Sense of coherence (SoC) is the origin of health according to Antonovsky. The link between SoC and risk of cancer has however rarely been assessed. We performed a cohort study of 46,436 women from ...the Karolinska Mammography Project for Risk Prediction of Breast Cancer (Karma). Participants answered a SoC-13 questionnaire at recruitment to Karma and were subsequently followed up for incident breast cancer. Multivariate Cox models were used to assess the hazard ratios (HRs) of breast cancer in relation to SoC. We identified 771 incident cases of breast cancer during follow-up (median time: 5.2 years). No association was found between SoC, either as a categorical (strong vs. weak SoC, HR: 1.08, 95% CI: 0.90-1.29) or continuous (HR: 1.08; 95% CI: 1.00-1.17 per standard deviation increase of SoC) variable, and risk of breast cancer. In summary, we found little evidence to support an association between SoC and risk of breast cancer.
Preeclampsia is frequently linked to reduced breast cancer risk. However, little is known regarding the underlying genetic association and the association between preeclampsia and mammographic ...density.
This study estimates the incidence rate ratios (IRRs) of breast cancer in patients with preeclampsia, when compared to women without preeclampsia, using Poisson regression models in two cohorts of pregnant women: a Swedish nationwide cohort (n = 1,337,934, 1973-2011) and the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA, n = 55,044, 1958-2015). To identify the genetic association between preeclampsia and breast cancer, we used logistic regression models to calculate the odds ratios (ORs) of preeclampsia in sisters of breast cancer patients, and in women with different percentiles of breast cancer polygenic risk scores (PRS). Linear regression models were used to estimate the mammographic density by preeclampsia status in the KARMA cohort.
A decreased risk of breast cancer was observed among patients with preeclampsia in both the nationwide (IRR = 0.90, 95% CI = 0.85; 0.96) and KARMA cohorts (IRR = 0.75, 95% CI = 0.61; 0.93). Women with high breast cancer PRS and sisters of breast cancer patients had a lower risk of preeclampsia (OR = 0.89, 95% CI = 0.83; 0.96). Mammographic density was lower in women with preeclampsia compared to women without preeclampsia (-2.04%, 95% CI = -2.65; -1.43). Additionally, among sisters in the KARMA cohort (N = 3500), density was lower in sisters of patients with preeclampsia compared to sisters of women without preeclampsia (-2.76%, 95% CI = -4.96; -0.56).
Preeclampsia is associated with reduced risk of breast cancer and mammographic density. Inherited factors contribute to this inverse association.
Mammographic percentage density is an established and important risk factor for breast cancer. In this paper, we investigate the role of the spatial organisation of (dense vs. fatty) regions of the ...breast defined from mammographic images in terms of breast cancer risk.
We present a novel approach that provides a thorough description of the spatial organisation of different types of tissue in the breast. Each mammogram is first segmented into four regions (fatty, semi-fatty, semi-dense and dense tissue). The spatial relations between each pair of regions is described using so-called forces histograms (FHs) and summarised using functional principal component analysis. In our main analysis, association with case-control status is assessed using a Swedish population-based case-control study (1,170 cases and 1283 controls), for which digitised mammograms were available. We also carried out a small validation study based on digital images.
For our main analysis, we obtained a global p value of 2×10
indicating a significant association between the spatial relations of the four segmented regions and breast cancer status after adjustment for percentage density and other important breast cancer risk factors. Our (spatial relations) score had a per standard deviation odds ratio 1.29, after accounting for overfitting (percentage density had a per standard deviation odds ratio of 1.34). The spatial relations between the fatty and semi-fatty tissue and the spatial relations between the fatty and dense tissue were the most significant. The spatial relations between the fatty and semi-fatty tissue were associated with parity and age at first birth (p=6×10
). Using digital images, we were able to verify that the same characteristics of tissue organisation can be identified and we validated the association for the spatial relations between the fatty and semi-fatty tissue.
Our findings are consistent with the notion that fibroglandular and adipose tissue plays a role in breast cancer risk and, more specifically, they suggest that fatty tissue in the lower quadrants and the absence of density in the retromammary space, as shown in mediolateral oblique images, are protective against breast cancer.
Breast cancer prognosis is strongly associated with tumor size at diagnosis. We aimed to identify factors associated with diagnosis of large (> 2 cm) compared to small tumors, and to examine ...implications for long-term prognosis.
We examined 2012 women with invasive breast cancer, of whom 1466 had screen-detected and 546 interval cancers that were incident between 2001 and 2008 in a population-based screening cohort, and followed them to 31 December 2015. Body mass index (BMI) was ascertained after diagnosis at the time of study enrollment during 2009. PD was measured based on the contralateral mammogram within 3 years before diagnosis. We used multiple logistic regression modeling to examine the association between tumor size and body mass index (BMI), mammographic percent density (PD), or hormonal and genetic risk factors. Associations between the identified risk factors and, in turn, the outcomes of local recurrence, distant metastases, and death (153 events in total) in women with breast cancer were examined using Cox regression. Analyses were carried out according to mode of detection.
BMI and PD were the only factors associated with tumor size at diagnosis. For BMI (≥25 vs. < 25 kg/m
), the multiple adjusted odds ratios (OR) were 1.37 (95% CI 1.02-1.83) and 2.12 (95% CI 1.41-3.18), for screen-detected and interval cancers, respectively. For PD (≥20 vs. < 20%), the corresponding ORs were 1.72 (95% CI 1.29-2.30) and 0.60 (95% CI 0.40-0.90). Among women with interval cancers, those with high BMI had worse prognosis than women with low BMI (hazard ratio 1.70; 95% CI 1.04-2.77), but PD was not associated with the hazard rate. Among screen-detected cancers, neither BMI nor PD was associated with the hazard rate.
In conclusion, high BMI was associated with the risk of having a tumor larger than 2 cm at diagnosis. Among women with interval cancer, high BMI was associated with worse prognosis. We believe that women with high BMI should be especially encouraged to attend screening.
Increased breast density decreases mammographic sensitivity due to masking of cancers by dense tissue. Tamoxifen exposure reduces mammographic density and, therefore, should improve screening ...sensitivity. We modelled how low-dose tamoxifen exposure could be used to increase mammographic sensitivity. Mammographic sensitivity was calculated using the KARMA prospective screening cohort. Two models were fitted to estimate screening sensitivity and detected tumor size based on baseline mammographic density. BI-RADS-dependent sensitivity was estimated. The results of the 2.5 mg tamoxifen arm of the KARISMA trial were used to define expected changes in mammographic density after six months exposure and to predict changes in mammographic screening sensitivity and detected tumor size. Rates of interval cancers and detection of invasive tumors were estimated for women with mammographic density relative decreases by 10-50%. In all, 517 cancers in premenopausal women were diagnosed in KARMA: 287 (56%) screen-detected and 230 (44%) interval cancers. Screening sensitivities prior to tamoxifen, were 76%, 69%, 53%, and 46% for BI-RADS density categories A, B, C, and D, respectively. After exposure to tamoxifen, modelled screening sensitivities were estimated to increase by 0% (
= 0.35), 2% (
< 0.01), 5% (
< 0.01), and 5% (
< 0.01), respectively. An estimated relative density decrease by ≥20% resulted in an estimated reduction of interval cancers by 24% (
< 0.01) and reduction in tumors >20 mm at detection by 4% (
< 0.01). Low-dose tamoxifen has the potential to increase mammographic screening sensitivity and thereby reduce the proportion of interval cancers and larger screen-detected cancers.
An increasing number of women are evaluated for potential breast cancer and may experience mental distress during evaluation. We aim to assess the risks of psychiatric disorders and cardiovascular ...diseases during the diagnostic workup of potential breast cancer.
All women with a new diagnosis of unspecified lump in breast (N = 15,714), benign tumor or breast cancer in situ (N = 4435), or breast cancer (N = 8512) during 2005-2014 in Skåne, Sweden, were considered as exposed to a breast diagnostic workup. We used multivariable Poisson regression to compare rates of psychiatric disorders and cardiovascular diseases during the 6 weeks before the date of diagnosis of these women with the corresponding rates of women not undergoing such workup. The commonest waiting time for breast cancer patients was 6 weeks during the study period. A within-individual comparison was performed to control for potential unmeasured time-stationary confounders.
Compared to the reference, we found a higher rate of psychiatric disorders during the 6 weeks before diagnosis of benign tumor or breast cancer in situ (incidence rate ratio IRR, 1.3; 95% confidence interval CI, 1.1 to 1.5) and breast cancer (IRR, 1.4; 95% CI, 1.2 to 1.6). A higher rate was also noted for cardiovascular diseases (IRR, 1.3; 95% CI, 1.1 to 1.6 for benign tumor or breast cancer in situ, and IRR, 1.9; 95% CI, 1.8 to 2.0 for breast cancer). The rate increases for breast cancer were greater comparing a diagnostic workup due to symptoms to a workup due to screening. Little rate increase of neither psychiatric disorders nor cardiovascular diseases was noted during the 6 weeks before the diagnosis of unspecified lump in breast. The within-individual comparison largely confirmed these findings.
Women with benign and malignant breast tumor had increased rates of psychiatric disorders and cardiovascular diseases during the waiting for a final diagnosis.
A link has been proposed between the use of nonsteroidal anti-inflammatory drugs (NSAIDs) and the risk of breast cancer. There is, however, insufficient data regarding the subtype and stage of breast ...cancer, and few studies have assessed the interaction between the use of NSAIDs and breast density or previous breast disorders. There is also a lack of data from population-based studies. We first conducted a nested case-control study within the general female population of Sweden, including 56,480 women with newly diagnosed breast cancer during 2006-2015 and five breast cancer-free women per case as controls, to assess the association of NSAID use with the risk of incident breast cancer, focusing on subtype and stage of breast cancer as well as the interaction between NSAID use and previous breast disorders. We then used the Karolinska Mammography Project for Risk Prediction of Breast Cancer (Karma) cohort to assess the interaction between NSAID use and breast density in relation to the risk of breast cancer. Conditional logistic regression was used to estimate the hazard ratio (HR) and a 95% confidence interval (CI) was used for breast cancer in relation to the use of aspirin and non-aspirin NSAIDs. In the nested case-control study of the general population, exclusive use of aspirin was not associated with the risk of breast cancer, whereas exclusive use of non-aspirin NSAIDs was associated with a modestly higher risk of stage 0-2 breast cancer (HR: 1.05; 95% CI: 1.02-1.08) but a lower risk of stage 3-4 breast cancer (HR 0.80; 95% CI: 0.73-0.88). There was also a statistically significant interaction between the exclusive use of NSAIDs and previous breast disorders (
for interaction: <0.001). In the analysis of Karma participants, the exclusive use of non-aspirin NSAIDs was associated with a lower risk of breast cancer among women with a breast dense area of >40 cm
(HR: 0.72; 95% CI: 0.59-0.89). However, the possibility of finding this by chance cannot be ruled out. Overall, we did not find strong evidence to support an association between the use of NSAIDs and the risk of breast cancer.
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.
Mammographic density is a strong risk factor for breast cancer. Apart from hormone replacement therapy (HRT), little is known about lifestyle factors that influence breast density.
We examined the ...effect of smoking, alcohol and physical activity on mammographic density in a population-based sample of postmenopausal women without breast cancer. Lifestyle factors were assessed by a questionnaire and percentage and area measures of mammographic density were measured using computer-assisted software. General linear models were used to assess the association between lifestyle factors and mammographic density and effect modification by body mass index (BMI) and HRT was studied.
Overall, alcohol intake was positively associated with percent mammographic density (P trend = 0.07). This association was modified by HRT use (P interaction = 0.06): increasing alcohol intake was associated with increasing percent density in current HRT users (P trend = 0.01) but not in non-current users (P trend = 0.82). A similar interaction between alcohol and HRT was found for the absolute dense area, with a positive association being present in current HRT users only (P interaction = 0.04). No differences in mammographic density were observed across categories of smoking and physical activity, neither overall nor in stratified analyses by BMI and HRT use.
Increasing alcohol intake is associated with an increase in mammography density, whereas smoking and physical activity do not seem to influence density. The observed interaction between alcohol and HRT may pose an opportunity for HRT users to lower their mammographic density and breast cancer risk.
Mammographic density, the white radiolucent part of a mammogram, is a marker of breast cancer risk and mammographic sensitivity. There are several means of measuring mammographic density, among which ...are area-based and volumetric-based approaches. Current volumetric methods use only unprocessed, raw mammograms, which is a problematic restriction since such raw mammograms are normally not stored. We describe fully automated methods for measuring both area and volumetric mammographic density from processed images.
The data set used in this study comprises raw and processed images of the same view from 1462 women. We developed two algorithms for processed images, an automated area-based approach (CASAM-Area) and a volumetric-based approach (CASAM-Vol). The latter method was based on training a random forest prediction model with image statistical features as predictors, against a volumetric measure, Volpara, for corresponding raw images. We contrast the three methods, CASAM-Area, CASAM-Vol and Volpara directly and in terms of association with breast cancer risk and a known genetic variant for mammographic density and breast cancer, rs10995190 in the gene ZNF365. Associations with breast cancer risk were evaluated using images from 47 breast cancer cases and 1011 control subjects. The genetic association analysis was based on 1011 control subjects.
All three measures of mammographic density were associated with breast cancer risk and rs10995190 (p<0.025 for breast cancer risk and p<1 × 10(-6) for rs10995190). After adjusting for one of the measures there remained little or no evidence of residual association with the remaining density measures (p>0.10 for risk, p>0.03 for rs10995190).
Our results show that it is possible to obtain reliable automated measures of volumetric and area mammographic density from processed digital images. Area and volumetric measures of density on processed digital images performed similar in terms of risk and genetic association.
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