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Keywords:

  • INFLAMMATORY BOWEL DISEASE;
  • OSTEOPOROSIS;
  • BONE MINERAL DENSITY;
  • FRACTURE;
  • FRAX;
  • POPULATION-BASED

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

Subjects with inflammatory bowel disease (IBD) are at increased risk for hip and other major osteoporotic fractures. However, previous analyses have not fully accounted for differences in bone mineral density (BMD) and other clinical factors that affect the risk of fracture. The World Health Organization Fracture Risk Assessment tool (FRAX) can be used to predict the 10-year fracture risk from BMD and clinical risk factors. A population-based database containing clinical information on all IBD subjects in the province of Manitoba, Canada, was linked with the Manitoba Bone Mineral Density Database, which contains results of all dual X-ray absorptiometry (DXA) scans in the province. FRAX probabilities were calculated for all subjects aged 50 years or more undergoing baseline DXA testing. Subjects were followed for occurrence of major osteoporotic fractures (MOF; hip, clinical spine, wrist, humerus). Cox proportional hazards models were used to determine whether IBD was independently predictive of MOF or hip fracture. After controlling for FRAX fracture probability computed with BMD, IBD was not associated with a significantly increased risk for MOF (hazard ratio [HR] = 1.12, 95% confidence interval [CI], 0.83–1.55) but was associated with an increased risk for hip fracture (HR = 2.14; 95% CI, 1.26–3.65). The addition of femoral neck T-score to FRAX probability without knowledge of BMD had a negligible effect on the estimated HRs for IBD, suggesting that IBD mediates any effect on fracture risk independently of femoral neck BMD. After controlling for FRAX probability, subjects with IBD are not at an increased risk for overall MOF, but may be at increased risk of hip fracture. © 2013 American Society for Bone and Mineral Research.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

The development of fracture is the most clinically relevant complication of reduced bone mineral density (BMD).1 Although decreasing BMD is strongly associated with an increased risk of fracture, the use of BMD measurement alone to predict fracture is limited.2–5 It has been demonstrated that fracture risk is assessed more accurately by considering other clinical risk factors in addition to BMD.6, 7 The most widely used fracture prediction instrument is the World Health Organization's fracture risk assessment tool (FRAX).8 FRAX combines multiple clinical parameters known to affect fracture risk independently of their effects on BMD. FRAX used with BMD has been demonstrated to more accurately predict 10-year fracture probability than BMD or clinical risk factors alone in both men and women over age 50 years of age.8, 9

The clinical risk factors included in the calculation of the FRAX probability include age, sex, body mass index (BMI), prolonged use of glucocorticoids, parental hip fracture, current smoking, alcohol intake ≥3 units per day, rheumatoid arthritis, prior fragility fracture, and femoral neck BMD. FRAX can be used to estimate fracture risk in situations where the femoral neck BMD is not known (clinical FRAX).10 In the clinical FRAX score, the presence of other conditions that are believed to increase the risk of fracture and reduced BMD are included in the model as causes of “secondary osteoporosis.” Therefore, when considering the presence of comorbid conditions, one must determine whether that condition increases the risk of fracture only by affecting BMD, or whether it exerts an effect on fracture risk independent of BMD. Whereas rheumatoid arthritis is the only disease diagnosis currently considered within FRAX to exert a BMD-independent effect on fracture risk, there is emerging evidence that other conditions, including diabetes, may increase the risk of fracture over and above any effects on BMD and the other risk factors already included in FRAX.11, 12 This may justify inclusion of diabetes and other conditions as primary entry variables in future iterations of the FRAX algorithm.13

The inflammatory bowel diseases (IBD)—Crohn's disease (CD) and ulcerative colitis (UC)—are associated with up to a 40% increased risk of fracture and an increased prevalence of osteoporosis.14, 15 However, it is not clear whether IBD is a primary risk factor for low BMD and fracture, or whether other factors common in persons with IBD, such as corticosteroid use and low BMI, may predispose to both low BMD and fracture and mediate the effect of IBD on skeletal outcomes.16, 17 Although IBD is not currently considered in the calculation of FRAX when BMD is known, it is considered as a cause of secondary osteoporosis in the calculation of clinical FRAX, even though the evidence supporting a direct effect of IBD on BMD is equivocal.18, 19 Therefore, we sought to determine whether IBD predicts either major osteoporotic fractures (MOF) or hip fractures independent of FRAX probability.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

Identification of IBD subjects

The University of Manitoba IBD Epidemiologic Database (UMIBDED) is a validated population-based administrative database of all Manitobans with IBD dating back to 1984 that has been well described. Manitoba is a central Canadian province with a population of 1.25 million.20 Persons in the UMIBDED were considered to be incident cases if initial case definition occurred in 1987 or later and there had been no IBD-related diagnoses in the 3 years prior. Every Manitoba resident is provided with a nine-digit personal health identification number (PHIN). Every time the individual has an inpatient or outpatient encounter (including hospitalization, outpatient clinic visits, prescription drug dispensation, or diagnostic testing), Manitoba Health tracks that encounter by individual PHIN. As of March 31, 2008, there were over 10,467 unique subjects in the UMIBDED database. Subjects were matched by age, sex, and geography 10:1 to controls without a diagnosis of IBD. The UMIBDED includes all outpatient physician contacts and hospitalizations since 1984, but prescription drug use dating back to only 1995 (because that is when the provincial prescription drug database was established). The UMIBDED does not contain any information on subjective patient symptoms, the results of radiographic and/or endoscopic examinations, or the use of over-the-counter medications.

Tracking of BMD testing

Dual X-ray absorptiometry (DXA) testing has been managed as an integrated clinical program in Manitoba since 1997.21 The program maintains a database of all DXA results performed in Manitoba (the Manitoba Bone Mineral Densitometry Database [MBMDD]), capturing demographics, risk factors, and anthropometric measures (weight, height, and BMI). Furthermore, the MBMDD has also been linked to other population-based healthcare datasets, such as a province-wide drug dispensation database, allowing prescription medications that may affect BMD and/or fracture risk to be accurately tracked.22 Fracture-related outcomes are linked to the MBMDD, permitting detection of diagnosed MOF (hip, clinical vertebra, forearm, humerus) using a validated coding algorithm.23 DXA testing criteria are broadly consistent with published guidelines and emphasize the importance of female sex, age greater than 65 years, premature gonadal failure, prior fragility fracture, X-ray evidence of osteopenia, and prolonged glucocorticoid use. Testing is not restricted to these indications and is performed whenever additional justification is provided. Virtually all scans were performed on one of four cross-calibrated instruments (Lunar DPX and Prodigy; GE Healthcare, Madison, WI, USA). T-scores were calculated using the manufacturer's USA reference values for the lumbar spine and the Third National Health and Nutrition Examination Survey (NHANES III) white reference values for the hip.24 The database has been carefully validated and extensively used for clinical research, with completeness and accuracy exceeding 99%.21 Densitometers have shown stable long-term performance (phantom coefficient of variation <0.5%) and satisfactory in vivo short-term precision (coefficient of variation for mean interval 1 week, 1.9% to 2.4% for the femoral neck).25

Database linkage

Using a scrambled version of the PHIN to preserve confidentiality, it was possible to anonymously link the health care utilization data tracked in the UMIBDED to the MBMDD (by matching PHINs in both databases), allowing for all subjects in the MBMDD who have diagnosed IBD to be linked with indicators of healthcare utilization, demographics, anthropometrics, and BMD results.

Calculation of FRAX probability

Weight and height were obtained by self-report at the time of the DXA examination before the year 2000. After 2000, height was assessed with a wall-mounted stadiometer and weight was assessed without shoes using a standard floor scale. BMI (in kg/m2) was calculated as weight (kg) divided by height (m) squared. Additional clinical risk factors required for calculating fracture probability with FRAX were assessed through a combination of hospital discharge abstracts (diagnoses and procedures coded using the International Classification of Diseases (ICD)-9-CM before 2004 and ICD-10-CA thereafter) and physician billing claims (coded using ICD-9-CM). We defined prior fragility fracture as a MOF fracture that occurred before BMD testing and that was not associated with external injury codes, as described.23 A diagnosis of rheumatoid arthritis was taken from physician office visits or hospitalizations with a compatible ICD-9-CM/ICD-10-CA code in a 3-year period before BMD testing. Proxies were used for smoking (chronic obstructive pulmonary disease [COPD] diagnosis) and high alcohol intake (alcohol or substance abuse diagnosis) over the same time frame.9 Prolonged glucocorticoid use was defined as greater than 90 days dispensed in the year before DXA testing. We adjusted for the effect of missing parental hip fracture information on FRAX probability estimates before 2005 using age- and sex-specific adjustment factors derived from 2005 to 2008 parental hip fracture responses as described.9 We used the provincial prescription drug database to identify use of osteoporosis-related medication (90 days or more of pharmacy dispensations for hormone therapy, bisphosphonate, selective estrogen receptor modulator, parathyroid hormone or recombinant human parathyroid hormone analog [1-34], or calcitonin during the year before the BMD test). We did not include secondary causes of osteoporosis in the calculation of FRAX probabilities in order to test the hypothesis that IBD is a risk factor for fracture independent of FRAX.

Ten-year probabilities of a MOF and hip fracture were calculated for each subject by the WHO Collaborating Centre for Metabolic Bone Diseases without knowledge of the fracture outcomes with the Canadian FRAX tool (version 3.1) from the previously defined variables and femoral neck BMD.26 FRAX estimates with the Canadian tool agree closely with observed fracture rates in the Canadian population.9, 27 Ten-year MOF probabilities from FRAX with BMD were categorized as low (<10%), moderate (10% to 19%), or high (≥20%), in accordance with national guidelines.28, 29

Assessing effect of IBD on fracture risk

Analyses included all persons in Manitoba who were aged 50 years or over on the date of initial DXA. Persons with IBD were included if they met diagnostic criteria for IBD prior to the date of the initial DXA. Subjects were then followed forward until the occurrence of the first MOF, end of follow-up (March 31, 2008), death, or outmigration, with observations truncated at 10 years from the time of DXA. In a secondary analysis, subjects were followed forward until the occurrence of hip fracture. Cox proportional hazards modeling was performed to assess the independent effect of IBD on the hazard of both MOF and hip fracture, controlling (1) for the individual components of FRAX, and (2) FRAX probability as a continuous variable (log-transformed to account for a skewed distribution). We then compared the estimated hazard of MOF for IBD predicted using FRAX without BMD (clinical FRAX) with that obtained with FRAX utilizing BMD in order to assess whether the association of IBD and fracture was mediated through changes in BMD. Subgroup analyses were also performed for IBD disease subtypes (CD and UC), and for duration of IBD from time of diagnosis until date of BMD testing (greater than versus less than 10 years duration). We also performed a secondary analysis in which all users of osteoprotective medications were excluded to ensure that use of osteoprotectives prior to the initial BMD would not lead to an underestimation of fracture risk. We then compared the incidence of MOF between IBD and non-IBD subjects stratified into low-, moderate-, and high-risk categories using log-rank testing. In these analyses, death was treated as a competing risk for fracture.6, 30 All analyses were performed using SAS 9.2 (SAS Institute, Inc., Cary, NC, USA).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

A total of 38,812 subjects age 50 years and older underwent baseline DXA studies from 1997 through 2008, 647 of whom (1.7%) had a diagnosis of IBD (333 CD, 314 UC). The mean duration from time of DXA to final follow up was 5.3 ± 2.7 years. During follow-up, a total of 2579 persons developed at least one MOF, 43 of which occurred among subjects with IBD. Hip fractures were identified in 503 persons, 14 of whom had a prior diagnosis of IBD.

Baseline characteristics of subjects with and without IBD are displayed in Table 1. Subjects with IBD were more likely to be male and to have used glucocorticoids in the last year. Patients with IBD had slightly greater BMI and were slightly younger than subjects without IBD. Subjects with CD were on average older than persons with UC within this cohort. The mean femoral neck Z-scores were +0.1 (SD 1.0) and −0.2 (SD 1.0) for non-IBD and IBD subjects, respectively (p < 0.001), indicating that non-IBD subjects were representative of the BMD reference population whereas IBD subjects had slightly lower BMD than expected for age and sex.

Table 1. Baseline Characteristics of Subjects With and Without IBD
 Non-IBD n = 38165IBD n = 647p
  • IBD = inflammatory bowel disease; BMI = body mass index; COPD = chronic obstructive pulmonary disease; FRAX = Fracture Risk Assessment Tool; MOF = major osteoporotic fractures.

  • a

    Parental fracture history known in 204 IBD subjects and 10,539 non IBD subjects.

Male, %7.219.6<0.0001
 Age (years), mean (SD)65.6 (9.8)62.4 (9.3)<0.0001
BMI (kg/m2), mean (SD)26.8 (5.2)26.3 (5.0)0.015
Rheumatoid arthritis (%)3.93.40.62
COPD (%)8.710.80.064
Diabetes (%)9.09.60.65
Alcohol abuse (%)2.54.00.026
Recent glucocorticoid use (%)5.218.4<0.0001
Recent osteoporosis treatment (%)5.56.30.39
Prior fracture (%)13.810.40.013
Parental hip fracturea (%)13.08.80.18
Femoral neck T-score, mean (SD)−1.4 (1.0)−1.1 (1.0)<0.0001
Femoral neck Z-score, mean (SD)+0.1 (1.0)−0.2 (1.0)<0.0001
FRAX predicted probability of MOF   
 Mean (SD)10.9 (7.2)9.7 (6.2)<0.0001
 Median (interquartile range)8.7 (6.0–13.7)7.7 (5.4–12.5)<0.0001
FRAX predicted probability of hip fracture   
 Mean (SD)2.8 (4.4)2.3 (3.5)0.0004
 Median (interquartile range)1.2 (0.4–3.5)0.9 (0.3–3.0)0.0076

IBD was not significantly associated with an increased risk of MOF when adjusted for age and sex (hazard ratio [HR] = 1.14; 95% confidence interval [CI] = 0.84–1.55; Table 2). Results were similar when patients with CD and UC were considered separately. In the model that used the individual components of FRAX in place of the calculated FRAX probability, increasing age, rheumatoid arthritis, COPD, alcohol abuse, lower femoral neck T-score, and previous fracture were all associated with increased risk of subsequent MOF. Stratifying IBD subjects by duration of disease (greater than versus less than 10 years at the time of BMD testing) did not significantly alter the point estimates for IBD-related fracture risk (IBD duration >10 years: HR = 1.13; 95% CI, 0.69–1.84; IBD duration <10 years: HR = 1.27; 95% CI, 0.79–2.05). Exclusion of subjects using osteoprotective medications at the time of their initial BMD assessment also did not greatly influence the estimated magnitude of the association of IBD with MOF (HR = 1.20; 95% CI, 0.85–1.69).

Table 2. Predictors of Major Osteoporotic Fracture Risk
PredictorHazard ratio (95% confidence interval)
  • Results obtained for fracture prediction model in 38,249 subjects undergoing initial DXA testing.

  • IBD = inflammatory bowel disease; CD = Crohn's disease; UC = ulcerative colitis; FRAX = Fracture Risk Assessment Tool; BMD = bone mineral density; BMI = body mass index; COPD = chronic obstructive pulmonary disease; MOF = major osteoporotic fractures.

  • a

    FRAX probability for MOF calculated using the Canadian tool (version 3.1).

IBD (controlling for age/sex only)1.14 (0.84–1.55)
CD (controlling for age/sex only)1.38 (0.92–2.06)
UC (controlling for age/sex only)0.94 (0.60–1.47)
IBD (controlling for FRAX with BMD)a1.12 (0.83–1.53)
CD (controlling for FRAX with BMD)1.26 (0.83–1.90)
UC (controlling for FRAX with BMD)1.00 (0.64–1.67)
IBD (controlling for all variables below)1.08 (0.81–1.44)
CD (controlling for all variables below)1.16 (0.77–1.73)
UC (controlling for all variables below)1.01 (0.67–1.51)
IBD (adjusted for FRAX clinical)1.15 (0.85–1.55)
Male sex1.15 (0.98–1.35)
Age (year)1.03 (1.03–1.04)
BMI (kg/m2)1.00 (0.99–1.01)
Rheumatoid arthritis1.49 (1.26–1.77)
COPD1.28 (1.13–1.44)
Alcohol abuse1.62 (1.32–1.98)
Glucocorticoid use1.09 (0.92–1.29)
Osteoprotective medication use1.13 (0.97–1.31)
Previous fracture2.12 (1.94–2.31)
Femoral neck T-score (per SD decrease)1.55 (1.48–1.64)

Analysis of hip fractures was limited by the small number of events in IBD patients, and was insufficient to compare CD and UC, or model the individual components of FRAX. IBD was independently predictive of hip fracture risk after simple age/sex adjustment (HR = 2.34; 95% CI, 1.37–3.99) and after adjustment for FRAX probability estimated with BMD (HR = 2.14; 95% CI, 1.26–3.65) (Table 3).

Table 3. Predictors of Hip Fracture
PredictorHazard ratio (95% confidence interval)
  • Results obtained for fracture prediction model in 38,249 subjects undergoing initial DXA testing.

  • IBD = inflammatory bowel disease; FRAX = Fracture Risk Assessment Tool; BMD = bone mineral density; DXA = dual-energy X-ray absorptiometry.

  • a

    FRAX probability for hip fracture calculated using the Canadian tool (version 3.1).

IBD (controlling for age/sex only)2.34 (1.37–3.99)
IBD (controlling for FRAX with BMD)a2.14 (1.26–3.64)
IBD (adjusted for FRAX clinical)2.10 (1.23–3.57)

After controlling for the FRAX probability without knowledge of femoral neck T-score (clinical FRAX), IBD was not independently predictive of MOF (HR = 1.15; 95% CI, 0.85–1.55 for MOF) but was predictive of hip fracture (HR = 2.10; 95% CI, 1.23–3.57). The addition of femoral neck T-score to the model had negligible effect on the estimated HRs for IBD (for MOF: HR = 1.12, 95% CI, 0.83–1.53; for hip fracture: HR = 2.14, 95% CI, 1.26–3.64), suggesting that IBD mediates any effect on fracture risk independently of femoral neck BMD.

The 10-year cumulative incidences of MOF for subjects with and without IBD, stratified as low, medium, or high risk, are displayed in Fig. 1. There were no significant differences in the risk of fracture at any of the predicted risk levels between subjects with and without IBD for MOF.

thumbnail image

Figure 1. Ten-year observed fracture incidence versus predicted MOF probability category.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

We did not detect an increase in the risk of MOF in subjects with IBD after controlling for FRAX probability estimated both with and without BMD. Conversely, the risk of developing a hip fracture among subjects with IBD was increased even after controlling for FRAX probability estimated with and without BMD, though confidence in this observation is limited by the small number of fracture events and the wide CIs. The addition of femoral neck BMD to the calculation of the FRAX score did not significantly influence the estimated risk associated with IBD for hip fracture, suggesting that IBD exerts a BMD-independent effect on hip fracture risk.

The results of this study are in contrast to the current body of evidence, which generally show an association between IBD and the risk of nontraumatic fracture. Bernstein and colleagues14 demonstrated that subjects with IBD were at 40% increased risk of fracture compared to age-, sex-, and geographically-matched controls. However, this study did not control for potential confounders which may be related to a diagnosis of IBD and the occurrence of fracture, including higher rates of glucocorticoid use, lower BMI, and lower BMD among persons with IBD when compared to the general population. In another study Bernstein and colleagues31 reported that most subjects with IBD who fractured hips, spine, ribs, or wrists were not using glucocorticoids within 2 years prior to fracture. Hence, these earlier studies showed that factors other than glucocorticoids, including possibly IBD itself, contribute to the fracture risk. Subjects with IBD have higher rates of glucocorticoid use and lower BMI than non-IBD subjects, although a recent study did not find an independent association between IBD and lower T-scores at the lumbar spine, femoral neck, or total hip after adjustment for other risk factors including glucocorticoid use and BMI.19 These findings suggest that although subjects with IBD may indeed be at increased risk of MOF, the increased risk may be mediated through other factors (such as low BMI and glucocorticoid use) rather than being directly attributable to the IBD diagnosis.

Despite our not being able to identify an independent association between IBD and MOFs, we still found that IBD was a risk factor for hip fracture even after controlling for FRAX. Multiple population-based studies have demonstrated an association between IBD and hip fracture,14, 15, 32 although this is the first study that has demonstrated the persistence of this risk after controlling for FRAX probability. The reason for the apparent difference between hip fractures and MOFs remain speculative. It is possible that persons with IBD thought to be at increased risk for hip fracture were preferentially channeled toward BMD testing, and that these IBD subjects may not be representative of the IBD population as a whole. Furthermore, because there were only a small number of IBD patients who underwent BMD testing who developed fractures, this raises the possibility of a Type II error in our estimates of the association of IBD with MOFs. The upper limit of the 95% CI reaches 1.55, which would be in keeping with previous studies that have found an association between IBD and overall fracture risk. Also, it is possible that IBD, and especially chronically or recurrently active IBD with ongoing inflammation, may be associated with malnutrition and/or weight loss, may predispose to muscle weakness, sarcopenia, or sideways falls, or may negatively affect femoral strength or structure beyond its effect on BMD alone, thereby predisposing to hip fracture in a manner independent of FRAX. More research is required to determine which FRAX risk factors are driving the apparent increased risk of hip fractures in IBD. However, given the limited number of hip fractures in the IBD cohort and the wide CIs in the HR estimate, it is difficult to accurately ascertain the magnitude of the effect of IBD on hip fracture risk.

Although some studies have suggested that the risk of low BMD is higher in patients with CD than in UC,33, 34 large population-based studies have demonstrated little difference in the fracture risk between these two subsets of IBD.14, 15 On the other hand, previous work using the MBMDD suggested that CD subjects are twice as likely to have osteoporosis (T-score ≤ −2.5) at the femoral neck than UC subjects.19 Furthermore, CD subjects in the MBMDD have BMIs that are on average 6% lower than subjects with UC. Because we were able to control for many of the fracture risk factors that may differ between CD and UC, such as lower BMI and BMD, this may have eliminated any difference between CD and UC in the apparent fracture risk.

Currently, rheumatoid arthritis is the only chronic inflammatory disease that is taken into consideration in the calculation of FRAX probability with BMD, based on previous work that has demonstrated that rheumatoid arthritis independently increases the risk of osteoporosis-related fractures.7 Recent analyses have also demonstrated that diabetics are at increased risk of MOFs and hip fracture, independent of FRAX probability computed with BMD, suggesting that diabetes status could be considered for inclusion as a primary entry variable in future iterations of the FRAX algorithm or other fracture prediction tools.11, 12 Our finding that IBD was not associated with MOF after controlling for FRAX probability but was independently predictive of hip fracture risk indicates the need for additional studies in populations with greater numbers of fractures before a final conclusion can be reached.

This study has the advantage of having the largest population of BMD testing, including over 1000 subjects with a validated diagnosis of IBD; however, there are some limitations worthy of mention. Although this dataset contains the results of all DXA testing performed within the population, not everyone in the population undergoes BMD testing. Therefore, it is possible that subjects in the MBMDD are not necessarily representative of the population at large. However, even if there is a referral bias toward subjects at a higher baseline risk of fracture, there is little reason to believe that the magnitude of the estimates of risk for any of the specific variables would differ between the tested population and the untested population. Indeed, previous studies have shown that observed fracture incidence in the MBMDD population is in close agreement with predicted fracture risk as determined with FRAX. Also, it is possible that subjects with IBD who underwent testing were not representative of the spectrum of IBD severity, and thus the risk estimates obtained for IBD would not represent the full spectrum of disease. However, assuming that the referral bias would be in favor of subjects with more severe IBD being more likely to undergo BMD testing, one would expect the fracture risk associated with IBD in this analysis to be overestimated.

In conclusion, IBD does not affect MOF fracture risk independent of fracture probability calculated with FRAX. IBD was associated with a significantly increased risk of hip fracture, and if this is confirmed in larger studies then it would imply that FRAX could underestimate hip fracture risk in the presence of IBD.

Disclosures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

CNB is supported in part by the Bingham Chair in Gastroenterology and has served on advisory boards or consulted to Abbott Canada, Janssen Canada, Bristol Myers Squibb, and Vertex Pharmaceuticals, and received research grants from Abbott Canada and Prometheus Laboratories and an unrestricted educational grant from Aptalis Pharmaceuticals. EM has received speaker fees and/or unrestricted research grants from Novartis, Amgen, AstraZeneca, Pfizer, Bayer, Warner-Chilcott/Procter & Gamble, Lilly, Roche, Servier, and Hologic. JAK: Industry: Abiogen, Italy; Amgen, USA, Switzerland and Belgium; Bayer, Germany; Besins-Iscovesco, France; Biosintetica, Brazil; Boehringer Ingelheim, UK; Celtrix, USA; D3A, France; Gador, Argentina; General Electric, USA; GSK, UK, USA; Hologic, Belgium and USA; Kissei, Japan; Leiras, Finland; Leo Pharma, Denmark; Lilly, USA, Canada, Japan, Australia and UK; Merck Research Labs, USA; Merlin Ventures, UK; MRL, China; Novartis, Switzerland and USA; Novo Nordisk, Denmark; Nycomed, Norway; Ono, UK and Japan; Organon, Holland; Parke-Davis, USA; Pfizer USA; Pharmexa, Denmark; Procter and Gamble, UK, USA; ProStrakan, UK; Roche, Germany, Australia,Switzerland, USA; Rotta Research, Italy; Sanofi-Aventis, USA; Schering, Germany and Finland; Servier, France and UK; Shire, UK; Solvay, France and Germany; Strathmann, Germany; Tethys, USA; Teijin, Japan;Teva, Israel; UBS, Belgium; Unigene, USA; Warburg-Pincus, UK; Warner-Lambert, USA; Wyeth, USA. Governmental and NGOs: National Institute for Health and Clinical Excellence (NICE), UK; International Osteoporosis Foundation; National Osteoporosis Guideline Group (NOGG), UK; INSERM, France; Ministry of Public Health, China; Ministry of Health, Australia; National Osteoporosis Society (UK); WHO. WDL has served on advisory boards for Novartis, Amgen, Genzyme; received unrestricted research grants from Amgen; received speaker fees from Amgen. LET has served on an advisory board for Merck Canada and Janssen Canada, and on the Speakers' Panel for Pfizer Canada. The other authors report no competing interests.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

This project was funded through the American College of Gastroenterology 2011 Clinical Research Award. LET is supported by a Canadian Institutes of Health Research (CIHR)/Osteoporosis Canada New Investigator Grant. CNB is supported by the University of Manitoba Bingham Chair in Gastroenterology. LET, CNB, ZN, and WDL had access to raw data as allowed through the Manitoba Health Information Privacy Committee. The authors are indebted to Manitoba Health for the provision of data (HIPC file no. 2009/2010 -42). The results and conclusions are those of the authors and no official endorsement by the Manitoba Centre for Health Policy, Manitoba Health, or other data providers is intended or should be inferred. This article has been reviewed and approved by the members of the Manitoba Bone Density Program Committee.

Authors' roles: Study design, study conduct: data analysis, data interpretation: LET, CNB, ZN, and WDL. Drafting of initial manuscript: LET. Revising manuscript content: LET, CNB, WDL, JAK, AO, HJ, EM. Approving final version of manuscript: LET, CNB, ZN, WDL, JAK, AO, HJ, EM. LET takes responsibility for the integrity of the data analysis.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References
  • 1
    Johnell O, Kanis JA, Oden A, Johansson H, De Laet C, Delmas P, Eisman JA, Fujiwara S, Kroger H, Mellstrom D, Meunier PJ, Melton LJ 3rd, O'Neill T, Pols H, Reeve J, Silman A, Tenenhouse A. Predictive value of BMD for hip and other fractures. J Bone Miner Res. 2005;20(7):118594.
  • 2
    Cranney A, Jamal SA, Tsang JF, Josse RG, Leslie WD. Low bone mineral density and fracture burden in postmenopausal women. CMAJ. 2007;177(6):57580.
  • 3
    Marshall D, Johnell O, Wedel H. Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ. 1996;312(7041):12549.
  • 4
    Stone KL, Seeley DG, Lui LY, Cauley JA, Ensrud K, Browner WS, Nevitt MC, Cummings SR. Osteoporotic Fractures Research Group. BMD at multiple sites and risk of fracture of multiple types: long-term results from the Study of Osteoporotic Fractures. J Bone Miner Res. 2003;18(11):194754.
  • 5
    Siris ES, Chen YT, Abbott TA, Barrett-Connor E, Miller PD, Wehren LE, Berger ML. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med. 2004;164(10):110812.
  • 6
    Robbins J, Aragaki AK, Kooperberg C, Watts N, Wactawski-Wende J, Jackson RD, LeBoff MS, Lewis CE, Chen Z, Stefanick ML, Cauley J. Factors associated with 5-year risk of hip fracture in postmenopausal women. JAMA. 2007;298(20):238998.
  • 7
    Kanis JA, Borgstrom F, De Laet C, Johansson H, Johnell O, Jonsson B, Oden A, Zethraeus N, Pfleger B, Khaltaev N. Assessment of fracture risk. Osteoporos Int. 2005;16(6):5819.
  • 8
    Kanis JA, Oden A, Johnell O, Johansson H, De Laet C, Brown J, Burckhardt P, Cooper C, Christiansen C, Cummings S, Eisman JA, Fujiwara S, Glüer C, Goltzman D, Hans D, Krieg MA, La Croix A, McCloskey E, Mellstrom D, Melton LJ 3rd, Pols H, Reeve J, Sanders K, Schott AM, Silman A, Torgerson D, van Staa T, Watts NB, Yoshimura N. The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women. Osteoporos Int. 2007;18(8):103346.
  • 9
    Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA. Independent clinical validation of a Canadian FRAX tool: fracture prediction and model calibration. J Bone Miner Res. 2010;25(11):23508.
  • 10
    Kanis JA, McCloskey E, Johansson H, Oden A, Leslie WD. FRAX® with and without bone mineral density. Calcif Tissue Int. 2012;90(1):113.
  • 11
    Giangregorio LM, Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA. FRAX underestimates fracture risk in patients with diabetes. J Bone Miner Res. 2012;27(2):3018.
  • 12
    Schwartz AV, Vittinghoff E, Bauer DC, Hillier TA, Strotmeyer ES, Ensrud KE, Donaldson MG, Cauley JA, Harris TB, Koster A, Womack CR, Palermo L, Black DM. Study of Osteoporotic Fractures (SOF) Research Group; Osteoporotic Fractures in Men (MrOS) Research Group; Health, Aging, and Body Composition (Health ABC) Research Group. Association of BMD and FRAX score with risk of fracture in older adults with type 2 diabetes. JAMA. 2011;305(21):218492.
  • 13
    Leslie WD, Rubin MR, Schwartz AV, Kanis JA. Type 2 diabetes and bone. J Bone Miner Res. 2012;27(11):22317.
  • 14
    Bernstein CN, Blanchard JF, Leslie W, Wajda A, Yu BN. The incidence of fracture among patients with inflammatory bowel disease. A population-based cohort study. Ann Intern Med. 2000;133(10):7959.
  • 15
    van Staa TP, Cooper C, Brusse LS, Leufkens H, Javaid MK, Arden NK. Inflammatory bowel disease and the risk of fracture. Gastroenterology. 2003;125(6):15917.
  • 16
    Bernstein CN, Seeger LL, Sayre JW, Anton PA, Artinian L, Shanahan F. Decreased bone density in inflammatory bowel disease is related to corticosteroid use and not disease diagnosis. J Bone Miner Res. 1995;10(2):2506.
  • 17
    Jahnsen J, Falch JA, Aadland E, Mowinckel P. Bone mineral density is reduced in patients with Crohn's disease but not in patients with ulcerative colitis: a population based study. Gut. 1997;40(3):3139.
  • 18
    Jahnsen J, Falch JA, Mowinckel P, Aadland E. Bone mineral density in patients with inflammatory bowel disease: a population-based prospective two-year follow-up study. Scand J Gastroenterol. 2004;39(2):14553.
  • 19
    Targownik LE, Bernstein CN, Leslie WD, Nugent Z. The relationship between inflammatory bowel disease and bone mineral density. Results of a population-based study. Am J Gastroenterol. 2011;106(S2):S492.
  • 20
    Bernstein CN, Blanchard JF, Rawsthorne P, Wajda A. Epidemiology of Crohn's disease and ulcerative colitis in a central Canadian province: a population-based study. Am J Epidemiol. 1999;149(10):91624.
  • 21
    Leslie WD, Caetano PA, Macwilliam LR, Finlayson GS. Construction and validation of a population-based bone densitometry database. J Clin Densitom. 2005;8(1):2530.
  • 22
    Kozyrskyj AL, Mustard CA. Validation of an electronic, population-based prescription database. Ann Pharmacother. 1998;32(11):11527.
  • 23
    Lix LM, Azimaee M, Acan Osman B, Caetano P, Morin S, Metge C, Goltzman D, Kreiger N, Prior J, Leslie WD. Osteoporosis-related fracture case definitions for population-based administrative data. BMC Public Health. 2012;12(1):301.
  • 24
    Looker AC, Orwoll ES, Johnston CC Jr, Lindsay RL, Wahner HW, Dunn WL, Calvo MS, Harris TB, Heyse SP. Prevalence of low femoral bone density in older U.S. adults from NHANES III. J Bone Miner Res. 1997;12(11):1761178.
  • 25
    Leslie WD. The importance of spectrum bias on bone density monitoring in clinical practice. Bone. 2006;39(2):3618.
  • 26
    Leslie WD, Lix LM, Langsetmo L, Berger C, Goltzman D, Hanley DA, Adachi JD, Johansson H, Oden A, McCloskey E, Kanis JA. Construction of a FRAX® model for the assessment of fracture probability in Canada and implications for treatment. Osteoporos Int. 2011;22(3):81727.
  • 27
    Fraser LA, Langsetmo L, Berger C, Ioannidis G, Goltzman D, Adachi JD, Papaioannou A, Josse R, Kovacs CS, Olszynski WP, Towheed T, Hanley DA, Kaiser SM, Prior J, Jamal S, Kreiger N, Brown JP, Johansson H, Oden A, McCloskey E, Kanis JA, Leslie WD. CaMos Research Group. Fracture prediction and calibration of a Canadian FRAX® tool: a population-based report from CaMos. Osteoporos Int. 2011;22(3):82937.
  • 28
    Papaioannou A, Morin S, Cheung AM, Atkinson S, Brown JP, Feldman S, Hanley DA, Hodsman A, Jamal SA, Kaiser SM, Kvern B, Siminoski K, Leslie WD. Scientific Advisory Council of Osteoporosis Canada. 2010 clinical practice guidelines for the diagnosis and management of osteoporosis in Canada: summary. CMAJ. 2010;182(17):186473.
  • 29
    Dawson-Hughes B. A revised clinician's guide to the prevention and treatment of osteoporosis. J Clin Endocrinol Metab. 2008;93(7):24635.
  • 30
    Satagopan JM, Ben-Porat L, Berwick M, Robson M, Kutler D, Auerbach AD. A note on competing risks in survival data analysis. Br J Cancer. 2004;91(7):122935.
  • 31
    Bernstein CN, Blanchard JF, Metge C, Yogendran M. The association between corticosteroid use and development of fractures among IBD patients in a population-based database. Am J Gastroenterol. 2003;98(8):1797801.
    Direct Link:
  • 32
    Card T, West J, Hubbard R, Logan RF. Hip fractures in patients with inflammatory bowel disease and their relationship to corticosteroid use: a population based cohort study. Gut. 2004;53(2):2515.
  • 33
    Gokhale R, Favus MJ, Karrison T, Sutton MM, Rich B, Kirschner BS. Bone mineral density assessment in children with inflammatory bowel disease. Gastroenterology. 1998;114(5):90211.
  • 34
    Ghosh S, Cowen S, Hannan WJ, Ferguson A. Low bone mineral density in Crohn's disease, but not in ulcerative colitis, at diagnosis. Gastroenterology. 1994;107(4):10319.