Affiliations of authors: S. E. Hankinson, G. A. Colditz,Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, and Department of Epidemiology, Harvard School of Public Health, Boston; W. C. Willett, D. S. Michaud, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, and Departments of Epidemiology and Nutrition, Harvard School of Public Health; J. E. Manson, Channing Laboratory, Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School; C. Longcope, Department of Obstetrics and Gynecology and Medicine, University of Massachusetts Medical School, Worcester; B. Rosner, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, and Department of Biostatistics, Harvard School of Public Health; F. E. Speizer, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School and Department of Environmental Health, Harvard School of Public Health.
Correspondence to: Susan E. Hankinson, Sc.D., Department of Medicine, Channing Laboratory, 181 Longwood Ave., Boston, MA 02115.
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The epidemiologic data relating plasma prolactin levels to risk of breast cancer have been limited and the results inconsistent. In postmenopausal women, prolactin levels have been associated with an increased risk in several (10,11), but not all (12-14), case-control studies. Because prolactin secretion can be affected by either physical or psychological stress (15-17), levels in women with breast cancer may not reflect predisease levels. To date, only one prospective study of prolactin and breast cancer risk has been reported (18), with just 40 postmenopausal breast cancer cases, and a nonsignificant positive relationship was observed.
To evaluate the relationship between plasma prolactin levels and breast cancer risk in postmenopausal women, we conducted a nested case-control study within the large prospective Nurses' Health Study (NHS) cohort.
![]() |
METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The NHS cohort was established in 1976 when 121 700 U.S. female registered nurses, 30-55 years of age, completed and returned a mailed questionnaire. The cohort continues to be followed every 2 years by questionnaire to update exposure status and to identify cases of newly diagnosed disease. Data have been collected on risk factors for breast cancer, including height, weight, ages at menarche and menopause, age at first birth, parity, postmenopausal hormone (PMH) use, diagnosis of benign breast disease, and family history of breast cancer. Weight, use of PMH, and diagnosis of benign breast disease have been updated every 2 years.
From 1989 through 1990, blood samples were collected from 32 826 cohort members who were 43-69 years of age at collection. Details regarding the blood collection methods have been published previously (19). Briefly, each woman arranged to have her blood drawn and shipped, via overnight courier and with an icepack, to our laboratory where it was processed and separated into plasma, red blood cell, and white blood cell components. Ninety-seven percent of the samples were received within 26 hours of being drawn. The stability of prolactin in whole blood for 24-48 hours has been previously documented (20). Samples have been archived in continuously monitored liquid nitrogen freezers since collection. At blood collection, women were asked if they were currently using antidepressant medications, many of which (e.g., phenothiazines) can increase prolactin levels. Subjects were not queried about other medications that can alter prolactin levels. As of 1994, the follow-up rate among women who provided a blood sample was 98%. The study was approved by the Committee on the Use of Human Subjects in Research at the Brigham and Women's Hospital.
Both case patients and control subjects are women who were postmenopausal at the time of blood collection. Women were defined as postmenopausal if they reported having a natural menopause (no menstrual cycles in the previous 12 months) or a bilateral oophorectomy, or, for women who reported a hysterectomy and who had either one or both ovaries remaining, when they were 56 (if a nonsmoker) or 54 (if a current smoker) years of ageages at which natural menopause had occurred in 90% of the cohort.
Case patients were women with no reported cancer diagnosis prior to blood collection and who were diagnosed with breast cancer after blood collection, but before June 1, 1994. In all, 337 cases of breast cancer were reported. All cases of breast cancer were confirmed by medical record review with one exception, for which the nurse confirmed the diagnosis but the medical record was unavailable; because of the high confirmation rate (99%) upon medical record review, this case was kept in the analysis. Time from blood collection to diagnosis ranged from less than 1 month to 57 months (mean, 27.8 months). For each case patient who reported PMH use within 3 months prior to blood collection (i.e., "recent use" of PMH) (n = 181), one control was matched per case by age (±2 years), recent PMH use, month of blood collection (±1 month), time of day of blood draw (±2 hours), and fasting status (at least 10 hours since a meal versus <10 hours or unknown). For each case patient who had not reported recent PMH use at blood collection (n = 156), two control subjects were selected using the same matching factors (this was done to increase our statistical power in analyses using only this patient subgroup). Exact control subject matches were obtained for 94% of the patients based on age, 96% based on time of day, and 98% based on month; the most relaxed match was ±5 years of age, ±7 hours, and ±3 months, respectively.
Reproducibility Study
Three hundred ninety NHS participants who gave a first blood sample from 1989 through 1990 were asked to collect two additional samples over the following 2-3 years. The women were postmenopausal, had no prior diagnosis of cancer (except nonmelanoma skin cancer), and had no history of recent PMH use; these criteria were applied at each sample collection. Of the 390 women, 186 (48%) sent two additional samples. A random sample of 80 of these women who had all three samples drawn between 6 AM and 12 noon was sent for prolactin analysis, at the same laboratory as the main study, and forms the basis of the reproducibility study. Details regarding this study have been published elsewhere (21).
Laboratory Analyses
Prolactin was assayed at C. Longcope's laboratory at the University of Massachusetts Medical Center. Prolactin was measured using a microparticle enzyme immunoassay (IMx System; Abbott Laboratory, Abbott Park, IL). The assay detection limit was 0.6 ng/mL; none of our values was less than this limit.
All case-control pairs (or case-control-control triplets) were assayed together; the samples were ordered randomly within a pair (or triplet) and labeled such that the laboratory could not identify case-control status. Although all members of a pair (or triplet) were analyzed at the same time, the pairs (or triplets) were analyzed in two different batches (1993 and 1996). In each batch, we interspersed replicate plasma samples, labeled to preclude their identification by the hormone laboratory, to assess laboratory precision. The intra-assay laboratory coefficient of variation was 7.6%.
We previously measured insulin-like growth factor-I (IGF-I) levels among all of the case patients and control subjects (22) as well as steroid hormone levels (estradiol, estrone, percent-free estradiol, percent-bioavailable estradiol, estrone sulfate, androstenedione, testosterone, dehydroepiandrosterone, and dehydroepiandrosterone sulfate) among the case patients and control subjects who were not using postmenopausal hormones at blood collection (23).
Data Analyses
Prolactin values tended to be higher in the first batch of samples assayed, such that quartile cut points based on all control subjects combined resulted in uneven batch-specific distributions (e.g., the highest quartile contained 41% of batch 1 control subjects and 18% of batch 2). Because the mean levels of the quality control samples varied in the same manner between batches, this difference appeared to be due to laboratory variation over time. We therefore defined batch-specific cut points, based on the distribution of the control values in each batch. The quartile cut points were 6.4, 9.3, and 13.7 ng/mL for batch 1 and 5.9, 7.6, and 9.7 ng/mL for batch 2.
One matched set was removed from the analysis because the case patient's estrogen values were in the premenopausal range. In addition, individual prolactin values more than 2.5-fold higher than the normal range (1.8-18 ng/mL) were removed from the analysis (four case patients and one control subject); however, in a secondary analysis that included these participants, our findings were essentially unchanged. A number of women either did not have plasma available for laboratory analysis or had implausible values related to initial technical difficulties with the assay, resulting in a loss of 25 case patients and 33 control subjects. One case patient and nine control subjects were excluded because the other members of their matched set did not have prolactin values. Overall, 306 case patients (representing 277 invasive, 28 in situ, and one unknown breast cancer) and 448 control subjects were included.
To test for differences in means between case patients and control subjects, we used mixed-effect regression models for clustered data to adjust for possible confounding due to the matching factors and for any residual correlation between case patients and control subjects within the matched set (24). To compare proportions between case patients and control subjects, we employed the Mantel-Haenszel test (25). We used conditional logistic regression analyses to estimate relative risks (RRs) or odds ratios and 95% confidence intervals (95% CIs) (26). Tests for trend were conducted by modeling prolactin levels continuously and calculating a Wald statistic (27). All P values were based on two-sided tests and, if less than .05, considered statistically significant.
The regression calibration method was used to correct point and interval estimates of the RRs for laboratory measurement error and random within-person variation (28-31). The within-person variance was calculated from the reproducibility study and the between-person variance from the case-control study; thus, the intraclass correlation coefficient for prolactin was slightly different from the previously published value (21). Because the measurement error correction methods require that the relationship between exposure and disease be linear on the logistic scale, four knot-restricted cubic spline models (32) for breast cancer incidence in relation to log-transformed prolactin levels were fit to the data. With the use of these graphical techniques as well as significance testing criteria for nonlinearity, prolactin levels did not show evidence of departure from linearity (P = .49).
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
Controlling in addition for levels of plasma IGF-I, another hormone that may influence risk of breast cancer (22,33), did not alter the observed relationship. We also were able to control for plasma levels of several sex steroid hormones among the 145 case patients and 290 control subjects who were not using PMH at the time of blood collection. None of the steroids substantially altered the relationship between plasma prolactin and breast cancer risk. For example, when controlling for quartile of plasma estradiol levels, the RR for the top versus bottom quartile of plasma prolactin changed from 2.45 to 2.35 (95% CI = 1.20-4.61).
We also evaluated this relationship after excluding the 28 case patients with in situ breast cancer and observed that the RRs were slightly strengthened (Table 2). When we excluded case patients who were diagnosed with breast cancer within the
first 2 years of providing their blood sample (and their matched control subjects), the RRs were
very similar to those observed for all case patients and control subjects combined (top versus
bottom quartile comparison RR = 2.39; 95% CI = 1.24-4.61). Ten case
patients and 21 control subjects had reported antidepressant medication use at the time of blood
collection; removing these women from the analysis also did not appreciably alter the RRs.
Controlling for fasting status more tightly (in 2-hour increments) also did not alter our findings.
The RR associated with having prolactin levels at or above the 87.5 percentile (i.e., median of the top quartile) compared with levels at or below the 12.5 percentile (i.e., median of the bottom quartile) was 1.62 (95% CI = 1.12-2.37). The intraclass correlation coefficient for prolactin, measured over a 2- to 3-year period, was .45. Correcting for measurement error resulted in a substantially higher RR for the same contrast in levels (RR = 3.05; 95% CI = 1.27-7.36).
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Our study is larger than all of the previous epidemiologic studies of postmenopausal prolactin levels and risk of breast cancer combined and much larger than the only other published prospective study (n = 40 case patients). Because prolactin is known to be influenced by both physical and emotional stress, the prospective nature of our study is an important strength. The observation of similar RRs after excluding case patients diagnosed in the first 2 years after blood collection further assures that the relationship is not due to an influence of the breast cancer on hormone levels. Although 9% of our case samples were unavailable for analysis, this is unlikely to have been related to their prolactin levels and thus would not bias our RRs. Prolactin levels were measured with excellent precision by the laboratory. However, substantial drift in the prolactin values between the two laboratory batches limited our ability to evaluate the relationship between absolute levels of plasma prolactin and risk of breast cancer; nevertheless, positive findings were observed in each of the two batches. Circulating prolactin has a strong circadian variation (17), increases substantially with a noontime meal (34), andpostmenopausallytends to fluctuate more over time (within a woman) than do most sex steroid hormones (21). To minimize misclassification related to these factors (which would have attenuated our RRs), we closely matched our case patients and control subjects on both time of day of blood draw and fasting status; furthermore, by using multiple hormone measures from a subset of study participants, we were able to correct our RR estimates for the random (and largely biologic) variation in hormone levels that cannot be captured by a single hormone measurement.
Postmenopausal prolactin levels have been evaluated in relation to risk of breast cancer in a few previous studies. In addition to the potential limitations of case-control studies of prolactin described above, these studies were all small, with the largest including just 66 cases (10). In these studies, either a positive association (10,11) or essentially no association (12-14) between prolactin and breast cancer has been observed. In the only previous prospective study (18), women in the top quintile of prolactin levels were at a nonsignificant 63% higher risk of breast cancer compared with those in the bottom quintile, results comparable to our findings. Epidemiologic data on premenopausal prolactin levels and breast cancer risk are similarly sparse (10,11,13,18,35,36) and thus additional assessments are needed.
Long-term recent use of both oral contraceptives and postmenopausal hormones has been associated with an increased risk of breast cancer (37,38). The increase in prolactin levels observed with use of these hormones (17) could conceivably be playing a role in this effect. Other medications also are known to increase (e.g., reserpine, haldol, cimetidine, and phenothiazines) or decrease (e.g., levodopa) plasma prolactin levels (17). Of these, the relationship between reserpine use, an antihypertensive medication, and breast cancer risk has been evaluated most extensively. Reserpine initially causes an acute elevation of prolactin; however, long-term use (>5 years' duration) results in about a 50% elevation in plasma levels (39). Although a positive association between reserpine use and breast cancer was noted in several previous studies (40-42), this finding has not been consistently observed (43-48). Reasons for this lack of consistency may include the small size of many of the studies and the exposure definition used (e.g., most investigators reported the relationship with "ever use" of reserpine only). If prolactin is a promoter rather than an initiator of breast cancer (as would seem most likely), only longer durations of use might be expected to have a discernible influence on risk, as is observed with postmenopausal hormone use (37). Further assessment of this and other medications known to alter prolactin levels, including an evaluation of the effect of duration of medication use, is warranted.
Several indirect lines of evidence suggest prolactin could play a role in breast carcinogenesis. Although prolactin is secreted primarily by the anterior pituitary, expression in both normal (49) and malignant (49-51) breast tissue has been reported. In addition, prolactin receptors have been found on more than 50% of breast tumors (52,53). Prolactin also increases DNA synthesis of breast cancer cells in vitro(5-7) and the hormone's removal inhibits the growth rate of epithelial cells from nonmalignant breast tissue (54). These findings have not been universal (8,9), however, and might relate to the amount or type of prolactin used or the prolactin receptor status of the cells (5). Prolactin administration also is well documented to increase rates of mammary tumors in mice (3).
Several forms of prolactin circulate in human plasma, including the native hormone (23 kd), a 16-kd fragment (55,56), and several glycosylated forms (57,58). These different forms appear to have varying bioactivities (59,60) and perhaps differing biologic actions (60,61). Which isoform(s) are most implicated in increasing the risk of breast cancer is unknown. The two laboratory methods used most commonly to assess prolactin levels are immunoassay (which we used) and bioassay. Immunoassay will identify most prolactin isoforms, but to differing degrees (62); this assay is unable to distinguish between these different forms. The correlation between the two assays has generally been reported to be high (63,64); however, this may vary by study population as a differential release of prolactin isoforms can occur (17,58,65).
Most research on endogenous hormones and breast cancer has focused on plasma estrogens (4,66). The positive relationship we observe between plasma prolactin levels and the risk of breast cancer is generally similar in magnitude to that observed for plasma estrogen levels and breast cancer. Because our study provides the first detailed evaluation of this relationship, additional prospective assessments are warranted.
![]() |
NOTES |
---|
We thank the participants in the Nurses' Health Study for their continuing dedication and commitment and Rachel Meyer, Michele Lachance, Charlotte Bukowski, MaryAnn Grigg, Kathryn Starzyk, Jeanne Sparrow, and Sandra Melanson for their expert assistance on this project. We also thank Dr. Donna Spiegelman for her input into the statistical analysis.
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
1 Vonderhaar BK. Prolactin transport, function, and receptors in mammary gland development and differentiation. In: Neville MC, Daniels CW, editors. The mammary gland development, regulation and function. New York (NY): Plenum Press; 1987. p. 383-438.
2 Meites J. Biological functions of prolactin in mammals. In: Hoshino K, editor. Prolactin gene family and its receptors. Molecular biology to clinical problems. Proceedings of the Fifth International Congress on Prolactin, Kyoto, Japan, 13-16 July 1988. Amsterdam (The Netherlands): Elsevier; 1988. p. 123-30.
3 Welsch CW, Nagasawa H. Prolactin and murine mammary tumorigenesis: a review. Cancer Res 1977;37:951-63.[Abstract]
4 Bernstein L, Ross RK. Endogenous hormones and breast cancer risk. In: Kelsey JL editor. Epidemiologic reviews. Baltimore (MD): The Johns Hopkins University School of Hygiene and Public Health; 1993. p. 48-65.
5 Peyrat JP, Djiane J, Bonneterre J, Vandewalle B, Vennin PH, Delobelle A, et al. Stimulation of DNA synthesis by prolactin in human breast tumor explants. Relation to prolactin receptors. Anticancer Res 1984;4:257-61.[Medline]
6 Malarkey WB, Kennedy M, Allred LE, Milo G. Physiological concentrations of prolactin can promote the growth of human breast tumor cells in culture. J Clin Endocrinol Metab 1983;56:673-7.[Abstract]
7 Simon WE, Albrecht M, Trams G, Dietel M, Holzel F. In vitro growth promotion of human mammary carcinoma cells by steroid hormones, tamoxifen, and prolactin. J Natl Cancer Inst 1984;73:313-21.[Medline]
8 Calaf G, Garrido F, Moyano C, Rodriguez R. Influence of hormones on DNA synthesis of breast tumors in culture. Breast Cancer Res Treat 1986;8:223-32.[Medline]
9 Beeby DI, Easty GC, Gazet JC, Grigor K, Neville AM. An assessment of the effects of hormones on short term organ cultures of human breast carcinomata. Br J Cancer 1975;31:317-28.[Medline]
10 Rose DP, Pruitt BT. Plasma prolactin levels in patients with breast cancer. Cancer 1981;48:2687-91.[Medline]
11 Ingram DM, Nottage EM, Roberts AN. Prolactin and breast cancer risk. Med J Aust 1990;153:469-73.[Medline]
12 Malarkey WB, Schroeder LL, Stevens VC, James AG, Lanese RR. Disordered nocturnal prolactin regulation in women with breast cancer. Cancer Res 1977;37:4650-4.[Abstract]
13 Secreto G, Recchione C, Cavalleri A, Miraglia M, Dati V. Circulating levels of testosterone, 17ß-oestradiol, luteinising hormone and prolactin in postmenopausal breast cancer patients. Br J Cancer 1983;47:269-75.[Medline]
14 Bernstein L, Ross RK, Pike MC, Brown JB, Henderson BE. Hormone levels in older women: a study of post-menopausal breast cancer patients and healthy population controls. Br J Cancer 1990;61:298-302.[Medline]
15 Berger RL, Joison J, Braverman LE. Lactation after incision on the thoracic cage. N Engl J Med 1966;274:1493-5.[Medline]
16 Herman V, Kalk WJ, de Moor NG, Levin J. Serum prolactin after chest wall surgery: elevated levels after mastectomy. J Clin Endocrinol Metab1981 ;52:148-51.[Abstract]
17 Yen SS, Jaffe RB, editors. Reproductive endocrinology. 3rd ed. Philadelphia (PA): Saunders; 1991.
18 Wang DY, De Stavola BL, Bulbrook RD, Allen DS, Kwa HG, Fentiman IS, et al. Relationship of blood prolactin levels and the risk of subsequent breast cancer. Int J Epidemiol 1992;21:214-21.[Abstract]
19 Hankinson SE, Willett WC, Manson JE, Hunter DJ, Colditz GA, Stampfer MJ, et al. Alcohol, height, and adiposity in relation to estrogen and prolactin levels in postmenopausal women. J Natl Cancer Inst 1995;87:1297-302.[Abstract]
20
Hankinson SE, London SJ, Chute CG, Barbieri RL, Jones L,
Kaplan LA, et al. Effect of transport conditions on the stability of biochemical markers in blood. Clin Chem 1989;35:2313-6.
21 Hankinson SE, Manson JE, Spiegelman D, Willett WC, Longcope C, Speizer FE. Reproducibility of plasma hormone levels in postmenopausal women over a two to three year period. Cancer Epidemiol Bio Prev 1995;4:649-54.[Abstract]
22 Hankinson S, Willett WC, Colditz GA, Hunter DJ, Michaud DS, Deroo B, et al. Circulating concentrations of insulin-like growth factor-I and risk of breast cancer. Lancet 1998;351:1393-6.[Medline]
23
Hankinson SE, Willett WC, Manson JE, Colditz GA, Hunter
DJ, Spiegelman D, et al. Plasma sex steroid hormone levels and risk of breast cancer in
postmenopausal women. J Natl Cancer Inst 1998;90:1292-9.
24 Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986;73:13-22.
25 Rothman KJ. Modern epidemiology. Boston (MA): Little, Brown; 1986.
26 Rosner B. Fundamentals of biostatistics. Belmont (CA): Wadsworth; 1993.
27 Hosmer DW, Lemeshow S. Applied logistic regression. New York (NY): John Wiley & Sons; 1989.
28 Carroll RJ, Ruppert D, Stefanski LA. Measurement error in nonlinear models. London (U.K.): Chapman & Hall; 1995.
29 Prentice RL. Covariate measurement errors and parameter estimation in a failure time regression model. Biometrika 1982;69:331-42.
30 Wang CY, Hsu L, Feng ZD, Prentice RL. Regression calibration in failure time regression. Biometrics 1997;53:131-45.[Medline]
31 Spiegelman D, McDermott A, Rosner B. Regression calibration method for correcting measurement-error bias in nutritional epidemiology. Am J Clin Nutr 1997;65(4 Suppl):1179S-1186S.[Abstract]
32 Durrleman S, Simon R. Flexible regression models with cubic splines. Stat Med 1989;8:551-61.[Medline]
33 Bruning PF, Van Doorn J, Bonfrer JM. Insulin-like growth-factor-binding protein 3 is decreased in early-stage operable premenopausal breast cancer [published erratum appears in Int J Cancer 1995;63:762]. Int J Cancer 1995;62:266-70.[Medline]
34 Ishizuka B, Quigley ME, Yen SS. Pituitary hormone release in response to food ingestion: evidence for neuroendocrine signals from gut to brain. J Clin Endocrinol Metab 1983;57:1111-6.[Abstract]
35 Meyer F, Brown JB, Morrison AS, MacMahon B. Endogenous sex hormones, prolactin, and breast cancer in premenopausal women. J Natl Cancer Institute 1986;77:613-6.[Medline]
36 Love RR, Rose DR, Surawicz TS, Newcomb PA. Prolactin and growth hormone levels in premenopausal women with breast cancer and healthy women with a strong family history of breast cancer. Cancer 1991;68:1401-5.[Medline]
37 Collaborative Group on Hormonal Factors in Breast Cancer. Breast cancer and hormone replacement therapy: collaborative reanalysis of data from 51 epidemiological studies of 52 705 women with breast cancer and 108 411 women without breast cancer. Lancet 1997;350:1047-59.[Medline]
38 Collaborative Group on Hormonal Factors in Breast Cancer. Breast cancer and hormonal contraceptives: collaborative reanalysis of individual data on 53 297 women with breast cancer and 100 239 women without breast cancer from 54 epidemiological studies. Lancet 1996;347:1713-27.[Medline]
39 Ross RK, Paganini-Hill A, Krailo MD, Gerkins VR, Henderson BE, Pike MC. Effects of reserpine on prolactin levels and incidence of breast cancer in postmenopausal women. Cancer Res 1984;44:3106-8.[Abstract]
40 Reserpine and breast cancer. Lancet 1974;2:669-71.[Medline]
41 Heinonen OP, Shapiro S, Tuominen L, Turunen MI. Reserpine use in relation to breast cancer. Lancet 1974;2:675-7.[Medline]
42 Armstrong B, Skegg D, White G, Doll R. Rauwolfia derivatives and breast cancer in hypertensive women. Lancet 1976;2:8-12.[Medline]
43 Mack TM, Henderson BE, Gerkins VR, Arthur M, Baptista J, Pike MC. Reserpine and breast cancer in a retirement community. N Engl J Med 1975;292:1366-71.[Abstract]
44 Aromaa A, Hakama M, Hakulinen T, Saxen E, Teppo L, Ida lan-Heikkila J. Breast cancer and use of rauwolfia and other antihypertensive agents in hypertensive patients: a nationwide case-control study in Finland. Int J Cancer 1976;18:727-38.[Medline]
45 Laska EM, Siegel C, Meisner M, Fischer S, Wanderling J. Matched-pairs study of reserpine use and breast cancer. Lancet 1975;2:296-300.[Medline]
46 Curb JD, Hardy RJ, Labarthe DR, Borhani NO, Taylor JO. Reserpine and breast cancer in the Hypertension Detection and Follow-Up Program. Hypertension 1982;4:307-11.[Abstract]
47 Labarthe DR, O'Fallon WM. Reserpine and breast cancer: a community-based longitudinal study of 2,000 hypertensive women. JAMA 1980;243:2304-10.[Abstract]
48 Shapiro S, Parsells JL, Rosenberg L, Kaufman DW, Stolley PD, Schottenfeld D. Risk of breast cancer in relation to the use of rauwolfia alkaloids. Eur J Clin Pharmacol 1984;26:143-6.[Medline]
49 Fields K, Kulig E, Lloyd RV. Detection of prolactin messenger RNA in mammary and other normal and neoplastic tissues by polymerase chain reaction. Lab Invest 1993;68:354-60.[Medline]
50 Clevenger CV, Chang WP, Ngo W, Pasha TL, Montone KT, Tomaszewski JE. Expression of prolactin and prolactin receptor in human breast carcinoma. Evidence for an autocrine/paracrine loop. Am J Pathol 1995;146:695-705.[Abstract]
51 Ginsburg E, Vonderhaar BK. Prolactin synthesis and secretion by human breast cancer cells. Cancer Res 1995;55:2591-5.[Abstract]
52 Partridge RK, Hahnel R. Prolactin receptors in human breast carcinoma. Cancer 1979;43:643-6.[Medline]
53 Peyrat JP, Dewailly D, Djiane J, Kelly PA, Vandewalle B, Bonneterre J, et al. Total prolactin binding sites in human breast cancer biopsies. Breast Cancer Res Treat 1981;1:369-73.[Medline]
54 Takahashi K, Kawahara S, Ono T. Effects of growth factors and hormones on growth and morphological differentiation of human breast epithelial cells within collagen gel in serum-free medium. Jpn J Cancer Res 1990;81:52-7.[Medline]
55 Sinha YN, Gilligan TA, Lee DW, Hollingsworth D, Markoff E. Cleaved prolactin: evidence for its occurrence in human pituitary gland and plasma. J Clin Endocrinol Metab 1985;60:239-43.[Abstract]
56 Pellegrini I, Gunz G, Ronin C, Fenouillet E, Peyrat JP, Delori P, et al. Polymorphism of prolactin secreted by human prolactinoma cells: immunological, receptor binding, and biological properties of the glycosylated and nonglycosylated forms. Endocrinology 1988;122:2667-74.[Abstract]
57 Warner MD, Sinha YN, Peabody CA. Growth hormone and prolactin variants in normal subjects. Relative proportions in morning and afternoon samples. Horm Metab Res 1993;25:425-9.[Medline]
58 Brue T, Caruso E, Morange I, Hoffmann T, Evrin M, Gunz G, et al. Immunoradiometric analysis of circulating human glycosylated and nonglycosylated prolactin forms: spontaneous and stimulated secretions. J Clin Endocrinol Metab 1992;75:1338-44.[Abstract]
59 Hoffmann T, Penel C, Ronin C. Glycosylation of human prolactin regulates hormone bioactivity and metabolic clearance. J Endocrinol Invest 1993;16:807-16.[Medline]
60 Sinha YN. Structural variants of prolactin: occurrence and physiological significance. Endocr Rev 1995;16:354-69.[Medline]
61 Clapp C, Martial JA, Guzman RC, Rentier-Delrue F, Weiner RI. The 16-kilodalton N-terminal fragment of human prolactin is a potent inhibitor of angiogenesis. Endocrinology 1993;133:1292-9.[Abstract]
62 Haro LS, Lee DW, Singh RN, Bee G, Markoff E, Lewis UJ. Glycosylated human prolactin: alterations in glycosylation pattern modify affinity for lactogen receptor and values in prolactin radioimmunoassay. J Clin Endocrinol Metab 1990;71:379-83.[Abstract]
63 Tanaka T, Shiu RP, Gout PW, Beer CT, Nobel RL, Friesen HG. A new sensitive and specific bioassay for lactogenic hormones: measurement of prolactin and growth hormone in human serum. J Clin Endocrinol Metab 1980;51:1058-63.[Abstract]
64 Maddox PR, Jones DL, Mansel RE. A new microbioassay for the measurement of lactogenic hormones in human serum. Horm Res 1989;32:218-23.
65 Liu JH, Lee DW, Markoff E. Differential release of prolactin variants in postpartum and early follicular phase women. J Clin Endocrinol Metab 1990;71:605-10.[Abstract]
66 Thomas HV, Reeves GK, Key TJ. Endogenous estrogen and postmenopausal breast cancer: a quantitative review. Cancer Causes Control 1997;8:922-8.[Medline]
Manuscript received August 19, 1998; revised January 6, 1999; accepted January 28, 1999.
This article has been cited by other articles in HighWire Press-hosted journals:
![]() |
||||
|
Oxford University Press Privacy Policy and Legal Statement |