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1.
J Clin Oncol ; : JCO1901535, 2019 Dec 04.
Artigo em Inglês | MEDLINE | ID: mdl-31800347

RESUMO

PURPOSE: To examine the association between CYP2D6 genotype, discontinuation of tamoxifen therapy, and prognosis for breast cancer. PATIENTS AND METHODS: We conducted a prospective-retrospective study linking data from a clinical breast cancer register, the Swedish Prescribed Drug Register, and self-reported questionnaires. We genotyped CYP2D6 in 1,309 patients with breast cancer who were treated with tamoxifen and were diagnosed from 2005 to 2012; they were categorized as poor, intermediate, normal, or ultrarapid CYP2D6 metabolizers. We investigated whether metabolizer status was associated with tamoxifen discontinuation and prognosis for breast cancer using Cox regression analysis. RESULTS: The 6-month discontinuation rates of tamoxifen among poor, intermediate, normal, and ultrarapid CYP2D6 metabolizers were 7.1%, 7.6%, 6.7%, and 18.8%, respectively. A U-shaped association was found between CYP2D6 metabolizer status and breast cancer-specific mortality, with adjusted hazard ratios of 2.59 (95% CI, 1.01 to 6.67) for poor, 1.48 (95% CI, 0.72 to 3.05) for intermediate, 1 (reference) for normal, and 4.52 (95% CI, 1.42 to 14.37) for ultrarapid CYP2D6 metabolizers. CONCLUSION: Both poor and ultrarapid CYP2D6 metabolizers of tamoxifen have a worse prognosis for breast cancer compared with normal metabolizers after receiving a standard dose of tamoxifen. This U-shaped association might call for individualized tamoxifen dosage.

2.
Sci Rep ; 9(1): 14604, 2019 Oct 10.
Artigo em Inglês | MEDLINE | ID: mdl-31601987

RESUMO

Using for-presentation and for-processing digital mammograms, the presence of microcalcifications has been shown to be associated with short-term risk of breast cancer. In a previous article we developed an algorithm for microcalcification cluster detection from for-presentation digital mammograms. Here, we focus on digitised mammograms and use a three-step algorithm. In total, 253 incident invasive breast cancer cases (with a negative mammogram between three months and two years before diagnosis, from which we measured microcalcifications) and 728 controls (also with prior mammograms) were included in a short-term risk study. After adjusting for potential confounding variables, we found evidence of an association between the number of microcalcification clusters and short-term (within 3-24 months) invasive breast cancer risk (per cluster OR = 1.30, 95% CI = (1.11, 1.53)). Using the 728 postmenopausal healthy controls, we also examined association of microcalcification clusters with reproductive factors and other established breast cancer risk factors. Age was positively associated with the presence of microcalcification clusters (p = 4 × 10-04). Of ten other risk factors that we studied, life time breastfeeding duration had the strongest evidence of association with the presence of microcalcifications (positively associated, unadjusted p = 0.001). Developing algorithms, such as ours, which can be applied on both digitised and digital mammograms (in particular for presentation images), is important because large epidemiological studies, for deriving markers of (clinical) risk prediction of breast cancer and prognosis, can be based on images from these different formats.

3.
Nat Commun ; 10(1): 4648, 2019 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-31641120

RESUMO

Breast cancer (BC) patients diagnosed between two screenings (interval cancers) are more likely than screen-detected patients to carry rare deleterious mutations in cancer genes potentially leading to increased risk for other non-breast cancer (non-BC) tumors. In this study, we include 14,846 women diagnosed with BC of which 1,772 are interval and 13,074 screen-detected. Compared to women with screen-detected cancers, interval breast cancer patients are more likely to have a non-BC tumor before (Odds ratio (OR): 1.43 [1.19-1.70], P = 9.4 x 10-5) and after (OR: 1.28 [1.14-1.44], P = 4.70 x 10-5) breast cancer diagnosis, are more likely to report a family history of non-BC tumors and have a lower genetic risk score based on common variants for non-BC tumors. In conclusion, interval breast cancer is associated with other tumors and common cancer variants are unlikely to be responsible for this association. These findings could have implications for future screening and prevention programs.

4.
Twin Res Hum Genet ; : 1-7, 2019 Sep 12.
Artigo em Inglês | MEDLINE | ID: mdl-31512575

RESUMO

Nordic twin studies have played a critical role in understanding cancer etiology and elucidating the nature of familial effects on site-specific cancers. The NorTwinCan consortium is a collaborative effort that capitalizes on unique research advantages made possible through the Nordic system of registries. It was constructed by linking the population-based twin registries of Denmark, Finland, Norway and Sweden to their country-specific national cancer and cause-of-death registries. These linkages enable the twins to be followed many decades for cancer incidence and mortality. To date, two major linkages have been conducted: NorTwinCan I in 2011-2012 and NorTwinCan II in 2018. Overall, there are 315,413 eligible twins, 57,236 incident cancer cases and 58 years of follow-up, on average. In the initial phases of our work, NorTwinCan established the world's most comprehensive twin database for studying cancer, developed novel analytical approaches tailored to address specific research considerations within the context of the Nordic data and leveraged these models and data in research publications that provide the most accurate estimates of heritability and familial risk of cancers reported in the literature to date. Our findings indicate an excess familial risk for nearly all cancers and demonstrate that the incidence of cancer among twins mirrors the rate in the general population. They also revealed that twin concordance for cancer most often manifests across, rather than within, cancer sites, and we are currently focusing on the analysis of these cross-cancer associations.

5.
Sci Rep ; 9(1): 12524, 2019 Aug 29.
Artigo em Inglês | MEDLINE | ID: mdl-31467304

RESUMO

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.

6.
Breast Cancer Res ; 21(1): 95, 2019 08 16.
Artigo em Inglês | MEDLINE | ID: mdl-31420051

RESUMO

PURPOSE: Breast cancer is a common disease with a relatively good prognosis. Therefore, understanding the spectrum of diseases and mortality among breast cancer patients is important, though currently incomplete. We systematically examined the incidence and mortality of all diseases following a breast cancer diagnosis, as well as the sequential association of disease occurrences (trajectories). METHODS: In this national cohort study, 57,501 breast cancer patients (2001-2011) were compared to 564,703 matched women from the general Swedish population and followed until 2012. The matching criteria included year of birth, county of residence, and socioeconomic status. Based on information from the Swedish Patient and Cause of Death Registries, hazard ratios (HR) were estimated for disease incidence and mortality. Conditional logistic regression models were used to identify disease trajectories among breast cancer patients. RESULTS: Among 225 diseases, 45 had HRs > 1.5 and p < 0.0002 when comparing breast cancer patients with the general population. Diseases with highest HRs included lymphedema, radiodermatitis, and neutropenia, which are side effects of surgery, radiotherapy, and chemotherapy. Other than breast cancer, the only significantly increased cause of death was other solid cancers (HR = 1.16, 95% CI = 1.08-1.24). Two main groups of disease trajectories were identified, which suggest menopausal disorders as indicators for other solid cancers, and both neutropenia and dorsalgia as diseases and symptoms preceding death due to breast cancer. CONCLUSIONS: While an increased incidence of other diseases was found among breast cancer patients, increased mortality was only due to other solid cancers. Preventing death due to breast cancer should be a priority to prolong life in breast cancer patients, but closer surveillance of other solid cancers is also needed.

7.
JAMA Oncol ; 2019 Aug 08.
Artigo em Inglês | MEDLINE | ID: mdl-31393518

RESUMO

Importance: Patients with estrogen receptor (ER)-positive breast cancer have a long-term risk for fatal disease. However, the tumor biological factors that influence the long-term risk and the benefit associated with endocrine therapy are not well understood. Objective: To compare the long-term survival from tamoxifen therapy for patients with luminal A or luminal B tumor subtype. Design, Setting, and Participants: Secondary analysis of patients from the Stockholm Tamoxifen (STO-3) trial conducted from 1976 to 1990, which randomized postmenopausal patients with lymph node-negative breast cancer to receive adjuvant tamoxifen or no endocrine therapy. Tumor tissue sections were assessed in 2014 using immunohistochemistry and Agilent microarrays. Only patients with luminal A or B subtype tumors were evaluated. Complete long-term follow-up data up to the end of the STO-3 trial on December 31, 2012, were obtained from the Swedish National registers. Data analysis for the secondary analysis was conducted in 2017 and 2018. Interventions: Patients were randomized to receive at least 2 years of tamoxifen therapy or no endocrine therapy; patients without recurrence who reconsented were further randomized to 3 additional years of tamoxifen therapy or no endocrine therapy. Main Outcomes and Measures: Distant recurrence-free interval (DRFI) by luminal A and luminal B subtype and trial arm was assessed by Kaplan-Meier analyses and time-dependent flexible parametric models to estimate time-varying hazard ratios (HRs) that were adjusted for patient and tumor characteristics. Results: In the STO-3 treated trial arm, 183 patients had luminal A tumors and 64 patients had luminal B tumors. In the untreated arm, 153 patients had luminal A tumors and 62 had luminal B tumors. Age at diagnosis ranged from 45 to 73 years. A statistically significant difference in DRFI by trial arm was observed (log rank, P < .001 [luminal A subtype, n = 336], P = .04 [luminal B subtype, n = 126]): the 25-year DRFI for luminal A vs luminal B subtypes was 87% (95% CI, 82%-93%) vs 67% (95% CI, 56%-82%) for treated patients, and 70% (95 % CI, 62%-79%) vs 54% (95% CI, 42%-70%) for untreated patients, respectively. Patients with luminal A tumors significantly benefited from tamoxifen therapy for 15 years after diagnosis (HR, 0.57; 95% CI, 0.35-0.94), and those with luminal B tumors benefited from tamoxifen therapy for 5 years (HR, 0.38; 95% CI, 0.24-0.59). Conclusions and Relevance: Patients with luminal A subtype tumors had a long-term risk of distant metastatic disease, which was reduced by tamoxifen treatment, whereas patients with luminal B tumors had an early risk of distant metastatic disease, and tamoxifen benefit attenuated over time.

8.
J Natl Cancer Inst ; 2019 Jul 12.
Artigo em Inglês | MEDLINE | ID: mdl-31298705

RESUMO

BACKGROUND: We examined the association between annual mammographic density change (MDC) and breast cancer (BC) risk, and how annual MDC influences the association between baseline mammographic density (MD) and BC risk. METHODS: We used the KARMA cohort of Swedish women (N = 43,810) aged 30-79 years with full access to BC risk factors and mammograms. MD was measured as dense area (cm2) and percent MD using the STRATUS method. We used the contralateral mammogram for women with BC, and randomly selected a mammogram from either left or right breast for healthy women. We calculated relative area MDC between repeated examinations. Relative area MDC was categorized as decreased (>10% decrease/year), stable (no change) or increased (>10% increase/year). We used Cox proportional hazards regression to estimate the association of BC with MDC and interaction analysis to investigate how MDC modified the association between baseline MD and BC risk. All tests of statistical significance were two sided. RESULTS: In all, 563 women were diagnosed with BC. Compared to women with a decreased MD over time, no statistically significant different in BC risk was seen for women with either stable MD or increasing MD (HR = 1.01, 95% CI = 0.82 to 1.23, P = 0.90 and HR = 0.98, 95%CI= 0.80 to 1.22, P = 0.90 respectively). Categorizing baseline MD and subsequently adding MDC did not seem to influence the association between baseline MD and BC risk. CONCLUSIONS: Our results suggest that annual MDC does not influence BC risk. Furthermore, MDC does not seem to influence the association between baseline MD and BC risk.

9.
Int J Epidemiol ; 48(3): 781-794, 2019 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-31243447

RESUMO

BACKGROUND: Evidence linking breast size to breast cancer risk has been inconsistent, and its interpretation is often hampered by confounding factors such as body mass index (BMI). Here, we used linkage disequilibrium score regression and two-sample Mendelian randomization (MR) to examine the genetic associations between BMI, breast size and breast cancer risk. METHODS: Summary-level genotype data from 23andMe, Inc (breast size, n = 33 790), the Breast Cancer Association Consortium (breast cancer risk, n = 228 951) and the Genetic Investigation of ANthropometric Traits (BMI, n = 183 507) were used for our analyses. In assessing causal relationships, four complementary MR techniques [inverse variance weighted (IVW), weighted median, weighted mode and MR-Egger regression] were used to test the robustness of the results. RESULTS: The genetic correlation (rg) estimated between BMI and breast size was high (rg = 0.50, P = 3.89x10-43). All MR methods provided consistent evidence that higher genetically predicted BMI was associated with larger breast size [odds ratio (ORIVW): 2.06 (1.80-2.35), P = 1.38x10-26] and lower overall breast cancer risk [ORIVW: 0.81 (0.74-0.89), P = 9.44x10-6]. No evidence of a relationship between genetically predicted breast size and breast cancer risk was found except when using the weighted median and weighted mode methods, and only with oestrogen receptor (ER)-negative risk. There was no evidence of reverse causality in any of the analyses conducted (P > 0.050). CONCLUSION: Our findings indicate a potential positive causal association between BMI and breast size and a potential negative causal association between BMI and breast cancer risk. We found no clear evidence for a direct relationship between breast size and breast cancer risk.

10.
Eur Radiol ; 29(11): 6227-6235, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31115623

RESUMO

PURPOSE: We aimed to estimate the incremental cancer detection rate achieved by adding three-dimensional functional infrared imaging (3DIRI) to digital mammography in women with dense breasts. MATERIALS AND METHODS: In this prospective study conducted between December 2014 and April 2016, 1727 women (median age 56) with percentage volumetric breast density > 6% were recruited at routine screening mammography to undergo additional 3DIRI. The 3DIRI findings were classified as negative or positive. Women with a negative mammography but positive 3DIRI were referred to dynamic contrast-enhanced MRI, whereas all other women underwent routine follow-up based on the mammography finding. Diagnosis of breast cancer was verified by histopathologic examination. The number of women diagnosed with a malignancy formed the basis of our statistical analysis. RESULTS: Mammography detected 7 cancers in 7 women. Of 1692 women with negative mammography, 222 women (13%) had a positive 3DIRI of which 219 underwent MRI. An additional 6 cancers were identified in 5 women, increasing the diagnostic yield from 7 of 1727 (0.41%) to 12 of 1727 (0.69%). The incremental cancer detection rate associated with using 3DIRI to select women for MRI was 5 of 222 (22.5 additional cancers per 1000). CONCLUSION: The use of 3DIRI to select women for an additional MRI can result in the detection of additional cancers in women with dense breasts, but at the expense of additional false positives and considerably lower positive predictive value of the combined examinations. Additional studies are necessary to evaluate the role of 3DIRI as an adjunct to mammography. KEY POINTS: • Use of three-dimensional functional infrared imaging to select women for an MRI in addition to screening mammography has the potential to improve breast cancer detection in women with dense breasts.

11.
Breast Cancer Res ; 21(1): 68, 2019 05 22.
Artigo em Inglês | MEDLINE | ID: mdl-31118087

RESUMO

BACKGROUND: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. METHODS: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. RESULTS: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. CONCLUSIONS: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.

12.
Nat Commun ; 10(1): 1741, 2019 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-30988301

RESUMO

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.


Assuntos
Neoplasias da Mama/genética , Predisposição Genética para Doença , Feminino , Perfilação da Expressão Gênica , Estudo de Associação Genômica Ampla , Humanos , Locos de Características Quantitativas
13.
Twin Res Hum Genet ; 22(2): 99-107, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-31020942

RESUMO

The Nordic countries have comprehensive, population-based health and medical registries linkable on individually unique personal identity codes, enabling complete long-term follow-up. The aims of this study were to describe the NorTwinCan cohort established in 2010 and assess whether the cancer mortality and incidence rates among Nordic twins are similar to those in the general population. We analyzed approximately 260,000 same-sexed twins in the nationwide twin registers in Denmark, Finland, Norway and Sweden. Cancer incidence was determined using follow-up through the national cancer registries. We estimated standardized incidence (SIR) and mortality (SMR) ratios with 95% confidence intervals (CI) across country, age, period, follow-up time, sex and zygosity. More than 30,000 malignant neoplasms have occurred among the twins through 2010. Mortality rates among twins were slightly lower than in the general population (SMR 0.96; CI 95% [0.95, 0.97]), but this depends on information about zygosity. Twins have slightly lower cancer incidence rates than the general population, with SIRs of 0.97 (95% CI [0.96, 0.99]) in men and 0.96 (95% CI [0.94, 0.97]) in women. Testicular cancer occurs more often among male twins than singletons (SIR 1.15; 95% CI [1.02, 1.30]), while cancers of the kidney (SIR 0.82; 95% CI [0.76, 0.89]), lung (SIR 0.89; 95% CI [0.85, 0.92]) and colon (SIR 0.90; 95% CI [0.87, 0.94]) occur less often in twins than in the background population. Our findings indicate that the risk of cancer among twins is so similar to the general population that cancer risk factors and estimates of heritability derived from the Nordic twin registers are generalizable to the background populations.

14.
Sci Rep ; 9(1): 3527, 2019 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-30837593

RESUMO

Breast cancer patients commonly present with comorbidities which are known to influence treatment decisions and survival. We aim to examine agreement between self-reported and register-based medical records (National Patient Register [NPR]). Ascertainment of nine conditions, using individually-linked data from 64,961 women enrolled in the Swedish KARolinska MAmmography Project for Risk Prediction of Breast Cancer (KARMA) study. Agreement was assessed using observed proportion of agreement (overall agreement), expected proportion of agreement, and Cohen's Kappa statistic. Two-stage logistic regression models taking into account chance agreement were used to identify potential predictors of overall agreement. High levels of overall agreement (i.e. ≥86.6%) were observed for all conditions. Substantial agreement (Cohen's Kappa) was observed for myocardial infarction (0.74), diabetes (0.71) and stroke (0.64) between self-reported and NPR data. Moderate agreement was observed for preeclampsia (0.51) and hypertension (0.46). Fair agreement was observed for heart failure (0.40) and polycystic ovaries or ovarian cysts (0.27). For hyperlipidemia (0.14) and angina (0.10), slight agreement was observed. In most subgroups we observed negative specific agreement of >90%. There is no clear reference data source for ascertainment of conditions. Negative specific agreement between NPR and self-reported data is consistently high across all conditions.

15.
Stat Methods Med Res ; : 962280219832901, 2019 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-30854935

RESUMO

Comparisons of survival times between screen-detected and symptomatically detected breast cancer cases are subject to lead time and length biases. Whilst the existence of these biases is well known, correction procedures for these are not always clear, as are not the interpretation of these biases. In this paper we derive, based on a recently developed continuous tumour growth model, conditional lead time distributions, using information on each individual's tumour size, screening history and percent mammographic density. We show how these distributions can be used to obtain an individual-based (conditional) procedure for correcting survival comparisons. In stratified analyses, our correction procedure works markedly better than a previously used unconditional lead time correction, based on multi-state Markov modelling. In a study of postmenopausal invasive breast cancer patients, we estimate that, in large (>12 mm) tumours, the multi-state Markov model correction over-corrects five-year survival by 2-3 percentage points. The traditional view of length bias is that tumours being present in a woman's breast for a long time, due to being slow-growing, have a greater chance of being screen-detected. This gives a survival advantage for screening cases which is not due to the earlier detection by screening. We use simulated data to share the new insight that, not only the tumour growth rate but also the symptomatic tumour size will affect the sampling procedure, and thus be a part of the length bias through any link between tumour size and survival. We explain how this has a bearing on how observable breast cancer-specific survival curves should be interpreted. We also propose an approach for correcting survival comparisons for the length bias.

16.
Breast Cancer Res ; 21(1): 34, 2019 02 28.
Artigo em Inglês | MEDLINE | ID: mdl-30819233

RESUMO

BACKGROUND: Use of cyclin D1 (CCND1) gene amplification as a breast cancer biomarker has been hampered by conflicting assessments of the relationship between cyclin D1 protein levels and patient survival. Here, we aimed to clarify its prognostic and treatment predictive potential through comprehensive long-term survival analyses. METHODS: CCND1 amplification was assessed using SNP arrays from two cohorts of 1965 and 340 patients with matching gene expression array and clinical follow-up data of over 15 years. Kaplan-Meier and multivariable Cox regression analyses were used to determine survival differences between CCND1 amplified vs. non-amplified tumours in clinically relevant patient sets, within PAM50 subtypes and within treatment-specific subgroups. Boxplots and differential gene expression analyses were performed to assess differences between amplified vs. non-amplified tumours within PAM50 subtypes. RESULTS: When combining both cohorts, worse survival was found for patients with CCND1-amplified tumours in luminal A (HR = 1.68; 95% CI, 1.15-2.46), luminal B (1.37; 1.01-1.86) and ER+/LN-/HER2- (1.66; 1.14-2.41) subgroups. In gene expression analysis, CCND1-amplified luminal A tumours showed increased proliferation (P < 0.001) and decreased progesterone (P = 0.002) levels along with a large overlap in differentially expressed genes when comparing luminal A and B-amplified vs. non-amplified tumours. CONCLUSIONS: Our results indicate that CCND1 amplification is associated with worse 15-year survival in ER+/LN-/HER2-, luminal A and luminal B patients. Moreover, luminal A CCND1-amplified tumours display gene expression changes consistent with a more aggressive phenotype. These novel findings highlight the potential of CCND1 to identify patients that could benefit from long-term treatment strategies.


Assuntos
Biomarcadores Tumorais/genética , Neoplasias da Mama/genética , Ciclina D1/genética , Amplificação de Genes/genética , Adulto , Neoplasias da Mama/mortalidade , Neoplasias da Mama/terapia , Feminino , Seguimentos , Testes Genéticos/métodos , Humanos , Linfonodos/patologia , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Prognóstico , Receptor ErbB-2/metabolismo , Receptores Estrogênicos/metabolismo , Estudos Retrospectivos , Análise de Sobrevida
17.
Med Phys ; 46(4): 1938-1946, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30801718

RESUMO

PURPOSE: We explore using the number of potential microcalcification clusters detected in for-presentation mammographic images (the images which are typically accessible to large epidemiological studies) a marker of short-term breast cancer risk. METHODS: We designed a three-step algorithm for detecting potential microcalcification clusters in for-presentation digital mammograms. We studied association with short-term breast cancer risk using a nested case control design, with a mammography screening cohort as a source population. In total, 373 incident breast cancer cases (diagnosed at least 3 months after a negative screen at study entry) and 1466 matched controls were included in our study. Conditional logistic regression Wald tests were used to test for association with the presence of microcalcifications at study entry. We compared results of these analyses to those obtained using a Computer-aided Diagnosis (CAD) software (VuComp) on corresponding for-processing images (images which are used clinically, but typically not saved). RESULTS: We found a moderate agreement between our measure of potential microcalcification clusters on for-presentation images and a CAD measure on for-processing images. Similar evidence of association with short-term breast cancer risk was found (P =  1 × 10 - 10 and P =  9 × 10 - 09 , for our approach on for-presentation images and for the CAD measure on for-processing images, respectively) and interestingly both measures contributed independently to association with a short-term risk (P =  9 × 10 - 03 for the CAD measure, adjusted for our proposed method and P =  1 × 10 - 04 for our proposed method, adjusted for the CAD measure). CONCLUSION: Meaningful measurement of potential microcalcifications, in the context of short-term breast cancer risk assessment, is feasible for for-presentation images across a range of vendors. Our algorithm for for-presentation images performs similarly to a CAD algorithm on for-processing images, hence our algorithm can be a useful tool for research on microcalcifications and their role on breast cancer risk, based on large-scale epidemiological studies with access to for-presentation images.


Assuntos
Neoplasias da Mama/patologia , Calcinose/patologia , Mamografia/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/etiologia , Calcinose/complicações , Calcinose/diagnóstico por imagem , Feminino , Humanos , Fatores de Risco , Software
18.
BMC Med ; 17(1): 24, 2019 01 31.
Artigo em Inglês | MEDLINE | ID: mdl-30700300

RESUMO

BACKGROUND: Breast cancer patients who have not previously attended mammography screening may be more likely to discontinue adjuvant hormone therapy and therefore have a worse disease prognosis. METHODS: We conducted a population-based cohort study using data from Stockholm Mammography Screening Program, Stockholm-Gotland Breast Cancer Register, Swedish Prescribed Drug Register, and Swedish Cause of Death Register. Women in Stockholm who were diagnosed with breast cancer between 2001 and 2008 were followed until December 31, 2015. Non-participants of mammography screening were defined as women who, prior to their breast cancer diagnosis, were invited for mammography screening but did not attend. RESULTS: Of the 5098 eligible breast cancer patients, 4156 were defined as screening participants and 942 as non-participants. Compared with mammography screening participants, non-participants were more likely to discontinue adjuvant hormone therapy, with an adjusted hazard ratio (HR) of 1.30 (95% CIs, 1.11 to 1.53). Breast cancer patients not participating in mammography screening were also more likely to have worse disease-free survival, even after adjusting for tumor characteristics and other covariates (adjusted HR 1.22 (95% CIs, 1.05 to 1.42 for a breast cancer event). CONCLUSIONS: Targeted interventions to prevent discontinuation of adjuvant hormone therapy are needed to improve breast cancer outcomes among women not attending mammography screening.


Assuntos
Neoplasias da Mama/tratamento farmacológico , Mamografia/estatística & dados numéricos , Adesão à Medicação/estatística & dados numéricos , Adulto , Idoso , Neoplasias da Mama/diagnóstico , Estudos de Coortes , Intervalo Livre de Doença , Detecção Precoce de Câncer/estatística & dados numéricos , Feminino , Humanos , Pessoa de Meia-Idade , Modelos de Riscos Proporcionais , Suécia
19.
Breast Cancer Res ; 21(1): 8, 2019 01 22.
Artigo em Inglês | MEDLINE | ID: mdl-30670066

RESUMO

BACKGROUND: High mammographic density is associated with breast cancer and with delayed detection. We have examined whether localized density, at the site of the subsequent cancer, is independently associated with being diagnosed with a large-sized or interval breast cancer. METHODS: Within a prospective cohort of 63,130 women, we examined 891 women who were diagnosed with incident breast cancer. For 386 women, retrospective localized density assessment was possible. The main outcomes were interval cancer vs. screen-detected cancer and large (> 2 cm) vs. small cancer. In negative screening mammograms, overall and localized density were classified reflecting the BI-RADS standard. Density concordance probabilities were estimated through multinomial regression. The associations between localized density and the two outcomes were modeled through logistic regression, adjusted for overall density, age, body mass index, and other characteristics. RESULTS: The probabilities of concordant localized density were 0.35, 0.60, 0.38, and 0.32 for overall categories "A," "B," "C," and "D." Overall density was associated with large cancer, comparing density category D to A with OR 4.6 (95%CI 1.8-11.6) and with interval cancer OR 31.5 (95%CI 10.9-92) among all women. Localized density was associated with large cancer at diagnosis with OR 11.8 (95%CI 2.7-51.8) among all women and associated with first-year interval cancer with OR 6.4 (0.7 to 58.7) with a significant linear trend p = 0.027. CONCLUSIONS: Overall density often misrepresents localized density at the site where cancer subsequently arises. High localized density is associated with interval cancer and with large cancer. Our findings support the continued effort to develop and examine computer-based measures of localized density for use in personalized breast cancer screening.


Assuntos
Densidade da Mama , Neoplasias da Mama/diagnóstico por imagem , Diagnóstico Tardio/prevenção & controle , Detecção Precoce de Câncer/métodos , Programas de Rastreamento/métodos , Mama/diagnóstico por imagem , Mama/patologia , Neoplasias da Mama/patologia , Estudos de Casos e Controles , Reações Falso-Negativas , Feminino , Humanos , Processamento de Imagem Assistida por Computador/métodos , Mamografia/métodos , Pessoa de Meia-Idade , Estudos Prospectivos , Estudos Retrospectivos , Fatores de Tempo , Carga Tumoral
20.
Stat Methods Med Res ; 28(12): 3822-3842, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30606087

RESUMO

Continuous growth models show great potential for analysing cancer screening data. We recently described such a model for studying breast cancer tumour growth based on modelling tumour size at diagnosis, as a function of screening history, detection mode, and relevant patient characteristics. In this article, we describe how the approach can be extended to jointly model tumour size and number of lymph node metastases at diagnosis. We propose a new class of lymph node spread models which are biologically motivated and describe how they can be extended to incorporate random effects to allow for heterogeneity in underlying rates of spread. Our final model provides a dramatically better fit to empirical data on 1860 incident breast cancer cases than models in current use. We validate our lymph node spread model on an independent data set consisting of 3961 women diagnosed with invasive breast cancer.

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