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Breast cancer is a major health concern worldwide. Mammography, a cost-effective and accurate tool, is crucial in combating this issue. However, low contrast, noise, and artifacts can limit the diagnostic capabilities of radiologists. Computer-Aided Diagnosis (CAD) systems have been developed to overcome these challenges, with the accurate outlining of the breast being a critical step for further analysis. This study introduces the SAM-breast model, an adaptation of the Segment Anything Model (SAM) for segmenting the breast region in mammograms. This method enhances the delineation of the breast and the exclusion of the pectoral muscle in both medio lateral-oblique (MLO) and cranio-caudal (CC) views. We trained the models using a large, multi-center proprietary dataset of 2492 mammograms. The proposed SAM-breast model achieved the highest overall Dice Similarity Coefficient (DSC) of 99.22% ± 1.13 and Intersection over Union (IoU) 98.48% ± 2.10 over independent test images from five different datasets (two proprietary and three publicly available). The results are consistent across the different datasets, regardless of the vendor or image resolution. Compared with other baseline and deep learning-based methods, the proposed method exhibits enhanced performance. The SAM-breast model demonstrates the power of the SAM to adapt when it is tailored to specific tasks, in this case, the delineation of the breast in mammograms. Comprehensive evaluations across diverse datasets-both private and public-attest to the method's robustness, flexibility, and generalization capabilities.
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BACKGROUND: Personalized breast cancer screening is a novel strategy that estimates individual risk based on age, breast density, family history of breast cancer, personal history of benign breast lesions, and polygenic risk. Its goal is to propose personalized early detection recommendations for women in the target population based on their individual risk. Our aim was to synthesize the factors that influence women's decision to participate in personalized breast cancer screening, from the perspective of women and health care professionals. METHODS: Systematic review of qualitative evidence on factors influencing participation in personalized Breast Cancer Screening. We searched in Medline, Web of science, Scopus, EMBASE, CINAHL and PsycINFO for qualitative and mixed methods studies published up to March 2022. Two reviewers conducted study selection and extracted main findings. We applied the best-fit framework synthesis and adopted the Multilevel influences on the cancer care continuum model for analysis. After organizing initial codes into the seven levels of the selected model, we followed thematic analysis and developed descriptive and analytical themes. We assessed the methodological quality with the Critical Appraisal Skills Program tool. RESULTS: We identified 18 studies published between 2017 and 2022, conducted in developed countries. Nine studies were focused on women (n = 478) and in four studies women had participated in a personalized screening program. Nine studies focused in health care professionals (n = 162) and were conducted in primary care and breast cancer screening program settings. Factors influencing women's decision to participate relate to the women themselves, the type of program (personalized breast cancer screening) and perspective of health care professionals. Factors that determined women participation included persistent beliefs and insufficient knowledge about breast cancer and personalized screening, variable psychological reactions, and negative attitudes towards breast cancer risk estimates. Other factors against participation were insufficient health care professionals knowledge on genetics related to breast cancer and personalized screening process. The factors that were favourable included the women's perceived benefits for themselves and the positive impact on health systems. CONCLUSION: We identified the main factors influencing women's decisions to participate in personalized breast cancer screening. Factors related to women, were the most relevant negative factors. A future implementation requires improving health literacy for women and health care professionals, as well as raising awareness of the strategy in society.
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Background: Image-derived artificial intelligence (AI)-based risk models for breast cancer have shown high discriminatory performances compared with clinical risk models based on family history and lifestyle factors. However, little is known about their generalizability across European screening settings. We therefore investigated the discriminatory performances of an AI-based risk model in European screening settings. Methods: Using four European screening populations in three countries (Italy, Spain, Germany) screened between 2009 and 2020 for women aged 45-69, we performed a nested case-control study to assess the predictive performance of an AI-based risk model. In total, 739 women with incident breast cancers were included together with 7812 controls matched on year of study-entry. Mammographic features (density, microcalcifications, masses, left-right breast asymmetries of these features) were extracted using AI from negative digital mammograms at study-entry. Two-year absolute risks of breast cancer were predicted and assessed after two years of follow-up. Adjusted risk stratification performance metrics were reported per clinical guidelines. Findings: The overall adjusted Area Under the receiver operating characteristic Curve (aAUC) of the AI risk model was 0.72 (95% CI 0.70-0.75) for breast cancers developed in four screening populations. In the 6.2% [529/8551] of women at high risk using the National Institute of Health and Care Excellence (NICE) guidelines thresholds, cancers were more likely diagnosed after 2 years follow-up, risk-ratio (RR) 6.7 (95% CI 5.6-8.0), compared with the 69% [5907/8551] of women classified at general risk by the model. Similar risk-ratios were observed across levels of mammographic density. Interpretation: The AI risk model showed generalizable discriminatory performances across European populations and, predicted â¼30% of clinically relevant stage 2 and higher breast cancers in â¼6% of high-risk women who were sent home with a negative mammogram. Similar results were seen in women with fatty and dense breasts. Funding: Swedish Research Council.
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INTRODUCTION: The study examined whether increased physical activity (PA) in nonmetropolitan cancer survivors was maintained 12 weeks following the PPARCS intervention. METHODS: PA outcomes were assessed using an accelerometer at baseline, end of the intervention, and at 24 weeks. Linear mixed models were used to examine between-group changes in PA outcomes. RESULTS: The increased moderate-to-vigorous PA (MVPA) following intervention was maintained with significantly higher MVPA in the intervention group at 24 weeks (vs. controls) compared to baseline nett change of 52.5 min/week (95% CI 11.0-94.0.4). CONCLUSIONS: Distance-based interventions using wearables and health coaching may produce MVPA maintenance amongst nonmetropolitan cancer survivors.
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Sobreviventes de Câncer , Neoplasias , Humanos , Exercício Físico , Promoção da SaúdeRESUMO
PURPOSE: To ensure high-quality screening programmes and effective utilization of resources, it is important to monitor how cancer detection is affected by different strategies performed at recall assessment. This study aimed to describe procedures performed at recall assessment and compare and evaluate the performance of the assessment in Denmark, Norway, and Spain in terms of screen-detected cancer (SDC) and interval cancer (IC) rates. METHODS: We included women aged 50-69 years from Denmark, Norway, and Spain, who were recalled for assessment after screening mammography, and recorded all procedures performed during six months after diagnosis, and the timing of the procedures. Women were followed for two years and screen-detected and interval cancer, and sensitivity of recall was calculated and compared. RESULTS: In total, data from 24,645 Danish, 30,050 Norwegian, and 41,809 Spanish women were included in the study. Most of the women had some assessment within 2 months in all three countries. SDC rates were higher in Denmark (0.57) and Norway (0.60) compared to Spain (0.38), as were the IC rates, i.e. 0.25 and 0.18 vs. 0.12, respectively. The sensitivity of the diagnostic follow-up was somewhat higher in Denmark (98.3%) and Norway (98.2%), compared to Spain (95.4%), but when excluding non-invasive assessment pathways, the sensitivities were comparable. CONCLUSION: This comparison study showed variation in the assessment procedures used in the three countries as well as the SDC and IC rates and the sensitivity of recall.
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Neoplasias da Mama , Detecção Precoce de Câncer , Mamografia , Humanos , Feminino , Mamografia/métodos , Mamografia/estatística & dados numéricos , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/epidemiologia , Pessoa de Meia-Idade , Espanha/epidemiologia , Idoso , Noruega/epidemiologia , Dinamarca/epidemiologia , Detecção Precoce de Câncer/métodos , Programas de Rastreamento/métodosRESUMO
BACKGROUND: Physical activity (PA) is important for cancer survivors. Trials of remotely delivered interventions are needed to assist in reaching under-served non-metropolitan cancer survivors. The objective of this study was to ascertain whether wearable technology, coupled with health coaching was effective in increasing PA in breast and colorectal cancer survivors living in regional and remote areas in Australia. METHODS: Cancer survivors from 5 states were randomized to intervention and control arms. Intervention participants were given a Fitbit Charge 2TM and received up to 6 telephone health coaching sessions. Control participants received PA print materials. Accelerometer assessments at baseline and 12 weeks measured moderate-to-vigorous PA (MVPA), light PA, and sedentary behavior. RESULTS: Eighty-seven participants were recruited (ageâ¯=â¯63 ± 11 years; 74 (85%) female). There was a significant net improvement in MVPA of 49.8 min/week, favoring the intervention group (95% confidence interval (95%CI): 13.6-86.1, pâ¯=â¯0.007). There was also a net increase in MVPA bouts of 39.5 min/week (95%CI: 11.9-67.1, pâ¯=â¯0.005), favoring the intervention group. Both groups improved light PA and sedentary behavior, but there were no between-group differences. CONCLUSION: This is the first study to demonstrate that, when compared to standard practice (i.e., PA education), a wearable technology intervention coupled with distance-based health coaching, improves MVPA in non-metropolitan cancer survivors. The results display promise for the use of scalable interventions using smart wearable technology in conjunction with phone-based health coaching to foster increased PA in geographically disadvantaged cancer survivors.
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Sobreviventes de Câncer , Neoplasias , Humanos , Feminino , Pessoa de Meia-Idade , Idoso , Masculino , Exercício Físico , Sobreviventes , Promoção da Saúde/métodos , Monitores de Aptidão FísicaRESUMO
Drug combinations are key to circumvent resistance mechanisms compromising response to single anti-cancer targeted therapies. The implementation of combinatorial approaches involving MEK1/2 or KRASG12C inhibitors in the context of KRAS-mutated lung cancers focuses fundamentally on targeting KRAS proximal activators or effectors. However, the antitumor effect is highly determined by compensatory mechanisms arising in defined cell types or tumor subgroups. A potential strategy to find drug combinations targeting a larger fraction of KRAS-mutated lung cancers may capitalize on the common, distal gene expression output elicited by oncogenic KRAS. By integrating a signature-driven drug repurposing approach with a pairwise pharmacological screen, here we show synergistic drug combinations consisting of multi-tyrosine kinase PKC inhibitors together with MEK1/2 or KRASG12C inhibitors. Such combinations elicit a cytotoxic response in both in vitro and in vivo models, which in part involves inhibition of the PKC inhibitor target AURKB. Proteome profiling links dysregulation of MYC expression to the effect of both PKC inhibitor-based drug combinations. Furthermore, MYC overexpression appears as a resistance mechanism to MEK1/2 and KRASG12C inhibitors. Our study provides a rational framework for selecting drugs entering combinatorial strategies and unveils MEK1/2- and KRASG12C-based therapies for lung cancer.
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Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Reposicionamento de Medicamentos , Proteínas Proto-Oncogênicas p21(ras)/genética , Proteínas Proto-Oncogênicas p21(ras)/metabolismo , Combinação de Medicamentos , Inibidores de Proteínas Quinases/farmacologia , Inibidores de Proteínas Quinases/uso terapêutico , Mutação , Linhagem Celular TumoralRESUMO
BACKGROUND: We aimed to develop and validate a model predicting breast cancer risk for women targeted by breast cancer screening. METHOD: This retrospective cohort study included 57,411 women screened at least once in BreastScreen Norway during the period from 2007 to 2019. The prediction model included information about age, mammographic density, family history of breast cancer, body mass index, age at menarche, alcohol consumption, exercise, pregnancy, hormone replacement therapy, and benign breast disease. We calculated a 4-year absolute breast cancer risk estimates for women and in risk groups by quartiles. The Bootstrap resampling method was used for internal validation of the model (E/O ratio). The area under the curve (AUC) was estimated with a 95% confidence interval (CI). RESULTS: The 4-year predicted risk of breast cancer ranged from 0.22-7.33%, while 95% of the population had a risk of 0.55-2.31%. The thresholds for the quartiles of the risk groups, with 25% of the population in each group, were 0.82%, 1.10%, and 1.47%. Overall, the model slightly overestimated the risk with an E/O ratio of 1.10 (95% CI: 1.09-1.11) and the AUC was 62.6% (95% CI: 60.5-65.0%). CONCLUSIONS: This 4-year risk prediction model showed differences in the risk of breast cancer, supporting personalized screening for breast cancer in women aged 50-69 years.
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In this study, we aimed to conduct a descriptive analysis of the primary physiological and psychological factors influencing the quality of life in women with breast cancer who engage in physical exercise. The study examined the key psychological variables predicting patients' quality of life, perceived support from family and friends, and the perception of physical condition. The sample consisted of 46 women from Cáceres (Spain) aged between 30 and 75 years undergoing breast cancer treatment. The Functional Evaluation Scale in Cancer Therapy (FACT-B+4) was used to measure quality of life; the Basic Psychological Needs Satisfaction Scale was used to measure autonomy, competence, and social relationships; the Behavior Regulation Questionnaire in Exercise (BREQ-3) was used to measure the types of self-determined motivation for sports participation; the General Evaluation of Self-Esteem Scale was used to measure self-esteem; the International Fitness Scale (IFIS) was used to measure perceived physical condition; and the Perceived Autonomy Support Scale for Exercise Settings (PASSES) was used to measure the perceived autonomy support from family and friends. A multiple regression analysis revealed that perceived physical condition and self-esteem were significant positive predictors of a variance in quality of life, while intrinsic motivation did not significantly predict it. The findings underscore the importance of promoting autonomous motivation in patients to enhance their physical and psychological well-being through physical activity.
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KRAS is a frequent driver in lung cancer. To identify KRAS-specific vulnerabilities in lung cancer, we performed RNAi screens in primary spheroids derived from a Kras mutant mouse lung cancer model and discovered an epigenetic regulator Ubiquitin-like containing PHD and RING finger domains 1 (UHRF1). In human lung cancer models UHRF1 knock-out selectively impaired growth and induced apoptosis only in KRAS mutant cells. Genome-wide methylation and gene expression analysis of UHRF1-depleted KRAS mutant cells revealed global DNA hypomethylation leading to upregulation of tumor suppressor genes (TSGs). A focused CRISPR/Cas9 screen validated several of these TSGs as mediators of UHRF1-driven tumorigenesis. In vivo, UHRF1 knock-out inhibited tumor growth of KRAS-driven mouse lung cancer models. Finally, in lung cancer patients high UHRF1 expression is anti-correlated with TSG expression and predicts worse outcomes for patients with KRAS mutant tumors. These results nominate UHRF1 as a KRAS-specific vulnerability and potential target for therapeutic intervention.
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Adenocarcinoma de Pulmão , Proteínas Estimuladoras de Ligação a CCAAT , Neoplasias Pulmonares , Ubiquitina-Proteína Ligases , Animais , Humanos , Camundongos , Adenocarcinoma de Pulmão/genética , Proteínas Estimuladoras de Ligação a CCAAT/genética , Proteínas Estimuladoras de Ligação a CCAAT/metabolismo , Transformação Celular Neoplásica/genética , Metilação de DNA , Epigênese Genética , Neoplasias Pulmonares/genética , Proteínas Proto-Oncogênicas p21(ras)/genética , Proteínas Proto-Oncogênicas p21(ras)/metabolismo , Ubiquitina-Proteína Ligases/genética , Ubiquitina-Proteína Ligases/metabolismoRESUMO
The increased frequency of heatwaves expected in the context of global warming will affect socio-ecological systems such as shellfish beds at intertidal seagrass meadows. A mesocosm experiment was performed to assess the effects of a simulated atmospheric heatwave during low tide on the bioturbation indicators and growth of the commercial juvenile native Ruditapes decussatus and the introduced clam R. philippinarum, and on their interactions with the seagrass Zostera noltei. Under the heatwave, heat dissipation at 5 cm depth was significantly greater in the sediments below Z. noltei than below bare sand, the photosynthetic efficiency (Fv/Fm) of Z. noltei decreased and the clams tended to grow less. Furthermore, after the heatwave clams below bare sand tended to burrow deeper than those below Z. noltei, indicating that seagrass provided a refuge for clams. Ruditapes philippinarum grew less, and did not burrow as deeply as R. decussatus, which may imply greater vulnerability to desiccation and heat at low tide. The particle displacement coefficient (PDC) of R. philippinarum indicated lower bioturbation values in Z. noltei than in bare sand and was a suitable bioturbation indicator for juvenile Ruditapes spp. clams. In Z. noltei coexisting with R. philippinarum, the Fv/Fm values were higher than without clams after a recovery period, which may be linked to the assimilation of phosphate excreted by the clams and suggests a facilitative interaction. No such interaction was observed with R. deccusatus, probably because of its deeper burrowing depth. The findings suggest reciprocal facilitative interactions between R. philippinarum and Z. noltei and the potential contribution of Z. noltei to the sustainability of clams under global warming scenarios, which may support management actions aimed at enhancing the coexistence between shellfishing activities and seagrass conservation.
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Bivalves , Areia , Animais , Frutos do Mar , Alimentos Marinhos , EcossistemaRESUMO
Breast density assessed from digital mammograms is a known biomarker related to a higher risk of developing breast cancer. Supervised learning algorithms have been implemented to determine this. However, the performance of these algorithms depends on the quality of the ground-truth information, which expert readers usually provide. These expert labels are noisy approximations to the ground truth, as there is both intra- and inter-observer variability among them. Thus, it is crucial to provide a reliable method to measure breast density from mammograms. This paper presents a fully automated method based on deep learning to estimate breast density, including breast detection, pectoral muscle exclusion, and dense tissue segmentation. We propose a novel confusion matrix (CM)-YNet model for the segmentation step. This architecture includes networks to model each radiologist's noisy label and gives the estimated ground-truth segmentation as well as two parameters that allow interaction with a threshold-based labeling tool. A multi-center study involving 1785 women whose "for presentation" mammograms were obtained from 11 different medical facilities was performed. A total of 2496 mammograms were used as the training corpus, and 844 formed the testing corpus. Additionally, we included a totally independent dataset from a different center, composed of 381 women with one image per patient. Each mammogram was labeled independently by two expert radiologists using a threshold-based tool. The implemented CM-Ynet model achieved the highest DICE score averaged over both test datasets (0.82±0.14) when compared to the closest dense-tissue segmentation assessment from both radiologists. The level of concordance between the two radiologists showed a DICE score of 0.76±0.17. An automatic breast density estimator based on deep learning exhibited higher performance when compared with two experienced radiologists. This suggests that modeling each radiologist's label allows for better estimation of the unknown ground-truth segmentation. The advantage of the proposed model is that it also provides the threshold parameters that enable user interaction with a threshold-based tool.
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Mutations in Kristen Rat Sarcoma viral oncogene (KRAS) are among the most frequent gain-of-function genetic alterations in human cancer. Most KRAS-driven cancers depend on its sustained expression and signaling. Despite spectacular recent success in the development of inhibitors targeting specific KRAS alleles, the discovery and utilization of effective directed therapies for KRAS-mutant cancers remains a major unmet need. One potential approach is the identification of KRAS-specific synthetic lethal vulnerabilities. For example, while KRAS-driven oncogenesis requires the activation of a number of signaling pathways, it also triggers stress response pathways in cancer cells that could potentially be targeted for therapeutic benefit. This review will discuss how the latest advances in functional genomics and the development of more refined models have demonstrated the existence of molecular pathways that can be exploited to uncover synthetic lethal interactions with a promising future as potential clinical treatments in KRAS-mutant cancers.
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Background: To assess the effect of the COVID-19 pandemic on performance indicators in the population-based breast cancer screening program of Parc de Salut Mar (PSMAR), Barcelona, Spain. Methods: We conducted a before-and-after, study to evaluate participation, recall, false positives, the cancer detection rate, and cancer characteristics in our screening population from March 2020 to March 2021 compared with the four previous rounds (2012-2019). Using multilevel logistic regression models, we estimated the adjusted odds ratios (aORs) of each of the performance indicators for the COVID-19 period, controlling by type of screening (prevalent or incident), socioeconomic index, family history of breast cancer, and menopausal status. We analyzed 144,779 invitations from 47,571women. Results: During the COVID-19 period, the odds of participation were lower in first-time invitees (aOR = 0.90 [95% CI = 0.84-0.96]) and in those who had previously participated regularly and irregularly (aOR = 0.63 [95% CI = 0.59-0.67] and aOR = 0.95 [95% CI = 0.86-1.05], respectively). Participation showed a modest increase in women not attending any of the previous rounds (aOR = 1.10 [95% CI = 1.01-1.20]). The recall rate decreased in both prevalent and incident screening (aOR = 0.74 [95% CI = 0.56-0.99] and aOR = 0.80 [95% CI = 0.68-0.95], respectively). False positives also decreased in both groups (prevalent aOR = 0.92 [95% CI = 0.66-1.28] and incident aOR = 0.72 [95% CI = 0.59-0.88]). No significant differences were observed in compliance with recall (OR = 1.26, 95% CI = 0.76-2.23), cancer detection rate (aOR = 0.91 [95% CI = 0.69-1.18]), or cancer stages. Conclusions: The COVID-19 pandemic negatively affected screening attendance, especially in previous participants and newcomers. We found a reduction in recall and false positives and no marked differences in cancer detection, indicating the robustness of the program. There is a need for further evaluations of interval cancers and potential diagnostic delays. Funding: This study has received funding by grants PI19/00007 and PI21/00058, funded by Instituto de Salud Carlos III (ISCIII) and cofunded by the European Union and Grant RD21/0016/0020 funded by Instituto de Salud Carlos III and by the European Union NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (MRR).
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Neoplasias da Mama , COVID-19 , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/epidemiologia , COVID-19/diagnóstico , COVID-19/epidemiologia , Estudos de Coortes , Detecção Precoce de Câncer , Feminino , Humanos , Mamografia , PandemiasRESUMO
OBJECTIVES: We compared the compression force, breast thickness, and glandular dose, as well as the severity of discomfort and women's experience between the patient-assisted compression (PAC) and standard compression (SC) modes. MATERIALS AND METHODS: We conducted a prospective randomized controlled study at Hospital del Mar in Barcelona, Spain. We included 448 asymptomatic women aged 50 to 69 years old, attending their screening round from December 2017 to December 2019. Mammograms included the two bilateral views. In each woman, one breast was studied with SC and the other with PAC. The mode used in each breast was selected following a randomized list. Compression force, breast thickness, and average glandular dose were obtained for each of the 1792 images. We also recorded the degree of discomfort and women's experience, after mammogram acquisitions, using a predefined survey. RESULTS: Higher compression forces were obtained with PAC than with SC (99.27 N vs 83.25 N, p < 0.001). Breast thickness mode (56.11 mm vs 57.52 mm, p = 0.015) and glandular dose (1.34 mGy vs 1.37 mGy, p = 0.018) were lower in PAC. The discomfort score was slightly higher with PAC (mean 3.94 vs 3.69, p = 0.042), but in the satisfaction survey, more women reported that PAC caused less discomfort. Additionally, 63.2% of women (289/448) preferred PAC. CONCLUSION: PAC achieved higher compression forces without impairing the other technical imaging parameters and enhanced women's experience of screening mammography. We believe there were no clinically significant differences in the severity of discomfort between the two modes. KEY POINTS: ⢠Self-compression allows higher compression forces than the standard compression mode. ⢠Self-compression does not affect technical imaging parameters. ⢠Self-compression improved women's experience of screening mammography when standard compression was used on one breast and self-compression on the other.
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Neoplasias da Mama , Mamografia , Feminino , Humanos , Pessoa de Meia-Idade , Idoso , Mamografia/métodos , Detecção Precoce de Câncer , Método Simples-Cego , Estudos Prospectivos , Neoplasias da Mama/diagnóstico por imagemRESUMO
OBJECTIVES: Evaluate the image quality of a mammography screening device using the patient-assisted compression (PAC) compared with the standard compression (SC) mode. METHODS: This prospective within-woman, randomized controlled trial was conducted between September 2017 and December 2019. Participants were asymptomatic women aged 50 to 69 years attending their second or subsequent screening mammography round. By random assignment, one breast underwent the SC and the other breast, the PAC. Image quality was evaluated as perfect, good, moderate, or inadequate (PGMI) on 10 criteria for the craniocaudal (CC) view and 8 criteria for the mediolateral oblique (MLO) view. Pearson's chi-square test, with Yates' correction if pertinent, was performed to compare image quality between compression modes. RESULTS: A total of 444 participants were included (mean [± standard deviation] age, 60 [± 4.9] years). There were no differences in the percentages of PGMI between the PAC and SC modes for the CC view (perfect, 37% [162/444] vs 37% [163/444]; good, 1% [5/444] vs 2% [9/444]; moderate, 62% [277/444] vs 61% [271/444]; inadequate, 0% vs 0.2% [1/444]; p = .88) or for the MLO view (perfect, 53% [237/444] vs 56% [247/444]; good, 22% [99/444] vs 22% [97/444]; moderate, 23% [102/444] vs 22% [98/444]; inadequate, 1% [6/444] vs 0.5% [2/444]; p = .72). No differences were found when we stratified by laterality or when analyzed by PGMI criteria. CONCLUSION: PAC does not seem to impair mammographic image quality. Future research should focus in a daily practice setting. KEY POINTS: No differences were found in the distribution of the PGMI classification, a tool for quality assessment, between patient-assisted compression and standard compression. Similar results were found on stratification of image quality by mammographic view and breast laterality for both types of compression. None of the PGMI criteria had significantly more errors in patient-assisted compression than in standard compression.
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Neoplasias da Mama , Mamografia , Feminino , Humanos , Pessoa de Meia-Idade , Mamografia/métodos , Estudos Prospectivos , Neoplasias da Mama/diagnóstico por imagem , Detecção Precoce de Câncer , Mama/diagnóstico por imagem , HiperplasiaRESUMO
Assessing the long-term risk of breast cancer after diagnosis of benign breast disease by mammography is of utmost importance to design personalised screening strategies. We analysed individual-level data from 778,306 women aged 50-69 years with at least one mammographic screening participation in any of ten breast cancer screening centers in Spain from 1996 to 2015, and followed-up until 2017. We used Poisson regression to compare the rates of incident breast cancer among women with and without benign breast disease. During a median follow-up of 7.6 years, 11,708 (1.5%) women had an incident of breast cancer and 17,827 (2.3%) had a benign breast disease. The risk of breast cancer was 1.77 times higher among women with benign breast disease than among those without (95% CI: 1.61 to 1.95). The relative risk increased to 1.99 among women followed for less than four years, and remained elevated for two decades, with relative risk 1.96 (95% CI: 1.32 to 2.92) for those followed from 12 to 20 years. Benign breast disease is a long-term risk factor for breast cancer. Women with benign breast disease could benefit from closer surveillance and personalized screening strategies.
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Neoplasias da Mama , Doença da Mama Fibrocística , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/epidemiologia , Detecção Precoce de Câncer , Feminino , Humanos , Mamografia , Programas de Rastreamento , Fatores de RiscoRESUMO
The main objective of this study was to validate the Healthy Lifestyle Questionnaire-EVS III, using confirmatory factor analysis of the measurement model. A total of 822 Portuguese individuals of both genders, aged between 18 and 66 years old (M = 28.43 SD = 12.07), participated in this study, of which 382 were male (46.5%) and 440 were female (53.5%). The main results obtained revealed that the psychometric qualities prove the adequacy of the factor structure of the Healthy Lifestyles Questionnaire-EVS III (7 factors/32 items) and that it has acceptable validity indices: χ2 = 644.6828, p = 0.000, df = 168, χ2/df = 3.84, NFI = 0.901, TLI = 0.902, CFI = 0.921, IFI = 0.922, MFI = 0.900, GFI = 0.909, AGFI = 0.901, RMR = 0.073, SRMR = 0.059 and RMSEA = 0.059, enabling the assessment of factors related to a balanced diet, respect for mealtimes, tobacco consumption, alcohol consumption, consumption of other drugs, resting habits and physical activity habits. The Portuguese version of the Healthy Lifestyles Questionnaire-EVS III can be used with reasonable confidence for the assessment of healthy lifestyles.