| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
1 Channing Laboratory, Department of Medicine, and 2 Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham and Women's Hospital and Harvard Medical School; Departments of 3 Epidemiology and 4 Biostatistics, Harvard School of Public Health, Boston, Massachusetts; 5 Department of Public Health, University of Massachusetts, Amherst, Massachusetts; and 6 Department of Oncology, McGill University and Lady Davis Research Institute, Montreal, Quebec, Canada
Requests for reprints: Stacey A. Missmer, Channing Laboratory, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115. Phone: 617-525-2021; Fax: 617-525-2008 alternate fax: 617-525-4597. E-mail: stacey.missmer{at}channing.harvard.edu
| Abstract |
|---|
|
|
|---|
| Introduction |
|---|
|
|
|---|
Previously, we assessed the reproducibility of plasma estradiol, estrone, estrone sulfate, and progesterone among 87 premenopausal women over a 1-year period (11). However, evaluation of the reproducibility of these and additional hormones over a longer period of time has not been undertaken. Therefore, we conducted a prospective study within the Nurses' Health Study II to examine the reproducibility of plasma estradiol, free estradiol, estrone, estrone sulfate, androstenedione, testosterone, dehydroepiandrostenedione (DHEA), dehydroepiandrostenedione sulfate (DHEAS), progesterone, sex hormone binding globulin (SHBG), prolactin, insulin-like growth factorI (IGF-I), free IGF-I, and IGF binding protein3 (IGFBP-3)endogenous factors that may be related to chronic disease riskin both the follicular and luteal phases of the menstrual cycle among 113 premenopausal women over a 2- to 3-year period.
| Materials and Methods |
|---|
|
|
|---|
Each blood collection kit contained all of the supplies needed to have blood samples drawn by a local laboratory or a colleague (e.g., needle, tourniquet, and blood collection tubes with sodium heparin). Premenopausal participants were asked to have their first blood sample drawn on the 3rd, 4th, or 5th day of their menstrual cycle ("follicular" blood draw) and to have the second blood sample drawn 7 to 9 days before the anticipated start of their next cycle ("luteal" blood draw). Timing of the luteal sample from the estimated first day of the next menstrual cycle is generally more accurate than counting forward from day 1 of the current cycle because the length of the follicular phase is more variable than the length of the luteal phase (12, 13). Participants placed their follicular blood samples in a refrigerator for 8 to 24 hours after it was drawn; they then aliquoted the plasma into cryotubes. The plasma was kept in the participant's home freezer until the second (luteal) blood collection. Then the woman arranged to have both samples shipped, via overnight courier and with an ice pack, to our laboratory; on arrival, the luteal whole blood sample was processed and aliquoted into labeled cryotubes. All samples have been stored in the vapor phase of continuously monitored liquid nitrogen freezers since collection.
We previously reported that plasma hormones remained stable when collected in the manner used for the luteal phase samples (14, 15). We additionally conducted a pilot study to determine if hormone levels remained stable with our follicular phase processing method. Two tubes of blood were collected in the follicular phase from each of 16 premenopausal women. One tube was processed and frozen immediately and the second was treated identically to the processing method described above. Estradiol, free and bioavailable estradiol, estrone, and testosterone were assayed on all samples. For all hormones, the mean and SD for each of the processing methods were almost identical and, with the exception of estrone, the ICC ranged from 0.93 to 0.98. For estrone, the ICC was 0.8, due primarily to a single replicate (values of 48 and 70 pg/mL); without this replicate, the ICC was 0.87.
Among blood study participants, invitation to participate in the "hormone stability study" was extended to a random sample of responders who were premenopausal, not using exogenous hormones (e.g., oral contraceptives), and who were not currently nor planning to be pregnant or lactating. Second and third blood collection kits were mailed to women who returned the first kit without reminding (i.e., excellent responders) and remained eligible to participate. Of the 412 invited women, 74% (n = 304) provided a second set of samples and, of these, 236 (57%) sent a third set. These 236 women did not significantly differ by age, race, parity, body mass index, or cigarette use from the 412 who received the initial invitation (data not shown). Overall, six blood samplesa follicular and a luteal in each of the three setswere collected from each of 236 women over the 3-year period.
For each menstrual cycle sampled, a questionnaire was sent with the blood collection kit on which to record the first day of the menstrual cycle during which the blood samples were drawn and the dates of both blood draws. Details on the number of hours since last food intake before the two blood draws, time of day and month of blood collection, and the participant's current weight, menstrual cycle length, exercise frequency, and smoking status were also collected. Finally, a postcard on which to record the first day of the next menstrual cycle was provided; all but one postcard (99.7%) was returned.
For these analyses, based on a desired final sample size of 100 women and given the estimated proportion of women who would be found to have had anovulatory cycles and limiting to women whose luteal phase samples were each collected between 3 and 11 days before the start of her next menstrual period, blood samples collected from a total of 113 women were selected for hormone and SHBG level analysis. For financial reasons and to decrease plasma use, follicular samples from only 50% of the women were submitted for assays where the correlation across the menstrual cycle was expected to be relatively high (i.e., free estradiol, DHEA, DHEAS, IGF-I, free IGF-I, and IGFBP-3).
The study was approved by the Committee on the Use of Human Subjects in Research at the Brigham and Women's Hospital.
Laboratory Methods
Assays were conducted by three different laboratories. Estradiol, free estradiol, estrone, estrone sulfate, progesterone, androstenedione, testosterone, dehydroepiandrosterone, and dehydroepiandrosterone sulfate were assayed at Quest Diagnostics-Nichols Institute (San Juan Capistrano, CA). SHBG and prolactin were assayed by Dr. P. Sluss at the Reproductive Endocrinology Unit Laboratory of the Massachusetts General Hospital (Boston, MA). IGF-I, free IGF-I, and IGFBP-3 were assayed by Dr. M. Pollak at McGill University (Quebec, Canada).
Hormone and growth factor assay methods have previously been described in detail (15-17). In brief, samples were extracted with hexane-ethyl acetate, the steroids were eluted from celite columns, and the fractions were then assayed by radioimmunossay (18-22). DHEAS was assayed by radioimmunossay without a prior separation step (23). After extraction of estrone, estrone sulfate was assayed by radioimmunossay of estrone, after enzyme hydrolysis, organic extraction, and separation by column chromatography (24). Prolactin levels were assayed using the AxSYM Immunoassay system (Abbott Diagnostics, Chicago, IL). IGF-I and IGFBP-3 levels were assayed by ELISA with reagents from Diagnostic Systems Laboratory (Webster, TX).
All of the follicular and luteal samples from a single woman were assayed together; the samples were ordered randomly and labeled so that the laboratory could not identify samples from the same woman. To assess laboratory precision, quality control replicates of 10% of all samples assayed were randomly interspersed and labeled to preclude their identification. Overall, with the exception of progesterone, within-batch laboratory coefficients of variation for the assays ranged from 4% for IGF-I to 14% for estrone sulfate. Progesterone had a coefficient of variation of 40% due primarily to a single outlier among 53 samples tested; when this value was excluded, the coefficient of variation was 14%.
Statistical Analyses
We used the extreme studentized deviate many-outlier procedure (25, 26) to assess for outliers in each set of laboratory results. This resulted in the removal of 5 estradiol, 1 free estradiol, 5 estrone, 10 estrone sulfate, 1 androstenedione, 2 DHEA, 3 testosterone, 12 prolactin, 1 SHBG, and 1 IGFBP-3 values from among the 678 possible values per hormone (113 women x 2 blood samples x 3 time periods). The final number of samples available for each phase of the menstrual cycle within each collection is provided in Table 1
.
|
To assess the utility of a single hormone measurement to correctly classify longer term hormone levels into quartile categories, we compared quartiles of hormone levels (as measured by the first blood sample) to quartiles as defined by the mean of the second and third blood samples. Quartile cut points were defined separately and thus were not necessarily the same.
| Results |
|---|
|
|
|---|
Whereas differences in absolute levels between the follicular and luteal phases at each blood sample were most evident for the estrogens, androgens and growth factors also differed significantly across the menstrual cycle (paired t test P < 0.05; Table 1). The correlations between the follicular and luteal phase levels based on the first blood sample, with the exception of free estradiol, were all statistically significant (Table 2 ), suggesting that women tended to rank similarly between the two menstrual cycle phases. The strongest correlations were for SHBG and DHEAS (r > 0.8) and secondarily for testosterone, DHEA, IGF-I, free IGF-I, and IGFBP-3 (r > 0.6). If the mean of all three samples was used, all correlations tended to increase slightly (data not shown). The notable exceptions to this were androstenedione and IGF-I where the increase in the correlation was substantial (androstenedione, r = 0.52 to 0.79; IGF-I, r = 0.65 to 0.86).
|
|
|
|
Finally, we addressed how well a single sample would classify women into the appropriate quartile of exposure using the mean of the second and third samples as the "gold standard." Shown in Table 6 are matrices for four of the hormones of interest that represent a range of ICCs: follicular estradiol (ICC = 0.38), follicular testosterone (ICC = 0.68), follicular SHBG (ICC = 0.83), and follicular DHEAS (ICC = 0.94). The quartiles are approximate because of a number of women with identical plasma hormone values. For estradiol, 38 of 92 (41%) were perfectly classified, 79 of 92 (86%) were off by one category or less, and just 3 values (3.3%) were misclassified into an extreme category. Percentages for testosterone were 55%, 90%, and 1.3%, respectively. For SHBG, 57% were perfectly classified, 93% were off by one category or less, and none were misclassified into an extreme category. For DHEAS, 79% were perfectly classified whereas 100% were off by one category or less. Although concordance was high, these results will tend to underestimate agreement with true long-term levels as two, rather than a large number of replicates, were used as the gold standard.
|
| Discussion |
|---|
|
|
|---|
We observed little change in the within-woman characteristics across the 3-year blood sampling period. Only three current smokers became past smokers and only 11 women (10%) became postmenopausal in the follow-up period (through June 2003) after their final blood draw. Therefore, analyses excluding these women did not alter the observed ICCs appreciably. Even analyses taking into account weight gaincommon in this study populationdid not alter the ICCs. This is likely because among premenopausal women, estrogens derive primarily from the ovary, whereas among postmenopausal women, where adipose is the primary source of estrogens, an effect of weight change would be expected (31).
Most previous studies have measured hormone reliability over time among postmenopausal women (28, 32-35). Within the Nurses' Health Study, we observed ICCs of 0.68 and 0.74 for estradiol and estrone, 0.75 for DHEA, and 0.88 for testosterone, suggesting substantial reproducibility over a 2- to 3-year period. The ICC observed for prolactin was 0.53 and for SHBG was 0.92 (28). Of course, among postmenopausal women, endogenous levels of steroid hormones are not fluctuating in response to the menstrual cycle. In the current study of premenopausal women, we observed similar ICCs for endogenous hormones that do not change with the postmenopausal transition, such as DHEA and DHEAS, whereas we observed quite different ICCs for hormones such as estrogens that change dramatically from premenopause to postmenopause.
Few studies have evaluated reproducibility over time among premenopausal women (11, 32, 35). Two have reported ICCs for plasma androgens ranging from 0.60 to 0.85 over a 1-year period (32, 35); our ICCs over a 2- to 3-year period were similar to these. Only our previous study (n = 87 women) evaluated the ICC for both the follicular and luteal phases, reporting ICCs over a 1-year period for estradiol, estrone, estrone sulfate, and progesterone (11). With the exception of estradiol in the luteal phase, observed ICCs in that study ranged from 0.52 to 0.71. The ICC for luteal estradiol was 0.19, which increased to 0.49 after restricting to ovulatory cycles and to 0.62 when further restricting luteal timing of the sample to 4 to 10 days. The latter analysis, however, included only 39 women. In the current study, the ICC for the intervals between years 1 and 2 and between years 2 and 3 were similar to the ICCs observed across the entire 3-year period, suggesting that this between-study difference may be due to chance. Of note, in our previous study, 30 of 174 (18%) cycles from the 87 women were anovulatory with a cut point of <300 ng/dL of progesterone, whereas here only 25 of 339 (7%) cycles from the 113 women were identified as anovulatory with a more specific cut point of <400 ng/dL, which may explain why the current results change very little when excluding anovulatory cycles.
The poor reproducibility of luteal progesterone contradicts our previous findings over a 1-year period (ICC = 0.54), despite sampling from women within the same cohort with similar personal characteristic distributions (e.g., age, body mass index). When we limited our current analyses to include only the first and second blood samples, the ICC for progesterone improved slightly to 0.38, whereas when we limited the analyses to include only the second and third blood samples, the ICC for progesterone was 0.28neither approached the coefficient previously observed. Progesterone secretion is somewhat pulsatile (36) and exhibits a rapid and steep increase and then a decrease in the luteal phase, factors that would contribute to the observed lower reproducibility. If, as seems most likely, the difference between the ICC observed in this and in our previous study is due to chance, then a combination of the estimates is most appropriate. Regardless, it remains likely that a single measurement of progesterone is at least valid for identification of anovulation within a single menstrual cycle as, in this instance, only very low values are being identified.
Whereas the absolute levels of IGF-I and IGFBP-3 were observed to be slightly greater in the luteal phase than in the follicular phase, these growth factors seem to be quite stable across the 3-year period with follicular ICCs of 0.7 and luteal ICCs of 0.8. Indeed, when IGF-I levels were averaged across the follicular and luteal phases, the ICC approached 0.9. These results are similar to a study where the ICCs for two samples collected 1 year apart in 59 women were 0.8 for IGF-I and 0.6 for IGFBP-3, although when analyses were restricted to premenopausal women, the ICC for IGF-I was 0.6 (37). Spearman rank correlations reported from reproducibility studies conducted across shorter periods (2-8 weeks) among men and women of ages 50 to 97 years ranged from 0.92 (38) to 0.97 (39).
For reference, cholesterol is generally accepted as measured reasonably well with a single blood sample, and the observed ICC over a 1- to 2-year period ranges from 0.65 to 0.76 (40-42). Correlations in this range result in relatively modest decreases in the estimated relative risk, although the degree of attenuation will depend on the magnitude of the relative risk and the sample size (28). For example, measurement error in a variable with an ICC of 0.68 will underestimate a true relative risk of 2.0 and 2.5 to 1.6 and 1.9, respectively (28). For a variable with an ICC of 0.45 (as we observed for the estrone and estradiol in the luteal phase), these true relative risks would be lowered further to 1.4 and 1.5. Besides providing important information on the reproducibility of a variable, ICCs can be used to correct relative risk estimates for random within-person measurement error in epidemiologic studies (30).
The follicular-phase and luteal-phase ICCs for estradiol and for estrone were similar, suggesting that measurement during neither phase is superior in this regard. Not surprisingly, averaging across the phases worsened the ICC. In addition, we calculated an ICC for each using all six sample levels, as this estimate of reliability mimics that underlying past case-control studies in premenopausal women that collected a random blood sample and did not match cases and controls on cycle day of collection. In fact, these ICCs were worse than those of the averaged values (estradiol, 0.02; estrone, 0.08). Interestingly, in both menstrual cycle phases, estrone sulfate was the most reliably measured estrogen, perhaps due to its longer half life compared with estrone and estradiol (31). Our results suggest that estrone sulfate may be the most accurate measure of estrogen levels among premenopausal women. Interestingly, the correlation of estrone sulfate with estradiol was only 0.16 and 0.07 in the follicular and luteal phases, respectively; however, this may be due to the small sample size.
These data among premenopausal women suggest that for androgens, estrone sulfate, prolactin, and IGFs, a single blood measurement can reliably categorize average levels over at least a 3-year period in premenopausal women and is valid for use in the investigation of the relation between endogenous hormone levels and disease risk. For estradiol and estrone, where ICCs were somewhat low, it will be particularly important to use these reproducibility data to correct relative risks (e.g., when assessing plasma hormones and breast cancer risk) for measurement error. We are currently using these data to correct relative risks in our ongoing study of the relation between endogenous premenopausal hormones and growth factors and breast cancer risk.
| Acknowledgments |
|---|
| Footnotes |
|---|
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 11/ 7/05; revised 2/ 8/06; accepted 2/21/06.
| References |
|---|
|
|
|---|
This article has been cited by other articles:
![]() |
M. J. Gunter, D. R. Hoover, H. Yu, S. Wassertheil-Smoller, J. E. Manson, J. Li, T. G. Harris, T. E. Rohan, X. Xue, G. Y.F. Ho, et al. A Prospective Evaluation of Insulin and Insulin-like Growth Factor-I as Risk Factors for Endometrial Cancer Cancer Epidemiol. Biomarkers Prev., April 1, 2008; 17(4): 921 - 929. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. S. Tworoger, I-M. Lee, J. E. Buring, and S. E. Hankinson Plasma Androgen Concentrations and Risk of Incident Ovarian Cancer Am. J. Epidemiol., January 15, 2008; 167(2): 211 - 218. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. G. Harris, R. D. Burk, H. Yu, H. Minkoff, L. S. Massad, D. H. Watts, Y. Zhong, S. Gange, R. C. Kaplan, K. Anastos, et al. Insulin-Like Growth Factor Axis and Oncogenic Human Papillomavirus Natural History Cancer Epidemiol. Biomarkers Prev., January 1, 2008; 17(1): 245 - 248. [Abstract] [Full Text] [PDF] |
||||
![]() |
E. S Schernhammer, S. S Tworoger, A H. Eliassen, S. A Missmer, J. M Holly, M. N Pollak, and S. E Hankinson Body shape throughout life and correlations with IGFs and GH Endocr. Relat. Cancer, September 1, 2007; 14(3): 721 - 732. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. S. Tworoger, I-M. Lee, J. E. Buring, M. N. Pollak, and S. E. Hankinson Insulin-like Growth Factors and Ovarian Cancer Risk: A Nested Case-Control Study in Three Cohorts Cancer Epidemiol. Biomarkers Prev., August 1, 2007; 16(8): 1691 - 1695. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. S. Tworoger, A. H. Eliassen, P. Sluss, and S. E. Hankinson A Prospective Study of Plasma Prolactin Concentrations and Risk of Premenopausal and Postmenopausal Breast Cancer J. Clin. Oncol., April 20, 2007; 25(12): 1482 - 1488. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. S. Tworoger, A. H. Eliassen, S. A. Missmer, H. Baer, J. Rich-Edwards, K. B. Michels, R. L. Barbieri, M. Dowsett, and S. E. Hankinson Birthweight and Body Size throughout Life in Relation to Sex Hormones and Prolactin Concentrations in Premenopausal Women Cancer Epidemiol. Biomarkers Prev., December 1, 2006; 15(12): 2494 - 2501. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. H. Eliassen, S. A. Missmer, S. S. Tworoger, D. Spiegelman, R. L. Barbieri, M. Dowsett, and S. E. Hankinson Endogenous steroid hormone concentrations and risk of breast cancer among premenopausal women. J Natl Cancer Inst, October 4, 2006; 98(19): 1406 - 1415. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Cancer Research | Clinical Cancer Research |
| Cancer Epidemiology Biomarkers & Prevention | Molecular Cancer Therapeutics |
| Molecular Cancer Research | Cancer Prevention Research |
| Cancer Prevention Journals Portal | Cancer Reviews Online |
| Annual Meeting Education Book | Cell Growth & Differentiation |