Ursin, Giske

Little is known about how health-related quality of life (HRQoL) in breast cancer cases differed from that of controls during and after the COVID-19 pandemic. This study used data from an ongoing, nationwide HRQoL survey of 4279 newly diagnosed breast cancer cases and 2911 controls to investigate how breast cancer patients fared during different phases of the pandemic compared to controls. Responders during 2020–2022 were categorized into three COVID-19-related phases: the social restrictions phase, the high infection rate phase, and the post-pandemic phase. Across phases, breast cancer cases had significantly worse scores in most HRQoL domains compared to controls. Apart from slightly more insomnia in the high infection rate phase for both cases and controls, and better social functioning for young cases in the post-COVID-19 phase, the case-control differences in HRQoL remained consistent across phases. When the phases were assessed as one period, young women and those living with children <18 years of age fared the worst among breast cancer cases, while single women fared the worst among controls. In contrast, controls living with children <18 years of age exhibited better HRQoL than controls without children. In summary, women with breast cancer did not appear to fare differently than controls in terms of HRQoL across COVID-19 phases. However, breast cancer cases with young children fared worse in their HRQoL than other breast cancer cases.

Abstract Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P &lt; 10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. Cancer Res; 75(12); 2457–67. ©2015 AACR.

Abstract Purpose: Mammographic breast density (MBD) is decreased by tamoxifen, but the effect of aromatase inhibitors is less clear. Experimental Design: We enrolled early-stage postmenopausal patients with breast cancer initiating adjuvant aromatase inhibitor therapy and ascertained mammograms before and at an average 10 months of aromatase inhibitor therapy. We matched cases to healthy postmenopausal women (controls) from a large mammography screening cohort on age, baseline body mass index, baseline MBD, and interval between mammograms. We estimated change in MBD using a computer-assisted thresholding program (Cumulus) and compared differences between cases and matched controls. Results: In predominantly White women (96%), we found 14% of the 387 eligible cases had a MBD reduction of at least 5% after an average of 10 months of aromatase inhibitor therapy. MBD reductions were associated with higher baseline MBD, aromatase inhibitor use for more than 12 months, and prior postmenopausal hormone use. Comparing each case with her matched control, there was no evidence of an association of change in MBD with aromatase inhibitor therapy [median case–control difference among 369 pairs was −0.1% (10th and 90th percentile: −5.9%, 5.2%) P = 0.51]. Case–control differences were similar by type of aromatase inhibitor (P's 0.41 and 0.56); prior use of postmenopausal hormones (P = 0.85); baseline MBD (P = 0.55); and length of aromatase inhibitor therapy (P = 0.08). Conclusions: In postmenopausal women treated with aromatase inhibitors, 14% of cases had a MBD reduction of more than 5%, but these decreases did not differ from matched controls. These data suggest that MBD is not a clinically useful biomarker for predicting the value of aromatase inhibitor therapy in White postmenopausal women. Clin Cancer Res; 19(8); 2144–53. ©2013 AACR.

Abstract Some studies show that childbearing at older age is associated with lower risk of endometrial cancer, but whether the association is independent of number of children or other factors still requires clarification. We pooled individual-level data from epidemiologic studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Data on age at last birth and/or last pregnancy were available from 14 studies: 11 case-control studies and 3 cohort studies; the latter were analyzed using a nested case-control design. A total of 9,613 endometrial cancer cases and 17,112 controls were included in the analysis. The majority of women were White (82%) and older than 55 years (69%). We estimated the effects of age at last birth using data from 12 studies and age at last pregnancy using data from 10 studies on the risk of endometrial cancer by calculating odds ratios (OR) and 95% confidence intervals (95% CI) using logistic regression models. Potential confounders included in the analysis were race, body mass index, parity, age at menarche, age at first birth, oral contraceptive use, postmenopausal hormone use, smoking status, and report of diabetes. After adjusting for potential confounders, a reduction in endometrial cancer risk was observed in women with increasing age at last birth (P trend &lt;0.0001) and age at last pregnancy (P trend &lt;0.0001). The OR per five-year increase in age at last birth and age at last pregnancy was 0.90 (95%CI: 0.86, 0.94) and 0.91 (95% CI: 0.87, 0.95), respectively. Women who had their last child at an age &gt;40 years were at a 34% decreased risk compared with women who had their last child at an age &lt;25 years (95% CI: 0.52, 0.82). Compared to women with age at last pregnancy &lt;25 years, those with age at last pregnancy &gt;40 years had a 30% decreased risk of endometrial cancer (95%CI: 0.57, 0.86). Inverse associations were observed for Whites and Asians in race-specific analysis and also in analysis restricted to women with at least 2 births. In this large pooled analysis, we show that late age at last birth or last pregnancy is a strong and independent protective factor for endometrial cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1900. doi:10.1158/1538-7445.AM2011-1900

Abstract Background. Breast density assessed from mammography is a strong predictor of breast cancer risk, but the strength of the association may vary with adiposity. To examine effect modification by adiposity, we combined data from four case-control studies on breast density that represented an ethnically diverse population with a wide variation in level of adiposity as measured by body mass index (BMI, kg/m2). Methods. We combined data from four case-control studies representing different locations: California, Hawaii and Minnesota in the United States, and Gifu in Japan. All studies included incident breast cancer cases diagnosed between 1994 and 2002 and matched controls representing the underlying case population. One mammographic image per subject was selected, specifically the mammogram at diagnosis for the studies from California, Minnesota, and Japan and the closest prediagnostic mammogram for Hawaii. Percent density was measured by one reader, who was blinded to case status, using a computer-assisted method. Self-reported anthropometric measures were used to classify women as normal, overweight, and obese according to ethnic-specific BMI cut points (&lt;23, 23-27.4, and ≥27.5 for Asian women and &lt;25, 25-29.9, and ≥30 for other ethnic groups). Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) and to evaluate interactions using the likelihood ratio while adjusting for potential confounders, including age and ethnicity. Heterogeneity across studies was marginally significant as assessed by examining density-by-study interaction (P = 0.09) and, therefore, we also adjusted for study-site. Results. The study included 1,699 cases and 2,422 controls of diverse ethnicity: 45% Caucasian, 40% Asian, 9% African-American, and 7% Other. Of these women, we classified 34% as overweight and19% as obese. Age-adjusted mean percent density was significantly greater for cases than for controls: 31.7% versus 28.9%, respectively (P &lt; 0.001). BMI was inversely associated with breast density; the estimated age-adjusted mean percent density was 36.5%, 26.8%, and 19.3% for normal, overweight, and obese, respectively (Ptrend &lt; 0.001). The overall OR for a 10% higher percent density was 1.15 (95% CI: 1.05, 1.18) with higher estimates in overweight (OR: 1.19, 95% CI: 1.09, 1.29) and obese (OR: 1.25, 95% CI: 1.11, 1.41) than normal BMI (OR: 1.11, 95% CI: 1.05, 1.18). The effect modification by BMI was statistically significant (Pinteraction = 0.01). Conclusions. Our findings confirm that the elevated risk of breast cancer associated with breast density differs by level of adiposity, with a higher risk for overweight and obese than normal BMI. Further research is needed to understand the underlying biological reasons for these noted differences in association by adiposity. Citation Information: Cancer Prev Res 2010;3(12 Suppl):B25.