scholarly journals Prediagnostic Sex Steroid Hormones in Relation to Male Breast Cancer Risk

2015 ◽  
Vol 33 (18) ◽  
pp. 2041-2050 ◽  
Author(s):  
Louise A. Brinton ◽  
Tim J. Key ◽  
Laurence N. Kolonel ◽  
Karin B. Michels ◽  
Howard D. Sesso ◽  
...  

Purpose Although previous studies have implicated a variety of hormone-related risk factors in the etiology of male breast cancers, no previous studies have examined the effects of endogenous hormones. Patients and Methods Within the Male Breast Cancer Pooling Project, an international consortium comprising 21 case-control and cohort investigations, a subset of seven prospective cohort studies were able to contribute prediagnostic serum or plasma samples for hormone quantitation. Using a nested case-control design, multivariable unconditional logistic regression analyses estimated odds ratios and 95% CIs for associations between male breast cancer risk and 11 individual estrogens and androgens, as well as selected ratios of these analytes. Results Data from 101 cases and 217 matched controls were analyzed. After adjustment for age and date of blood draw, race, and body mass index, androgens were found to be largely unrelated to risk, but circulating estradiol levels showed a significant association. Men in the highest quartile had an odds ratio of 2.47 (95% CI, 1.10 to 5.58) compared with those in the lowest quartile (trend P = .06). Assessment of estradiol as a ratio to various individual androgens or sum of androgens showed no further enhancement of risk. These relations were not significantly modified by either age or body mass index, although estradiol was slightly more strongly related to breast cancers occurring among younger (age < 67 years) than older men. Conclusion Our results support the notion of an important role for estradiol in the etiology of male breast cancers, similar to female breast cancers.

2014 ◽  
Vol 50 ◽  
pp. S234-S235
Author(s):  
P. Rizzolo ◽  
V. Silvestri ◽  
G. Giannini ◽  
L. Varesco ◽  
A. Viel ◽  
...  

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Zhoufeng Ye ◽  
Gillian Dite ◽  
John Hopper

Abstract Background Our previous work on body mass index (BMI) and breast cancer risk found that the association depended on menopausal status but not on familial risk (Hopper, JL., et al, 2018). We now consider whether weight is a more informative risk factor for breast cancer than BMI. Methods We used data from the Prospective Family Study Cohort, a consortium of international prospective cohorts that are enriched for familial risk of breast cancer and include 16,035 unaffected women from 6701 families. Participants were followed for up to 20 years (mean 10.5 years) and there were 896 incident breast cancers with a mean age at diagnosis of 55.7 years. Cox regression was used to model risk associations as a function of age, menopausal status and underlying familial risk. We calculated robust confidence intervals by clustering by family. Model comparisons were made using the Bayesian Information Criterion (BIC). Results In repeating the best-fitting model from our original analyses, but using weight instead of BMI, we found that the log likelihood for the model using weight was 1.92 units greater than for the model using BMI (difference in BIC = 3.84). Therefore, the data are almost 50 times more likely under the model using weight. Conclusions The study found positive evidence that weight gives more information on risk than does BMI. Key messages Analysing breast cancer risk in terms of weight, rather than only BMI, might give greater insight and results that are easier to convey to the public.


2010 ◽  
Vol 19 (6) ◽  
pp. 1532-1544 ◽  
Author(s):  
Paula Berstad ◽  
Ralph J. Coates ◽  
Leslie Bernstein ◽  
Suzanne G. Folger ◽  
Kathleen E. Malone ◽  
...  

2000 ◽  
Vol 83 (9) ◽  
pp. 1234-1237 ◽  
Author(s):  
E Petridou ◽  
G Giokas ◽  
H Kuper ◽  
L A Mucci ◽  
D Trichopoulos

2014 ◽  
Vol 25 (2) ◽  
pp. 519-524 ◽  
Author(s):  
K. Wada ◽  
C. Nagata ◽  
A. Tamakoshi ◽  
K. Matsuo ◽  
I. Oze ◽  
...  

2018 ◽  
Vol 111 (4) ◽  
pp. 350-364 ◽  
Author(s):  
Frank Qian ◽  
Shengfeng Wang ◽  
Jonathan Mitchell ◽  
Lesley McGuffog ◽  
Daniel Barrowdale ◽  
...  

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