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Sökning: WFRF:(Rosner Bernard A.)

  • Resultat 1-7 av 7
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1.
  • Arndt, D. S., et al. (författare)
  • STATE OF THE CLIMATE IN 2017
  • 2018
  • Ingår i: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 99:8, s. S1-S310
  • Forskningsöversikt (refereegranskat)
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2.
  • Hendrickson, Sara J., et al. (författare)
  • Plasma Carotenoid- and Retinol-Weighted Multi-SNP Scores and Risk of Breast Cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
  • 2013
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia, PA, USA : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 22:5, s. 927-936
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Dietary and circulating carotenoids have been inversely associated with breast cancer risk, but observed associations may be due to confounding. Single-nucleotide polymorphisms (SNPs) in beta-carotene 15,15'-monooxygenase 1 (BCMO1), a gene encoding the enzyme involved in the first step of synthesizing vitamin A from dietary carotenoids, have been associated with circulating carotenoid concentrations and may serve as unconfounded surrogates for those biomarkers. We determined associations between variants in BCMO1 and breast cancer risk in a large cohort consortium. Methods: We used unconditional logistic regression to test four SNPs in BCMO1 for associations with breast cancer risk in 9,226 cases and 10,420 controls from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also tested weighted multi-SNP scores composed of the two SNPs with strong, confirmed associations with circulating carotenoid concentrations. Results: Neither the individual SNPs nor the weighted multi-SNP scores were associated with breast cancer risk [OR (95% confidence interval) comparing extreme quintiles of weighted multi-SNP scores = 1.04 (0.94-1.16) for beta-carotene, 1.08 (0.98-1.20) for alpha-carotene, 1.04 (0.94-1.16) for beta-cryptoxanthin, 0.95 (0.87-1.05) for lutein/zeaxanthin, and 0.92 (0.83-1.02) for retinol]. Furthermore, no associations were observed when stratifying by estrogen receptor status, but power was limited. Conclusions: Our results do not support an association between SNPs associated with circulating carotenoid concentrations and breast cancer risk. Impact: Future studies will need additional genetic surrogates and/or sample sizes at least three times larger to contribute evidence of a causal link between carotenoids and breast cancer. (C) 2013 AACR.
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3.
  • Lucht, Sarah A., et al. (författare)
  • Circulating lipids, mammographic density, and risk of breast cancer in the Nurses’ Health Study and Nurses’ Health Study II
  • 2019
  • Ingår i: Cancer Causes and Control. - : Springer Science and Business Media LLC. - 0957-5243 .- 1573-7225. ; 30:9, s. 943-953
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose: Epidemiologic evidence supports an association between high mammographic density and increased breast cancer risk yet etiologic mechanisms remain largely unknown. Mixed evidence exists as to whether circulating lipid levels influence mammographic density and breast cancer risk. Therefore, we examined these associations in the Nurses’ Health Study (NHS) and Nurses’ Health Study II (NHSII), two large prospective cohorts with information on PMD and circulating lipid measures, long follow-up, and breast cancer risk factor and outcome data. Methods: We conducted a nested case–control study among women in the NHS and NHSII. Percent mammographic density (PMD) was measured using Cumulus software, a computer-assisted method, on digitized film mammograms. Cross-sectional associations between circulating lipids [total cholesterol (n = 1,502), high-density lipoprotein (HDL-C; n = 579), and triglycerides (n = 655)] and PMD were evaluated among controls. All analyses were stratified by menopausal status at time of mammogram. Relative risks for breast cancer by lipid and PMD measures were estimated among postmenopausal women in the full nested case–control study (cases/controls for cholesterol, HDL-C, and triglycerides were 937/975, 416/449, and 506/537, respectively). Results: There were no significant associations between circulating lipid levels and PMD among healthy women, irrespective of menopausal status. The association between PMD and breast cancer risk among postmenopausal women was not modified by circulating lipid levels (p interaction = 0.83, 0.80, and 0.34 for total cholesterol, HDL-C, and triglycerides, respectively). Conclusion: Overall, no association was observed between lipid levels and PMD, and there was no evidence that lipid levels modified the association between PMD and breast cancer risk.
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4.
  • Gaudet, Mia M, et al. (författare)
  • Pooled Analysis of Nine Cohorts Reveals Breast Cancer Risk Factors by Tumor Molecular Subtype.
  • 2018
  • Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 78:20, s. 6011-6021
  • Tidskriftsartikel (refereegranskat)abstract
    • Various subtypes of breast cancer defined by estrogen receptor (ER), progesterone receptor (PR), and HER2 exhibit etiologic differences in reproductive factors, but associations with other risk factors are inconsistent. To clarify etiologic heterogeneity, we pooled data from nine cohort studies. Multivariable, joint Cox proportional hazards regression models were used to estimate HRs and 95% confidence intervals (CI) for molecular subtypes. Of 606,025 women, 11,741 invasive breast cancers with complete tissue markers developed during follow-up: 8,700 luminal A–like (ER+ or PR+/HER2−), 1,368 luminal B–like (ER+ or PR+/HER2+), 521 HER2-enriched (ER−/PR−/HER2+), and 1,152 triple-negative (ER−/PR−/HER2−) disease. Ever parous compared with never was associated with lower risk of luminal A–like (HR, 0.78; 95% CI, 0.73–0.83) and luminal B–like (HR, 0.74; 95% CI, 0.64–0.87) as well as a higher risk of triple-negative disease (HR, 1.23; 95% CI, 1.02–1.50; P value for overall tumor heterogeneity < 0.001). Direct associations with luminal-like, but not HER2-enriched or triple-negative, tumors were found for age at first birth, years between menarche and first birth, and age at menopause (P value for overall tumor heterogeneity < 0.001). Age-specific associations with baseline body mass index differed for risk of luminal A–like and triple-negative breast cancer (P value for tumor heterogeneity = 0.02). These results provide the strongest evidence for etiologic heterogeneity of breast cancer to date from prospective studies.Significance: These findings comprise the largest study of prospective data to date and contribute to the accumulating evidence that etiological heterogeneity exists in breast carcinogenesis. Cancer Res; 78(20); 6011–21. ©2018 AACR..
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5.
  • Cao, Yin, et al. (författare)
  • Insulin-like growth factor pathway genetic polymorphisms, circulating IGF1 and IGFBP3, and prostate cancer survival
  • 2014
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 106:5
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: The insulin-like growth factor (IGF) signaling pathway has been implicated in prostate cancer (PCa) initiation, but its role in progression remains unknown.METHODS: Among 5887 PCa patients (704 PCa deaths) of European ancestry from seven cohorts in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium, we conducted Cox kernel machine pathway analysis to evaluate whether 530 tagging single nucleotide polymorphisms (SNPs) in 26 IGF pathway-related genes were collectively associated with PCa mortality. We also conducted SNP-specific analysis using stratified Cox models adjusting for multiple testing. In 2424 patients (313 PCa deaths), we evaluated the association of prediagnostic circulating IGF1 and IGFBP3 levels and PCa mortality. All statistical tests were two-sided.RESULTS: The IGF signaling pathway was associated with PCa mortality (P = .03), and IGF2-AS and SSTR2 were the main contributors (both P = .04). In SNP-specific analysis, 36 SNPs were associated with PCa mortality with P-trend less than .05, but only three SNPs in the IGF2-AS remained statistically significant after gene-based corrections. Two were in linkage disequilibrium (r(2) = 1 for rs1004446 and rs3741211), whereas the third, rs4366464, was independent (r(2) = 0.03). The hazard ratios (HRs) per each additional risk allele were 1.19 (95% confidence interval [CI] = 1.06 to 1.34; P-trend = .003) for rs3741211 and 1.44 (95% CI = 1.20 to 1.73; P-trend < .001) for rs4366464. rs4366464 remained statistically significant after correction for all SNPs (P-trend.corr = .04). Prediagnostic IGF1 (HRhighest (vs lowest quartile) = 0.71; 95% CI = 0.48 to 1.04) and IGFBP3 (HR = 0.93; 95% Cl = 0.65 to 1.34) levels were not associated with PCa mortality.CONCLUSIONS: The IGF signaling pathway, primarily IGF2-AS and SSTR2 genes, may be important in PCa survival.
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6.
  • Sasamoto, Naoko, et al. (författare)
  • Development and validation of circulating CA125 prediction models in postmenopausal women
  • 2019
  • Ingår i: Journal of Ovarian Research. - : BioMed Central (BMC). - 1757-2215. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Cancer Antigen 125 (CA125) is currently the best available ovarian cancer screening biomarker. However, CA125 has been limited by low sensitivity and specificity in part due to normal variation between individuals. Personal characteristics that influence CA125 could be used to improve its performance as screening biomarker.Methods: We developed and validated linear and dichotomous (>= 35 U/mL) circulating CA125 prediction models in postmenopausal women without ovarian cancer who participated in one of five large population-based studies: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, n = 26,981), European Prospective Investigation into Cancer and Nutrition (EPIC, n = 861), the Nurses' Health Studies (NHS/NHSII, n = 81), and the New England Case Control Study (NEC, n = 923). The prediction models were developed using stepwise regression in PLCO and validated in EPIC, NHS/NHSII and NEC. Result The linear CA125 prediction model, which included age, race, body mass index (BMI), smoking status and duration, parity, hysterectomy, age at menopause, and duration of hormone therapy (HT), explained 5% of the total variance of CA125. The correlation between measured and predicted CA125 was comparable in PLCO testing dataset (r = 0.18) and external validation datasets (r = 0.14). The dichotomous CA125 prediction model included age, race, BMI, smoking status and duration, hysterectomy, time since menopause, and duration of HT with AUC of 0.64 in PLCO and 0.80 in validation dataset.Conclusions: The linear prediction model explained a small portion of the total variability of CA125, suggesting the need to identify novel predictors of CA125. The dichotomous prediction model showed moderate discriminatory performance which validated well in independent dataset. Our dichotomous model could be valuable in identifying healthy women who may have elevated CA125 levels, which may contribute to reducing false positive tests using CA125 as screening biomarker.
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7.
  • Sasamoto, Naoko, et al. (författare)
  • Predicting Circulating CA125 Levels among Healthy Premenopausal Women
  • 2019
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 28:6, s. 1076-1085
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Cancer antigen 125 (CA125) is the most promising ovarian cancer screening biomarker to date. Multiple studies reported CA125 levels vary by personal characteristics, which could inform personalized CA125 thresholds. However, this has not been well described in premenopausal women. Methods: We evaluated predictors of CA125 levels among 815 premenopausal women from the New England Case Control Study (NEC). We developed linear and dichotomous (>= 35 U/mL) CA125 prediction models and externally validated an abridged model restricting to available predictors among 473 premenopausal women in the European Prospective Investigation into Cancer and Nutrition Study (EPIC). Results: The final linear CA125 prediction model included age, race, tubal ligation, endometriosis, menstrual phase at blood draw, and fibroids, which explained 7% of the total variance of CA125. The correlation between observed and predicted CA125 levels based on the abridged model (including age, race, and menstrual phase at blood draw) had similar correlation coefficients in NEC (r = 0.22) and in EPIC (r = 0.22). The dichotomous CA125 prediction model included age, tubal ligation, endometriosis, prior personal cancer diagnosis, family history of ovarian cancer, number of miscarriages, menstrual phase at blood draw, and smoking status with AUC of 0.83. The abridged dichotomous model (including age, number of miscarriages, menstrual phase at blood draw, and smoking status) showed similar AUCs in NEC (0.73) and in EPIC (0.78). Conclusions: We identified a combination of factors associated with CA125 levels in premenopausal women. Impact: Our model could be valuable in identifying healthy women likely to have elevated CA125 and consequently improve its specificity for ovarian cancer screening.
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