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  • 1. Clendenen, Tess V.
    et al.
    Ge, Wenzhen
    Koenig, Karen L.
    Afanasyeva, Yelena
    Agnoli, Claudia
    Brinton, Louise A.
    Darvishian, Farbod
    Dorgan, Joanne F.
    Eliassen, A. Heather
    Falk, Roni T.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health.
    Hankinson, Susan E.
    Hoffman-Bolton, Judith
    Key, Timothy J.
    Krogh, Vittorio
    Nichols, Hazel B.
    Sandler, Dale P.
    Schoemaker, Minouk J.
    Sluss, Patrick M.
    Sund, Malin
    Swerdlow, Anthony J.
    Visvanathan, Kala
    Zeleniuch-Jacquotte, Anne
    Liu, Mengling
    Breast cancer risk prediction in women aged 35-50 years: impact of including sex hormone concentrations in the Gail model2019In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 21, article id 42Article in journal (Refereed)
    Abstract [en]

    Background: Models that accurately predict risk of breast cancer are needed to help younger women make decisions about when to begin screening. Premenopausal concentrations of circulating anti-Mullerian hormone (AMH), a biomarker of ovarian reserve, and testosterone have been positively associated with breast cancer risk in prospective studies. We assessed whether adding AMH and/or testosterone to the Gail model improves its prediction performance for women aged 35-50.

    Methods: In a nested case-control study including ten prospective cohorts (1762 invasive cases/1890 matched controls) with pre-diagnostic serum/plasma samples, we estimated relative risks (RR) for the biomarkers and Gail risk factors using conditional logistic regression and random-effects meta-analysis. Absolute risk models were developed using these RR estimates, attributable risk fractions calculated using the distributions of the risk factors in the cases from the consortium, and population-based incidence and mortality rates. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory accuracy of the models with and without biomarkers.

    Results: The AUC for invasive breast cancer including only the Gail risk factor variables was 55.3 (95% CI 53.4, 57.1). The AUC increased moderately with the addition of AMH (AUC 57.6, 95% CI 55.7, 59.5), testosterone (AUC 56.2, 95% CI 54.4, 58.1), or both (AUC 58.1, 95% CI 56.2, 59.9). The largest AUC improvement (4.0) was among women without a family history of breast cancer.

    Conclusions: AMH and testosterone moderately increase the discriminatory accuracy of the Gail model among women aged 35-50. We observed the largest AUC increase for women without a family history of breast cancer, the group that would benefit most from improved risk prediction because early screening is already recommended for women with a family history.

  • 2. Fortner, Renee T.
    et al.
    Tolockiene, Egle
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Schock, Helena
    Oda, Husam
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Lakso, Hans-Åke
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Clinical chemistry.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Kaaks, Rudolf
    Toniolo, Paolo
    Zeleniuch-Jacquotte, Anne
    Grankvist, Kjell
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Clinical chemistry.
    Lundin, Eva
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Early pregnancy sex steroids during primiparous pregnancies and maternal breast cancer: a nested case-control study in the Northern Sweden Maternity Cohort2017In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 19, article id 82Article in journal (Refereed)
    Abstract [en]

    Background: Pregnancy and parity are associated with subsequent breast cancer risk. Experimental and epidemiologic data suggest a role for pregnancy sex steroid hormones.

    Methods: We conducted a nested case–control study in the Northern Sweden Maternity Cohort (1975–2007). Eligible women had provided a blood sample in the first 20 weeks of gestation during a primiparous pregnancy leading to a term delivery. The current study includes 223 cases and 417 matched controls (matching factors: age at and date of blood collection). Estrogen receptor (ER) and progesterone receptor (PR) status was available for all cases; androgen receptor (AR) data were available for 41% of cases (n = 92). Sex steroids were quantified by high-performance liquid chromatography tandem mass spectrometry. Odds ratios (ORs) and 95% confidence intervals were estimated using conditional logistic regression.

    Results: Higher concentrations of circulating progesterone in early pregnancy were inversely associated with ER+/PR+ breast cancer risk (ORlog2: 0.64 (0.41–1.00)). Higher testosterone was positively associated with ER+/PR+ disease risk (ORlog2: 1.57 (1.13–2.18)). Early pregnancy estrogens were not associated with risk, except for relatively high estradiol in the context of low progesterone (split at median, relative to low concentrations of both; OR: 1.87 (1.11–3.16)). None of the investigated hormones were associated with ER–/PR– disease, or with AR+ or AR+/ER+/PR+ disease.

    Conclusions: Consistent with experimental models, high progesterone in early pregnancy was associated with lower risk of ER+/PR+ breast cancer in the mother. High circulating testosterone in early pregnancy, which likely reflects nonpregnant premenopausal exposure, was associated with higher risk of ER+/PR+ disease.

  • 3. Frisk, Gabriella
    et al.
    Ekberg, Sara
    Lidbrink, Elisabet
    Eloranta, Sandra
    Sund, Malin
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences.
    Fredriksson, Irma
    Lambe, Mats
    Smedby, Karin E.
    No association between low-dose aspirin use and breast cancer outcomes overall: a Swedish population-based study2018In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 20, article id 142Article in journal (Refereed)
    Abstract [en]

    Background: Results from previous studies indicate that use of low-dose aspirin may improve breast cancer prognosis. We evaluated aspirin use and breast cancer outcomes in relation to clinical characteristics as well as dose and duration of aspirin use.

    Methods: We used information from the Regional Breast Cancer Quality-of-Care Registries in three Swedish regions to identify 21,414 women diagnosed with a first stage I-III breast cancer between 1 April 2006 and 31 December 2012. The cohort was further linked to nationwide registers to retrieve information about dispensing low-dose aspirin before and after breast cancer diagnosis, comorbidity and causes of death. In a separate analysis, we investigated time to breast cancer death among 621 women with stage IV disease at diagnosis. Associations were evaluated using a multivariable Cox proportional hazards model.

    Results: Among women with stage I-III breast cancer, 2660 (12.4%) used low-dose aspirin shortly before breast cancer diagnosis and 4091 (19.1%) were users during follow-up. Women were followed for a median of 3.8years after diagnosis. There was no association between aspirin use and breast cancer-specific death in multivariable analyses (use before diagnosis: hazard ratio (HR) 0.93, 95% confidence interval (CI) 0.77-1.12; use after diagnosis: HR 1.00, 95% CI 0.74-1.37). Similarly, aspirin use was not associated with risk of first recurrence/metastases in a subgroup of stage I-III breast cancer patients (HR 0.97, 95% CI 0.86-1.10). However, in analyses stratified by stage, an inverse association between low-dose aspirin use after diagnosis and breast cancer death was found for women with stage I tumors (HR 0.53, 95% CI 0.29-0.96). Among women with stage IV disease at diagnosis, aspirin use was not associated with time to breast cancer death (HR 0.91, 95% CI 0.67-1.23).

    Conclusion: In this large population-based cohort study there was no evidence that low-dose aspirin use before or after breast cancer diagnosis is associated with a reduced risk of adverse outcomes overall in breast cancer. However, a potential benefit was noted among women with stage I tumors, warranting further investigation.

  • 4. Li, Kuanrong
    et al.
    Anderson, Garnet
    Viallon, Vivian
    Arveux, Patrick
    Kvaskoff, Marina
    Fournier, Agnès
    Krogh, Vittorio
    Tumino, Rosario
    Sánchez, Maria-Jose
    Ardanaz, Eva
    Chirlaque, María-Dolores
    Agudo, Antonio
    Muller, David C
    Smith, Todd
    Tzoulaki, Ioanna
    Key, Timothy J
    Bueno-de-Mesquita, Bas
    Trichopoulou, Antonia
    Bamia, Christina
    Orfanos, Philippos
    Kaaks, Rudolf
    Hüsing, Anika
    Fortner, Renée T
    Zeleniuch-Jacquotte, Anne
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Department of Population Health, New York University School of Medicine, New York, USA; Department of Environmental Medicine, New York University School of Medicine, New York, USA; Perlmutter Cancer Center, New York University School of Medicine, New York, USA.
    Sund, Malin
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences.
    Dahm, Christina C
    Overvad, Kim
    Aune, Dagfinn
    Weiderpass, Elisabete
    Romieu, Isabelle
    Riboli, Elio
    Gunter, Marc J
    Dossus, Laure
    Prentice, Ross
    Ferrari, Pietro
    Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts2018In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 20, article id 147Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction.

    METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.

    RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.

    CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.

  • 5. Santucci-Pereira, Julia
    et al.
    Zeleniuch-Jacquotte, Anne
    Afanasyeva, Yelena
    Zhong, Hua
    Slifker, Michael
    Peri, Suraj
    Ross, Eric A
    López de Cicco, Ricardo
    Zhai, Yubo
    Nguyen, Theresa
    Sheriff, Fathima
    Russo, Irma H
    Su, Yanrong
    Arslan, Alan A
    Bordas, Pal
    Lenner, Per
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Åhman, Janet
    Landström Eriksson, Anna Stina
    Johansson, Robert
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health.
    Toniolo, Paolo
    Russo, Jose
    Genomic signature of parity in the breast of premenopausal women2019In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 21, no 1, article id 46Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Full-term pregnancy (FTP) at an early age confers long-term protection against breast cancer. Previously, we reported that a FTP imprints a specific gene expression profile in the breast of postmenopausal women. Herein, we evaluated gene expression changes induced by parity in the breast of premenopausal women.

    METHODS: Gene expression profiling of normal breast tissue from 30 nulliparous (NP) and 79 parous (P) premenopausal volunteers was performed using Affymetrix microarrays. In addition to a discovery/validation analysis, we conducted an analysis of gene expression differences in P vs. NP women as a function of time since last FTP. Finally, a laser capture microdissection substudy was performed to compare the gene expression profile in the whole breast biopsy with that in the epithelial and stromal tissues.

    RESULTS: Discovery/validation analysis identified 43 differentially expressed genes in P vs. NP breast. Analysis of expression as a function of time since FTP revealed 286 differentially expressed genes (238 up- and 48 downregulated) comparing all P vs. all NP, and/or P women whose last FTP was less than 5 years before biopsy vs. all NP women. The upregulated genes showed three expression patterns: (1) transient: genes upregulated after FTP but whose expression levels returned to NP levels. These genes were mainly related to immune response, specifically activation of T cells. (2) Long-term changing: genes upregulated following FTP, whose expression levels decreased with increasing time since FTP but did not return to NP levels. These were related to immune response and development. (3) Long-term constant: genes that remained upregulated in parous compared to nulliparous breast, independently of time since FTP. These were mainly involved in development/cell differentiation processes, and also chromatin remodeling. Lastly, we found that the gene expression in whole tissue was a weighted average of the expression in epithelial and stromal tissues.

    CONCLUSIONS: Genes transiently activated by FTP may have a role in protecting the mammary gland against neoplastically transformed cells through activation of T cells. Furthermore, chromatin remodeling and cell differentiation, represented by the genes that are maintained upregulated long after the FTP, may be responsible for the lasting preventive effect against breast cancer.

  • 6.
    Wu, Wendy Yi-Ying
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Törnberg, Sven
    Elfström, Klara Miriam
    Liu, Xijia
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Nyström, Lennarth
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Jonsson, Håkan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Overdiagnosis in the population-based organized breast cancer screening program estimated by a non-homogeneous multi-state model: a cohort study using individual data with long-term follow-up2018In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 20, article id 153Article in journal (Refereed)
    Abstract [en]

    Background: Overdiagnosis, defined as the detection of a cancer that would not become clinically apparent in a woman’s lifetime without screening, has become a growing concern. Similar underlying risk of breast cancer in the screened and control groups is a prerequisite for unbiased estimates of overdiagnosis, but a contemporary control group is usually not available in organized screening programs.

    Methods: We estimated the frequency of overdiagnosis of breast cancer due to screening in women 50–69 years old by using individual screening data from the population-based organized screening program in Stockholm County 1989–2014. A hidden Markov model with four latent states and three observed states was constructed to estimate the natural progression of breast cancer and the test sensitivity. Piecewise transition rates were used to consider the time-varying transition rates. The expected number of detected non-progressive breast cancer cases was calculated.

    Results: During the study period, 2,333,153 invitations were sent out; on average, the participation rate in the screening program was 72.7% and the average recall rate was 2.48%. In total, 14,648 invasive breast cancer cases were diagnosed; among the 8305 screen-detected cases, the expected number of non-progressive breast cancer cases was 35.9, which is equivalent to 0.43% (95% confidence interval (CI) 0.10%–2.2%) overdiagnosis. The corresponding estimates for the prevalent and subsequent rounds were 15.6 (0.87%, 95% CI 0.20%–4.3%) and 20.3 (0.31%, 95% CI 0.07%–1.6%), respectively. The likelihood ratio test showed that the non-homogeneous model fitted the data better than an age-homogeneous model (P<0.001).

    Conclusions: Our findings suggest that overdiagnosis in the organized biennial mammographic screening for women 50–69 in Stockholm County is a minor phenomenon. The frequency of overdiagnosis in the prevalent screening round was higher than that in subsequent rounds. The non-homogeneous model performed better than the simpler, traditional homogeneous model.

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