PURPOSE: Accurate classification of menopausal status is important to epidemiological research evaluating the role of reproductive hormones in disease processes. Algorithms relying on repeat hormone assays are unfeasible in large epidemiological studies. This paper summarizes the development of the Women's Ischemia Syndrome Evaluation (WISE) Hormonal menopausal status algorithm for determining premenopausal, perimenopausal, and postmenopausal status using menstrual and reproductive history and reproductive hormone levels obtained at a single clinic visit. METHODS: The authors compared the accuracy of this algorithm with two currently used self-report algorithms: Menstrual, based only on months since last menstrual period, and Historical, which adds age and surgical history. RESULTS: The study population consisted of 515 women (329 clearly postmenopausal) enrolled in the WISE study who were undergoing coronary angiography for suspected ischemia. A subgroup of 186, not clearly postmenopausal, was classified by these three algorithms. Results were evaluated against individualized expert consensus classification. The Menstrual and Historical classifications differed significantly (p < 0.0001) from expert consensus, with 32%-26% discordant classifications, respectively. For the WISE Hormonal classification, discordance was 4%. CONCLUSIONS: The authors conclude that inaccurate classifications of menopausal status occur frequently in self-report algorithms. Use of the relatively simple WISE algorithm can improve the accuracy of menopausal status classification for epidemiological research.
PURPOSE: Accurate classification of menopausal status is important to epidemiological research evaluating the role of reproductive hormones in disease processes. Algorithms relying on repeat hormone assays are unfeasible in large epidemiological studies. This paper summarizes the development of the Women's Ischemia Syndrome Evaluation (WISE) Hormonal menopausal status algorithm for determining premenopausal, perimenopausal, and postmenopausal status using menstrual and reproductive history and reproductive hormone levels obtained at a single clinic visit. METHODS: The authors compared the accuracy of this algorithm with two currently used self-report algorithms: Menstrual, based only on months since last menstrual period, and Historical, which adds age and surgical history. RESULTS: The study population consisted of 515 women (329 clearly postmenopausal) enrolled in the WISE study who were undergoing coronary angiography for suspected ischemia. A subgroup of 186, not clearly postmenopausal, was classified by these three algorithms. Results were evaluated against individualized expert consensus classification. The Menstrual and Historical classifications differed significantly (p < 0.0001) from expert consensus, with 32%-26% discordant classifications, respectively. For the WISE Hormonal classification, discordance was 4%. CONCLUSIONS: The authors conclude that inaccurate classifications of menopausal status occur frequently in self-report algorithms. Use of the relatively simple WISE algorithm can improve the accuracy of menopausal status classification for epidemiological research.
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