Hormonal and reproductive risk factors for ... - Wiley Online Library

ARTHRITIS & RHEUMATISM Vol. 46, No. 7, July 2002, pp 1830–1839 DOI 10.1002/art.10365 © 2002, American College of Rheumatology

Hormonal and Reproductive Risk Factors for Development of Systemic Lupus Erythematosus Results of a Population-Based, Case–Control Study Glinda S. Cooper,1 Mary Anne Dooley,2 Edward L. Treadwell,3 E. William St.Clair,4 and Gary S. Gilkeson5 Objective. Estrogen and prolactin may accelerate the progression of murine systemic lupus erythematosus (SLE). In humans, 85% of lupus patients are women, which also suggests the importance of hormonal factors in disease pathogenesis. The purpose of this study was to examine hormonal and reproductive risk factors for lupus among women. Methods. This population-based, case–control study included 240 female SLE patients diagnosed between January 1, 1995 and July 31, 1999 who fulfilled the American College of Rheumatology classification criteria. Female controls (n ⴝ 321) were identified through driver’s license records. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) as measures of association, adjusting for age, state, race, and education. Analyses were limited to exposures before diagnosis. Results. Breast-feeding was associated with a decreased risk of developing SLE (OR 0.6, 95% CI 0.4– 0.9), with a statistically significant trend for number of babies breast-fed and total weeks of breast-feeding. There were no associations with number of pregnancies or live

births. Natural menopause occurred earlier in women with subsequent development of SLE compared with controls (P < 0.001). There was little association between SLE and current use or duration of use of hormone replacement therapy or oral contraceptives, and no association with previous use of fertility drugs. Conclusion. We found little evidence that estrogen- or prolactin-related exposures are associated with an increased risk of lupus. The reduced risk observed among women who had breast-fed one or more babies should be examined in other studies. Early natural menopause, rather than decreasing risk of SLE because of reduced estrogen exposure, may be a marker of susceptibility to development of SLE. Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease characterized by the production of non–organ-specific autoantibodies. Significant health consequences include renal failure, vasculitis, thrombosis, and seizures and other neurologic complications (1). SLE most often affects young adults (median age at diagnosis ⬍40 years) (2,3), and the incidence and prevalence of SLE are at least 3 times higher in African Americans and African Caribbeans compared with whites (4). Almost all autoimmune diseases are more common in women, but the female predominance in SLE is particularly strong. At least 85% of patients with SLE are women (5). Reduced androgen levels, increased 16 ␣-hydroxylation of estradiol, and increased prolactin levels have been reported in SLE patients (6–9). Additional evidence that hormonal differences may contribute to the increased risk of SLE experienced by women comes from experimental studies in mouse models of SLE demonstrating disease exacerbation by estrogen

Supported by the National Institute of Environmental Health Sciences Intramural Research Program and the National Center for Minority Health and Health Disparities, NIH. 1 Glinda S. Cooper, PhD: National Institute of Environmental Health Sciences, Durham, North Carolina; 2Mary Anne Dooley, MD, MPH: University of North Carolina, Chapel Hill; 3Edward L. Treadwell, MD: East Carolina University School of Medicine, Greenville, North Carolina; 4E. William St.Clair, MD: Duke University Medical Center, Durham, North Carolina; 5Gary S. Gilkeson, MD: Ralph H. Johnson Veterans Administration Medical Center, Charleston, South Carolina, and Medical University of South Carolina, Charleston. Address correspondence and reprint requests to Glinda S. Cooper, PhD, Epidemiology Branch A3-05, NIEHS, PO Box 12233, Durham, NC 27709-12233. E-mail: [email protected]. Submitted for publication July 19, 2001; accepted in revised form March 11, 2002. 1830

HORMONAL AND REPRODUCTIVE RISK FACTORS FOR SLE

and prolactin and amelioration by androgens (10–12). However, hormonal differences between males and females do not fully explain the age and sex distribution of SLE and of other autoimmune diseases (13,14) and cannot explain differences in risk within each sex. Few epidemiologic studies have examined hormonal or reproductive risk factors for the development of SLE. We examined pregnancy history, use of hormones, and markers of endogenous sources of exposure to estrogen and prolactin (e.g., age at menarche, age at natural menopause, history of breast-feeding) in relation to risk of developing SLE in the present population-based, case–control study. PATIENTS AND METHODS Study participants. The Carolina Lupus Study is based in 60 contiguous counties in eastern and central North Carolina and South Carolina. Thirty of the 40 community-based rheumatologists in the study area agreed to participate by referring eligible patients to the study, 7 other practices displayed a poster and brochures about the study, and 3 did not participate. At the university practices and at 14 of the community-based practices, we reviewed the medical records of lupus patients seen during the study period to identify eligible patients. These 14 practices were the larger practices in the study area. We used a system of monthly phone calls to the physician and designated office staff, as well as periodic letters and other reminders to solicit eligible referrals at the 16 other community-based practices. The study protocol was approved by the review boards at all participating institutions. Eligibility was based on fulfillment of the revised American College of Rheumatology classification criteria for SLE (15,16), diagnosis between January 1, 1995 and July 31, 1999, age ⱖ18 years at study enrollment, residence within the study area during at least 6 months of the year prior to diagnosis, and ability to speak and understand English. We received 285 referrals of patients who were eligible for the study based on medical record data pertaining to the diagnostic criteria. Six patients refused screening (the initial telephone call to ascertain residence before diagnosis) and 14 declined to participate, leaving a total of 265 case participants (93% of referred patients). The median time from diagnosis to study interview was 13 months, and 75% of patients were interviewed within 1.7 years of diagnosis. Population-based controls were identified through driver’s license records and were frequency-matched to the cases by age (5-year age groups), sex, and state. Eligibility criteria were the same as the nonmedical criteria used for cases, with the additional criterion of never having been diagnosed as having any kind of lupus. Participation rates in epidemiologic studies tend to be lower in minority groups (17), and we therefore did not enroll a randomly selected portion (one-third) of the white controls. This was done to ensure that the racial distribution of the controls would reflect the racial distribution of the source population, which was estimated using census data for the counties in our study area (online at http://factfinder.census.gov). From the driver’s license records,

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we selected 962 controls who could be reached for telephone screening; 163 refused screening, 195 were screened and were not eligible, 120 were screened and eligible for the study but declined to participate, 129 were eligible and agreed to participate but were not selected for enrollment, and 355 (75% of the screened and eligible controls who were not deferred) participated in the study. Data collection. Data collection included a structured, 60-minute, in-person interview to obtain an extensive reproductive and menstrual history that included information on age at menarche, age at and type of menopause, pregnancy history (age at and outcome of all pregnancies), and breast-feeding history (for each live birth, we asked the subject if she had breast-fed for at least 2 weeks and, if so, for how many weeks), as well as use of oral contraceptives (years of use and reasons for discontinuation), other hormonal contraceptives, and hormone replacement therapy. This information was recorded by age using a reproductive history calendar. We also asked about infertility and use of fertility drugs, other aspects of gynecologic history, and menstrual cycle duration for years during which hormonal contraceptives were not being used and the participant was not pregnant. Response categories for the menstrual cycle questions were ⱕ24 days, 25–30 days, 31–34 days, 35–60 days, infrequent (⬎2 months apart), and irregular (participant could not tell within 1 week when her period would come). The interview also included information on education level and smoking history. After data collection had begun, a report by Holzgreve et al indicated that a significantly higher level of fetal cells in maternal cell circulation could be seen in women with preeclampsia (18). Because we were interested in the possible relation, proposed by Nelson (14), between maternal–fetal cell circulation as a source of microchimerism and development of autoimmune disease, we added a question to the interview about history of preeclampsia or eclampsia during pregnancy. Data for this question are missing for 154 women (79 patients, 75 controls) who had been pregnant but who were interviewed before this question was added. We abstracted data pertaining to the diagnosis of SLE and the course of the disease from patients’ medical records. The abstracting was done by a combination of the investigators (one rheumatologist at each institution and an epidemiologist trained for this purpose by two of the rheumatologists). A rheumatologist reviewed the original data from all of the university-based practices. The epidemiologist reviewed the original data from all of the community-based practices and from three of the university-based practices as an additional check on completeness and interabstracter agreement. In addition, any ambiguous or confusing information was presented to two rheumatologists for review. Reviewers were not blinded to hypotheses, but were blinded to exposure information collected in the study. Common clinical features in the female patients that occurred up to 6 months postdiagnosis included arthritis (74%), photosensitivity (38%), malar rash (37%), pleuritis (36%), and proteinuria (23%); 98% of the female patients were positive for antinuclear antibodies. Analysis. Ninety percent of the SLE patients in the Carolina Lupus Study are female, and analysis of menstrual and reproductive risk factors was limited to the 240 female patients and 321 female controls. Controls were randomly assigned a reference month and year to correspond to the

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Table 1. Demographic characteristics of female patients and controls in the Carolina Lupus Study*

Age in years† 15–24 25–34 35–44 45–54 55–64 65–81 Ethnicity African American White Other‡ Education Less than high school Completed high school Some college Completed college

Patients (n ⫽ 240)

Controls (n ⫽ 321)

42 (18) 79 (33) 46 (19) 41 (17) 17 (7) 15 (6)

44 (14) 92 (29) 70 (22) 64 (20) 29 (9) 22 (7)

150 (63) 75 (31) 15 (6)

89 (28) 206 (64) 26 (8)

54 (23) 61 (25) 71 (30) 54 (23)

27 (8) 70 (22) 117 (36) 107 (33)

* Values are the number (%). † At diagnosis for patients or corresponding reference age for controls. ‡ Includes American Indians, Asians, and Hispanics.

frequency distribution of the diagnosis months and years of patients. Analyses were limited to experiences that occurred either before the age at diagnosis for patients or before the reference age for controls. We used unconditional logistic regression to examine the association between menstrual and reproductive factors and the risk of developing SLE. The associations were estimated as odds ratios (ORs) and 95% confidence intervals (95% CIs) and were adjusted for potential confounders. Confounders are factors that are associated both with the disease and with an exposure. Confounders can lead to a biased estimate of the relation between exposure and disease if the confounder is not adequately addressed in the analysis. An example within this study is race, in that the risk of developing SLE is higher among African Americans (4), and African Americans may, on average, have a younger age at menarche (19). Age at menarche could thus appear to be associated with SLE solely because of its association with race, if race was not included in the analysis. We adjusted for age, state, race, and education in all models. Since we limited the analyses of reproductive and hormonal factors to women, we controlled for sex as well. We also conducted additional stratified analyses for African Americans and whites to examine whether effect estimates differed between groups. Matching can improve the efficiency (that is, the cost) of a study in situations in which there is a large imbalance between cases and controls in the frequency of the confounding factor (e.g., if 90% of the patients were African American compared with 10% of the controls). Matching by race is not necessary, however, to produce unbiased effect estimates (20) and was not necessary in this study because the major ethnic groups (African Americans and whites) were adequately represented among both cases and controls (Table 1). We assessed the goodness of fit and effect on effect estimates of age as continuous and categorical (5-year age groups) variables. There was little difference, and the results

we present are adjusted for age as a continuous variable. All analyses were conducted using SAS software (SAS Institute, Cary, NC). Women who have never been pregnant can be excluded from analyses of pregnancy-related outcomes, such as gravidity, parity, and lactation history, or they can be included in the referent (“no exposure”) group. The former approach is appropriate if the exposure is thought of as a characteristic of the women that manifests itself during pregnancy, so that data on this characteristic are missing in the absence of a pregnancy. The latter approach is appropriate if the absence of a pregnancy is equivalent to a pregnancy that did not produce the exposure. We were interested in breast-feeding as a marker of prolactin exposure. Therefore, women who were never pregnant were considered “unexposed” and included in the referent group. For the analysis of age at natural menopause, we used survival curves to compare the “survival” of ovarian function among cases and controls, censoring at surgical menopause (i.e., hysterectomy or bilateral oophorectomy) or diagnosis/ reference age. This analysis is of ovarian function before diagnosis and does not include ovarian failure that may occur as a consequence of cyclophosphamide therapy. We used proportional hazards modeling to estimate the risk of experiencing natural menopause among women who subsequently develop SLE, adjusting for state, race, education, and smoking (current, ex-, and nonsmoker). Smoking was included in this model because women who smoke cigarettes experience natural menopause 1–2 years earlier than women who have never smoked (21). A similar strategy was used to analyze the probability of undergoing surgical menopause as a risk factor for the development of SLE. The onset of SLE can be difficult to pinpoint, and symptoms may occur over a period of years before the diagnosis is made. In our study, most patients (60%) reported a duration of ⬍1 year between occurrence of the first symptom and diagnosis, 13% reported a duration of 1–2 years, 6% reported a duration of 3–4 years, and 20% reported a duration of ⱖ5 years. To examine the potential influence of the longer-onset cases on our results, we repeated the analyses excluding patients who reported ⱖ5 years between initial symptom and diagnosis. Results were similar using this morelimited sample. Since controls were selected from the state driver’s license registries, we also repeated the analyses excluding 24 female patients (10%) who reported that they did not have a state-issued driver’s license. This exclusion had little effect on any of the measures examined. We present the results from the full sample.

RESULTS The mean age at diagnosis was 38 years in female patients, but African American women had a younger mean age than white women (37 years versus 42 years; P ⬍ 0.001 by t-test). The age distribution was similar in controls, since this was one of the matching criteria used in sampling. Sixty-three percent of female SLE patients were African American (Table 1), and the racial distri-


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Table 2. Associations between pregnancy, lactation, and risk of developing systemic lupus erythematosus Total sample

No. of pregnancies 0 1 2 3 4 ⱖ5 No. of live births‡ 0 1 2 3 ⱖ4 No. of babies breast-fed§ 0 1 2 ⱖ3 Weeks of breast-feeding§ 0 2–12 13–51 ⱖ52 History of preeclampsia¶ Yes No

African Americans

Whites

Patients (n ⫽ 240)*

Controls (n ⫽ 321)*

Adjusted OR†

95% CI

Adjusted OR†

95% CI

Adjusted OR†

95% CI

51 (21) 42 (18) 58 (24) 40 (17) 23 (10) 26 (11)

77 (24) 47 (15) 74 (23) 57 (18) 38 (12) 28 (9)

1.0 1.1 1.2 1.1 0.8 0.9

Referent 0.6–2.1 0.7–2.0 0.6–2.1 0.4–1.7 0.4–2.0

1.0 1.6 1.7 1.2 1.1 0.7

Referent 0.7–3.9 0.7–4.1 0.5–3.2 0.4–3.3 0.2–2.3

1.0 0.9 0.9 0.7 0.4 1.2

Referent 0.3–2.2 0.4–2.0 0.3–1.8 0.1–1.5 0.4–3.7

69 (29) 51 (21) 58 (24) 35 (15) 27 (11)

93 (29) 64 (20) 84 (26) 51 (16) 29 (9)

1.0 1.0 1.3 1.3 1.1

Referent 0.6–1.8 0.7–2.3 0.7–2.7 0.5–2.6

1.0 1.6 1.3 1.4 1.4

Referent 0.7–3.8 0.6–3.2 0.5–3.8 0.5–3.8

1.0 0.8 1.1 0.8 1.4

Referent 0.3–2.1 0.4–2.5 0.3–2.5 0.4–5.5

186 (78) 36 (15) 12 (5) 6 (3)

207 (64) 57 (18) 34 (11) 23 (7)

1.0 0.9 0.4 0.3

Referent 0.5–1.4 0.2–0.9 0.1–0.8

1.0 1.3 0.5 0.3

Referent 0.5–3.2 0.2–1.6 0.1–1.0

1.0 0.7 0.3 0.3

Referent 0.3–1.4 0.1–1.1 0.1–1.5

186 (78) 23 (10) 21 (9) 10 (4)

207 (64) 47 (15) 36 (11) 31 (10)

1.0 0.7 0.7 0.4

Referent 0.4–1.3 0.4–1.3 0.2–0.9

1.0 1.2 0.6 0.5

Referent 0.4–3.4 0.2–1.7 0.2–1.6

1.0 0.5 0.8 0.3

Referent 0.2–1.1 0.3–1.9 0.1–1.0

10 (6) 151 (94)

6 (2) 240 (98)

3.7 1.0

1.2–11.2 Referent

2.5 1.0

0.5–13.1 Referent

3.8 1.0

0.9–16.2 Referent

* Values are the number (%). † Logistic regression adjusted for age (continuous), race (white, African American, or other minority groups), state, and education (did not complete high school, completed high school, completed some college or technical school, or graduated from college) was used to examine associations, which were estimated as odds ratios (ORs) and 95% confidence intervals (95% CIs). ‡ Also adjusted for lactation history (no. of babies breast-fed). § Women who were never pregnant or who had no live births are included in the referent group (no lactation). A positive history of lactation is defined as ⱖ2 weeks. Weeks of breast-feeding are summed across all pregnancies. ¶ Women who were never pregnant are included in the referent group (no history of preeclampsia). Data are missing for 79 patients and 75 controls who were interviewed before this question was added to the interview.

bution of female controls was similar to that of the population in the study area. There was no association between risk of developing SLE and number of pregnancies or live births (Table 2). However, we observed an inverse association between lactation and risk of developing SLE: 23% of patients compared with 36% of controls had breast-fed a baby for ⱖ2 weeks (OR 0.6, 95% CI 0.4–0.9). A statistically significant trend (P ⬍ 0.001) using the ordinal variables was seen with number of babies breastfed and total number of weeks of breast-feeding summed across pregnancies (Table 2). These associations were not appreciably altered when adjusted for number of live births. Similar associations were seen in race-stratified analyses (for African Americans, ever lactated OR 0.7 [95% CI 0.4–1.4]; for whites, ever lactated OR 0.5 [95% CI 0.3–1.0]). The observed asso-

ciations were also seen in age-stratified analyses (for age ⬍40 years, ever lactated OR 0.5 [95% CI 0.3–0.9]; for age ⱖ40 years, ever lactated OR 0.7 [95% CI 0.4–1.3]). A history of preeclampsia was associated with increased risk of developing SLE (OR 3.7) (Table 2). When 59 patients and 88 controls who had never been pregnant were excluded, the association was similar but slightly stronger (OR 5.3, 95% CI 1.6–17.7). The preeclampsia occurred a minimum of 3 years before SLE diagnosis. There was little difference between patients and controls in menopausal status at diagnosis age (patients) or reference age (controls): 29 patients (12%) and 37 controls (12%) had experienced natural menopause, and 46 patients (19%) and 66 controls (21%) had undergone surgical menopause. There was no association between age at surgical menopause and disease status (P ⫽ 0.46

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years) was associated with an increased risk of SLE (OR 4.7), but this association was not statistically significant. Short cycles (ⱕ24 days) during the postmenarche years were associated with an increased risk of SLE compared with cycles of 25–30 days, but an increased risk was also seen with longer cycles (31–34 days). There was little association with severity of menstrual pain and cramps or with a history of endometriosis, but a history of dysfunctional uterine bleeding was more common among patients (Table 4). The association with dysfunctional uterine bleeding was not appreciably altered by additional adjustment for endometriosis. DISCUSSION

Figure 1. Cumulative distribution of the probability of experiencing natural menopause among women who subsequently developed systemic lupus erythematosus (SLE; cases) compared with women who did not develop SLE (controls). Observations are censored at surgical menopause or age at diagnosis (for cases) or at the reference age (for controls; see Patients and Methods).

by log-rank test of survival curves). However, natural menopause occurred earlier in women with subsequent development of SLE. Six of the 29 postmenopausal patients (21%) reported having their last menstrual period before age 45, compared with 2 of 37 controls (5%). As shown in Figure 1, the median age at natural menopause was 3 years younger among women who developed SLE compared with controls (P ⬍ 0.001 by log-rank test of survival curves). In the proportional hazards model, the adjusted relative risk (estimated as the hazard ratio) conferred by natural menopause, comparing patients with controls, was 2.4 (95% CI 1.3–4.4). This association was also seen in race-specific analyses, which yielded hazard ratios of 3.6 (95% CI 0.9–13.9) among African Americans and 2.2 (95% CI 1.0–4.6) among whites. Only 2 patients reported having natural menopause before age 40, and both of these women were diagnosed as having SLE more than 20 years after their menopause. We saw little association between risk of developing SLE and either current use or duration of use of hormone replacement therapy or oral contraceptives (Table 3). No association was seen with having ever used oral contraceptives (adjusted OR 1.3, 95% CI 0.9–2.1), other hormonal contraceptives, or fertility drugs. There was no clear association with early age at menarche (Table 4). Greater age at menarche (17–18

Our results provide little evidence that estrogenrelated exposures in women are associated with an increased risk of SLE. An increased risk with these exposures was expected based on the results of other research, particularly the extensive experimental studies of estrogen and androgen exposure in relation to disease progression in mice (10–12). Investigators in other studies have also reported a decrease in the number or severity of disease flares in female patients after menopause (22,23). If the risk of developing SLE is related to estrogen exposure, disease risk would be expected to be reduced in women with an early natural menopause and increased in women with early menarche. These associations have been observed in numerous epidemiologic studies of breast cancer (24–26). However, in our study, we observed earlier natural menopause among women who subsequently developed SLE compared with population-based controls, and early menarche was not related to SLE risk. Early menopause is often a manifestation of autoimmune conditions involving the ovary or the adrenal or thyroid glands (27), but there was no indication of previously diagnosed autoimmune thyroiditis or Addison’s disease noted in the medical records of the patients in our study with natural menopause before age 48. Antiovarian autoantibodies have been detected in women with SLE (28) and in women with premature (at age ⬍40 years) ovarian failure (29), but additional research is needed to understand the potential role of ovarian-related autoimmunity in SLE. There was little association between risk of developing SLE and use of hormone replacement therapy in our study. Few (⬍20) participants had used hormone replacement therapy for ⬎10 years, so we had limited power to assess risk of long-term use or risk from specific types of medications (e.g., estrogen alone and


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Table 3. Associations between hormonal medications and risk of developing systemic lupus erythematosus Total sample

Hormone replacement therapy‡ Never used Formerly used Currently using§ Months of use 1–23 24–59 ⱖ60 Oral contraceptives Never used Formerly used Currently using§ Months of use 1–11 12–23 24–59 ⱖ60 Ever stopped/changed because of problem¶ Other hormonal contraceptives (shots or implants)# Fertility drugs**

African Americans

Whites



Adjusted OR†

95% CI

Adjusted OR†

95% CI

Adjusted OR†

95% CI

39 (52) 10 (13) 26 (35)

45 (44) 14 (14) 44 (43)

1.0 1.1 1.1

Referent 0.4–3.1 0.5–2.3

1.0 4.5 1.5

Referent 0.4–51.3 0.4–5.9

1.0 1.2 1.4

Referent 0.3–4.7 0.5–3.8

15 (20) 10 (13) 11 (15)

21 (20) 16 (16) 21 (20)

1.0 1.5 1.0

0.4–2.4 0.5–4.2 0.4–2.7

1.2 4.0 ‡

0.3–5.0 0.2–69.9 ‡

1.2 1.8 1.2

0.3–4.2 0.5–6.4 0.4–4.0

59 (25) 141 (59) 40 (17)

79 (25) 187 (58) 55 (17)

1.0 1.3 1.5

Referent 0.8–2.0 0.8–2.7

1.0 1.8 1.1

Referent 0.9–3.4 0.4–2.5

1.0 1.1 1.8

Referent 0.5–2.3 0.7–4.9

56 (23) 19 (8) 44 (18) 62 (26) 94 (52)

57 (18) 24 (7) 51 (16) 110 (34) 108 (45)

1.6 1.5 1.5 1.1 1.4

0.9–2.7 0.7–3.2 0.8–2.8 0.6–1.8 0.9–2.1

1.5 1.7 1.8 1.5 1.3

0.7–3.4 0.5–5.7 0.8–4.1 0.7–3.1 0.7–2.6

1.7 1.4 1.3 0.8 1.5

0.7–3.9 0.5–4.1 0.5–3.3 0.4–1.8 0.8–2.9

25 (10)

26 (8)

1.1

0.6–2.0

1.9

0.8–4.6

0.5

0.1–1.8

4 (2)

10 (3)

1.0

0.3–3.5

**

**

1.1

0.3–4.4

* Values are the number (%). † Logistic regression adjusted for age (continuous), race (white, African American, or other minority groups), state, and education (did not complete high school, completed high school, completed some college or technical school, or graduated from college) was used to examine associations, which were estimated as odds ratios (ORs) and 95% confidence intervals (95% CIs). ‡ Includes only those who had experienced natural menopause or who had undergone surgical menopause (75 patients, 103 controls). No African American controls reported use of hormone replacement therapy for ⱖ60 months, so this association was not estimated. § Using at the same age as at diagnosis (patients) or at the corresponding reference age (controls). ¶ Among those who ever used oral contraceptives. The referent group is women who reported they had never stopped or changed pills because of side effects or problems. # Referent group is that with no history of use of other hormonal contraceptives. ** Values are missing for 1 patient. No African American patients or controls reported use of fertility drugs; therefore, this association was not estimated. Referent group is that with no history of use of fertility drugs.

estrogen-plus-progestogen combinations), or to distinguish risk among former versus current users. In terms of statistical power and quality of design, the strongest data available on this issue are from the Nurses’ Health Study, a 14-year prospective study of 69,435 postmenopausal women (30). In that study, an increased risk of SLE with use of estrogen replacement therapy was observed. This association was strongest with current use (relative risk 2.5, 95% CI 1.2–5.0) and with long-term use (relative risk 3.5, 95% CI 1.2–10.9 for ⱖ11 years of use). However, the Nurses’ Health Study analysis did not adjust for age at menopause. The observed association between long-term use of estrogen replacement therapy and SLE could have been partly confounded, since early menopause may be related to longer use of this medication. Future studies should include both factors in the analysis. We observed little evidence of an association

between SLE risk and use of oral contraceptives (when analyzed in terms of having ever used, duration of use, or current use) or between SLE risk and having ever used other hormonal contraceptives (shots and implants). Other case–control studies have also shown little association with oral contraceptives (31,32). The Nurses’ Health Study found a weak association with oral contraceptive use, with a relative risk of 1.4 for having ever used oral contraceptives (33). Moncayo and Moncayo have suggested that ovarian stimulation with fertility drugs may increase the risk of developing SLE (34), and cases of patients who developed SLE after ovulation induction therapy have been reported (35). Use of fertility drugs was low (⬍3% of patients) in our study, but we did not see an association with disease risk. Experimental studies with murine models of SLE have demonstrated disease acceleration with prolactin exposure (36,37). In humans, higher levels of disease

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Table 4. Associations between menstrual and gynecologic history and risk of developing systemic lupus erythematosus (SLE) Total sample

Age at menarche in years‡ 8–9 10 11 12 13 14 15–16 17–18 Menstrual cycle duration¶ ⱕ24 days 25–30 days 31–34 days Other Menstrual pain and cramps# None Mild Moderate Severe Endometriosis (diagnosed by laparoscopy)** Dysfunctional uterine bleeding (diagnosed by a physician)††

African Americans

Whites



Adjusted OR†

95% CI

Adjusted OR†

95% CI

Adjusted OR†

95% CI

7 (3) 15 (6) 26 (11) 63 (26) 74 (31) 26 (11) 22 (9) 7 (3)

9 (3) 10 (3) 59 (18) 78 (24) 99 (31) 41 (13) 23 (7) 2 (1)

0.6 2.2 0.5 1.1 1.0 0.8 1.1 4.7

0.2–1.7 0.9–5.5 0.3–0.9 0.7–1.8 Referent 0.4–1.4 0.5–2.2 0.9–25.7

0.8 0.8 0.4 1.1 1.0 0.7 1.4 §

0.2–2.9 0.2–3.3 0.2–1.0 0.5–2.3 Referent 0.3–1.7 0.5–4.2 §

§ 4.6 0.4 1.0 1.0 1.0 0.9 2.6

§ 1.3–15.8 0.1–1.1 0.5–2.1 Referent 0.4–2.5 0.3–2.8 0.3–20.5

20 (8) 184 (78) 12 (5) 20 (8)

13 (4) 265 (83) 13 (4) 29 (9)

2.2 1.0 2.6 1.0

1.0–4.7 Referent 1.1–6.2 0.5–1.9

3.0 1.0 ¶ 1.5

0.8–11.1 Referent ¶ 0.5–4.6

2.1 1.0 1.8 0.5

0.7–6.4 Referent 0.7–5.0 0.2–1.6

37 (18) 91 (45) 44 (22) 31 (15) 11 (5)

55 (18) 122 (39) 69 (22) 63 (20) 13 (4)

1.0 1.4 1.5 0.8 1.8

Referent 0.8–2.5 0.8–2.7 0.4–1.5 0.8–4.4

1.0 1.3 1.5 0.7 0.7

Referent 0.6–2.7 0.6–3.9 0.3–1.6 0.1–3.6

1.0 1.7 1.7 1.0 2.3

Referent 0.7–4.3 0.6–4.7 0.3–2.9 0.9–6.3

10 (4)

7 (2)

3.0

1.0–8.8

2.1

0.2–21.1

4.2

1.2–14.5

* Values are the number (%). † Logistic regression adjusted for age (continuous), race (white, African American, or other minority groups), state, and education (did not complete high school, completed high school, completed some college or technical school, or graduated from college) was used to examine associations, which were estimated as odds ratios (ORs) and 95% confidence intervals (95% CIs). ‡ A trend test for increased SLE risk with age at menarche in the 8 categories shown yielded P values of 0.20, 0.11, and 0.79 for the total sample, African Americans, and whites, respectively. § No African American controls reported menarche at ages 17–18 years, and no white patients reported menarche at ages 8–9 years; therefore, these associations were not estimated. ¶ Reported for the first set of years after menarche during which hormonal contraceptives were not being used and the participant was not pregnant. “Other” category includes 35–60 days, “infrequent” (⬎2 months apart), and “irregular” (participant could not tell within 1 week when her period would come). Data were missing for 4 patients and 1 control. No African American controls reported menstrual cycle duration of 31–34 days, so this association was not estimated. # Data were missing for 37 patients and 12 controls. ** Referent group is that with no history of endometriosis. †† Referent group is that with no history of dysfunctional uterine bleeding.

activity have been reported in association with higher prolactin levels (38), but other studies have yielded conflicting results (39). Investigators in a recent study reported an increased prevalence of anti–doublestranded DNA, anti-Sm, anti-SSA/Ro, and other autoantibodies in 33 women with hyperprolactinemia but without a clinical diagnosis of an autoimmune disease, compared with 19 women with normal prolactin levels (40). We found a strongly and statistically significantly decreased risk in association with breast-feeding, a marker of prolactin exposure, in our study. It should be noted, however, that lactation is not a marker of hyperprolactinemia. Breast-feeding is more common among whites and among women with higher levels of educa-

tion. Race and education were included in the logistic regression models, and we observed the reduced risk in separate analyses for African Americans and for whites, so the association was not likely to be confounded by these factors. Ovulation and estrogen production are suppressed during lactation, but ovulation usually resumes as the frequency of breast-feeding declines. We did not obtain information on resumption of menses after pregnancy, so we cannot assess the effect of postpregnancy suppression of ovulation on the risk of SLE. However, it seems unlikely that an effect on estrogen production would explain the reduced risk we observed with breastfeeding, since we saw little evidence of an association


between risk of developing SLE and estrogen exposure from a variety of endogenous and exogenous sources. There has been relatively little research on the immunologic effect of breast-feeding on the mother. Zimmer et al (41,42) reported an inverse correlation between the percentage of circulating CD19⫹ B cells and serum prolactin levels among breast-feeding women. Additional research into the long-term immunologic effects of lactation on the mother is needed to understand the mechanisms that could contribute to an association between lactation and reduced risk of SLE. Other possible explanations for the observed association that should be examined include conditions or medications that prevent women from breast-feeding and that may also be related to the risk of developing SLE, as well as the potential role of breast-feeding in eliminating toxicants. The presence of fetal cells in the maternal circulation during pregnancy was demonstrated in 1969 (43), and in 1996 Bianchi et al reported the presence of male fetal cells up to 27 years after delivery (44). We were interested in the possible relation, proposed by Nelson (14), between maternal–fetal cell circulation as a source of microchimerism and development of autoimmune disease. After data collection had begun for the present study, Holzgreve et al reported that the level of fetal cells in the maternal circulation was significantly higher in 8 women with preeclampsia compared with 8 age- and gestation-matched controls (18), so we added questions about preeclampsia to the interview. We observed an increased risk of developing SLE among women who had preeclampsia in pregnancies preceding the diagnosis by at least 3 years. If an association between preeclampsia and risk of developing SLE is confirmed in future studies, other explanations should also be explored. There may be common risk factors or etiologic pathways between preeclampsia and SLE that do not involve microchimerism. It is also possible that a diagnosis of SLE could have been missed at the time of the pregnancy, if relevant laboratory tests were not performed. Future research studies pertaining to the association between preeclampsia and subsequent development of SLE should be designed to specifically address these different issues. The Carolina Lupus Study is the largest population-based, case–control study of patients recently diagnosed as having SLE that has been conducted in the US. We believe that the completeness of case ascertainment was fairly high, since we were able to use a systematic, active surveillance system (medical record review of all potentially eligible patients) at the univer-

1837

sities, the larger community-based practices, and the practices known for care of SLE patients. The frequencies of the clinical and immunologic features are similar to those reported in other large studies (45–47), suggesting that our referral system did not lead to a biased ascertainment of cases. Since our system for recruiting patients relied primarily on rheumatologists, we could have missed patients who were not seen by a rheumatologist. In a survey of 116 general practice physicians in New England, Felson et al found that 76% reported they were likely to refer SLE patients with relatively mild disease (polyarthritis and malar rash) to a rheumatologist, and 92% reported they would so refer SLE patients with other complications (e.g., seizures) (48). We found similar findings in a survey we conducted of 195 family practice physicians and internists in our study area (Cooper GS: unpublished observations): 93% reported that they routinely referred a lupus patient to a rheumatologist all or almost all of the time, either for an initial consultation (55%) or for consultation and followup (38%), and only 7% reported that they did not refer a patient newly diagnosed as having SLE to a rheumatologist unless the patient was severely ill. These studies do not provide specific data on the percent of cases that may have been missed through our referral system, but they do provide some support for our belief that focusing recruitment efforts on rheumatologists did not lead to a substantial loss of potential patients. Data collection involved a standardized, inperson interview to obtain an extensive reproductive and menstrual history. Recall error is possible, but investigators in previous studies have reported fairly high levels of accuracy or reliability (e.g., ␬ ⬎ 0.80) for interview- or questionnaire-based data on age at menarche (49–51), age at and type of menopause (49–53), pregnancy history (50,51,54), and breast-feeding history (50,53). These studies have been conducted in health professionals (52) and other selected groups (49), as well as in population- and hospital-based case–control studies of a variety of medical conditions (50,51,53). A lower level of agreement between self-report of preeclampsia or toxemia and medical record review was seen in a case– control study of childhood cancer (54), with sensitivity of 57%, specificity of 98%, and ␬ ⫽ 0.55 among controls. A limitation of this study is that the preeclampsia history was added to the interview after data collection had begun, and was therefore not available for 79 patients and 75 controls who had been pregnant. Also, we did not obtain details of the severity of the condition,

1838

COOPER ET AL

and the self-reported data were not verified by medical records. Our results suggest that factors (e.g., estrogen and prolactin exposure) that may be related to disease acceleration or progression in mice may not be related to the risk of developing SLE in humans. The associations we observed of SLE risk with breast-feeding, preeclampsia, and early menopause should stimulate additional epidemiologic, clinical, and experimental studies.

9. 10.

11. 12.

ACKNOWLEDGMENTS We thank our study manager (Lyle Lansdell), the interviewers (Sara Graham, Gwen McCoy, and Alesia Sanyika), and the programmers (Carol Lynn and Marsha Shepherd), whose efforts made this study possible. Special thanks and appreciation are also due to the physicians who participated in the Carolina Lupus Study Group in North Carolina (H. Vann Austin, Faye Banks, Franc Barada, George Brothers, Walter Chmelewski, Duncan Fagundus, David Fraser, Stephen G. Gelfand, Helen Harmon, Robert A. Harrell III, John Harshbarger, G. Wallace Kernodle, Jr., Elliot Kopp, Kara Martin, John L. McCain, Cathleen Melton, Gwenesta Melton, G. Radford Moeller, William Olds, David Puett, C. Michael Ramsdell, Byron Randolph, A. Silvia Ross, Gregory Schimizzi, Evelyn Schmidt, T. Smith, Claudia Svara, Anne Toohey, Randal White, Suzanne Zorn) and in South Carolina (Carlysle Barfield, Walter Bonner, John Brittis, William Edwards, Mitchell Feinman, Gary Fink, Frank Harper, Peter Hyman, Jr., Wendy Lee, Holly Mitchell, Alan Nussbaum, Georgia Roane, William Sheldon, Robert Turner). We also thank Drs. Donna Baird, Dale Sandler, and Allen Wilcox for their reviews of the manuscript.

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