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Keywords:

  • osteoporosis;
  • bone turnover;
  • fracture risk;
  • male;
  • epidemiology

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Among the potential risk factors for fragility fractures, bone turnover is considered an important determinant. In a case-cohort control study of 151 elderly men followed prospectively over 6.3 years, high bone resorption as assessed by S-ICTP was associated with increased risk of osteoporotic fracture, independent of BMD. Combining measurements of BMD and bone turnover may improve fracture prediction in elderly men.

Introduction: Approximately one-third of osteoporotic fractures occur in men. Among the potential risk factors for fragility fractures, bone turnover is considered an important determinant. The association between fracture risk and rates of bone turnover has not been well established in men. We examined this relationship in elderly community-dwelling men.

Materials and Methods: This case-cohort control study included 50 men with incident low-trauma fractures (cases; age, 72.3 ± 6.7 years) and 101 men without fracture (controls; age, 70.4 ± 4.1 years), who have been prospectively followed in the Dubbo Osteoporosis Epidemiology Study for a median of 6.3 years (range, 2-13 years). BMD at the lumbar spine (LSBMD) and at the femoral neck (FNBMD) and markers of bone turnover were measured at baseline. Bone resorption was assessed by measuring nonfasting serum concentrations of the carboxyterminal cross-linked telopeptide of type I collagen (S-ICTP) and of a linear octapeptide derived from the carboxyterminal type I collagen telopeptide (S-CTX). Bone formation was assessed by measuring the serum levels of the aminoterminal propeptide of type I procollagen (S-PINP).

Results: Men with subsequent fractures had lower BMD at baseline, both at the femoral neck and the spine, lower dietary calcium intake, and higher S-ICTP levels than age-and weight-matched controls. Smoking habits, S-CTX, and S-PINP did not differ between groups. Based on univariate regression analyses, S-ICTP (relative risk [RR] for 1 SD change: 1.8; 95% CI, 1.4-2.3) and serum creatinine levels (RR, 1.4; 95% CI, 1.1-1.7) were associated with increased risk of fracture. In multivariate regression analyses, S-ICTP (RR, 1.4; 95% CI, 1.0-1.9) and FNBMD (RR, 1.8; 95% CI, 1.4-2.3) remained independent predictors of fracture risk. Men within the highest quartile of S-ICTP had a 2.8-fold (95% CI 1.4-5.4) increased risk of fracture compared with those in the lowest quartile. The incidence of osteoporotic fractures was 10 times higher in men with high S-ICTP and low FNBMD compared with men with low S-ICTP and high FNBMD. Of the fracture risk in the population, 20% was attributable to high S-ICTP and low FNBMD, and S-ICTP contributed 17% to this increased risk.

Conclusion: High bone resorption is associated with an increased risk of osteoporotic fracture in elderly men, independent of BMD. Combining measurements of BMD and bone turnover, which correlated with fracture in this cohort, could improve fracture risk prediction in elderly men.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

OSTEOPOROTIC FRACTURES REPRESENT a major source of morbidity in the elderly. It is anticipated that the number of affected individuals, and thereby costs to health care systems, will increase with population aging.(1,2) Osteoporosis affects not only postmenopausal women but also men, and it is estimated that about one-third of all fractures occur in men.(3) The residual lifetime fracture risk in a man 60 years of age is up to 30%.(3,4) Moreover, the mortality rate after hip or vertebral fracture is even higher in men than in women.(5,6) Therefore, based on the observation that almost one-half of hip fractures in men occurred before 80 years of age,(7) early detection of individuals with osteoporosis, and more specifically, at risk for future osteoporotic fractures, is crucial.

Low BMD is an important risk factor for osteoporotic fractures. However, other determinants of bone strength are not captured by BMD. For example, bone turnover has been found to predict fracture risk independent of BMD in early postmenopausal(8–10) and in elderly women.(11–13) Bone resorption markers above the premenopausal reference range were associated with a 2-fold risk of hip fracture, comparable with the risk associated with 1 SD decrease in BMD.(14) Furthermore, the combination of low BMD and high resorption rate puts a woman at particularly high risk of fracture.(8) These results suggest that a combined approach, with BMD and markers of bone turnover, could improve fracture prediction.(15)

Whereas BMD seems to predict osteoporotic fractures similarly in men and women,(16,17) little is known to what extent markers of bone turnover are associated with bone loss and fracture risk in men. The aim of this study was to determine whether bone turnover is associated with incident osteoporotic fractures in elderly ambulatory men and whether any such effect is independent of BMD or other parameters related to fracture risk.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Subjects

This analysis is part of the Dubbo Osteoporosis Epidemiology Study. The design and participants of this large population based study have been described previously.(3,16,18,19) Briefly, since 1989, all men and women ≥60 years of age living in Dubbo, a city of ∼32,000 people 400 km northwest of Sydney, Australia, were invited to participate in the study. The population of Dubbo is 98.6% white, and its age and gender distribution closely resemble that of the entire Australian population. Because of the city's geographical situation, virtually all fractures occurring in the target population can be reliably ascertained. Although open to the whole population, all participants were of white background.

The Dubbo Osteoporosis Epidemiology Study is an ongoing prospective study. By February 2003, 989 men and 1661 women were participating in the study. This analysis was limited to the male members of the population who had had serum samples available and for whom clinical data and BMD measurements were available for at least two separate time-points during follow-up. Men with any fracture up to 12 months before blood collection were excluded. Men free of any bone or other major disease, who were on no medication affecting bone metabolism (i.e., glucocorticoids, calcitonin, anti-convulsants, vitamin D, or analogs), and had not had any known fractures in the past were deemed healthy and formed the control group (n = 101). Men with incident symptomatic minimal trauma fractures during the prospective follow-up formed the fracture group (n = 50). On the basis of these criteria, 151 men were included in the analysis. The median duration of follow-up was 6.3 years. The study was approved by the St. Vincent's Ethics Review Committee (Sydney), and all subjects gave written informed consent.

Clinical data collection

Subjects were interviewed by a nurse coordinator at initial and subsequent visits at ∼2-year intervals. At each visit, a structured questionnaire was used to collect data including lifestyle factors (i.e., smoking habits, dietary calcium intake), and anthropometric variables (including weight and height) were measured.

BMD (g/cm2) was measured at the lumbar spine (LSBMD) and the femoral neck (FNBMD) by DXA with a LUNAR DPX-L densitometer (GE Lunar, Madison, WI, USA). The measurement was performed at the same visit or within 1 month of the blood sample collection in 99% of cases. In those cases in which the blood was taken at a time other than at the scheduled visit, the BMD used was that closest to the time of blood collection. The CV for the BMD measurements in normal subjects at our institution is 1.3% at the lumbar spine and 3.5% at the femoral neck.(20)

Fractures were recorded from radiology centers servicing the Dubbo area, and the circumstances surrounding fracture were determined by personal interview after the fracture. All fractures included in the study were low-trauma fractures caused by a fall from a standing height or less. Vertebral fractures collected were clinically diagnosed. There was no systemic X-ray screening before the study to identify prevalent or asymptomatic vertebral fractures. Incidentally found, that is, asymptomatic, vertebral fractures were included, provided that there was no known malignancy or metabolic bone disease. Given the design of the study with blood being collected at the time of the second or even third visit, fractures occurred both before and after the data collection. Fractures occurring before the first blood collection were defined as prevalent, whereas all fractures thereafter were defined as incident. The study period was defined as the interval between the first visit with serum samples available until the most recent follow-up visit (up to February 2003).

Laboratory measurements

Serum samples were collected in the nonfasting state and not standardized in respect to sampling time, although most samples were collected in the morning. Samples were stored at −80°C until analysis. The carboxy-terminal telopeptide of type I collagen (S-ICTP; intra-assay CV, 3.8-6.7%, interassay CV, 6.7-8.5%; male reference range, 1.4-5.2 μg/liter) and the amino-terminal propeptide of type I collagen (S-PINP; intra-assay CV, 4.8-13.7%; interassay CV, 3.1-8.2%; male reference range, 21-78 μg/liter) were measured by competitive radioimmunoassay (Orion Diagnostica, Espoo, Finland).(21,22) The linear octapeptide derived from the carboxyterminal type I collagen telopeptide (S-CTX; intra-assay CV, 5.0-5.4%; interassay CV, 5.4-8.1%; male reference range, 0.33 ± 0.19 ng/ml) was measured in serum using an enzyme immunoassay (Nordic Bioscience Diagnostics, Herlev, Denmark).(23) All laboratory analysis were carried out in batches, with all samples from a single subject run in one assay. The same batch of the respective assay was used for all measurements.

Statistical analysis

The primary aim of statistical analysis in this study was to assess the association between bone turnover markers and fracture risk. This was done in three stages: univariate analysis, multivariate analysis, and attributable risk fraction analysis.

Differences in bone turnover markers and other clinical measures between fracture cases and controls were tested using unpaired t statistic (for normally distributed data), Mann-Whitney U test (for highly non-normally distributed data), or Fisher's exact test (for categorical variables).

In univariate and multivariate analyses, the magnitude of association between each risk factor (whether in the presence or absence of BMD) and fracture risk was estimated as rate ratio (RR, which was used as a measure of relative risk) based on the Poisson regression model. The model assumes that the incidence of fracture is a variable with a Poisson distribution that has a mean depending multiplicatively on the number of person-years and the potential predictor variables such as age, BMD, and bone turnover markers. The analysis was performed with the SAS PROC GENMOD procedure. The p values were based on two-tailed likelihood ratio tests, and 95% CIs were calculated from the maximum likelihood estimates. Because there were several possible models (for different risk factors), the goodness-of-fit of the models was assessed by the deviance. For models with the deviance close to the degrees of freedom, it is considered the fit as adequate. It is further assumed that changes in deviance between two models were distributed as χ2 with degrees of freedom equal to the difference in the number of parameters in the two models.

To estimate the proportion of fracture liability that may be hypothetically reduced by the elimination of a particular risk factor, population attributable risk fraction (PARF) was calculated. The PARF is a function of two parameters: the prevalence of a risk factor and the relative risk associated with the risk factor. To estimate the prevalence, each of the independent risk factors (obtained from the multivariate model) was dichotomized into high-risk and low-risk groups. For bone resorption marker (S-ICTP), the high-risk group was defined as those with a measured level being in the highest quartile of the distribution. For BMD, the high-risk group consisted of men whose BMD was 2.5 SD lower than the young normal mean. The statistical estimation of PARF was based on the “sequential attributable fraction.”(24) Briefly, for each threshold criterion used to define high-risk individuals, the expected probability of fracture was calculated from the logistic regression model. The expected probability was compared with the observed probability, and components of attributable risk fraction were subsequently estimated for each possible combination of risk factors.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

During the follow-up period (median, 6.3 years; range, 2-13 years) 50 men sustained at least one symptomatic low-trauma fracture (fracture group). Fifteen men experienced multiple incident nontraumatic fractures during follow-up. A total number of 65 fractures was reported including 15 hip fractures, 22 vertebral fractures, 5 wrist fractures, 17 rib fractures, and 6 low extremity fractures. The average time from study entry to fracture (or first fracture in men with multiple fractures) was 6.5 years (range, 0.3-12.4 years).

Men with incident fractures (n = 50; mean age, 72.3 ± 6.7 years) and nonfracture subjects (n = 101; mean age, 70.4 ± 4.1 years) were similar for age, weight, height, BMI, and smoking habits (Table 1). Subjects who had incident fractures had had significantly lower FNBMD (p = 0.02) and LSBMD (p = 0.03), higher serum creatinine concentrations (p = 0.05), lower endogenous creatinine clearance (p = 0.02), and a lower dietary calcium intake (p = 0.05) compared with controls. One man with incident fractures (two rib fractures) suffered a nontraumatic vertebral fracture before the first blood sample. Exclusion of this subject from the analyses did not affect the group comparisons.

Table Table 1.. Population Characteristics of Men With Incident Fractures and Controls During Follow-up of 6.3 Years
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S-ICTP levels were significantly higher in men with incident fractures compared with controls (p < 0.001), whereas S-CTX levels did not differ between these groups. S-ICTP levels were above the upper limit of normal in 37 individuals (fracture group, n = 23 [46.0%], control group, n = 14 [13.8%]), whereas S-CTX was elevated in 4 men (fracture group, n = 3, control group, n = 1). S-PINP concentrations were comparable in the fracture and nonfracture groups. Significant correlations were observed between all measured bone turnover markers (S-ICTP versus S-CTX: r = 0.48, p < 0.001; S-ICTP versus S-PINP: r = 0.23, p = 0.005; S-CTX versus S-PINP: r = 0.55, p < 0.001). Furthermore, S-ICTP was positively correlated with age (r = 0.29, p < 0.001) and serum creatinine (r = 0.44, p < 0.001), negatively with creatinine clearance (r = −0.37, p < 0.001), but not with FNBMD (r = 0.09, p = 0.25), ΔFNBMD/year (r = −0.05, p = 0.57), BMI (r = 0.07, p = 0.39), or serum albumin (r = 0.005, p = 0.10). S-PINP was not correlated with any other parameter except for the bone resorption markers.

When the entire sample was analyzed by quartiles of baseline S-ICTP levels, only men with S-ICTP levels in the highest quartile (>5.2 μg/liter; mean S-ICTP level: 6.7 ± 1.1 μg/liter) had an increased risk of fracture compared with men with levels in the lowest quartile (risk ratio, 2.8; 95% CI, 1.4, 5.4; mean S-ICTP level: 3.2 ± 0.4 μg/liter; Fig. 1A). Similar analyses of S-CTX and S-PINP levels showed similar but nonsignificant association with subsequent fracture risk (Figs. 1B and 1C).

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Figure FIG. 1.. Serum levels of biochemical markers of bone turnover at baseline—(A) S-ICTP, (B) S-CTX, and (C) S-PINP—and risk of subsequent fracture in elderly men (RR, 95% CI). The reference group consisted of men with marker serum concentrations in the lowest quartile (Q1).

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S-ICTP, serum creatinine concentration, and creatinine clearance at baseline were significant predictors of osteoporotic fractures in elderly men by univariate analysis. Each SD increase in S-ICTP (1.5 μg/liter) was associated with a 1.8-fold increase in fracture risk, and each SD increase in serum creatinine levels was associated with a 1.4-fold increase in fracture risk. There was a 1.3-fold, albeit nonsignificant, increase in fracture risk for each SD decrease in FNBMD (0.14 g/cm2; 95% CI, 0.96, 1.8) and LSBMD (0.22 g/cm2; 95% CI, 0.95, 1.7). Serum levels of CTX and PINP, ΔFNBMD/year, calcium intake, age, weight, height, and serum albumin were not significantly associated with future fractures (Table 2).

Table Table 2.. Univariate RR Ratios for Major Fracture Risk Factors, Expressed as RR and 95% CIs for 1 SD Change
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When all risk factors were simultaneously considered in a multivariate model, S-ICTP levels and FNBMD remained as sole and independent predictors of any atraumatic fracture. For each SD increase in S-ICTP, the relative risk of any type of fracture was 1.4 (95% CI, 1.0-1.9; p = 0.025). By comparison, each SD decrease in FNBMD was associated with a risk ratio of 1.8 (95% CI, 1.4-2.3; p = 0.015; Table 3). Both parameters were significant independent risk factors for hip fractures (ICTP: RR, 1.7 [95% CI, 1.2-2.6]; FNBMD: RR, 2.5 [95% CI, 1.4-4.6]) and vertebral fractures (ICTP: RR, 2.1 [95% CI, 1.3-3.3]; FNBMD: RR, 2.1 [95% CI, 1.1-4.1]). Only S-ICTP was an independent predictor of risk of nonhip/nonvertebral fractures (RR, 1.7; 95% CI, 1.1-2.4; Table 3). S-ICTP and FNBMD remained significant predictors of subsequent fractures irrespective of addition of serum creatinine levels or creatinine clearance to the multivariate regression model.

Table Table 3.. Independent Risk Factors for Atraumatic Fracture (Multivariate Analysis)
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In a risk-stratified approach, the incidence of osteoporotic fractures was calculated based on the combination of tertile values in S-ICTP and FNBMD. Men with both low FNBMD (lowest tertile) and levels of S-ICTP in the highest tertile were found to have the highest incidence of osteoporotic fractures (62%, n = 10). The lowest fracture incidence was observed in men with FNBMD in the highest tertile and S-ICTP levels in the lowest tertile (6%, n = 1; Fig. 2). The presence of a high bone resorption rate (S-ICTP in highest tertile) among men with even high bone mass (FNBMD in the highest tertile) increased the fracture incidence (47% versus 12% and 6% in lower S-ICTP tertiles). Conversely, the presence of low FNBMD amongst men with S-ICT p values in the lowest tertile increased the fracture incidence (29% versus 6% in highest FNBMD tertile; Fig. 2).

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Figure FIG. 2.. Incidence of osteoporotic fracture according to the level of S-ICTP and femoral neck BMD. The numbers in the bars represent the number of patients in each subset with at least one incident osteoporotic fracture.

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The two independent risk factors for fracture (S-ICTP, FNBMD) were analyzed as dichotomous variables to estimate the population attributable risk fraction (Table 4). Osteoporosis was defined as an FNBMD being 2.5 SD below the value for young normal males (<0.74 g/cm2), and the highest quartile cut-off was used for S-ICTP (≥5.2 μg/liter) compared with the lower three quartiles. Overall, 20% of the risk of fracture in this sample was attributable to the presence of a low BMD and/or the presence of an elevated S-ICTP level. The attributable risks for at least one osteoporotic fracture for S-ICTP and FNBMD were 17.5% and 6.5%, respectively. Because of the low prevalence of subjects having osteoporosis and also being in the high-risk quartile of S-ICTP, addition of S-ICTP levels to the presence of osteoporosis or vice versa did not add to and, specifically, lessened the individual attributable risks. Indeed, the combination of these two risk factors affected less than 3% of the population and had an attributable risk of 3.7%, which was less than that of S-ICTP alone (13.8%) but higher than FNBMD alone (2.8%). However, all four men with both low BMD and high S-ICTP sustained subsequent major fractures (vertebral and hip fractures).

Table Table 4.. Prevalence and Attributable Risks of Atraumatic Fracture for Groupings of Bone Turnover Rateand BMD
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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Prospective studies in postmenopausal women have shown that biochemical markers of bone turnover are associated with increased risk of osteoporotic fractures. In contrast, little is known about the predictive value of biochemical markers of bone turnover for osteoporotic fractures in elderly men. This longitudinal study shows that accelerated bone resorption is associated with an increased risk of osteoporotic fractures in older community-dwelling men. Notably, the association between S-ICTP levels and the risk of fracture was independent of BMD. Estimates of population attributable risk fractions indicate that 20% of the fracture risk in our population could be accounted by S-ICTP and FNBMD, to which S-ICTP alone contributed 14%.

Fracture risk in men is determined by several modifiable and nonmodifiable risk factors, including those related to BMD and bone loss. In this study, a reduction in FNBMD by 1 SD was associated with a 2.5- (95% CI, 1.4-4.6), 2.1- (95% CI, 1.1-4.1), and 1.8-fold (95% CI, 1.4-2.3) increase in risk of hip, vertebral, or any osteoporotic fracture, respectively. These risk estimates are comparable with those previously reported in men(16,25) and women.(26,27)

Other determinants of skeletal strength not necessarily reflected in BMD measurements, such as the rate of bone remodeling, may also contribute to fracture risk. In fact, several large prospective studies in postmenopausal women indicate an association between osteoporotic fracture and rate of bone turnover, independent of BMD.(8–13) Bone resorption markers above the premenopausal reference range were associated with a 2-fold increased risk of hip fracture.(12) The combination of low BMD and high resorption rate had an additive effect on fracture risk (4.2-fold increased risk).(8) The contribution of bone turnover to the risk of osteoporotic fracture in elderly men, however, had not been studied so far.

As far as men are concerned, there are only a few inconclusive studies investigating the prediction of bone loss by measurements of biochemical markers of bone turnover. Some studies found weak or nonsignificant inverse relations between markers of bone turnover and the change in BMD at the hip and spine (S-PINP, S-ICTP)(28) or at the calcaneus (osteocalcin),(29) whereas nonsignificant correlations have been reported at the forearm.(30) In accordance with previous reports,(30,31) S-ICTP and S-PINP in this study did not correlate with FNBMD at baseline or with the longitudinal change in FNBMD. This would further support our findings in that bone turnover, and more specifically, bone resorption, predicts fracture risk independent of BMD.

In adolescents, higher levels of bone turnover markers correspond to accrual and consolidation of peak bone mass. Thereafter, bone marker levels gradually decrease until the age of 40 years and remain stable until 60 years of age.(31) In elderly men (>60 years), an age-dependent dissociation between accelerated bone resorption and stable bone formation has been observed.(32–35) This imbalance in bone turnover may, at least in part, be responsible for the increased fracture risk in elderly men, which is strengthened by our findings that S-ICTP, a marker of bone resorption, predicts fracture risk independent of BMD.

In this study, only S-ICTP levels but not S-CTX levels were significantly elevated in men with subsequent fractures, and only S-ICTP was predictive for incident fractures. This discrepancy between two otherwise similar and correlated markers of bone resorption may be largely caused by differences in preanalytical variability. In the Dubbo study, serum was collected at different time-points during the day, with most patients having had their usual meals. Serum CTX levels are subject to substantial diurnal variation, and this pattern is further exaggerated by food intake,(36) whereas S-ICTP levels exhibit little diurnal variability and are little affected by food intake.(37,38) Under the circumstances of a large epidemiological study such as the Dubbo study, S-ICTP seems to be a more robust marker compared with S-CTX. To a certain extent, these findings contrast the current perception of the clinical usefulness of S-ICTP and S-CTX measurements in different bone pathologies. Thus, it has been suggested that S-ICTP is a sensitive marker of pathological bone resorption as seen in multiple myeloma, metastatic bone disease, and other processes involving rapid breakdown of type I collagen.(39,40) On the other hand, circulating S-ICTP levels seem not to reflect quite as well changes in physiological bone resorption, such as those seen in untreated early postmenopausal women or during antiresorptive therapy.(41) In contrast, the skeletal response to oestrogen withdrawal, replacement, and antiresorptive treatment is more pronounced when assessed with markers such as CTX, NTX, or DPD.(42,43) Our findings indicate that, in elderly community-dwelling men, measurement of S-ICTP levels are useful for the assessment of osteoporotic fracture risk, particularly in circumstances where sampling time frame cannot be well controlled. However, it remains to be elucidated whether, in a clinical setting, where preanalytical variability could be minimized by standardized blood sampling, other markers of bone resorption (including S-CTX) would be associated with fracture risk in elderly men.

At baseline, men with subsequent fractures were characterized by higher serum creatinine concentrations and a lower creatinine clearance than men in the control group. It is well recognized that impaired renal function affects excretion of bone resorption markers and, hence, their measured serum concentrations. Although both measures were well within the normal range in this study, the observed association between S-ICTP and risk of osteoporotic fractures might be related to impaired renal function. However, S-ICTP levels remained significantly different between men with incident fractures and controls after adjustments of individual ICTP levels for serum creatinine. Furthermore, a multivariate regression model was used to estimate the magnitude of the association between various clinical and biochemical risk factors and fracture risk to correct for confounding co-variables, including kidney function. In this model, S-ICTP remained a significant predictor of fractures after correcting for serum creatinine or creatinine clearance in the multivariate analysis. Therefore, the reported association between S-ICTP and fracture risk is independent of renal function.

Measurements of S-PINP, a marker of bone formation, were not significantly different between men with fractures and healthy controls and were not associated with increased fracture risk. This is consistent with recent cross-sectional studies(33,35) and our findings (correlation between age and S-PINP: r = −0.13, p = not significant) showing that bone formation remains largely unchanged in elderly men >60 years of age. Hence, the degree of uncoupling of bone remodeling with accelerated bone resorption and unchanged or decreased bone formation seems to be important in determining fracture risk.

The exact mechanisms by which bone resorption is regulated in aging men are not well understood. Several hormonal and biochemical parameters known to affect bone metabolism in women have been shown to change with age in men and have therefore been proposed to be involved into the age-related decline in BMD in males.(44–46) Promising candidates include gonadal hormones, vitamin D and its metabolites, and growth factors. Sex hormones play an important role in regulating bone turnover, and hence, in the acquisition and maintenance of skeletal integrity. Cross-sectional and interventional studies have shown that estradiol correlates better with BMD than circulating testosterone in elderly men.(47) In addition, recent longitudinal studies have shown that elderly men with lower total or bioavailable estradiol levels have higher rates of skeletal turnover and of bone loss.(48–50) In addition, aging has been associated with decreased serum 25-hydroxyvitamin D(51) and increased PTH levels,(52) and serum PTH was found to be an independent predictor of age- and weight-adjusted FNBMD.(46,53) Several reports have shown a significant reduction in IGF-I levels and have correlated these reductions with reduced BMD of the spine and the forearm.(54,55) Although low IGF-I levels are associated with lower BMD, an effect on bone turnover seems likely based on interactions between IGF-I and sex steroid and sex hormone-binding globulin levels.(46)

This study must be interpreted in the context of its limitations. First, as with all observational studies, the finding of this study cannot be interpreted as a causal relationship between bone resorption and fracture risk. Second, as with any cohort study, the present case-control study is potentially subject to the effect of extraneous factors, which may distort that results. However, such a confounding effect is problematic only if the confounder is a risk factor for fracture, and it is associated with the bone turnover marker. However, the controls and cases in this study have been matched for potential confounders (e.g., age). An additional strength of the study is that controls were sampled from the same source of population from which where the cases were selected. The strategy of selecting controls (by excluding individuals with concomitant diseases deemed to affect bone metabolism) is a potential weakness, because the fracture cases could have a higher prevalence of illnesses. Hence, as with any nonrandomized study, the odds ratio could be overestimated. However, the alternative strategy of including individuals with underlying illnesses likely to affect bone would be subject to potentially even more severe confounding. Third, bone formation rate was assessed by only one biochemical marker (S-PINP). S-PINP is considered an index of collagen synthesis, reflecting early osteoblastic function. However, we did assess the predictive ability of other bone formation markers, such as serum osteocalcin, reflecting the function of mature osteoblast, which has previously shown to predict fracture risk in postmenopausal women.(11,13) Fourth, asymptomatic vertebral deformity was not assessed, and this could potentially be a confounding factor, because it is a risk factor for symptomatic fracture. However, it could be argued that the magnitude of association observed is an underestimate, but more relevant to the real use of this data.

The results from this study indicate that the rate of bone resorption is an independent predictor of fracture risk also in men: for each increase in S-ICTP concentrations by 1 SD, overall fracture probability increased by 40%. The association was significant for hip fractures (RR, 1.7; 95% CI, 1.2-2.6; p < 0.01) and vertebral fractures (RR, 2.1; 95% CI, 1.3-3.3; p < 0.005). Men with S-ICTP levels in the highest quartile had a 2.8-fold increased risk of incident fractures compared with men with S-ICTP levels in the lowest quartile. In addition, fracture incidence was about 10 times higher in men with low BMD combined with a high bone resorption rate compared with men with high BMD and lower values of S-ICTP. These results indicate that bone resorption rate is an independent predictor of fracture risk and reflects aspects of bone strength distinct from the amount of mineralized bone tissue. Our findings suggest that a combination of data from BMD and bone resorption markers may improve fracture prediction in elderly men.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

This work was supported by the Australian Institute of Health and National Health and Medical Research Council of Australia. CM is the recipient of a medical research fellowship from the Swiss National Science Foundation (81BS-67544) and a research fellowship from the “Margarete und Walter Lichtenstein Stiftung der Universität Basel.”

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  • 1
    Cooper C, Campion G, Melton LJ III 1992 Hip fractures in the elderly: A world-wide projection. Osteoporos Int 2: 285289.
  • 2
    Gullberg B, Johnell O, Kanis JA 1997 World-wide projections for hip fracture. Osteoporos Int 7: 407413.
  • 3
    Jones G, Nguyen T, Sambrook PN, Kelly PJ, Gilbert C, Eisman JA 1994 Symptomatic fracture incidence in elderly men and women: The Dubbo Osteoporosis Epidemiology Study (DOES). Osteoporos Int 4: 277282.
  • 4
    Bilezikian JP 1999 Osteoporosis in men. J Clin Endocrinol Metab 84: 34313434.
  • 5
    Center JR, Nguyen TV, Schneider D, Sambrook PN, Eisman JA 1999 Mortality after all major types of osteoporotic fracture in men and women: An observational study. Lancet 353: 878882.
  • 6
    Wehren LE, Hawkes WG, Orwig DL, Hebel JR, Zimmerman SI, Magaziner J 2003 Gender differences in mortality after hip fracture: The role of infection. J Bone Miner Res 18: 22312237.
  • 7
    Chang KP, Center JR, Nguyen TV, Eisman JA 2004 Incidence of hip and other osteoporotic fractures in elderly men and women: Dubbo osteoporosis epidemiology study. J Bone Miner Res 19: 532536.
  • 8
    Garnero P, Sornay-Rendu E, Claustrat B, Delmas PD 2000 Biochemical markers of bone turnover, endogenous hormones and the risk of fractures in postmenopausal women: The OFELY study. J Bone Miner Res 15: 15261536.
  • 9
    Riis BJ, Hansen MA, Jensen AM, Overgaard K, Christiansen C 1996 Low bone mass and fast rate of bone loss at menopause: Equal risk factors for future fracture: A 15-year follow-up study. Bone 19: 912.
  • 10
    Hansen MA, Overgaard K, Riis BJ, Christiansen C 1991 Role of peak bone mass and bone loss in postmenopausal osteoporosis: 12 year study. BMJ 303: 961964.
  • 11
    van Daele PL, Seibel MJ, Burger H, Hofman A, Grobbee DE, van Leeuwen JP, Birkenhager JC, Pols HA 1996 Case-control analysis of bone resorption markers, disability, and hip fracture risk: The Rotterdam study. BMJ 312: 482483.
  • 12
    Garnero P, Hausherr E, Chapuy MC, Marcelli C, Grandjean H, Muller C, Cormier C, Breart G, Meunier PJ, Delmas PD 1996 Markers of bone resorption predict hip fracture in elderly women: The EPIDOS Prospective Study. J Bone Miner Res 11: 15311538.
  • 13
    Szulc P, Chapuy MC, Meunier PJ, Delmas PD 1996 Serum undercarboxylated osteocalcin is a marker of the risk of hip fracture: A three year follow-up study. Bone 18: 487488.
  • 14
    Cummings SR, Black DM, Nevitt MC, Browner W, Cauley J, Ensrud K, Genant HK, Palermo L, Scott J, Vogt TM 1993 Bone density at various sites for prediction of hip fractures. The Study of Osteoporotic Fractures Research Group. Lancet 341: 7275.
  • 15
    Kanis JA 2002 Diagnosis of osteoporosis and assessment of fracture risk. Lancet 359: 19291936.
  • 16
    Nguyen T, Sambrook P, Kelly P, Jones G, Lord S, Freund J, Eisman J 1993 Prediction of osteoporotic fractures by postural instability and bone density. BMJ 307: 11111115.
  • 17
    Nguyen TV, Center JR, Sambrook PN, Eisman JA 2001 Risk factors for proximal humerus, forearm, and wrist fractures in elderly men and women: The Dubbo Osteoporosis Epidemiology Study. Am J Epidemiol 153: 587595.
  • 18
    Simons LA, McCallum J, Simons J, Powell I, Ruys J, Heller R, Lerba C 1990 The Dubbo study: An Australian prospective community study of the health of elderly. Aust N Z J Med 20: 783789.
  • 19
    Nguyen TV, Kelly PJ, Sambrook PN, Gilbert C, Pocock NA, Eisman JA 1994 Lifestyle factors and bone density in the elderly: Implications for osteoporosis prevention. J Bone Miner Res 9: 13391346.
  • 20
    Nguyen TV, Sambrook PN, Eisman JA 1997 Sources of variability in bone mineral density measurements: Implications for study design and analysis of bone loss. J Bone Miner Res 12: 124135.
  • 21
    Risteli J, Elomaa I, Niemi S, Novamo A, Risteli L 1993 Radioimmunoassay for the pyridinoline cross-linked carboxy-terminal telopeptide of type I collagen: A new serum marker of bone collagen degradation. Clin Chem 39: 635640.
  • 22
    Melkko J, Kauppila S, Niemi S, Risteli L, Haukipuro K, Jukkola A, Risteli J 1996 Immunoassay for intact amino-terminal propeptide of human type I procollagen. Clin Chem 42: 947954.
  • 23
    Bonde M, Garnero P, Fledelius C, Qvist P, Delmas PD, Christiansen C 1997 Measurement of bone degradation products in serum using antibodies reactive with an isomerized form of an 8 amino acid sequence of the C-telopeptide of type I collagen. J Bone Miner Res 12: 10281034.
  • 24
    Eide GE, Gefeller O 1995 Sequential and average attributable fractions as aids in the selection of preventive strategies. J Clin Epidemiol 48: 645655.
  • 25
    Nguyen TV, Eisman JA, Kelly PJ, Sambrook PN 1996 Risk factors for osteoporotic fractures in elderly men. Am J Epidemiol 144: 255263.
  • 26
    Cummings SR, Black DM, Nevitt MC, Browner WS, Cauley JA, Genant HK, Mascioli SR, Scott JC, Seeley DG, Steiger P, Vogt TM 1990 Appendicular bone density and age predict hip fracture in women. The Study of Osteoporotic Fractures Research Group. JAMA 263: 665668.
  • 27
    Melton LJ III, Atkinson EJ, O'Fallon WM, Wahner HW, Riggs BL 1993 Long-term fracture prediction by bone mineral assessed at different skeletal sites. J Bone Miner Res 8: 12271233.
  • 28
    Chandani AK, Scariano JK, Glew RH, Clemens JD, Garry PJ, Baumgartner RN 2000 Bone mineral density and serum levels of aminoterminal propeptides and cross-linked N-telopeptides of type I collagen in elderly men. Bone 26: 513518.
  • 29
    Cheng S, Suominen H, Vaananen K, Kakonen SM, Pettersson K, Heikkinen E 2002 Serum osteocalcin in relation to calcaneal bone mineral density in elderly men and women: A 5-year follow-up. J Bone Miner Metab 20: 4956.
  • 30
    Scopacasa F, Wishart JM, Need AG, Horowitz M, Morris HA, Nordin BE 2002 Bone density and bone-related biochemical variables in normal men: A longitudinal study. J Gerontol A Biol Sci Med Sci 57: M385M391.
  • 31
    Szulc P, Delmas PD 2001 Biochemical markers of bone turnover in men. Calcif Tissue Int 69: 229234.
  • 32
    Khosla S, Melton LJ III, Atkinson EJ, O'Fallon WM, Klee GG, Riggs BL 1998 Relationship of serum sex steroid levels and bone turnover markers with bone mineral density in men and women: A key role for bioavailable estrogen. J Clin Endocrinol Metab 83: 22662274.
  • 33
    Fatayerji D, Eastell R 1999 Age-related changes in bone turnover in men. J Bone Miner Res 14: 12031210.
  • 34
    Wishart JM, Need AG, Horowitz M, Morris HA, Nordin BE 1995 Effect of age on bone density and bone turnover in men. Clin Endocrinol (Oxf) 42: 141146.
  • 35
    Szulc P, Garnero P, Munoz F, Marchand F, Delmas PD 2001 Cross-sectional evaluation of bone metabolism in men. J Bone Miner Res 16: 16421650.
  • 36
    Qvist P, Christgau S, Pedersen BJ, Schlemmer A, Christiansen C 2002 Circadian variation in the serum concentration of C-terminal telopeptide of type I collagen (serum CTx): Effects of gender, age, menopausal status, posture, daylight, serum cortisol, and fasting. Bone 31: 5761.
  • 37
    Hassager C, Risteli J, Risteli L, Jensen SB, Christiansen C 1992 Diurnal variation in serum markers of type I collagen synthesis and degradation in healthy premenopausal women. J Bone Miner Res 7: 13071311.
  • 38
    Seibel MJ 2003 Biochemical markers of bone remodeling. Endocrinol Metab Clin North Am 32: 83113. vi–vii.
  • 39
    Sassi ML, Eriksen H, Risteli L, Niemi S, Mansell J, Gowen M, Risteli J 2000 Immunochemical characterization of assay for carboxyterminal telopeptide of human type I collagen: Loss of antigenicity by treatment with cathepsin K. Bone 26: 367373.
  • 40
    Garnero P, Ferreras M, Karsdal MA, Nicamhlaoibh R, Risteli J, Borel O, Qvist P, Delmas PD, Foged NT, Delaisse JM 2003 The type I collagen fragments ICTP and CTX reveal distinct enzymatic pathways of bone collagen degradation. J Bone Miner Res 18: 859867.
  • 41
    Hassager C, Risteli J, Risteli L, Christiansen C 1994 Effect of the menopause and hormone replacement therapy on the carboxy-terminal pyridinoline cross-linked telopeptide of type I collagen. Osteoporos Int 4: 349352.
  • 42
    Garnero P, Shih WJ, Gineyts E, Karpf DB, Delmas PD 1994 Comparison of new biochemical markers of bone turnover in late postmenopausal osteoporotic women in response to alendronate treatment. J Clin Endocrinol Metab 79: 16931700.
  • 43
    Peris P, Alvarez L, Monegal A, Guanabens N, Duran M, Pons F, Martinez de Osaba MJ, Echevarria M, Ballesta AM, Munoz-Gomez J 1999 Biochemical markers of bone turnover after surgical menopause and hormone replacement therapy. Bone 25: 349353.
  • 44
    Nicolas V, Prewett A, Bettica P, Mohan S, Finkelman RD, Baylink DJ, Farley JR 1994 Age-related decreases in insulin-like growth factor-I and transforming growth factor-beta in femoral cortical bone from both men and women: Implications for bone loss with aging. J Clin Endocrinol Metab 78: 10111016.
  • 45
    Gray A, Feldman HA, McKinlay JB, Longcope C 1991 Age, disease, and changing sex hormone levels in middle-aged men: Results of the Massachusetts Male Aging Study. J Clin Endocrinol Metab 73: 10161025.
  • 46
    Center JR, Nguyen TV, Sambrook PN, Eisman JA 1999 Hormonal and biochemical parameters in the determination of osteoporosis in elderly men. J Clin Endocrinol Metab 84: 36263635.
  • 47
    Khosla S, Melton LJ III, Riggs BL 2002 Clinical review 144: Estrogen and the male skeleton. J Clin Endocrinol Metab 87: 14431450.
  • 48
    Slemenda CW, Longcope C, Zhou L, Hui SL, Peacock M, Johnston CC 1997 Sex steroids and bone mass in older men. Positive associations with serum estrogens and negative associations with androgens. J Clin Invest 100: 17551759.
  • 49
    Khosla S, Melton LJ III, Atkinson EJ, O'Fallon WM 2001 Relationship of serum sex steroid levels to longitudinal changes in bone density in young versus elderly men. J Clin Endocrinol Metab 86: 35553561.
  • 50
    Gennari L, Merlotti D, Martini G, Gonnelli S, Franci B, Campagna S, Lucani B, Dal Canto N, Valenti R, Gennari C, Nuti R 2003 Longitudinal association between sex hormone levels, bone loss, and bone turnover in elderly men. J Clin Endocrinol Metab 88: 53275333.
  • 51
    Orwoll ES, Meier DE 1986 Alterations in calcium, vitamin D, and parathyroid hormone physiology in normal men with aging: Relationship to the development of senile osteopenia. J Clin Endocrinol Metab 63: 12621269.
  • 52
    Endres DB, Morgan CH, Garry PJ, Omdahl JL 1987 Age-related changes in serum immunoreactive parathyroid hormone and its biological action in healthy men and women. J Clin Endocrinol Metab 65: 724731.
  • 53
    Martinez Diaz-Guerra G, Hawkins F, Rapado A, Ruiz Diaz MA, Diaz-Curiel M 2001 Hormonal and anthropometric predictors of bone mass in healthy elderly men: Major effect of sex hormone binding globulin, parathyroid hormone and body weight. Osteoporos Int 12: 178184.
  • 54
    Kurland ES, Rosen CJ, Cosman F, McMahon D, Chan F, Shane E, Lindsay R, Dempster D, Bilezikian JP 1997 Insulin-like growth factor-I in men with idiopathic osteoporosis. J Clin Endocrinol Metab 82: 27992805.
  • 55
    Reed BY, Zerwekh JE, Sakhaee K, Breslau NA, Gottschalk F, Pak CY 1995 Serum IGF 1 is low and correlated with osteoblastic surface in idiopathic osteoporosis. J Bone Miner Res 10: 12181224.