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Failure to Consider the Menstrual Cycle Phase May Cause Misinterpretation of Clinical and Research Findings of Cardiometabolic Biomarkers in Premenopausal Women
Author(s) -
Enrique F. Schisterman,
Sunni L. Mumford,
Lindsey A. Sjaarda
Publication year - 2013
Publication title -
epidemiologic reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.253
H-Index - 106
eISSN - 1478-6729
pISSN - 0193-936X
DOI - 10.1093/epirev/mxt007
Subject(s) - medicine , menstrual cycle , biomarker , luteal phase , follicular phase , physiology , disease , women's health initiative , endocrinology , hormone , postmenopausal women , biochemistry , chemistry
Biomarker assessment plays a critical role in the study and prevention of disease. However, variation in biomarkers attributable to the menstrual cycle in premenopausal women may impair understanding the role of certain biomarkers in disease development and progression. Thus, in light of the recently increasing evidence of menstrual cycle variability in multiple cardiometabolic biomarkers, a reexamination of approaches for appropriately studying and diagnosing cardiovascular disease in premenopausal women is warranted. We reviewed studies (from 1934 through 2012) evaluating changes in cardiometabolic biomarkers across phases of the menstrual cycle, including markers of oxidative stress, lipids, insulin sensitivity, and systemic inflammation. Each was observed to vary significantly during the menstrual cycle. For example, nearly twice as many women had elevated cholesterol levels warranting therapy (≥200 mg/dL) during the follicular phase compared with the luteal phase (14.3% vs. 7.9%), with only 3% having consistently high levels during all phases of the cycle. Similarly, nearly twice as many women were classified as being at an elevated risk of cardiovascular disease (high sensitivity C-reactive protein >3 mg/L) during menses compared with other phases (12.3% vs. 7.4%). Menstrual cycle-associated variability in cardiometabolic biomarkers is an important source of variability that should be accounted for in both research and clinical settings.

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