Literature DB >> 25503962

Immunoassay and Nb2 lymphoma bioassay prolactin levels and mammographic density in premenopausal and postmenopausal women the Nurses' Health Studies.

Megan S Rice1, Shelley S Tworoger, Kimberly A Bertrand, Susan E Hankinson, Bernard A Rosner, Yvonne B Feeney, Charles V Clevenger, Rulla M Tamimi.   

Abstract

Higher circulating prolactin levels have been associated with higher percent mammographic density among postmenopausal women in some, but not all studies. However, few studies have examined associations with dense area and non-dense breast area breast or considered associations with prolactin Nb2 lymphoma cell bioassay levels. We conducted a cross-sectional study among 1,124 premenopausal and 890 postmenopausal women who were controls in breast cancer case-control studies nested in the Nurses' Health Study (NHS) and NHSII. Participants provided blood samples in 1989-1990 (NHS) or 1996-1999 (NHSII) and mammograms were obtained from around the time of blood draw. Multivariable linear models were used to assess the associations between prolactin levels (measured by immunoassay or bioassay) with percent density, dense area, and non-dense area. Among 1,124 premenopausal women, percent density, dense area, and non-dense area were not associated with prolactin immunoassay levels in multivariable models (p trends = 0.10, 0.18, and 0.69, respectively). Among 890 postmenopausal women, those with prolactin immunoassay levels in the highest versus lowest quartile had modestly, though significantly, higher percent density (difference = 3.01 percentage points, 95 % CI 0.22, 5.80) as well as lower non-dense area (p trend = 0.02). Among women with both immunoassay and bioassay levels, there were no consistent differences in the associations with percent density between bioassay and immunoassay levels. Postmenopausal women with prolactin immunoassay levels in the highest quartile had significantly higher percent density as well as lower non-dense area compared to those in the lowest quartile. Future studies should examine the underlying biologic mechanisms, particularly for non-dense area.

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Year:  2014        PMID: 25503962      PMCID: PMC4381437          DOI: 10.1007/s10549-014-3232-z

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.624


  27 in total

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Journal:  Endocr Rev       Date:  1995-06       Impact factor: 19.871

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  6 in total

1.  Percent mammographic density prediction: development of a model in the nurses' health studies.

Authors:  Megan S Rice; Bernard A Rosner; Rulla M Tamimi
Journal:  Cancer Causes Control       Date:  2017-05-06       Impact factor: 2.506

2.  Early-Life and Adult Anthropometrics in Relation to Mammographic Image Intensity Variation in the Nurses' Health Studies.

Authors:  Hannah Oh; Megan S Rice; Erica T Warner; Kimberly A Bertrand; Erin E Fowler; A Heather Eliassen; Bernard A Rosner; John J Heine; Rulla M Tamimi
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-12-11       Impact factor: 4.254

3.  Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study.

Authors:  Erica T Warner; Megan S Rice; Oana A Zeleznik; Erin E Fowler; Divya Murthy; Celine M Vachon; Kimberly A Bertrand; Bernard A Rosner; John Heine; Rulla M Tamimi
Journal:  NPJ Breast Cancer       Date:  2021-05-31

4.  Hormone and receptor activator of NF-κB (RANK) pathway gene expression in plasma and mammographic breast density in postmenopausal women.

Authors:  Rachel Mintz; Mei Wang; Shuai Xu; Graham A Colditz; Chris Markovic; Adetunji T Toriola
Journal:  Breast Cancer Res       Date:  2022-04-14       Impact factor: 6.466

5.  A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density.

Authors:  Anja Rudolph; Peter A Fasching; Sabine Behrens; Ursula Eilber; Manjeet K Bolla; Qin Wang; Deborah Thompson; Kamila Czene; Judith S Brand; Jingmei Li; Christopher Scott; V Shane Pankratz; Kathleen Brandt; Emily Hallberg; Janet E Olson; Adam Lee; Matthias W Beckmann; Arif B Ekici; Lothar Haeberle; Gertraud Maskarinec; Loic Le Marchand; Fredrick Schumacher; Roger L Milne; Julia A Knight; Carmel Apicella; Melissa C Southey; Miroslav K Kapuscinski; John L Hopper; Irene L Andrulis; Graham G Giles; Christopher A Haiman; Kay-Tee Khaw; Robert Luben; Per Hall; Paul D P Pharoah; Fergus J Couch; Douglas F Easton; Isabel Dos-Santos-Silva; Celine Vachon; Jenny Chang-Claude
Journal:  Breast Cancer Res       Date:  2015-08-16       Impact factor: 6.466

6.  Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nurses' Health Studies.

Authors:  Natalie C DuPre; Jaime E Hart; Kimberly A Bertrand; Peter Kraft; Francine Laden; Rulla M Tamimi
Journal:  Breast Cancer Res       Date:  2017-11-23       Impact factor: 6.466

  6 in total

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