REPORT

Bone Mass and Breast Cancer Risk in Older Women: Differences by Stage at Diagnosis

Joseph M. Zmuda, Jane A. Cauley, Britt-Marie Ljung, Douglas C. Bauer, Steven R. Cummings, Lewis H. Kuller, For the Study of Osteoporotic Fractures Research Group

Affiliations of authors: J. M. Zmuda, J. A. Cauley, L. H. Kuller, Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, PA; D. C. Bauer, S. R. Cummings (Department of Epidemiology and Biostatistics), B.-M. Ljung (Department of Pathology), University of California, San Francisco.

Correspondence to: Joseph M. Zmuda, Ph.D., Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, 130 DeSoto St., Pittsburgh, PA 15261 (e-mail: epidjmz{at}pitt.edu).


    ABSTRACT
 Top
 Notes
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 Appendix
 References
 
Background: Older women with low bone mineral density (BMD) have a decreased incidence of breast cancer. It is not known whether this association is confined to early-stage, slow-growing tumors. Methods: We prospectively studied 8905 women who were 65 years of age or older during the period from 1986 through 1988 and had no history of breast cancer. At study entry, we used single-photon absorptiometry to measure each woman's BMD at three skeletal sites: the wrist, forearm, and heel. The women were followed for a mean of 6.5 years for the occurrence of breast cancer. All statistical tests were two-sided. Results: During 57 516 person-years of follow-up, 315 women developed primary invasive or in situ breast cancer. Multivariate analyses that adjusted for age, obesity, and other covariates revealed that the risk of breast cancer for women in the highest quartile of BMD for all three skeletal sites was 2.7 (95% confidence interval [CI] = 1.4 to 5.3) times greater than that for women in the lowest quartile at all three skeletal sites. The magnitude of increased risk associated with high BMD differed by the stage of disease at diagnosis and was greater for more advanced tumors (relative risk [RR] for TNM [i.e., tumor–lymph node–metastasis] stage II or higher tumors = 5.6; 95% CI = 1.2 to 27.4) than for early-stage disease (RR for in situ/TNM stage I tumors = 2.2; 95% CI = 1.0 to 4.8). Conclusions: Elderly women with high BMD have an increased risk of breast cancer, especially advanced cancer, compared with women with low BMD. These findings suggest an association between osteoporosis and invasive breast cancer, two of the most prevalent conditions affecting an older woman's health.



    INTRODUCTION
 Top
 Notes
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 Appendix
 References
 
Estrogen may have a prominent role in the etiology of breast cancer (1). Exogenous estrogen increases the incidence of mammary tumors in animals (2), and prospective studies (310) have shown that higher levels of serum estrogen is associated with an increased breast cancer risk among older women. Because bone contains estrogen receptors (11) and is, therefore, highly sensitive to levels of circulating estrogen (12), bone mineral density (BMD) may be a surrogate marker of a woman's long-term exposure to endogenous estrogen (1315). We (15) previously examined the relationship between BMD and the incidence of breast cancer in women aged 65 years and older who were participants in the Study of Osteoporotic Fractures (SOF). During a 3-year follow-up period, women with the highest BMD had a twofold to 2.5-fold increase in breast cancer risk compared with women with the lowest BMD (15). Similar analyses of 1373 women aged 47–80 years in the Framingham Study (16) demonstrated that women with the highest metacarpal bone mass have an increased risk of breast cancer. However, both of these reports were based on relatively few cases of breast cancer, and neither examined the relationship between bone mass and the stage of breast cancer at the time of diagnosis. This latter issue is important because it is unclear if the increased incidence of breast cancer among women with high bone mass is due to detection bias and confined to mammographically detected, early-stage tumors.

To further evaluate the relationship between bone mass and breast cancer risk, we expanded our initial analysis of the SOF cohort to include additional women affected with breast cancer during a 6.5-year follow-up period. In addition, we collected information on the stage of breast cancer at the time of diagnosis for all of the women to analyze the association between BMD and the risk of early- and advanced-stage breast cancers.


    SUBJECTS AND METHODS
 Top
 Notes
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 Appendix
 References
 
Study Population

All of the women in our study were participants in the SOF, a prospective study of 9704 white women at least 65 years of age. Women were recruited for the SOF during the period from 1986 through 1988 from population-based lists (e.g., voter registration, health maintenance organizations, and motor vehicle tapes) at clinical centers located at the University of Maryland (Baltimore), the University of Minnesota (Minneapolis), the University of Pittsburgh (PA), and The Kaiser Permanente Center for Health Research (Portland, OR) (17). Women were excluded from the SOF if they reported a bilateral hip replacement or were unable to walk without assistance. African-American women were also excluded from the SOF because of their low inherent risk of hip fracture. The institutional review boards at each institution approved the study. All women provided written informed consent at study entry and at each clinical examination.

Breast Cancer Ascertainment

One year after completing the baseline examination required for entry into the SOF, each woman was asked to complete a follow-up questionnaire that included information about her personal and family history of breast cancer. Incident cases of breast cancer were identified by self-report on follow-up questionnaires that were completed by each woman every 2 years during subsequent clinic examinations and by a review of death records obtained from state health departments. On each questionnaire, we asked if breast cancer had been diagnosed and, if so, the date of diagnosis. Women who missed an examination or who moved out of state were contacted by mail or telephone to obtain information about medical events, including a diagnosis of breast cancer, since their last examination or contact date. All women who reported that they had been diagnosed with breast cancer (or the next-of-kin, as listed on the study questionnaires, for decedents) were asked to provide permission for us to obtain and review relevant hospital records and histopathology reports to confirm their self-reported diagnoses. Histopathology reports were available for all women with breast cancer who were identified in this analysis. Breast cancers were staged according to the American Joint Committee on Cancer methodology by use of the standard tumor–lymph node–metastasis (TNM) staging criteria (18).

Women who reported a history of breast cancer before the first annual questionnaire (defined as year 1) (n = 513) were considered to be prevalent case subjects and were excluded from further analysis. We also excluded 101 women who died before year 1, 13 women who provided no breast cancer information at year 1, 28 women who had no medical records for breast cancer at the time of this analysis, and 144 women whose BMD measurements were missing. Thus, information on breast cancer was collected on 8905 women for this analysis.

Measurement of BMD

At study entry, BMD was measured at the proximal radius (forearm), distal radius (wrist), and calcaneus (heel) of each participant by single-photon absorptiometry with the use of OsteoAnalyzers (Siemens-Osteon, Wahiawa, HI). Measurements of BMD were made at more than one skeletal site because the composition and metabolism of bone are not uniform throughout the skeleton. The measurement methods and densitometry quality-control procedures have been described in detail previously (19). The mean coefficients of variation for the forearm, wrist, and heel BMD measurements were 1.3%, 1.5%, and 2.0%, respectively (17).

Covariate Information

Each woman was weighed at study entry. A modified body mass index (BMI), i.e., weight in kilograms divided by height in meters squared, was calculated with the use of each woman's self-reported height at age 25 years. This value for height was used because it was thought to be a more accurate reflection of each woman's adult height than her current height, since women with low bone mass often experience a reduction in height because of vertebral fractures. Reproductive history was obtained by questionnaire and personal interview and included information on ages at menarche and menopause, parity, type of menopause, history of benign breast disease, and family history (maternal or sister) of breast cancer. Participants were asked about current and past estrogen use (by pill, patch, or injection) since age 40 years. We confirmed self-reported use of estrogen by asking participants to bring their current medications to clinic visits. We also collected information on current cigarette and alcohol use. Alcohol consumption was measured in drinks per week and was adjusted for atypical, especially heavy, drinking in the 30 days before the clinic visit. Women were asked whether they walked for exercise. At year 3, participants were asked whether they had received a mammogram since entry in the study.

Statistical Analysis

Descriptive characteristics of women with and without breast cancer were compared by Student's t tests for continuous variables or chi-squared tests for categorical variables. We calculated the incidence rates for each exposure category by dividing the number of new cases of breast cancer by the number of person-years of follow-up and then multiplying by 1000. The duration of follow-up for each participant was defined as the time from completion of the first annual questionnaire during the period from 1987 through 1990 to the date of breast cancer diagnosis, the date of death, the date of the last follow-up contact, or September 28, 1998, the prespecified end of the study period for the present analysis, whichever occurred first. We used Cox proportional hazards models to assess the relationship between BMD and breast cancer risk, adjusting for age, modified BMI, and other potential confounding factors. We also adjusted for educational level, walking for exercise, alcohol consumption, smoking, parity, ages at menarche and menopause, use of estrogen replacement therapy, family history of breast cancer, and history of benign breast disease. BMD was modeled as a continuous variable to estimate the relative risk (RR) of breast cancer per 1 standard deviation (SD) increase in BMD. The values for BMD measured at each skeletal site were also divided into quartiles based on the distribution of those values in the entire cohort, and the RR of breast cancer was estimated for each quartile of BMD with the use of the lowest BMD quartile as the referent group. Separate models were constructed for BMD measurements obtained at each of the three skeletal sites (distal radius, proximal radius, and calcaneus). All statistical tests were two-sided.

Because BMD measurements at the three skeletal sites were correlated only modestly with each other (range, r = .64 to r = .76), we also determined the risk of breast cancer among women with BMD in the highest quartile at one, two, or three skeletal sites as compared with that among women with BMD in the lowest quartile at all three sites. To determine if risks differed by the stage of breast cancer at the time of diagnosis, we assigned each woman with breast cancer to one of two categories: 1) those with early-stage disease, representing in situ or TNM stage I tumors, and 2) those with advanced-stage disease, representing TNM stage II, III, or IV tumors. Two women with missing information on axillary lymph node status were included in the advanced-stage category based on the size of their tumors (T2).


    RESULTS
 Top
 Notes
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 Appendix
 References
 
Among the 8905 women participating in our study, 315 were newly diagnosed with primary invasive or in situ breast cancers during 57 516 person-years of follow-up. Of those 315 women, 43 (14%) were diagnosed with carcinoma in situ, 182 (58%) were diagnosed with stage I cancer, 30 (10%) were diagnosed with stage IIa, 33 (11%) were diagnosed with stage IIb, and 11 (4%) were diagnosed with stage III or IV cancer. Tumor staging could not be determined for 16 (5%) of the women newly diagnosed with breast cancer because axillary dissection was not performed in all cases of invasive cancer.

Traditional risk factors for breast cancer, including ages at menarche and menopause as well as nulliparity, were similar for women who did and did not develop breast cancer (Table 1Go). Walking habits, use of alcohol and tobacco, and current and past use of estrogen replacement therapy also did not differ between women with and without breast cancer. Women diagnosed with breast cancer were slightly younger, weighed more, and were taller at age 25 years than women without breast cancer. A history of breast cancer in first-degree relatives was more common among women diagnosed with breast cancer, but this association was statistically significant only for women who had earlier stage cancers at diagnosis. A history of benign breast disease was also reported more frequently by women with breast cancer than by women without breast cancer.


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Table 1. Baseline characteristics of women who did and did not develop breast cancer*
 
The incidence rate of breast cancer increased with increasing BMD (Table 2Go). For example, for BMD measured at the proximal radius, the incidence of breast cancer was 3.3 per 1000 person-years in the lowest BMD quartile and 7.3 per 1000 person-years in the highest BMD quartile. The age-adjusted RR of breast cancer increased by 30% (95% confidence interval [CI] = 1.1 to 1.4) with each SD increase in proximal radius BMD. Women in the highest quartile of proximal radius BMD had a twofold (95% CI = 1.4 to 2.9) greater age-adjusted RR of breast cancer compared with women in the lowest quartile. Additional adjustments for BMI and other known or suspected risk factors for breast cancer had little effect on the association between BMD and breast cancer risk. We found similar associations between BMD measurements taken at the other skeletal sites and the risk of breast cancer. We also found a statistically significant association between increasing BMD and increasing breast cancer risk after we excluded women who were taking estrogen replacement therapy at study entry (e.g., age-adjusted RR = 1.3 per SD increase in proximal radius BMD; 95% CI = 1.1 to 1.5) and women who did not have a mammogram during the first 3 years of the study (e.g., age-adjusted RR = 1.3 per SD increase in proximal radius BMD; 95% CI = 1.1 to 1.4) (data not shown).


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Table 2. Incidence rate and relative risk of breast cancer by quartile of bone mineral density*
 
The risk of breast cancer by quartile of BMD differed by stage of cancer at diagnosis (Table 3Go). For BMD measurements made at the calcaneus, the adjusted RRs of breast cancer for women in the highest quartile of BMD compared with those in the lowest quartile were 1.3 (95% CI = 0.8 to 2.1) for in situ or stage I cancer and 4.0 (95% CI = 1.5 to 11.1) for more advanced cancer (TNM stage II or higher). For BMD measurements made at the proximal radius, the adjusted RRs were 2.0 (95% CI = 1.2 to 3.3) for early-stage cancer and 1.6 (95% CI = 0.7 to 3.5) for advanced-stage cancer. At the distal radius, these risks were 1.5 (95% CI = 1.0 to 2.4) for early-stage cancer and 2.5 (95% CI = 1.2 to 5.3) for advanced-stage cancer.


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Table 3. Incidence rate and multivariate adjusted relative risk of breast cancer according to quartile of bone mineral density and stage of breast cancer*
 
The incidence rate of breast cancer for women with the lowest BMD at every (i.e., all three) skeletal site was 2.6 per 1000 person-years, whereas that for women with the highest BMD at every skeletal site was 7.8 per 1000 person-years (Table 4Go). Women in the highest quartile of BMD at every skeletal site had 2.8 (95% CI = 1.6 to 5.1) times greater age-adjusted risk of breast cancer compared with women in the lowest quartile of BMD at every site. Multivariate analyses that adjusted for age, obesity, and other covariates revealed that the risk of breast cancer for women in the highest quartile of BMD for all three skeletal sites was 2.7 (95% CI = 1.4 to 5.3) times greater than that for women in the lowest quartile at all three skeletal sites.


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Table 4. Incidence rate and relative risk of breast cancer by number of skeletal sites with low or high bone mineral density*
 
The magnitude of the association between BMD measurements taken at multiple skeletal sites and breast cancer risk was greater for women diagnosed with advanced-stage disease than for women diagnosed with early-stage disease (Table 4Go). For example, women with high BMD at all three sites had 5.6 (95% CI = 1.2 to 27.4) times the risk of advanced-stage breast cancer than women with low BMD at all three sites and 2.2 (95% CI = 1.0 to 4.8) times the risk of early-stage breast cancer than women with low BMD at all three skeletal sites in multivariate analyses (Table 4Go).


    DISCUSSION
 Top
 Notes
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 Appendix
 References
 
These results add to existing evidence that suggests that older women who have low bone mass have a decreased risk of breast cancer. The incidence of breast cancer among women in our study increased with increasing BMD measured at three skeletal sites. The risk of breast cancer was 1.7-fold to twofold greater among women in the highest quartile of BMD than among women in the lowest quartile of BMD, confirming earlier analyses in this cohort based on shorter follow-up and fewer cases of breast cancer (15). The association between BMD and breast cancer risk was greater when BMD measurements taken at all three skeletal sites were considered together, an observation that is not surprising given the modest correlation among BMD measurements at the different anatomic sites (20). The strength of the association between BMD and breast cancer risk was also considerably greater among women with more advanced breast cancer at the time of diagnosis. This association was not explained by known or suspected risk factors for breast cancer.

A gradation in risk associated with high BMD by stage of breast cancer at diagnosis suggests that biologic factors associated with high BMD may affect the growth rate of tumors and their progression to clinically advanced disease. However, we could not perform a more detailed examination of BMD and the aggressiveness of breast cancer because additional information on the biologic characteristics of tumors, such as histologic grading, was not available and too few women had distant metastases or fatal breast cancer. Nevertheless, it will be important in future studies to determine if women with high BMD are likely to develop a more aggressive form of breast cancer, as defined by high histologic grading, presence of distant metastases at diagnosis, and mortality.

Our results are consistent with the those of the Framingham Study (16), which found that, among 1373 middle-aged and elderly women, those with the highest metacarpal bone mass had a 3.5-fold (95% CI = 1.8 to 6.8) greater risk of breast cancer than those with the lowest metacarpal bone mass. Our results are also consistent with reports that link fractures with the risk of breast cancer (21,22). For example, the incidence of breast cancer was 46% lower (95% CI = 3% to 73%) than expected among women who had a distal forearm fracture (22) and 16% lower (95% CI = 5% to 26%) among women who experienced a hip fracture (21). These observations suggest a link between osteoporosis and breast cancer, two of the most common conditions affecting an older woman's health.

Our findings suggest that BMD is one of the most powerful predictors of breast cancer, especially advanced breast cancer, among elderly women (23). The gradient of increased breast cancer risk associated with BMD is similar to the gradient of fracture risk associated with BMD (24). Many women routinely undergo clinical assessments of BMD to determine their risk of fracture. This raises the possibility that BMD measurements taken at one or more skeletal sites could be used, perhaps in combination with other risk factors, to identify women at high risk for breast cancer who might benefit from preventive therapies, such as treatment with selective estrogen receptor modulators (25,26). Moreover, recent decision and cost-effectiveness analyses (27) suggest that continuing screening mammography in women older than 69 years results in relatively small gains in life expectancy, is moderately cost-effective in women with high BMD, and is less cost-effective for women with low BMD. Thus, BMD measurements might also assist with decision-making about continuing screening mammography in elderly women (27).

It is unlikely that estrogen use has confounded the association between BMD and breast cancer risk. We found similar frequencies of current and past estrogen use among women who did and did not develop breast cancer, and adjusting for estrogen use had little effect on the association between BMD and breast cancer risk. In addition, we found a similar association between BMD and breast cancer risk after excluding current estrogen users (data not shown). Likewise, the magnitude of the association between metacarpal bone mass and breast cancer risk in the Framingham study (16) was similar among women who did and did not use estrogen.

An association between BMD and breast cancer risk is also unlikely to be confounded by body size. Obesity, weight gain, and fat distribution are major determinants of bone mass (28,29) and potential risk factors for breast cancer among postmenopausal women (30). In our study, women who developed breast cancer weighed more and had higher BMIs than did women who did not develop breast cancer. However, adjusting for BMI had no appreciable effect on the association between BMD and breast cancer risk. Height is also strongly and positively related to bone mass (31) and, in several cohort studies (30,3239), it is associated with breast cancer risk. In our study, although women who developed breast cancer were statistically significantly taller than women without breast cancer, the absolute difference in height between these groups was small and unlikely to explain the strong association between BMD and breast cancer risk.

Another possible confounder is differential use of mammography according to BMD. Women with low BMD were less likely to have had a mammogram during the first 3 years of our study. For instance, 74% of the women in the lowest quartile of proximal radius BMD had had a mammogram, compared with 82% of the women in the highest quartile. However, we found a similar association between BMD and breast cancer risk after excluding women who did not have a mammogram during the first 3 years of the study (data not shown). Moreover, increased use of screening mammography among women with high BMD would be expected to increase the detection rate of otherwise undetectable in situ tumors, and we found a stronger association between BMD and the risk of later stage disease. Thus, detection bias is an unlikely explanation for the association between BMD and breast cancer risk.

Endogenous levels of hormones, growth factors, or cytokines may provide a link between BMD and breast cancer risk. Prospective studies (310) have demonstrated that higher levels of serum estrogen and testosterone are associated with an increased risk of breast cancer among older women. We (40) have shown previously, however, that the association between BMD and breast cancer risk is not dependent on levels of bioavailable estrogen or free testosterone. Serum levels of insulin are positively associated with bone mass (41), and exogenous insulin stimulates mammary cell proliferation in vitro (42). Insulin-like growth factors are also important determinants of bone mass (43), and their levels have been associated with increased breast cancer risk in premenopausal women (44). Increased levels of transforming growth factor-{beta} (TGF-{beta}) have been reported among osteoporotic women (45), and TGF-{beta} may suppress the growth of normal mammary epithelial and breast carcinoma cells in vitro (46). Finally, increased production of proinflammatory cytokines has been noted among osteoporotic women (47,48). In vitro data suggest that proinflammatory cytokines may have growth-inhibitory effects on breast cancer cells (49,50). The relationship between bone mass and breast cancer risk, therefore, may involve a complex interplay of hormones, growth factors, and cytokines.

This study has several potential limitations. First, because women enrolled in the SOF were white volunteers who resided in one of four specific communities and were in generally good health, our cohort may not be representative of older women in the United States. However, the incidence rate of breast cancer in the SOF cohort was similar to that reported in the Surveillance, Epidemiology, and End Results (SEER) Program1 for white women aged 65 years and older (15). Nevertheless, the observation that BMD is a strong predictor of breast cancer in older white women should be confirmed among younger women and women of other ethnicities. Second, some established risk factors for breast cancer, such as age at menarche, were not associated with breast cancer risk in our study participants. Recall of such characteristics might be more difficult for older women, thus diluting the strength of their association with breast cancer in the elderly women in our study. Third, relatively few women in our study had advanced breast cancer at the time of diagnosis, which resulted in wide CIs in analyses stratified by stage of disease. Thus, our finding that women with low BMD have a very low risk of more advanced breast cancer requires further study and validation in a larger sample.

In summary, these results suggest that bone mass is a powerful predictor of breast cancer, especially more advanced cancer, among older women. Identifying the factors linking osteoporosis and breast cancer could have important implications by suggesting new directions for studying the etiology, prevention, and treatment of both conditions.


    APPENDIX
 Top
 Notes
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 Appendix
 References
 
The affiliations and the names of the investigators in the Study of Osteoporotic Fractures Research Group are as follows:

University of California, San Francisco (Coordinating Center): S. R. Cummings (principal investigator), M. C. Nevitt (co-investigator), D. C. Bauer (co-investigator), K. Stone (project director), D. M. Black (study statistician), H. K. Genant (director, central radiology laboratory), P. Mannen (research associate), T. Blackwell, W. S. Browner, M. Dockrell, T. Duong, C. Fox, S. Harvey, M. Jaime-Chavez, L. Y. Lui, G. Milani, L. Nusgarten, L. Palermo, E. Williams, D. Tanaka, and C. Yeung.

University of Maryland, Baltimore: M. Hochberg (principal investigator), J. C. Lewis (project director), D. Wright (clinic coordinator), R. Nichols, C. Boehm, L. Finazzo, B. Hohman, T. Page, S. Trusty, and C. Williams.

University of Minnesota, Minneapolis: K. Ensrud (principal investigator), K. Margolis (co-investigator), P. Schreiner (co-investigator), K. Worzala (co-investigator), M. Oberdorfer (project director), E. Mitson (clinic coordinator), C. Bird, D. Blanks, F. Imker-Witte, K. Jacobson, K. Knauth, N. Nelson, E. Penland-Miller, and G. Saecker.

University of Pittsburgh, PA: J. A. Cauley (principal investigator), L. H. Kuller (co-principal investigator), M. Vogt (co-investigator), L. Harper (project director), L. Buck (clinic coordinator), C. Bashada, D. Cusick, G. Engleka, A. Flaugh, A. Githens, M. Gorecki, K. McCune, D. Medve, M. Nasim, C. Newman, S. Rudovsky, and N. Watson.

The Kaiser Permanente Center for Health Research, Portland, OR: T. Hillier (principal investigator), E. Harris (co-principal investigator), E. Orwoll (co-investigator), H. Nelson (co-investigator), M. Aiken (biostatistician), M. Erwin (project administrator), M. Rix (clinic coordinator), J. Wallace, K. Snider, K. Canova, K. Pedula, and J. Rizzo.


    NOTES
 
1 Editor's note: SEER is a set of geographically defined, population-based central cancer registries in the United States, operated by nonprofit organizations under contract to the National Cancer Institute (NCI). Registry data are submitted electronically without personal identifiers to the NCI on a biannual basis, and the NCI makes the data available to the public for scientific research. Back

See "Appendix" section for the names and affiliations of the investigators in the Study of Osteoporotic Fractures Research Group.

Supported in part by Public Health Service research grants AR35582, AR35583, AR35584, and 1P60AR44811 (National Institute of Arthritis and Musculoskeletal and Skin Diseases) and AG05407 and AG05394 (National Institute on Aging), National Institutes of Health, Department of Health and Human Services; and by grant DAMD17-96-6114 from the U.S. Army Medical Research and Material Command.


    REFERENCES
 Top
 Notes
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 Appendix
 References
 

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Manuscript received September 7, 2000; revised March 20, 2001; accepted April 10, 2001.


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