However, the added complexity that makes DL models so successful reduces their ability to explain which features are relevant to the model, or whether the model is biased. The main aim of this study is to propose a novel visualisation to help characterise breast cancer patients using Fisher Information Networks on features extracted from mammograms using a DL model. In the proposed visualisation, patients are mapped out according to their similarities and can be used to study new patients as a ‘patient-like-me’ approach. When applied to the CBIS-DDSM dataset, it was shown that it is a competitive methodology that can (i) facilitate the analysis and decision-making process in breast cancer diagnosis with the assistance of the FIN visualisations and ‘patient-like-me’ analysis, and (ii) help improve diagnostic accuracy and reduce overdiagnosis by identifying the most likely diagnosis based on clinical similarities with neighbouring patients.

Mammalian Resilience Revealed by a Comparison of Human Diseases and Mouse Models Associated With DNA Helicase Deficiencies

Maintaining genomic integrity is critical for sustaining individual animals and passing on the genome to subsequent generations. Several enzymes, such as DNA helicases and DNA polymerases, are involved in maintaining genomic integrity by unwinding and synthesizing the genome, respectively. Indeed, several human diseases that arise caused by deficiencies in these enzymes have long been known. In this review, the author presents the DNA helicases associated with human diseases discovered to date using recent analyses, including exome sequences. Since several mouse models that reflect these human diseases have been developed and reported, this study also summarizes the current knowledge regarding the outcomes of DNA helicase deficiencies in humans and mice and discusses possible mechanisms by which DNA helicases maintain genomic integrity in mammals. It also highlights specific diseases that demonstrate mammalian resilience, in which, despite the presence of genomic instability, patients and mouse models have lifespans comparable to those of the general population if they do not develop cancers; finally, this study discusses future directions for therapeutic applications in humans that can be explored using these mouse models.

An Integrated Machine Learning Scheme for Predicting Mammographic Anomalies in High-Risk Individuals Using Questionnaire-Based Predictors

This study aimed to investigate the important predictors related to predicting positive mammographic findings based on questionnaire-based demographic and obstetric/gynecological parameters using the proposed integrated machine learning (ML) scheme. The scheme combines the benefits of two well-known ML algorithms, namely, least absolute shrinkage and selection operator (Lasso) logistic regression and extreme gradient boosting (XGB), to provide adequate prediction for mammographic anomalies in high-risk individuals and the identification of significant risk factors. We collected questionnaire data on 18 breast-cancer-related risk factors from women who participated in a national mammographic screening program between January 2017 and December 2020 at a single tertiary referral hospital to correlate with their mammographic findings. The acquired data were retrospectively analyzed using the proposed integrated ML scheme. Based on the data from 21,107 valid questionnaires, the results showed that the Lasso logistic regression models with variable combinations generated by XGB could provide more effective prediction results. The top five significant predictors for positive mammography results were younger age, breast self-examination, older age at first childbirth, nulliparity, and history of mammography within 2 years, suggesting a need for timely mammographic screening for women with these risk factors.

Associated morbidity in screened and diagnosed breast cancer patients: a retrospective study

INTRODUCTION

Breast cancer (BC) screening has been associated with reduced mortality and morbidity. This study compares tumor characteristics and treatment morbidity in screened versus diagnosed women.

MATERIALS AND METHODS

This retrospective study, conducted between 2010 and 2013, included 666 BC screened or diagnosed patients. We compared patients and tumors characteristics and received treatments. We also analyzed the results after excluding patients at risk of BC and conducted a multivariate analysis to assess odds ratios (OR).

RESULTS

Screened women had smaller tumors (16,5 vs 22,6 mm, p < 0.001), of lower grade (p < 0.001) with a lower proliferation index (PI) (p < 0.001) than diagnosed women. Screened women were more frequently treated using conservative surgery (82.8% vs 59.7%, p < 0.001), needed less often axillary dissection (15.1% vs 35.4%, p < 0.001) and less often chemotherapy (20.8% vs 48.3% p < 0.001) than diagnosed women. In the multivariate analysis after adjustment for age and BC history, diagnosed women had increased (OR: 4.79, 95% IC: 3.19-7,18) risk to be administered chemotherapy and to undergo axillary dissection (OR: 4.18, 95% IC: 1.56-11.17) than screened women.

CONCLUSION

Patients should be informed about the benefits in terms of morbidity that screening confers to them.

Clinical utility of breast pathology data: implications for practising pathologists

In breast cancer, the quality of the pathology services is of paramount importance as inevitably, the pathologist makes the confirmatory diagnosis and provides prognostic and predictive information, informing treatment plans directly. Various national and international organisations provide a pathology reporting minimum dataset (MDS) to ensure consistency in reporting. While the use of MDS promotes clarity, there may be specific areas requiring the pathologist's input for individual patients and hence pathologists need to be aware of the clinical utility of pathology data to help tailor individualised patient treatment. In this article, we provide numerous examples of the role of pathology data in determining next steps in the patient pathway that are applicable to both the diagnostic and treatment pathways, including neoadjuvant treatment pathways. We also briefly discuss the important role and thereby the clinical utility of pathology data during the COVID-19 pandemic providing a template for the similar scenarios in the future if required.

Deep learning based on ultrasound images assists breast lesion diagnosis in China: a multicenter diagnostic study

BACKGROUND

Studies on deep learning (DL)-based models in breast ultrasound (US) remain at the early stage due to a lack of large datasets for training and independent test sets for verification. We aimed to develop a DL model for differentiating benign from malignant breast lesions on US using a large multicenter dataset and explore the model's ability to assist the radiologists.

METHODS

A total of 14,043 US images from 5012 women were prospectively collected from 32 hospitals. To develop the DL model, the patients from 30 hospitals were randomly divided into a training cohort (n = 4149) and an internal test cohort (n = 466). The remaining 2 hospitals (n = 397) were used as the external test cohorts (ETC). We compared the model with the prospective Breast Imaging Reporting and Data System assessment and five radiologists. We also explored the model's ability to assist the radiologists using two different methods.

RESULTS

The model demonstrated excellent diagnostic performance with the ETC, with a high area under the receiver operating characteristic curve (AUC, 0.913), sensitivity (88.84%), specificity (83.77%), and accuracy (86.40%). In the comparison set, the AUC was similar to that of the expert (p = 0.5629) and one experienced radiologist (p = 0.2112) and significantly higher than that of three inexperienced radiologists (p < 0.01). After model assistance, the accuracies and specificities of the radiologists were substantially improved without loss in sensitivities.

CONCLUSIONS

The DL model yielded satisfactory predictions in distinguishing benign from malignant breast lesions. The model showed the potential value in improving the diagnosis of breast lesions by radiologists.

Tendência Temporal da Cobertura de Mamografias no Sistema Único de Saúde, Brasil, 2010-2019

Introdução: O câncer de mama no Brasil apresenta elevadas taxas de incidência e mortalidade apesar da tendência de redução da mortalidade em algumas Regiões. Objetivo: Descrever a tendência da cobertura de mamografias de rastreamento nas Macrorregiões e Estados brasileiros e identificar a influência de Políticas Nacionais voltadas ao controle do câncer de mama entre 2010-2019. Método: Foi calculada a razão entre mamografias de rastreamento na faixa etária de 50-69 anos por local de residência e subtraída a população das residentes com plano de saúde na faixa etária e no período referidos. A tendência foi avaliada pelo modelo de regressão Joinpoint. Resultados: A cobertura aumentou no Brasil de 2010-2014 e apresentou queda de 2014-2019, com aumento na proporção de exames realizados na população-alvo. Esse padrão foi observado nas demais Regiões, exceto na Centro-Oeste, porém com ano de mudança da tendência diferente. Foram identificados dois pontos de mudança no país: de 2010-2014, com tendência crescente (APC 8,7, IC 95% 6,2; 11,3), e de 2014-2019, com tendência decrescente (APC -4,2, IC 95% -5,7; -2,7), ambos significantes. A Região Nordeste foi a única com três pontos de mudança de tendência: 2010-2012 (APC 30,3, IC 95% 22,9; 38,2), 2012-2017 (APC 4,7, IC 95% 3,0; 6,4) e 2017-2019 (APC -14,9, IC 95% -19,7; - 9,8). Não foi identificada tendência para a Região Centro-Oeste. Conclusão: Houve crescimento na proporção de mamografias de rastreamento realizadas na população-alvo no período, para Brasil e Regiões, e tendência de redução na cobertura da mamografia a partir de 2014. Esses resultados indicam priorização da população-alvo do programa nas ações de rastreamento.

Microinvasive breast cancer and the role of sentinel lymph node biopsy

Whether sentinel lymph node biopsy (SLNB) should be performed in patients with microinvasive breast cancer (MIBC) has been a matter of debate over the last decade. MIBC has a favorable prognosis and while metastasis to the axilla is rare, it can impact treatment recommendations. In this study we evaluated clinical and histological features in both MIBC and background DCIS including ER, PR, and HER-2, number of foci of MIBC, the extent of the DCIS, nuclear grade, presence of comedo necrosis, as well as surgical procedures, adjuvant treatment and follow up to identify variables which predict disease free survival (DFS), as well as the factors which influence clinical decision making. Our study included 72 MIBC patients with a mean patient follow-up time of 55 months. Three patients with MIBC had recurrence, and two deceased, leaving five patients in total with poor long-term outcomes and a DFS rate of 93.1%. Performing mastectomy, high nuclear grade, and negativity for ER and HER-2 were found to be associated with the use of SLNB, although none of these variables were found to be associated with DFS. One positive lymph node case was discovered following SLNB in our study. This suggests the use of SLNB may provide diagnostic information to some patients, although these are the anomalies. When comparing patients who had undergone SLNB to those which had not there was no difference in DFS. Certainly, the use of SLNB in MIBC is quite the conundrum. It is important to acknowledge that surgical complications have been reported, and traditional metrics used for risk assessment in invasive breast cancer may not hold true in the setting of microinvasion.

Surveillance mammography in older breast cancer survivors: Current practice patterns and patient perceptions

INTRODUCTION

Although the benefits of surveillance mammography for older breast cancer survivors have not been quantified prospectively, it is unlikely that mammography provides substantial benefit (and possible that mammography is harmful) to women with limited life expectancy and a low risk for in-breast cancer events.

MATERIALS AND METHODS

We identified 1268 women aged 77 and older with a history of Stage I-III breast cancer, who did not undergo bilateral mastectomy, were diagnosed with cancer at least three years prior to study entry, and who had consented to be surveyed as part of the Mayo Clinic Breast Disease Registry. We mailed them a one-time survey asking about their experiences with surveillance mammography. Women with metastatic disease were excluded. The primary endpoint was whether or not women reported at least one mammogram since breast cancer surgery.

RESULTS

Eight hundred forty-six of 1268 (67%) returned the survey, 734 of whom were eligible for analysis. The median age at the time of survey was 82, and the median time since cancer diagnosis was 12 years. Ninety-three percent reported having had at least one mammogram since their initial breast cancer surgery. Seventy-nine percent reported that they had surveillance mammography annually over the prior three years, including 76% of the 491 aged 80+ and 64% of the 189 aged 85 + .

DISCUSSION

Most older breast cancer survivors who have residual breast tissue are undergoing annual mammograms. Additional educational materials may be beneficial for patients and clinicians to better individualize plans for surveillance mammography in older breast cancer survivors.

Is mammography screening an effective public health intervention? Evidence from a natural experiment

Population-based breast screening programmes aim to improve clinical outcomes, alleviate health inequalities, and reduce healthcare costs. However, while screening can bring about immediate changes in mode of presentation and stage at diagnosis of breast cancer cases, the benefits and harms of these programmes can only be observed at a population level, and only over a long enough timeframe for the cascade of events triggered by screening to culminate in disease-specific mortality reductions. In this paper we exploit a natural experiment resulting from the phased geographic rollout of a national mammography screening programme to examine the impact of screening on breast cancer outcomes from both a patient cohort and a population perspective. Using data on 33,722 breast cancer cases over the period 1994-2011, we employ a difference-in-differences research design using ten-year follow-up data for cases diagnosed before and after the introduction of the programme in screened and unscreened regions. We conclude that although the programme produced the intended intermediate effects on breast cancer presentation and incidence, these failed to translate into significant decreases in overall population-level mortality, though screening may have helped to reduce socioeconomic disparities in late stage breast cancer incidence.

Is loss of p53 a driver of ductal carcinoma in situ progression?

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive carcinoma. Multiple studies have shown that DCIS lesions typically possess a driver mutation associated with cancer development. Mutation in the TP53 tumour suppressor gene is present in 15-30% of pure DCIS lesions and in ~30% of invasive breast cancers. Mutations in TP53 are significantly associated with high-grade DCIS, the most likely form of DCIS to progress to invasive carcinoma. In this review, we summarise published evidence on the prevalence of mutant TP53 in DCIS (including all DCIS subtypes), discuss the availability of mouse models for the study of DCIS and highlight the need for functional studies of the role of TP53 in the development of DCIS and progression from DCIS to invasive disease.

Change in effectiveness of mammography screening with decreasing breast cancer mortality: a population-based study

BACKGROUND

Reductions in breast cancer mortality observed over the last three decades are partly due to improved patient management, which may erode the benefit-harm balance of mammography screening.

METHODS

We estimated the numbers of women needed to invite (NNI) to prevent one breast cancer death within 10 years. Four scenarios of screening effectiveness (5-20% mortality reduction) were applied on 10,580 breast cancer deaths among Norwegian women aged 50-75 years from 1986 to 2016. We used three scenarios of overdiagnosis (10-40% excess breast cancers during screening period) for estimating ratios of numbers of overdiagnosed breast cancers for each breast cancer death prevented.

RESULTS

Under the base case scenario of 20% breast cancer mortality reduction and 20% overdiagnosis, the NNI rose from 731 (95% CI: 644-830) women in 1996 to 1364 (95% CI: 1181-1577) women in 2016, while the number of women with overdiagnosed cancer for each breast cancer death prevented rose from 3.2 in 1996 to 5.4 in 2016. For a mortality reduction of 8.7%, the ratio of overdiagnosed breast cancers per breast cancer death prevented rose from 7.4 in 1996 to 14.0 in 2016. For a mortality reduction of 5%, the ratio rose from 12.8 in 1996 to 25.2 in 2016.

CONCLUSIONS

Due to increasingly potent therapeutic modalities, the benefit in terms of reduced breast cancer mortality declines while the harms, including overdiagnosis, are unaffected. Future improvements in breast cancer patient management will further deteriorate the benefit-harm ratio of screening.

Effects of awareness of breast cancer overdiagnosis among women with screen-detected or incidentally found breast cancer: a qualitative interview study

OBJECTIVES

To explore experiences of women who identified themselves as having a possible breast cancer overdiagnosis.

DESIGN

Qualitative interview study using key components of a grounded theory analysis.

SETTING

International interviews with women diagnosed with breast cancer and aware of the concept of overdiagnosis.

PARTICIPANTS

Twelve women aged 48-77 years from the UK (6), USA (4), Canada (1) and Australia (1) who had breast cancer (ductal carcinoma in situ n=9, (invasive) breast cancer n=3) diagnosed between 2004 and 2019, and who were aware of the possibility of overdiagnosis. Participants were recruited via online blogs and professional clinical networks.

RESULTS

Most women (10/12) became aware of overdiagnosis after their own diagnosis. All were concerned about the possibility of overdiagnosis or overtreatment or both. Finding out about overdiagnosis/overtreatment had negative psychosocial impacts on women's sense of self, quality of interactions with medical professionals, and for some, had triggered deep remorse about past decisions and actions. Many were uncomfortable with being treated as a cancer patient when they did not feel 'diseased'. For most, the recommended treatments seemed excessive compared with the diagnosis given. Most found that their initial clinical teams were not forthcoming about the possibility of overdiagnosis and overtreatment, and many found it difficult to deal with their set management protocols.

CONCLUSION

The experiences of this small and unusual group of women provide rare insight into the profound negative impact of finding out about overdiagnosis after breast cancer diagnosis. Previous studies have found that women valued information about overdiagnosis before screening and this knowledge did not reduce subsequent screening uptake. Policymakers and clinicians should recognise the diversity of women's perspectives and ensure that women are adequately informed of the possibility of overdiagnosis before screening.

YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms

BACKGROUND AND OBJECTIVE

Both mass detection and segmentation in digital mammograms play a crucial role in early breast cancer detection and treatment. Furthermore, clinical experience has shown that they are the upstream tasks of pathological classification of breast lesions. Recent advancements in deep learning have made the analyses faster and more accurate. This study aims to develop a deep learning model architecture for breast cancer mass detection and segmentation using the mammography.

METHODS

In this work we proposed a double shot model for mass detection and segmentation simultaneously using a combination of YOLO (You Only Look Once) and LOGO (Local-Global) architectures. Firstly, we adopted YoloV5L6, the state-of-the-art object detection model, to position and crop the breast mass in mammograms with a high resolution; Secondly, to balance training efficiency and segmentation performance, we modified the LOGO training strategy to train the whole images and cropped images on the global and local transformer branches separately. The two branches were then merged to form the final segmentation decision.

RESULTS

The proposed YOLO-LOGO model was tested on two independent mammography datasets (CBIS-DDSM and INBreast). The proposed model performs significantly better than previous works. It achieves true positive rate 95.7% and mean average precision 65.0% for mass detection on CBIS-DDSM dataset. Its performance for mass segmentation on CBIS-DDSM dataset is F1-score=74.5% and IoU=64.0%. The similar performance trend is observed in another independent dataset INBreast as well.

CONCLUSIONS

The proposed model has a higher efficiency and better performance, reduces computational requirements, and improves the versatility and accuracy of computer-aided breast cancer diagnosis. Hence it has the potential to enable more assistance for doctors in early breast cancer detection and treatment, thereby reducing mortality.

Associations of Obesity, Physical Activity, and Screening With State-Level Trends and Racial and Ethnic Disparities of Breast Cancer Incidence and Mortality in the US

IMPORTANCE

Breast cancer causes disproportionate disease burden among various racial and ethnic groups in the US. However, state-level temporal trends and racial and ethnic disparities and whether metabolic and lifestyle factors and screening access are associated with temporal changes remain largely unknown.

OBJECTIVES

To investigate temporal trends and racial and ethnic variations at the state level and ecological correlations between obesity, physical activity, and mammography screening and breast cancer incidence and mortality trends among women in the US.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional study was conducted to analyze breast cancer incidence and mortality trends among women in the US from January 1, 1999, to December 31, 2017, whereas an ecological analysis was performed to assess the associations. Data were analyzed from March 1, 2021, to September 30, 2021. Population-based cancer registry data were obtained from US Cancer Statistics incidence and mortality data. Prevalence of obesity, physical activity, and mammography screening were obtained from the Behavioral Risk Factor Surveillance System.

EXPOSURES

Prevalence of obesity, physical activity, and mammography screening.

MAIN OUTCOMES AND MEASURES

Breast cancer incidence and mortality trends from 1999 to 2017 in the 50 US states and the District of Columbia.

RESULTS

A total of 4 136 123 breast cancer cases and 782 454 deaths were included in the analysis, with a significant reduction in incidence (average annual percent change [AAPC], -0.4% [95% CI, -0.6% to -0.2%)]) and mortality (AAPC, -1.7% [95% CI, -1.8% to -1.5%]) during the study period. A significant state-level variation in breast cancer incidence and mortality between White women and those of other races and ethnicities was observed. A significant positive correlation was found between obesity and breast cancer incidence (r = 0.316; P = .02) and mortality (r = 0.400; P = .004) and an inverse correlation was found between physical activity and incidence (r = -0.577; P < .001) in women 55 years or older and mammography screening and mortality trends (r = -0.644; P < .001) in women 40 years or older.

CONCLUSIONS AND RELEVANCE

The findings of this cross-sectional study suggest that racial and ethnic disparities exist at the state level with regard to breast cancer incidence and mortality among women in the US. Metabolic and lifestyle factors and screening access were associated with the observed trends and racial and ethnic disparities. Interventions targeting these factors may help reduce the incidence of breast cancer and related deaths.

Overdetection of Breast Cancer

Overdetection (often referred to as overdiagnosis) of cancer is the detection of disease, such as through a screening program, that would otherwise remain occult through an individual’s life. In the context of screening, this could occur for cancers that were slow growing or indolent, or simply because an unscreened individual would have died from some other cause before the cancer had surfaced clinically. The main harm associated with overdetection is the subsequent overdiagnosis and overtreatment of disease. In this article, the phenomenon is reviewed, the methods of estimation of overdetection are discussed and reasons for variability in such estimates are given, with emphasis on an analysis using Canadian data. Microsimulation modeling is used to illustrate the expected time course of cancer detection that gives rise to overdetection. While overdetection exists, the actual amount is likely to be much lower than the estimate used by the Canadian Task Force on Preventive Health Care. Furthermore, the issue is of greater significance in older rather than younger women due to competing causes of death. The particular challenge associated with in situ breast cancer is considered and possible approaches to avoiding overtreatment are suggested.

Development, validation, and implementation of a Short Breast Health Perception Questionnaire

BACKGROUND

Health status and perception can be assessed by general or disease-specific questionnaires, and disease specific questionnaires are more specific than general questionnaires. Considering the importance of breast health perception (BHP) in women's lives and the lack of any pertinent questionnaires, we performed this study to develop a valid and reliable short BHP questionnaire (BHPQ); and then used it to assess the participants' BHP.

METHODS

We first designed and developed the instrument and then measured its inter-rater agreement (IRA), content validity including content validity index (I-CVI) and scale content validity index (S-CVI), and reliability (through internal consistency and test-retest). We then evaluated the BHP of eligible women with normal breasts and benign breast disorders who attended our breast clinic.

RESULTS

The IRA index (78.6%) showed the optimal relevance and clarity of the questionnaire. The content validity was acceptable; with S-CVIs of 87.35 and 84.42 for clarity and relevance, respectively. The internal reliability was high (Cronbach's alpha = 0.93). Three questions were eliminated for internal consistency (intraclass correlation coefficient < 0.7) but the rest of the questions showed good and excellent reliability. In the next step, BHP in the 350 eligible participants showed an overall score of 43.89 ± 9.09.

CONCLUSION

This study introduces a valid and reliable 11-item BHPQ. We propose its use in various circumstances throughout breast cancer screening, diagnosis, and treatment; and in the assessment of BHP in various physiologic and reproductive situations.

Designing optimal allocations for cancer screening using queuing network models

Cancer is one of the leading causes of death, but mortality can be reduced by detecting tumors earlier so that treatment is initiated at a less aggressive stage. The tradeoff between costs associated with screening and its benefit makes the decision of whom to screen and when a challenge. To enable comparisons across screening strategies for any cancer type, we demonstrate a mathematical modeling platform based on the theory of queuing networks designed for quantifying the benefits of screening strategies. Our methodology can be used to design optimal screening protocols and to estimate their benefits for specific patient populations. Our method is amenable to exact analysis, thus circumventing the need for simulations, and is capable of exactly quantifying outcomes given variability in the age of diagnosis, rate of progression, and screening sensitivity and intervention outcomes. We demonstrate the power of this methodology by applying it to data from the Surveillance, Epidemiology and End Results (SEER) program. Our approach estimates the benefits that various novel screening programs would confer to different patient populations, thus enabling us to formulate an optimal screening allocation and quantify its potential effects for any cancer type and intervention.

We describe a mathematical modeling methodology that offers quantitative insights into the potential benefits of screening and other interventions on cancer mortality. Our queuing-theoretic approach represents a potentially useful alternative to more traditional modeling approaches, in that it can provide more detailed results and entirely circumvents the need for simulations. Our methodology can be widely applied to estimate costs and benefits of screening strategies. By providing a detailed example of our method applied to epidemiological data, we hope to encourage greater uptake of this methodology in the community.

"It's something I'll do until I die": A qualitative examination into why older women in the U.S. continue screening mammography

BACKGROUND

Professional guidelines in the U.S. do not recommend routine screening mammography for women ≥75 years with limited life expectancy and/or poor health. Yet, routine mammography remains widely used in older women. We examined older women's experiences, beliefs, and opinions about screening mammography in relation to aging and health.

METHODS

We performed thematic analysis of transcribed semi-structured interviews with 19 women who had a recent screening visit at a mammography clinic in New York City (average age: 75 years, 63% Hispanic, 53% ≤high school education).

RESULTS

Three main themes emerged: (1) older women typically perceive mammograms as a positive, beneficial, and routine component of care; (2) participation in routine mammography is reinforced by factors at interpersonal, provider, and healthcare system levels; and (3) older women do not endorse discontinuation of screening mammography due to advancing age or poor health, but some may be receptive to reducing screening frequency. Only a few older women reported having discussed mammography cessation or the potential harms of screening with their providers. A few women reported they would insist on receiving mammography even without a provider recommendation.

CONCLUSIONS

Older women's positive experiences and views, as well as multilevel and frequently automated cues toward mammography are important drivers of routine screening in older women. These findings suggest a need for synergistic patient, provider, and system level strategies to reduce mammography overuse in older women.

Volatile Organic Compounds Analysis as a Potential Novel Screening Tool for Breast Cancer: A Systematic Review

Introduction

An early diagnosis is crucial in reducing mortality among people who have breast cancer (BC). There is a shortfall of characteristic early clinical symptoms in BC patients, highlighting the importance of investigating new methods for its early detection. A promising novel approach is the analysis of volatile organic compounds (VOCs) produced and emitted through the metabolism of cancer cells.

Methods

The purpose of this systematic review is to outline the published research regarding BC-associated VOCs. For this, headspace analysis of VOCs was explored in patient-derived body fluids, animal model-derived fluids, and BC cell lines to identify BC-specific VOCs. A systematic search in PubMed and Web of Science databases was conducted according to the PRISMA guidelines.

Results

Thirty-two studies met the criteria for inclusion in this review. Results highlight that VOC analysis can be promising as a potential novel screening tool. However, results of in vivo, in vitro and case-control studies have delivered inconsistent results leading to a lack of inter-matrix consensus between different VOC sampling methods.

Discussion

Discrepant VOC results among BC studies have been obtained, highly due to methodological discrepancies. Therefore, methodological issues leading to disparities have been reviewed and recommendations have been made on the standardisation of VOC collection and analysis methods for BC screening, thereby improving future VOC clinical validation studies.

Factors Associated with Screening Mammogram Uptake among Women Attending an Urban University Primary Care Clinic in Malaysia

Screening mammograms have resulted in a reduction in breast cancer mortality, yet the uptake in Malaysia was low. This study aimed to determine the prevalence and factors associated with screening mammogram uptake among women attending a Malaysian primary care clinic. A cross-sectional study was conducted among 200 women aged 40 to 74 attending the clinic. The data was collected using questionnaires assessing sociodemographic, clinical characteristics, knowledge and health beliefs. Multiple logistic regression was used to identify factors associated with mammogram uptake. The prevalence of screening mammograms was 46.0%. About 45.5% of women with high breast cancer risk had never undergone a mammogram. Older participants, aged 50 to 74 (OR = 2.57, 95% CI: 1.05, 6.29, p-value = 0.039) and those who received a physician’s recommendation (OR = 7.61, 95% CI: 3.81, 15.20, p-value < 0.001) were more likely to undergo screening mammography. Significant health beliefs associated with mammogram uptake were perceived barriers (OR = 0.81, 95% CI: 0.67, 0.97, p-value = 0.019) and cues to action (OR = 1.30, 95% CI: 1.06, 1.59, p-value = 0.012). Approximately half of the participants and those in the high-risk group had never undergone a mammogram. Older age, physician recommendation, perceived barriers and cues to action were significantly associated with mammogram uptake. Physicians need to play an active role in promoting breast cancer screening and addressing the barriers.

Marrying Story with Science: The Impact of Outdated and Inconsistent Breast Cancer Screening Practices in Canada

Behind the science of breast cancer in Canada, as well as globally, are the stories of thousands of women, their families, and their communities. These include stories from those who have died or those suffering from the realities of stage III and stage IV breast cancer due to late detection, misinformation, and dismissal. The reality for these women is that, whilst grateful for the latest developments in cancer research, much of this knowledge is not reflected in policy and practice. Canadian guidelines do not reflect the recommended screening by experts within the field and inequities in screening practices and practitioner knowledge exist in different areas within Canada. Told through the stories of women with lived experiences of late-stage breast cancer and supported by scientific evidence, this paper explores the impact of outdated breast cancer screening practices on the lives of women. Recent patient advocacy is driving changes, such as notifying women of their breast density in a few jurisdictions in Canada, but we call for the whole medical community to take responsibility and ensure breast screening is optimised to save more lives.

The feasibility of implementing risk stratification into a national breast cancer screening programme: a focus group study investigating the perspectives of healthcare personnel responsible for delivery

BACKGROUND

Providing women with personalized estimates of their risk of developing breast cancer, as part of routine breast cancer screening programmes, allows women at higher risk to be offered more frequent screening or drugs to reduce risk. For this to be feasible, the concept and practicalities have to be acceptable to the healthcare professionals who would put it in to practice. The present research investigated the acceptability to healthcare professionals who were responsible for the implementation of this new approach to screening in the ongoing BC-Predict study.

METHODS

Four focus groups were conducted with 29 healthcare professionals from a variety of professional backgrounds working within three breast screening services in north-west England. An inductive-manifest thematic analysis was conducted.

RESULTS

Overall, healthcare professionals viewed the implementation of personalised breast cancer risk estimation as a positive step, but discussion focused on concerns. Three major themes are presented. (1) Service constraints highlights the limited capacity within current breast services and concerns about the impact of additional workload. (2) Risk communication concerns the optimal way to convey risk to women within resource constraints. (3) Accentuating inequity discusses how risk stratification could decrease screening uptake for underserved groups.

CONCLUSIONS

Staff who implemented risk stratification considered it a positive addition to routine screening. They considered it essential to consider improving capacity and demands on healthcare professional time. They highlighted the need for skilled communication of risks and new pathways of care to ensure that stratification could be implemented in financially and time constrained settings without impacting negatively on women.

Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial

BACKGROUND

Two dimensional (2D) full-field digital mammography is the current standard of breast cancer screening. Digital breast tomosynthesis generates pseudo-three dimensional datasets of the breast from which synthesised 2D (s2D) mammograms can be reconstructed. This innovative approach reduces the likelihood of overlapping breast tissues that can conceal features of malignancy. We aimed to compare digital breast tomosynthesis plus s2D mammography with digital screening mammography for the detection of invasive breast cancer.

METHODS

TOSYMA was a randomised, open-label, superiority trial done at 17 screening units in two federal states of Germany. Eligible participants were women aged 50-69 years who had been invited to participate in a population-wide, quality-controlled mammography screening programme. Women were randomly assigned (1:1) to digital breast tomosynthesis plus s2D mammography or digital mammography alone using block randomisation (block size of 32), stratified by site. The primary endpoints were the detection rate of invasive breast cancer and invasive interval cancer rate at 24 months, analysed in the modified full analysis set, which included all randomly assigned participants who underwent either type of screening examination. Ten examinations, corresponding to a second study participation, were excluded. Analyses were done according to the intention-to-treat principle. Interval cancer rates will be reported in the follow-up study. Safety was assessed in the as-treated population, which included all participants who were randomly assigned. This trial is registered with ClinicalTrials.gov, NCT03377036, and is closed to accrual.

FINDINGS

Between July 5, 2018, and Dec 30, 2020, 99 689 women were randomly assigned to digital breast tomosynthesis plus s2D mammography (n=49 804) or digital mammography (n=49 830). Invasive breast cancers were detected in 354 of 49 715 women with evaluable primary endpoint data in the digital breast tomosynthesis plus s2D group (detection rate 7·1 cases per 1000 women screened) and in 240 of 49 762 women in the digital mammography group (4·8 cases per 1000 women screened; odds ratio 1·48 [95% CI 1·25-1·75]; p<0·0001). Adverse events and device deficiencies were rare (six adverse events in each group; 23 device deficiencies in the digital breast tomosynthesis plus s2D group vs five device deficiencies in the digital mammography group) and no serious adverse events were reported.

INTERPRETATION

The results from this study indicate that the detection rate for invasive breast cancer was significantly higher with digital breast tomosynthesis plus s2D mammography than digital mammography alone. Evaluation of interval cancer rates in the follow-up study will further help to investigate incremental long-term benefits of digital breast tomosynthesis screening.

FUNDING

Deutsche Forschungsgemeinschaft (German Research Foundation).

Crossover based technique for data augmentation

BACKGROUND AND OBJECTIVE

Medical image classification problems are frequently constrained by the availability of datasets. "Data augmentation" has come as a data enhancement and data enrichment solution to the challenge of limited data. Traditionally data augmentation techniques are based on linear and label preserving transformations; however, recent works have demonstrated that even non-linear, non-label preserving techniques can be unexpectedly effective. This paper proposes a non-linear data augmentation technique for the medical domain and explores its results.

METHODS

This paper introduces "Crossover technique", a new data augmentation technique for Convolutional Neural Networks in Medical Image Classification problems. Our technique synthesizes a pair of samples by applying two-point crossover on the already available training dataset. By this technique, we create N new samples from N training samples. The proposed crossover based data augmentation technique, although non-label preserving, has performed significantly better in terms of increased accuracy and reduced loss for all the tested datasets over varied architectures.

RESULTS

The proposed method was tested on three publicly available medical datasets with various network architectures. For the mini-MIAS database of mammograms, our method improved the accuracy by 1.47%, achieving 80.15% using VGG-16 architecture. Our method works fine for both gray-scale as well as RGB images, as on the PH2 database for Skin Cancer, it improved the accuracy by 3.57%, achieving 85.71% using VGG-19 architecture. In addition, our technique improved accuracy on the brain tumor dataset by 0.40%, achieving 97.97% using VGG-16 architecture.

CONCLUSION

The proposed novel crossover technique for training the Convolutional Neural Network (CNN) is painless to implement by applying two-point crossover on two images to form new images. The method would go a long way in tackling the challenges of limited datasets and problems of class imbalances in medical image analysis. Our code is available at https://github.com/rishiraj-cs/Crossover-augmentation.

Development and evaluation of a method for tumor growth simulation in virtual clinical trials of breast cancer screening

Purpose: Image-based analysis of breast tumor growth rate may optimize breast cancer screening and diagnosis by suggesting optimal screening intervals and guide the clinical discussion regarding personalized screening based on tumor aggressiveness. Simulation-based virtual clinical trials (VCTs) can be used to evaluate and optimize medical imaging systems and design clinical trials. This study aimed to simulate tumor growth over multiple screening rounds. Approach: This study evaluates a preliminary method for simulating tumor growth. Clinical data on tumor volume doubling time (TVDT) was used to fit a probability distribution ("clinical fit") of TVDTs. Simulated tumors with TVDTs sampled from the clinical fit were inserted into 30 virtual breasts ("simulated cohort") and used to simulate mammograms. Based on the TVDT, two successive screening rounds were simulated for each virtual breast. TVDTs from clinical and simulated mammograms were compared. Tumor sizes in the simulated mammograms were measured by a radiologist in three repeated sessions to estimate TVDT. Results: The mean TVDT was 297 days (standard deviation, SD, 169 days) in the clinical fit and 322 days (SD, 217 days) in the simulated cohort. The mean estimated TVDT was 340 days (SD, 287 days). No significant difference was found between the estimated TVDTs from simulated mammograms and clinical TVDT values ( p > 0.5 ). No significant difference ( p > 0.05 ) was observed in the reproducibility of the tumor size measurements between the two screening rounds. Conclusions: The proposed method for tumor growth simulation has demonstrated close agreement with clinical results, supporting potential use in VCTs of temporal breast imaging.

Activation of mitochondrial-associated apoptosis signaling pathway and inhibition of PI3K/Akt/mTOR signaling pathway by voacamine suppress breast cancer progression

BACKGROUND

Breast cancer is one of the malignant tumors with the highest morbidity and mortality rate. Numerous efficient anti-breast cancer drugs are being derived from the development of natural products. Voacamine (VOA), a bisindole alkaloid isolated from Voacanga africana Stapf, possesses various pharmacological and biological activities.

PURPOSE

In this study, we investigated the efficacy of VOA against breast cancer cells and elucidated the underlying mechanisms in vitro and in vivo.

METHODS

Human breast cancer cell line MCF-7 and mouse breast cancer cell line 4T1 were used to study the underlying anti-cancer mechanisms of VOA. The proliferation was detected by MTT, colony formation, cell proliferation and wound-healing migration assays. Flow cytometry was utilized to determine the level of reactive oxygen species (ROS) cell-cycle, apoptosis and mitochondrial membrane potential. The target proteins were analyzed by Western blot. Molecular docking was performed and scored by AutoDock. Subcutaneous cancer models in mice were established to evaluate the anticancer effects in vivo.

RESULT

Our results demonstrated that VOA selectively suppressed breast cancer MCF-7 and 4T1 cells proliferation with IC50 values of 0.99 and 1.48 μM, and significantly inhibited the migration and colony formation of tumor cells. Furthermore, the cell cycle was arrested in the S phase with the decreased expression levels of CDK2, Cyclin A and Cyclin E. Additionally, exposure to VOA dose-dependently brought about dose-dependently the loss of mitochondrial membrane potential (Δψm) and amassment of reactive oxygen species (ROS), resulting in the initiation of the intrinsic apoptotic pathway. Western blot analysis unveiled that VOA significantly activated mitochondrial-associated apoptosis and obviously suppress the PI3K/Akt/mTOR pathway via modulation of related protein expression levels in both tumor cell lines. In tumor-bearing mouse models, administration of VOA dose-dependently inhibited the tumor growth without causing apparent toxicities.

CONCLUSION

These findings revealed the novel properties of VOA in promoting apoptosis of breast cancer cells by activating mitochondrial-associated apoptosis signaling pathway and inhibiting PI3K/Akt/mTOR signaling pathway and significantly decreasing tumor size without detecting appreciable toxicity. In summary, the present results demonstrated VOA could be an encouraging drug candidate to cure breast cancer, exhibiting an effective method to exploit unique drugs from natural components.

The projected impact of the COVID-19 lockdown on breast cancer deaths in England due to the cessation of population screening: a national estimation

BACKGROUND

Population breast screening services in England were suspended in March 2020 due to the COVID-19 pandemic. Here, we estimate the number of breast cancers whose detection may be delayed because of the suspension, and the potential impact on cancer deaths over 10 years.

METHODS

We estimated the number and length of screening delays from observed NHS Breast Screening System data. We then estimated additional breast cancer deaths from three routes: asymptomatic tumours progressing to symptomatically diagnosed disease, invasive tumours which remain screen-detected but at a later date, and ductal carcinoma in situ (DCIS) progressing to invasive disease by detection. We took progression rates, prognostic characteristics, and survival rates from published sources.

RESULTS

We estimated that 1,489,237 women had screening delayed by around 2-7 months between July 2020 and June 2021, leaving 745,277 outstanding screens. Depending on how quickly this backlog is cleared, around 2500-4100 cancers would shift from screen-detected to symptomatic cancers, resulting in 148-452 additional breast cancer deaths. There would be an additional 164-222 screen-detected tumour deaths, and 71-97 deaths from DCIS that progresses to invasive cancer.

CONCLUSIONS

An estimated 148-687 additional breast cancer deaths may occur as a result of the pandemic-related disruptions. The impact depends on how quickly screening services catch up with delays.

[Moving toward personalized breast cancer screening: The role of Primary Care]

Breast cancer is the leading cause of death in the world among women. The Spanish National Health System (SNHS) introduced population-based breast cancer screening in 2006. As in most European programs, risk is identified on the basis of age and a mammogram is offered every two years to women aged 50-69 years. Scientific evidence is moving toward personalized screening, based on individual risk. This article presents the clinical trials that will evaluate the efficacy of personalized screening and some studies carried out in our environment on the effect of informing women of the benefits and adverse effects of screening or the acceptability and feasibility of offering personalized screening, in the Shared Decision Making context. The Preventive Activities and Health Promotion Program can help transform screening in our SNHS.

Embedding the Community and Individuals in Disease Prevention

The primary prevention of non-communicable diseases is one of the most challenging and exciting aspects of medicine and primary care this century. For cancer, it is an urgent matter in light of the increasing burden of the disease among younger people and the higher frequency of more aggressive forms of the disease for all ages. Most chronic disorders result from the influence of the environment on the expression of genes within an individual. The environment at-large encompasses lifestyle (including nutrition), and chemical/physical and social exposures. In cancer, the interaction between the (epi)genetic makeup of an individual and a multiplicity of environmental risk and protecting factors is considered key to disease onset. Thus, like for precision therapy developed for patients, personalized or precision prevention is envisioned for individuals at risk. Prevention means identifying people at higher risk and intervening to reduce the risk. It requires biological markers of risk and non-aggressive preventive actions for the individual, but it also involves acting on the environment and the community. Social scientists are considering micro (individual/family), meso (community), and macro (country population) levels of care to illustrate that problems and solutions exist on different scales. Ideally, the design of interventions in prevention should integrate all these levels. In this perspective article, using the example of breast cancer, we are discussing challenges and possible solutions for a multidisciplinary community of scientists, primary health care practitioners and citizens to develop a holistic approach of primary prevention, keeping in mind equitable access to care.

A comparison of local therapy alone with local plus systemic therapy for stage I pT1aN0M0 HER2+ breast cancer: A National Cancer Database analysis

BACKGROUND

Small invasive breast cancers (BCs) with tumor sizes ≤5 mm (T1a) are associated with an excellent prognosis without systemic therapy. Although HER2 overexpression (HER2+) is associated with a higher risk of recurrence and poorer clinical outcomes, in the absence of HER2 directed therapy, it remains unclear whether adjuvant systemic therapy is necessary in node-negative patients diagnosed with HER2+ invasive BCs ≤5 mm (pT1aN0M0).

METHODS

The National Cancer Database was searched to identify patients diagnosed with HER2+ pT1aN0M0 BCs from 2004 to 2017. The cohort was stratified by treatment status: local therapy alone or local plus adjuvant systemic therapy. A 1:1 propensity match was performed. Overall survival (OS) was analyzed using stratified multivariable Cox proportional hazards regression analyses.

RESULTS

Of the 8948 patients found, 4026 (45.0%) underwent surgery alone, and 4922 (55.0%) received surgery plus systemic therapy. Patients with either moderately differentiated (odds ratio [OR], 2.053; P < .001) or poorly/undifferentiated tumors (OR, 3.780; P < .001) or with the presence of lymphovascular invasion (OR, 3.351; P < .001) were more likely to have received systemic therapy. Propensity matching generated 1162 pairs of patients who were hormone receptor positive (HR+) and 748 pairs who were hormone receptor negative (HR-). Propensity matching effectively reduced selection bias between study groups. In the matched cohort, the addition of systemic therapy was not associated with superior OS (hazard ratio for HR+, 1.613; P = .107, and hazard ratio for HR- 1.319; P = .369) compared with patients who received local therapy alone.

CONCLUSIONS

In pT1aN0M0 HER2+ BC, the addition of adjuvant systemic therapy after surgical excision was not associated with improved OS compared with local therapy alone.

The future of early cancer detection

A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish inconsequential changes from lesions that will lead to life-threatening cancer. Progress relies on a detailed understanding of individualized risk, clear delineation of cancer development stages, a range of testing methods with optimal performance characteristics, and robust evaluation of the implications for individuals and society. In the future, advances in sensors, contrast agents, molecular methods, and artificial intelligence will help detect cancer-specific signals in real time. To reduce the burden of cancer on society, risk-based detection and prevention needs to be cost effective and widely accessible.

Development and validation of clinical prediction models for breast cancer incidence and mortality: a protocol for a dual cohort study

INTRODUCTION

Breast cancer is the most common cancer and the leading cause of cancer-related death in women worldwide. Risk prediction models may be useful to guide risk-reducing interventions (such as pharmacological agents) in women at increased risk or inform screening strategies for early detection methods such as screening.

METHODS AND ANALYSIS

The study will use data for women aged 20-90 years between 2000 and 2020 from QResearch linked at the individual level to hospital episodes, cancer registry and death registry data. It will evaluate a set of modelling approaches to predict the risk of developing breast cancer within the next 10 years, the 'combined' risk of developing a breast cancer and then dying from it within 10 years, and the risk of breast cancer mortality within 10 years of diagnosis. Cox proportional hazards, competing risks, random survival forest, deep learning and XGBoost models will be explored. Models will be developed on the entire dataset, with 'apparent' performance reported, and internal-external cross-validation used to assess performance and geographical and temporal transportability (two 10-year time periods). Random effects meta-analysis will pool discrimination and calibration metric estimates from individual geographical units obtained from internal-external cross-validation. We will then externally validate the models in an independent dataset. Evaluation of performance heterogeneity will be conducted throughout, such as exploring performance across ethnic groups.

ETHICS AND DISSEMINATION

Ethics approval was granted by the QResearch scientific committee (reference number REC 18/EM/0400: OX129). The results will be written up for submission to peer-reviewed journals.