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Reproducibility of plasma steroid hormones, prolactin, and insulin-like growth factor levels among premenopausal women over a 2- to 3-year period. Export

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, Vol. 15, No. 5. (May 2006), pp. 972-978.

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Few studies have evaluated whether a single blood hormone measurement, as is available in most epidemiologic studies, sufficiently characterizes a premenopausal woman's long-term hormone levels; there is particular concern whether sex steroid hormones, which fluctuate during the menstrual cycle, are reliable. We conducted a prospective study within the Nurses' Health Study II to examine the reproducibility of plasma estrogens, androgens, progesterone, prolactin, sex hormone binding globulin, insulin-like growth factor-I (IGF-I), and IGF binding protein-3 (IGFBP-3). One blood sample per year over 3 years was collected from 113 premenopausal women during both the follicular and luteal phases of the menstrual cycle. We calculated intraclass correlation coefficients (ICC) across the three samples for all women. Among estrogens, ICCs ranged from 0.38 (estradiol) to 0.60 (estrone sulfate) in the follicular phase and from 0.44 (estrone) to 0.69 (estrone sulfate) in the luteal phase. Among androgens, ICCs ranged from 0.58 (androstenedione) to 0.94 [dehydroepiandrostenedione sulfate (DHEAS)] in the follicular phase and from 0.56 (testosterone) to 0.81 (DHEAS) in the luteal phase. When values were averaged across the follicular and luteal phases, the ICC for prolactin was 0.64 whereas ICCs for IGF-I and IGFBP-3 were 0.86 and 0.82, respectively. The ICC for progesterone in the luteal phase was only 0.29. These data suggest that for androgens, estrone sulfate, prolactin, IGF-I, and IGFBP-3, a single measurement can reliably categorize average levels over at least a 3-year period in premenopausal women. For estrone and estradiol, where ICCs were relatively low, it is important to use reproducibility data such as those to correct for measurement error in epidemiologic studies.


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