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Polycystic Ovary Syndrome, Oligomenorrhea, and Risk of Ovarian Cancer Histotypes: Evidence from the Ovarian Cancer Association Consortium

Overview of attention for article published in Cancer Epidemiology, Biomarkers & Prevention, February 2018
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Article details
Title
Polycystic Ovary Syndrome, Oligomenorrhea, and Risk of Ovarian Cancer Histotypes: Evidence from the Ovarian Cancer Association Consortium
Published in
Cancer Epidemiology, Biomarkers & Prevention, February 2018
DOI 10.1158/1055-9965.epi-17-0655
Pubmed ID
Authors
Abstract

Polycystic ovary syndrome (PCOS), and one if its distinguishing characteristics, oligomenorrhea, have both been associated with ovarian cancer risk in some but not all studies. However, these associations have been rarely been examined by ovarian cancer histotypes which may explain the lack of clear associations reported in previous studies. We analyzed data from 14 case-control studies including 16,594 women with invasive ovarian cancer (n=13,719) or borderline ovarian disease (n=2,875) and 17,718 controls. Adjusted study-specific odds ratios (ORs) were calculated using logistic regression and combined using random-effects meta-analysis. Pooled histotype-specific ORs were calculated using polytomous logistic regression. Women reporting menstrual cycle length >35 days had decreased risk of invasive ovarian cancer compared to women reporting cycle length <=35 days (OR=0.70; 95% Confidence Interval [CI]=0.58-0.84). Decreased risk of invasive ovarian cancer was also observed among women who reported irregular menstrual cycles compared to women with regular cycles (OR=0.83; 95% CI=0.76-0.89). No significant association was observed between self-reported PCOS and invasive ovarian cancer risk (OR=0.87; 95% CI=0.65-1.15). There was a decreased risk of all individual invasive histotypes for women with menstrual cycle length >35 days, but no association with serous borderline tumors (pheterogeneity=0.006). Similarly, we observed decreased risks of most invasive histotypes among women with irregular cycles but an increased risk of borderline serous and mucinous tumors (pheterogeneity<0.0001). Our results suggest that menstrual cycle characteristics influence ovarian cancer risk differentially based on histotype. These results highlight the importance of examining ovarian cancer risk factors associations by histologic subtype.

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X Demographics

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 121 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 13 11%
Researcher 10 8%
Student > Master 9 7%
Student > Ph. D. Student 5 4%
Other 4 3%
Other 13 11%
Unknown 67 55%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 18 15%
Biochemistry, Genetics and Molecular Biology 9 7%
Nursing and Health Professions 9 7%
Agricultural and Biological Sciences 2 2%
Computer Science 2 2%
Other 7 6%
Unknown 74 61%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 February 2019.
All research outputs
#24,723,713
of 34,350,842 outputs
Outputs from Cancer Epidemiology, Biomarkers & Prevention
#4,544
of 6,183 outputs
Outputs of similar age
#338,223
of 490,347 outputs
Outputs of similar age from Cancer Epidemiology, Biomarkers & Prevention
#28
of 50 outputs
Altmetric has tracked 34,350,842 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,183 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.4. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 490,347 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.