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Co-observation of a gene variant with a pathogenic variant in another gene that explains the disease presentation has been designated as evidence against pathogenicity for commonly used variant classification guidelines. Multiple variant curation expert panels have specified, from consensus opinion, that this evidence type is not applicable for the classification of breast cancer predisposition gene variants. Statistical analysis of sequence data for 55,815 individuals diagnosed with breast cancer from the BRIDGES sequencing project was undertaken to formally assess the utility of co-observation data for germline variant classification. Our analysis included expected loss-of-function variants in 11 breast cancer predisposition genes and pathogenic missense variants in BRCA1, BRCA2, and TP53. We assessed whether co-observation of pathogenic variants in two different genes occurred more or less often than expected under the assumption of independence. Co-observation of pathogenic variants in each of BRCA1, BRCA2, and PALB2 with the remaining genes was less frequent than expected. This evidence for depletion remained after adjustment for age at diagnosis, study design (familial versus population-based), and country. Co-observation of a variant of uncertain significance in BRCA1, BRCA2, or PALB2 with a pathogenic variant in another breast cancer gene equated to supporting evidence against pathogenicity following criterion strength assignment based on the likelihood ratio and showed utility in reclassification of missense BRCA1 and BRCA2 variants identified in BRIDGES. Our approach has applicability for assessing the value of co-observation as a predictor of variant pathogenicity in other clinical contexts, including for gene-specific guidelines developed by ClinGen Variant Curation Expert Panels.
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Conflicting results have appeared in the literature on whether the amount of non-dense, adipose tissue in the breast is a risk factor or a protective factor for breast cancer, and biological hypotheses supporting both have been proposed. We suggest here that limitations in study design and statistical methodology could potentially explain the inconsistent results. Specifically, we exploit recent advances in methodology and software developed for the joint analysis of multiple longitudinal outcomes and time-to-event data to jointly analyze dense and non-dense tissue trajectories and the risk of breast cancer in a large, Swedish, screening cohort. We also perform extensive sensitivity analyses by mimicking analyses/designs of previously published studies, e.g. ignoring available longitudinal data. Overall, we did not find strong evidence supporting an association between non-dense tissue and the risk of incident breast cancer. We hypothesize that (1) previous studies have not been able to isolate the effect of non-dense tissue from dense tissue or adipose tissue elsewhere in the body, that (2) estimates of the effect of non-dense tissue on risk are strongly sensitive to modeling assumptions, or that (3) the effect size of non-dense tissue on breast cancer risk is likely to be small/not clinically relevant.
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BACKGROUND: Mammographic density (MD) has been shown to be a strong and independent risk factor for breast cancer in women of European and Asian descent. However, the majority of Asian studies to date have used BI-RADS as the scoring method and none have evaluated area and volumetric densities in the same cohort of women. This study aims to compare the association of MD measured by two automated methods with the risk of breast cancer in Asian women, and to investigate if the association is different for premenopausal and postmenopausal women. METHODS: In this case-control study of 531 cases and 2297 controls, we evaluated the association of area-based MD measures and volumetric-based MD measures with breast cancer risk in Asian women using conditional logistic regression analysis, adjusting for relevant confounders. The corresponding association by menopausal status were assessed using unconditional logistic regression. RESULTS: We found that both area and volume-based MD measures were associated with breast cancer risk. Strongest associations were observed for percent densities (OR (95% CI) was 2.06 (1.42-2.99) for percent dense area and 2.21 (1.44-3.39) for percent dense volume, comparing women in highest density quartile with those in the lowest quartile). The corresponding associations were significant in postmenopausal but not premenopausal women (premenopausal versus postmenopausal were 1.59 (0.95-2.67) and 1.89 (1.22-2.96) for percent dense area and 1.24 (0.70-2.22) and 1.96 (1.19-3.27) for percent dense volume). However, the odds ratios were not statistically different by menopausal status [p difference = 0.782 for percent dense area and 0.486 for percent dense volume]. CONCLUSIONS: This study confirms the associations of mammographic density measured by both area and volumetric methods and breast cancer risk in Asian women. Stronger associations were observed for percent dense area and percent dense volume, and strongest effects were seen in postmenopausal individuals.
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Pueblo Asiatico , Densidad de la Mama , Neoplasias de la Mama , Mamografía , Humanos , Femenino , Neoplasias de la Mama/epidemiología , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Neoplasias de la Mama/etiología , Estudios de Casos y Controles , Persona de Mediana Edad , Adulto , Factores de Riesgo , Mamografía/métodos , Anciano , Posmenopausia , Premenopausia , Oportunidad Relativa , Glándulas Mamarias Humanas/anomalías , Glándulas Mamarias Humanas/diagnóstico por imagen , Glándulas Mamarias Humanas/patologíaRESUMEN
PURPOSE: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR). METHODS: We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status. RESULTS: Genetically predicted BMI was positively associated with non-dense area (IVW: ß = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10-63) and inversely associated with dense area (IVW: ß = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10-7). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (ß = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (ß = - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches. CONCLUSION: Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.
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Índice de Masa Corporal , Densidad de la Mama , Neoplasias de la Mama , Estudio de Asociación del Genoma Completo , Hormonas Esteroides Gonadales , Análisis de la Aleatorización Mendeliana , Humanos , Femenino , Neoplasias de la Mama/genética , Neoplasias de la Mama/sangre , Neoplasias de la Mama/diagnóstico por imagen , Hormonas Esteroides Gonadales/sangre , Globulina de Unión a Hormona Sexual/análisis , Globulina de Unión a Hormona Sexual/metabolismo , Globulina de Unión a Hormona Sexual/genética , Persona de Mediana Edad , Polimorfismo de Nucleótido Simple , Mamografía , Estradiol/sangre , Testosterona/sangre , FenotipoRESUMEN
Tamoxifen prevents recurrence of breast cancer and is also approved for preventive, risk-reducing, therapy. Tamoxifen alters the breast tissue composition and decreases the mammographic density. We aimed to test if baseline breast tissue composition influences tamoxifen-associated density change. This biopsy-based study included 83 participants randomised to 6 months daily intake of placebo, 20, 10, 5, 2.5, or 1 mg tamoxifen. The study is nested within the double-blinded tamoxifen dose-determination trial Karolinska Mammography Project for Risk Prediction of Breast Cancer Intervention (KARISMA) Study. Ultrasound-guided core-needle breast biopsies were collected at baseline before starting treatment. Biopsies were quantified for epithelial, stromal, and adipose distributions, and epithelial and stromal expression of proliferation marker Ki67, oestrogen receptor (ER) and progesterone receptor (PR). Mammographic density was measured using STRATUS. We found that greater mammographic density at baseline was positively associated with stromal area and inversely associated with adipose area and stromal expression of ER. Premenopausal women had greater mammographic density and epithelial tissue, and expressed more epithelial Ki67, PR, and stromal PR, compared to postmenopausal women. In women treated with tamoxifen (1-20 mg), greater density decrease was associated with higher baseline density, epithelial Ki67, and stromal PR. Women who responded to tamoxifen with a density decrease had on average 17% higher baseline density and a 2.2-fold higher PR expression compared to non-responders. Our results indicate that features in the normal breast tissue before tamoxifen exposure influences the tamoxifen-associated density decrease, and that the age-associated difference in density change may be related to age-dependant differences in expression of Ki67 and PR.
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Antineoplásicos Hormonales , Densidad de la Mama , Neoplasias de la Mama , Mamografía , Tamoxifeno , Humanos , Tamoxifeno/farmacología , Tamoxifeno/administración & dosificación , Femenino , Densidad de la Mama/efectos de los fármacos , Persona de Mediana Edad , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/patología , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/metabolismo , Mamografía/métodos , Adulto , Antineoplásicos Hormonales/uso terapéutico , Antineoplásicos Hormonales/administración & dosificación , Método Doble Ciego , Receptores de Estrógenos/metabolismo , Anciano , Receptores de Progesterona/metabolismo , Mama/efectos de los fármacos , Mama/diagnóstico por imagen , Mama/patología , Mama/metabolismo , Antígeno Ki-67/metabolismo , Antígeno Ki-67/análisis , PosmenopausiaRESUMEN
BACKGROUND: Associations between germline alterations in women and cancer risks among their relatives are largely unknown. METHODS: We identified women from 2 Swedish cohorts Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) and prevalent KARMA (pKARMA), including 28â362 women with genotyping data and 13â226 with sequencing data. Using Swedish Multi-Generation Register, we linked these women to 133â389 first-degree relatives. Associations between protein-truncating variants in 8 risk genes and breast cancer polygenic risk score in index women and cancer risks among their relatives were modeled via Cox regression. RESULTS: Female relatives of index women who were protein-truncating variant carriers in any of the 8 risk genes had an increased breast cancer risk compared with those of noncarriers (hazard ratio [HR] = 1.85, 95% confidence interval [CI] = 1.52 to 2.27), with the strongest association found for protein-truncating variants in BRCA1 and 2. These relatives had a statistically higher risk of early onset than late-onset breast cancer (P = .001). Elevated breast cancer risk was also observed in female relatives of index women with higher polygenic risk score (HR per SD = 1.28, 95% CI = 1.23 to 1.32). The estimated lifetime risk was 22.3% for female relatives of protein-truncating variant carriers and 14.4% for those related to women in the top polygenic risk score quartile. Moreover, relatives of index women with protein-truncating variant presence (HR = 1.30, 95% CI = 1.06 to 1.59) or higher polygenic risk score (HR per SD = 1.04, 95% CI = 1.01 to 1.07) were also at higher risk of nonbreast hereditary breast and ovary cancer syndrome-related cancers. CONCLUSIONS: Protein-truncating variants of risk genes and higher polygenic risk score in index women are associated with an increased risk of breast and other hereditary breast and ovary syndrome-related cancers among relatives.
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Neoplasias de la Mama , Predisposición Genética a la Enfermedad , Humanos , Femenino , Neoplasias de la Mama/genética , Neoplasias de la Mama/epidemiología , Persona de Mediana Edad , Suecia/epidemiología , Adulto , Anciano , Mutación de Línea Germinal , Factores de Riesgo , Medición de Riesgo , Familia , Proteína BRCA1/genética , Sistema de Registros , Proteína BRCA2/genética , LinajeRESUMEN
Importance: Breast cancers (BCs) diagnosed between 2 screening examinations are called interval cancers (ICs), and they have worse clinicopathological characteristics and poorer prognosis than screen-detected cancers (SDCs). However, the association of rare germline genetic variants with IC have not been studied. Objective: To evaluate whether rare germline deleterious protein-truncating variants (PTVs) can be applied to discriminate between IC and SDC while considering mammographic density. Design, Setting, and Participants: This population-based genetic association study was based on women aged 40 to 76 years who were attending mammographic screening in Sweden. All women with a diagnosis of BC between January 2001 and January 2016 were included, together with age-matched controls. Patients with BC were followed up for survival until 2021. Statistical analysis was performed from September 2021 to December 2022. Exposure: Germline PTVs in 34 BC susceptibility genes as analyzed by targeted sequencing. Main Outcomes and Measures: Odds ratios (ORs) were used to compare IC with SDC using logistic regression. Hazard ratios were used to investigate BC-specific survival using Cox regression. Results: All 4121 patients with BC (IC, n = 1229; SDC, n = 2892) were female, with a mean (SD) age of 55.5 (7.1) years. There were 5631 age-matched controls. The PTVs of the ATM, BRCA1, BRCA2, CHEK2, and PALB2 genes were more common in patients with IC compared with SDC (OR, 1.48; 95% CI, 1.06-2.05). This association was primarily influenced by BRCA1/2 and PALB2 variants. A family history of BC together with PTVs of any of these genes synergistically increased the probability of receiving a diagnosis of IC rather than SDC (OR, 3.95; 95% CI, 1.97-7.92). Furthermore, 10-year BC-specific survival revealed that if a patient received a diagnosis of an IC, carriers of PTVs in any of these 5 genes had significantly worse survival compared with patients not carrying any of them (hazard ratio, 2.04; 95% CI, 1.06-3.92). All of these associations were further pronounced in a subset of patients with IC who had a low mammographic density at prior screening examination. Conclusions and Relevance: The results of this study may be helpful in future optimizations of screening programs that aim to lower mortality as well as the clinical treatment of patients with BC.
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Neoplasias de la Mama , Femenino , Humanos , Neoplasias de la Mama/genética , Neoplasias de la Mama/diagnóstico , Proteína BRCA1/genética , Proteína BRCA2/genética , Predisposición Genética a la EnfermedadRESUMEN
Importance: False-positive mammography results are common. However, long-term outcomes after a false-positive result remain unclear. Objectives: To examine long-term outcomes after a false-positive mammography result and to investigate whether the association of a false-positive mammography result with cancer differs by baseline characteristics, tumor characteristics, and time since the false-positive result. Design, Setting, and Participants: This population-based, matched cohort study was conducted in Sweden from January 1, 1991, to March 31, 2020. It included 45â¯213 women who received a first false-positive mammography result between 1991 and 2017 and 452â¯130 controls matched on age, calendar year of mammography, and screening history (no previous false-positive result). The study also included 1113 women with a false-positive result and 11â¯130 matched controls with information on mammographic breast density from the Karolinska Mammography Project for Risk Prediction of Breast Cancer study. Statistical analysis was performed from April 2022 to February 2023. Exposure: A false-positive mammography result. Main Outcomes and Measures: Breast cancer incidence and mortality. Results: The study cohort included 497â¯343 women (median age, 52 years [IQR, 42-59 years]). The 20-year cumulative incidence of breast cancer was 11.3% (95% CI, 10.7%-11.9%) among women with a false-positive result vs 7.3% (95% CI, 7.2%-7.5%) among those without, with an adjusted hazard ratio (HR) of 1.61 (95% CI, 1.54-1.68). The corresponding HRs were higher among women aged 60 to 75 years at the examination (HR, 2.02; 95% CI, 1.80-2.26) and those with lower mammographic breast density (HR, 4.65; 95% CI, 2.61-8.29). In addition, breast cancer risk was higher for women who underwent a biopsy at the recall (HR, 1.77; 95% CI, 1.63-1.92) than for those without a biopsy (HR, 1.51; 95% CI, 1.43-1.60). Cancers after a false-positive result were more likely to be detected on the ipsilateral side of the false-positive result (HR, 1.92; 95% CI, 1.81-2.04) and were more common during the first 4 years of follow-up (HR, 2.57; 95% CI, 2.33-2.85 during the first 2 years; HR, 1.93; 95% CI, 1.76-2.12 at >2 to 4 years). No statistical difference was found for different tumor characteristics (except for larger tumor size). Furthermore, associated with the increased risk of breast cancer, women with a false-positive result had an 84% higher rate of breast cancer death than those without (HR, 1.84; 95% CI, 1.57-2.15). Conclusions and Relevance: This study suggests that the risk of developing breast cancer after a false-positive mammography result differs by individual characteristics and follow-up. These findings can be used to develop individualized risk-based breast cancer screening after a false-positive result.
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Neoplasias de la Mama , Femenino , Humanos , Persona de Mediana Edad , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/epidemiología , Incidencia , Estudios de Cohortes , Reacciones Falso Positivas , Mamografía/métodos , Detección Precoz del Cáncer/métodosRESUMEN
BACKGROUND: Earlier studies have shown that abbreviated protocol magnetic resonance imaging (AB-MRI) has similar diagnostic accuracy as the full protocol (Full MRI). PURPOSE: To compare the diagnostic accuracy, reading time, and inter-rater agreement of AB-MRI to Full MRI among women without known increased familial risk of breast cancer or prior biopsy. MATERIAL AND METHODS: In total, 395 MRI examinations were included in this study. Three readers were blinded to all patient information. The AB-MRI and Full MRI were read separately and in a different random order for each of the readers. Scores 1-2 were considered test negative while scores 3-5 were test positive. A positive reference test was the diagnosis of malignancy; a negative reference test was the absence of a diagnosis of breast cancer within a two-year follow-up. We used a generalized estimating equations approach to compare sensitivity and specificity between the two protocols. We used t-tests to compare the average reading time and Krippendorff's alpha to compare inter-rater agreement. RESULTS: MRI examinations of 395 women (median age=56 years) were evaluated. For AB-MRI and Full MRI, respectively, the sensitivity was 93.0% (95% CI=90.6-95.0) vs. 92.0% (95% CI=89.4-94.1), the specificity was 91.7% (95% CI=90.3-92.9) vs. 94.3% (95% CI=93.2-95.3), average reading time was 67 vs. 126â s, and the inter-rater agreement 0.79 vs. 0.83. The difference in sensitivity was not statistically significant (P=0.840), but the difference in specificity was significant (P=0.003). CONCLUSION: AB-MRI has similar sensitivity, but somewhat lower specificity. The average reading time for the abbreviated protocol is lower, as is inter-rater agreement.
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Neoplasias de la Mama , Mama , Femenino , Humanos , Persona de Mediana Edad , Mama/diagnóstico por imagen , Mama/patología , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Imagen por Resonancia Magnética/métodos , Radiografía , Sensibilidad y Especificidad , Estudios RetrospectivosRESUMEN
OBJECTIVE: Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk. SUBJECTS: In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort. RESULTS: In a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy. CONCLUSIONS: Our results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.
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Neoplasias de la Mama , Femenino , Humanos , Neoplasias de la Mama/diagnóstico , Estudios Prospectivos , Proteómica , Mamografía/métodos , Factores de Riesgo , Proteínas SanguíneasRESUMEN
Biomarkers for early detection of breast cancer may complement population screening approaches to enable earlier and more precise treatment. The blood proteome is an important source for biomarker discovery but so far, few proteins have been identified with breast cancer risk. Here, we measure 2929 unique proteins in plasma from 598 women selected from the Karolinska Mammography Project to explore the association between protein levels, clinical characteristics, and gene variants, and to identify proteins with a causal role in breast cancer. We present 812 cis-acting protein quantitative trait loci for 737 proteins which are used as instruments in Mendelian randomisation analyses of breast cancer risk. Of those, we present five proteins (CD160, DNPH1, LAYN, LRRC37A2 and TLR1) that show a potential causal role in breast cancer risk with confirmatory results in independent cohorts. Our study suggests that these proteins should be further explored as biomarkers and potential drug targets in breast cancer.
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Neoplasias de la Mama , Humanos , Femenino , Neoplasias de la Mama/diagnóstico , Neoplasias de la Mama/genética , Biomarcadores , Mamografía , Fenotipo , Proteínas Sanguíneas/genética , Análisis de la Aleatorización Mendeliana/métodos , Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , Lectinas Tipo C/genéticaRESUMEN
Light-at-night triggers the decline of pineal gland melatonin biosynthesis and secretion and is an IARC-classified probable breast-cancer risk factor. We applied a large-scale molecular epidemiology approach to shed light on the putative role of melatonin in breast cancer. We investigated associations between breast-cancer risk and polymorphisms at genes of melatonin biosynthesis/signaling using a study population of 44,405 women from the Breast Cancer Association Consortium (22,992 cases, 21,413 population-based controls). Genotype data of 97 candidate single nucleotide polymorphisms (SNPs) at 18 defined gene regions were investigated for breast-cancer risk effects. We calculated adjusted odds ratios (ORs) and 95% confidence intervals (CI) by logistic regression for the main-effect analysis as well as stratified analyses by estrogen- and progesterone-receptor (ER, PR) status. SNP-SNP interactions were analyzed via a two-step procedure based on logic regression. The Bayesian false-discovery probability (BFDP) was used for all analyses to account for multiple testing. Noteworthy associations (BFDP < 0.8) included 10 linked SNPs in tryptophan hydroxylase 2 (TPH2) (e.g. rs1386492: OR = 1.07, 95% CI 1.02-1.12), and a SNP in the mitogen-activated protein kinase 8 (MAPK8) (rs10857561: OR = 1.11, 95% CI 1.04-1.18). The SNP-SNP interaction analysis revealed noteworthy interaction terms with TPH2- and MAPK-related SNPs (e.g. rs1386483R ⧠rs1473473D ⧠rs3729931D: OR = 1.20, 95% CI 1.09-1.32). In line with the light-at-night hypothesis that links shift work with elevated breast-cancer risks our results point to SNPs in TPH2 and MAPK-genes that may impact the intricate network of circadian regulation.
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Neoplasias de la Mama , Melatonina , Humanos , Femenino , Neoplasias de la Mama/genética , Neoplasias de la Mama/epidemiología , Melatonina/genética , Melatonina/metabolismo , Teorema de Bayes , Polimorfismo de Nucleótido Simple , Modelos Logísticos , Estudios de Casos y Controles , Predisposición Genética a la EnfermedadRESUMEN
Introduction: Mammographic breast density (MBD) is an established breast cancer risk factor, yet the underlying molecular mechanisms remain to be deciphered. Fibroblast growth factor receptor 1 (FGFR1) amplification is associated with breast cancer development and aberrant FGF signaling found in the biological processes related to both high mammographic density and breast cancer microenvironment. The aim of this study was to investigate the FGF/FGFR1 expression in-between paired tumor-adjacent and tumor tissues from the same patient, and its associations with MBD and tumor characteristics. Methods: FGFR1 expression in paired tissues from 426 breast cancer patients participating in the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort study was analyzed by immunohistochemistry. FGF ligand expression was obtained from RNA-sequencing data for 327 of the included patients. Results: FGFR1 levels were differently expressed in tumor-adjacent and tumor tissues, with increased FGFR1 levels detected in 58% of the tumors. High FGFR1 expression in tumor tissues was associated with less favorable tumor characteristics; high histological grade (OR=1.86, 95% CI 1.00-3.44), high Ki67 proliferative index (OR=2.18, 95% CI 1.18-4.02) as well as tumors of Luminal B-like subtype (OR=2.56, 95%CI 1.29-5.06). While no clear association between FGFR1 expression and MBD was found, FGF ligand (FGF1, FGF11, FGF18) expression was positively correlated with MBD. Discussion: Taken together, these findings support a role of the FGF/FGFR1 system in early breast cancer which warrants further investigation in the MBD-breast cancer context.
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Understanding the detectability of breast cancer using mammography is important when considering nation-wide screening programmes. Although the role of imaging settings on image quality has been studied extensively, their role in detectability of cancer at a population level is less well studied. We wish to quantify the association between mammographic screening sensitivity and various imaging parameters. Using a novel approach applied to a population-based breast cancer screening cohort, we specifically focus on sensitivity as defined in the classical diagnostic testing literature, as opposed to the screen-detected cancer rate, which is often used as a measure of sensitivity for monitoring and evaluating breast cancer screening. We use a natural history approach to model the presence and size of latent tumors at risk of detection at mammography screening, and the screening sensitivity is modeled as a logistic function of tumor size. With this approach we study the influence of compressed breast thickness, x-ray exposure, and compression pressure, in addition to (percent) breast density, on the screening test sensitivity. When adjusting for all screening parameters in addition to latent tumor size, we find that percent breast density and compressed breast thickness are statistically significant factors for the detectability of breast cancer. A change in breast density from 6.6 to 33.5% (the inter-quartile range) reduced the odds of detection by 61% (95% CI 48-71). Similarly, a change in compressed breast thickness from 46 to 66 mm reduced the odds by 42% (95% CI 21-57). The true sensitivity of mammography, defined as the probability that an examination leads to a positive result if a tumour is present in the breast, is associated with compressed breast thickness after accounting for mammographic density and tumour size. This can be used to guide studies of setups aimed at improving lesion detection. Compressed breast thickness-in addition to breast density-should be considered when assigning complementary screening modalities and personalized screening intervals.
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Densidad de la Mama , Neoplasias de la Mama , Humanos , Femenino , Estudios de Cohortes , Mamografía , Mama/diagnóstico por imagen , Neoplasias de la Mama/diagnóstico por imagenRESUMEN
PURPOSE: Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown. METHOD: Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls. RESULTS: Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD. CONCLUSION: Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.
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Densidad de la Mama , Neoplasias de la Mama , Femenino , Humanos , Densidad de la Mama/genética , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/genética , Neoplasias de la Mama/epidemiología , Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , Factores de Riesgo , Asia Oriental , MamografíaRESUMEN
BACKGROUND: Image-derived artificial intelligence (AI) risk models have shown promise in identifying high-risk women in the short term. The long-term performance of image-derived risk models expanded with clinical factors has not been investigated. METHODS: We performed a case-cohort study of 8110 women aged 40-74 randomly selected from a Swedish mammography screening cohort initiated in 2010 together with 1661 incident BCs diagnosed before January 2022. The imaging-only AI risk model extracted mammographic features and age at screening. Additional lifestyle/familial risk factors were incorporated into the lifestyle/familial-expanded AI model. Absolute risks were calculated using the two models and the clinical Tyrer-Cuzick v8 model. Age-adjusted model performances were compared across the 10-year follow-up. RESULTS: The AUCs of the lifestyle/familial-expanded AI risk model ranged from 0.75 (95%CI: 0.70-0.80) to 0.68 (95%CI: 0.66-0.69) 1-10 years after study entry. Corresponding AUCs were 0.72 (95%CI: 0.66-0.78) to 0.65 (95%CI: 0.63-0.66) for the imaging-only model and 0.62 (95%CI: 0.55-0.68) to 0.60 (95%CI: 0.58-0.61) for Tyrer-Cuzick v8. The increased performances were observed in multiple risk subgroups and cancer subtypes. Among the 5% of women at highest risk, the PPV was 5.8% using the lifestyle/familial-expanded model compared with 5.3% using the imaging-only model, p < 0.01, and 4.6% for Tyrer-Cuzick, p < 0.01. CONCLUSIONS: The lifestyle/familial-expanded AI risk model showed higher performance for both long-term and short-term risk assessment compared with imaging-only and Tyrer-Cuzick models.
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BACKGROUND: Researchers have suggested that longitudinal trajectories of mammographic breast density (MD) can be used to understand changes in breast cancer (BC) risk over a woman's lifetime. Some have suggested, based on biological arguments, that the cumulative trajectory of MD encapsulates the risk of BC across time. Others have tried to connect changes in MD to the risk of BC. METHODS: To summarize the MD-BC association, we jointly model longitudinal trajectories of MD and time to diagnosis using data from a large ([Formula: see text]) mammography cohort of Swedish women aged 40-80 years. Five hundred eighteen women were diagnosed with BC during follow-up. We fitted three joint models (JMs) with different association structures; Cumulative, current value and slope, and current value association structures. RESULTS: All models showed evidence of an association between MD trajectory and BC risk ([Formula: see text] for current value of MD, [Formula: see text] and [Formula: see text] for current value and slope of MD respectively, and [Formula: see text] for cumulative value of MD). Models with cumulative association structure and with current value and slope association structure had better goodness of fit than a model based only on current value. The JM with current value and slope structure suggested that a decrease in MD may be associated with an increased (instantaneous) BC risk. It is possible that this is because of increased screening sensitivity rather than being related to biology. CONCLUSION: We argue that a JM with a cumulative association structure may be the most appropriate/biologically relevant model in this context.
Asunto(s)
Neoplasias de la Mama , Femenino , Humanos , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/epidemiología , Densidad de la Mama , Mama/diagnóstico por imagen , Mamografía , Investigación , Factores de RiesgoRESUMEN
Mammography screening programs are aimed at reducing mortality due to breast cancer by detecting tumors at an early stage. There is currently interest in moving away from the age-based screening programs, and toward personalized screening based on individual risk factors. To accomplish this, risk prediction models for breast cancer are needed to determine who should be screened, and when. We develop a novel approach using a (random effects) continuous growth model, which we apply to a large population-based, Swedish screening cohort. Unlike existing breast cancer prediction models, this approach explicitly incorporates each woman's individual screening visits in the prediction. It jointly models invasive breast cancer tumor onset, tumor growth rate, symptomatic detection rate, and screening sensitivity. In addition to predicting the overall risk of invasive breast cancer, this model can make separate predictions regarding specific tumor sizes, and the mode of detection (eg, detected at screening, or through symptoms between screenings). It can also predict how these risks change depending on whether or not a woman will attend her next screening. In our study, we predict, given a future diagnosis, that the probability of having a tumor less than (as opposed to greater than) 10-mm diameter, at detection, will be, on average, 2.6 times higher if a woman in the cohort attends their next screening. This indicates that the model can be used to evaluate the short-term benefit of screening attendance, at an individual level.
Asunto(s)
Neoplasias de la Mama , Humanos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Detección Precoz del Cáncer , Mamografía , Tamizaje Masivo , Suecia/epidemiologíaRESUMEN
BACKGROUND: Adherence to adjuvant tamoxifen therapy is suboptimal, and acceptance of tamoxifen for primary prevention is poor. Published results indicate effect of low-dose tamoxifen therapy. Using questionnaire data from a randomised controlled trial, we describe side effects of standard and low-dose tamoxifen in healthy women. METHODS: In the KARISMA trial, 1440 healthy women were randomised to 6 months of daily intake of 20, 10, 5, 2.5, 1 mg of tamoxifen or placebo. Participants completed a 48-item, five-graded Likert score symptom questionnaire at baseline and follow-up. Linear regression models were used to identify significant changes in severity levels across doses and by menopausal status. RESULTS: Out of 48 predefined symptoms, five were associated with tamoxifen exposure (hot flashes, night sweats, cold sweats, vaginal discharge and muscle cramps). When comparing these side effects in premenopausal women randomised to low doses (2.5, 5 mg) versus high doses (10, 20 mg), the mean change was 34% lower in the low-dose group. No dose-dependent difference was seen in postmenopausal women. CONCLUSIONS: Symptoms related to tamoxifen therapy are influenced by menopausal status. Low-dose tamoxifen, in contrast to high-dose, was associated with less pronounced side effects, a finding restricted to premenopausal women. Our findings give new insights which may influence future dosing strategies of tamoxifen in both the adjuvant and preventive settings. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT03346200.
Asunto(s)
Neoplasias de la Mama , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Femenino , Humanos , Tamoxifeno/uso terapéutico , Sofocos/inducido químicamente , Sofocos/tratamiento farmacológico , Sofocos/prevención & control , Premenopausia , Encuestas y Cuestionarios , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/inducido químicamente , Antineoplásicos Hormonales/efectos adversosRESUMEN
BACKGROUND: Risk assessment is important for breast cancer prevention and early detection. We aimed to examine whether common risk factors, mammographic features, and breast cancer risk prediction scores of a woman were associated with breast cancer risk for her sisters. METHODS: We included 53 051 women from the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Established risk factors were derived using self-reported questionnaires, mammograms, and single nucleotide polymorphism genotyping. Using the Swedish Multi-Generation Register, we identified 32 198 sisters of the KARMA women (including 5352 KARMA participants and 26 846 nonparticipants). Cox models were used to estimate the hazard ratios of breast cancer for both women and their sisters, respectively. RESULTS: A higher breast cancer polygenic risk score, a history of benign breast disease, and higher breast density in women were associated with an increased risk of breast cancer for both women and their sisters. No statistically significant association was observed between breast microcalcifications and masses in women and breast cancer risk for their sisters. Furthermore, higher breast cancer risk scores in women were associated with an increased risk of breast cancer for their sisters. Specifically, the hazard ratios for breast cancer per 1 standard deviation increase in age-adjusted KARMA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), and Tyrer-Cuzick risk scores were 1.16 (95% confidence interval [CI] = 1.07 to 1.27), 1.23 (95% CI = 1.12 to 1.35), and 1.21 (95% CI = 1.11 to 1.32), respectively. CONCLUSION: A woman's breast cancer risk factors are associated with her sister's breast cancer risk. However, the clinical utility of these findings requires further investigation.