Absolute fracture risk assessment using lumbar spine and femoral neck bone density measurements: Derivation and validation of a hybrid system†
Version of Record online: 18 FEB 2011
Copyright © 2011 American Society for Bone and Mineral Research
Journal of Bone and Mineral Research
Volume 26, Issue 3, pages 460–467, March 2011
How to Cite
Leslie, W. D., Lix, L. M. and for the Manitoba Bone Density Program (2011), Absolute fracture risk assessment using lumbar spine and femoral neck bone density measurements: Derivation and validation of a hybrid system. J Bone Miner Res, 26: 460–467. doi: 10.1002/jbmr.248
- Issue online: 18 FEB 2011
- Version of Record online: 18 FEB 2011
- Accepted manuscript online: 13 SEP 2010 02:17PM EST
- Manuscript Accepted: 31 AUG 2010
- Manuscript Revised: 4 AUG 2010
- Manuscript Received: 30 JUN 2010
- BONE MINERAL DENSITY;
- DUAL-ENERGY X-RAY ABSORPTIOMETRY;
- ADMINISTRATIVE DATA;
- HISTORICAL COHORT STUDY
The World Health Organization (WHO) Fracture Risk Assessment Tool (FRAX) computes 10-year probability of major osteoporotic fracture from multiple risk factors, including femoral neck (FN) T-scores. Lumbar spine (LS) measurements are not currently part of the FRAX formulation but are used widely in clinical practice, and this creates confusion when there is spine-hip discordance. Our objective was to develop a hybrid 10-year absolute fracture risk assessment system in which nonvertebral (NV) fracture risk was assessed from the FN and clinical vertebral (V) fracture risk was assessed from the LS. We identified 37,032 women age 45 years and older undergoing baseline FN and LS dual-energy X-ray absorptiometry (DXA; 1990–2005) from a population database that contains all clinical DXA results for the Province of Manitoba, Canada. Results were linked to longitudinal health service records for physician billings and hospitalizations to identify nontrauma vertebral and nonvertebral fracture codes after bone mineral density (BMD) testing. The population was randomly divided into equal-sized derivation and validation cohorts. Using the derivation cohort, three fracture risk prediction systems were created from Cox proportional hazards models (adjusted for age and multiple FRAX risk factors): FN to predict combined all fractures, FN to predict nonvertebral fractures, and LS to predict vertebral (without nonvertebral) fractures. The hybrid system was the sum of nonvertebral risk from the FN model and vertebral risk from the LS model. The FN and hybrid systems were both strongly predictive of overall fracture risk (p < .001). In the validation cohort, ROC analysis showed marginally better performance of the hybrid system versus the FN system for overall fracture prediction (p = .24) and significantly better performance for vertebral fracture prediction (p < .001). In a discordance subgroup with FN and LS T-score differences greater than 1 SD, there was a significant improvement in overall fracture prediction with the hybrid method (p = .025). Risk reclassification under the hybrid system showed better alignment with observed fracture risk, with 6.4% of the women reclassified to a different risk category. In conclusion, a hybrid 10-year absolute fracture risk assessment system based on combining FN and LS information is feasible. The improvement in fracture risk prediction is small but supports clinical interest in a system that integrates LS in fracture risk assessment. © 2011 American Society for Bone and Mineral Research.
Osteoporosis is a common condition affecting over one in five women over age 50 in Canada.1 The ability to accurately gauge fracture risk is critical in identifying cost-effective thresholds for intervention.2, 3 The World Health Organization (WHO) Collaborating Centre for Metabolic Bone Diseases at Sheffield recently has identified a set of seven clinical risk factors [ie, prior fragility fracture, a parental history of hip fracture, smoking, use of systemic corticosteroids, excess alcohol intake, body mass index (BMI), and rheumatoid arthritis] that, in addition to age and sex, contribute to fracture risk independent of bone mineral density (BMD).3, 4 The Fracture Risk Assessment Tool (FRAX), released in 2008, computes individualized 10-year probability of hip and osteoporotic fracture (ie, composite of hip, clinical spine, distal forearm, and proximal humerus) with and without BMD.5 The total burden of osteoporotic fractures is much larger than from these four fracture sites alone 1.
FRAX is calibrated to use femoral neck BMD (or T-score from the Third National Health and Nutrition Examination Survey (NHANES III) white female reference population) in estimating fracture risk when BMD is included. The femoral neck was selected as the reference site for osteoporosis diagnosis and fracture risk assessment based on large epidemiologic studies that have documented its performance for fracture prediction and especially for assessment of hip fracture risk.6 Although other BMD measurement sites also can be used for fracture risk assessment and for osteoporosis diagnosis,7 they are not currently part of the FRAX formulation. Simulation studies have shown very little expected benefit from combining BMD measurement sites because results tend to be moderately correlated.8 Large epidemiologic studies have failed to demonstrate a meaningful improvement in fracture risk stratification by using the lowest from among several measurements versus using the hip in isolation.9, 10
Notwithstanding these observations, lumbar spine BMD measurement with dual-energy X-ray absorptiometry (DXA) is used widely in clinical practice for initial assessment and monitoring, and there is uncertainty over how to interpret measurements that show discordance between the lumbar spine and femoral neck. Lumbar spine measurements are widely regarded as the best site for prediction of vertebral fractures, whereas hip measurements are the preferred assessment of hip fractures.7 Completely ignoring a reduced lumbar spine measurement when the femoral neck is normal seems counterintuitive to many clinicians.
We hypothesized that a hybrid risk assessment system might be constructed in which lumbar spine BMD was used to assess vertebral fracture risk and femoral neck BMD was used to assess nonvertebral fracture risk. Under this hybrid model, the relative advantages of the two measurement sites would be quantitatively integrated into a global measure of 10-year absolute fracture risk. We report the derivation and validation of this approach using a split-cohort design.
The study population for this retrospective cohort study consisted of all women age 45 years and older with valid DXA measurements from the lumbar spine and femoral neck. Women were required to have medical coverage from Manitoba Health during the observation period ending in March 2008. For women with more than one eligible set of measurements, only the first record was included. The final study population consisted of 37,032 women. The population was randomly divided into two equally sized subgroups, one for use in model derivation and the second for independent validation. The study was approved by the Research Ethics Board of the University of Manitoba and the Health Information Privacy Committee of Manitoba.
Bone density measurements
In the Province of Manitoba, Canada, health services are provided to virtually all residents through a single public health care system. Bone density testing with DXA has been managed as an integrated program since 1997; criteria and testing rates for this program have been published.11 The program maintains a database of all DXA results that can be linked with other population-based computerized health databases through an anonymous personal identifier.12 The DXA database has been described previously with completeness and accuracy in excess of 99%.
DXA scans were performed and analyzed in accordance with manufacturer recommendations. Lumbar spine T-scores (ie, number of SDs above or below young-adult mean BMD) and Z-scores (ie, number of SDs above or below age-matched mean BMD) were calculated using the manufacturer's US white female reference values. Hip T-scores and Z-scores were calculated from the revised NHANES III white female reference values (Prodigy Version 8.8, GE Lunar Corp., Madison, WI, USA).13, 14 Vertebral levels affected by artifact were excluded by experienced physicians using conventional criteria.15 Prior to 2000, DXA measurements were performed with a pencil-beam instrument (Lunar DPX, GE Lunar Corp.), and after this date, a fan-beam instrument was used (Lunar Prodigy, GE Lunar Corp.). Instruments were cross-calibrated using anthropomorphic phantoms and 59 volunteers. No clinically significant differences were identified (T-score differences < 0.2). Densitometers showed stable long-term performance [coefficient of variation (CV) < 0.5%] and satisfactory in vivo precision (CV = 1.7% for L1–L4 and 1.1% for the total hip).16
Definitions of fractures and other clinical risk factors
Fractures and other medical diagnoses was assessed through a combination of hospital discharge abstracts (ie, diagnoses and procedures coded using the ICD-9-CM prior to 2004 and ICD-10-CA thereafter) and physician billing claims (ie, coded using ICD-9-CM).17 Use of systemic corticosteroids and other medications was obtained by linkage to the provincial Drug Program Information Network (DPIN) database, with drugs classified according to the Anatomical Therapeutic Chemical (ATC) System of the WHO.18 Each prescription record contains the date of dispensation; an exact identification of the dispensed drug, including substance, strength, route, and dosage form; the number of doses provided; the anticipated duration of the prescription in days; and a code for prescribing physician and dispensing pharmacy. The pharmacy database is accurate both for capture of drug dispensations and the prescription details.19
Longitudinal health service records were assessed for the presence of hip, clinical vertebral, forearm, and humerus fracture codes (collectively designated as “osteoporotic”) before and after BMD testing that were not associated with trauma codes.20 Incident fractures were defined as fractures that occurred after the index BMD measurement and generated two or more site-specific fracture codes in any diagnosis field (hospitalization or physician visit). We required that hip fractures and forearm fractures be accompanied by a site-specific fracture reduction, fixation, or casting code because this enhances the diagnostic and temporal specificity for an acute fracture event. To minimize potential misclassification of prior fractures as incident fractures, we required that there be no hospitalization or physician visit(s) with the same fracture type in the 6 months preceding an incident fracture diagnosis. For purposes of the FRAX calculation, prior fragility fracture was taken to be an osteoporotic fracture prior to BMD testing. A diagnosis of rheumatoid arthritis was taken from physician office visits and/or hospitalizations with a compatible ICD-9-CM/ICD-10-CA code in a 3-year period prior to BMD testing. Proxies were used for smoking [chronic obstructive pulmonary disease (COPD) diagnosis] and high alcohol intake (alcohol or substance abuse diagnosis). Prolonged corticosteroid use (over 90 days dispensed in the year prior to DXA testing at a mean prednisone-equivalent dose of 7.5 mg/day or greater) was obtained from the provincial pharmacy system. Weight and height were recorded at the time of the DXA examination (prior to 2000, this was by self-report, and starting in 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 (in kg) divided by height squared (in m). Secondary causes of osteoporosis, other than rheumatoid arthritis, do not contribute to the probability of fracture as calculated by FRAX when information on BMD is present and therefore was not considered in this analysis.
Three fracture-prediction models were developed. The reference model was femoral neck BMD to predict all osteoporotic fractures (nonvertebral and vertebral). The hybrid comparator model reflected a simple sum of two mutually exclusive component models: femoral neck BMD to predict nonvertebral fractures and lumbar spine BMD to predict isolated clinical vertebral fractures. The requirement for additive independence in the nonvertebral and vertebral fracture models required that individuals satisfying both definitions be assigned to one or the other to avoid overestimation in the summed fracture risk. Therefore, women who sustained both nonvertebral and vertebral fractures during follow-up were included with the former and not the latter. The fracture-prediction models included age and BMD, with parameters derived from Cox proportional hazards regression. The hazard ratios (HRs) were adjusted for multiple risk factors that are considered in the FRAX tool [BMI, prior osteoporotic fracture, diagnosed rheumatoid arthritis, COPD (as a proxy for smoking), substance diagnosis (as a proxy for high alcohol intake), and prolonged corticosteroid use]. These proxy measures for smoking and high alcohol intake have been validated to predict major osteoporotic fractures in our data set independent of other FRAX variables.21 Use of osteoprotective medication in the year after BMD measurement also was included in the adjustments. The prediction models did not attempt to explicitly incorporate all the FRAX risk factors because the details of the FRAX model are not sufficiently well described for their inclusion, and it is uncertain whether they would apply equally for nonvertebral and vertebral fractures. This does not affect the current analysis, which isolates the variables of interest, namely, lumbar spine and femoral neck BMD, thereby providing a direct evaluation of the feasibility and utility of a combined risk assessment system. Age as a continuous variable was included in the models given its consistent association with fracture risk (independent of BMD) and age-related declines in BMD. There was no additional benefit to inclusion of age as a quadratic term. Death was considered a competing hazard in accordance with the approach adopted by the WHO Collaborating Centre.
All results are reported as mean ± SD unless otherwise stated. Group comparisons for continuous data were with the Student's t test and for categorical data used a chi-square test. Cox proportional hazards models were used to estimate hazard ratios (HRs) for age and BMD adjusted for FRAX risk factors (ie, BMI, prior osteoporotic fracture, rheumatoid arthritis, COPD, substance abuse, and recent corticosteroid use) as well as osteoprotective medication use in the year after BMD testing. Parental history of hip fracture was not available. The proportional hazard assumption was confirmed graphically from log[–log(survival)] versus log(time) plots. Statistical analyses were performed with SPSS for Windows, Version 16.0 (SPSS, Inc., Chicago, IL, USA).
Overall performance of the prediction system was assessed from the area under the curve (AUC) for receiver operating characteristic (ROC) plots. AUCs were compared using the nonparametric method of DeLong and colleagues,22 which allows for comparison of correlated curves originating from a common population (AccuROC 2.5, Accumetric Corp., Montreal, Quebec, Canada).
Absolute 10-year fracture probabilities under the femoral neck and hybrid prediction systems were categorized as low risk (< 10%), moderate risk (10% to 20%), and high risk (> 20%) in accordance with Canadian reporting guidelines.23 The number of individuals in whom the hybrid system reclassified risk to a different category was determined according to the method of Janes and colleagues.24 The number of fractures under the two prediction systems were cross-tabulated, and the linear trend in fracture rates when a risk category under the femoral neck system was reclassified under the hybrid system was assessed using the Cochran-Armitage test. Within each subgroup, fracture outcomes to 10 years were estimated using the Kaplan-Meier method.
The baseline characteristics of the 18,447 women in the derivation subgroup and the 18,585 women in the validation subgroup are summarized in Table 1. No significant differences (all p > .05) were seen in any of the baseline covariates or in subsequent outcomes.
|Derivation (n = 18,447)||Validation (n = 18,585)||p Value|
|Age (years)||63.6 ± 10.4||63.6 ± 10.3||.504|
|BMI (kg/cm2)||26.6 ± 5.2||26.6 ± 5.3||.673|
|Rheumatoid arthritis (%)||641 (3.5%)||703 (3.8%)||.113|
|COPD (%)||1346 (7.3%)||1393 (7.5%)||.465|
|Substance abuse diagnosis (%)||486 (2.6%)||472 (2.5%)||.565|
|Corticosteroid use before (%)||812 (4.4%)||832 (4.5%)||.726|
|Lumbar spine T-score||−1.3 ± 1.5||–1.3 ± 1.5||.708|
|Lumbar spine Z-score||−0.1 ± 1.4||–0.1 ± 1.4||.717|
|Femoral neck T-score||−1.4 ± 1.0||–1.4 ± 1.0||.634|
|Femoral neck Z-score||0.1 ± 1.0||0.1 ± 1.0||.612|
|Minimum T-score osteoporotic (%)||5451 (29.5%)||5485 (29.5%)||.939|
|Prior osteoporotic fracture||2354 (12.8%)||2357 (12.7%)||.820|
|Incident osteoporotic fracture||840 (4.6%)||908 (4.9%)||.132|
|Observation period (years)||5.5 ± 2.8||5.6 ± 2.8||.103|
During a mean 5.6 years of follow-up (range up to 10 years), 1748 women (4.7%) experienced one or more incident fractures satisfying one of the primary definitions for vertebral, hip, forearm, and humerus fracture. Of these, 1484 (4.0%) involved a nonvertebral fracture, and 264 (0.7%) were an isolated clinical vertebral fracture. Forty-four women had both vertebral and nonvertebral fractures and were counted with the nonvertebral fracture group.
Preliminary analyses looked at the ability of lumbar spine and femoral neck BMD to predict nonvertebral and vertebral fractures both alone and in combination (Table 2). There was moderate correlation between lumbar spine and femoral neck T-scores (Pearson r2 = 0.50). Each BMD measurement site was able to predict vertebral and nonvertebral fractures (all p < .001). When both the lumbar spine and femoral neck were included in the prediction model, the lumbar spine (p < .001) but not the femoral neck (p = .275) was predictive of vertebral fracture, whereas the femoral neck (p < .001) but not the lumbar spine (p = .757) was predictive of nonvertebral fractures. The independence of the lumbar spine and femoral neck for prediction of vertebral and nonvertebral fractures, respectively, provides justification for the two-compartment model described in this article. After adjustment for FRAX risk factors and treatment, the lumbar spine was strongly predictive of isolated vertebral fractures (HR = 1.84 per SD, HR per T-score score = 1.49), and the femoral neck was strongly predictive of nonvertebral fractures (HR = 1.66 per SD, HR per T-score score = 1.68). Gradients of risk for fracture prediction are similar to those from a previous meta-analysis.7
|HR per T-score unita (95% CI)||HR per SDa (95% CI)|
|Construction of FN model|
|FN for any fracture||1.65 (1.5−1.81)||1.63 (1.48−1.78)|
|Construction of hybrid model|
|FN for nonvertebral fracture||1.68 (1.51−1.86)||1.66 (1.50−1.83)|
|LS for vertebral fracture||1.49 (1.28−1.73)||1.84 (1.46−2.32)|
ROC AUC measures for fracture discrimination for the validation subgroup are summarized in Table 3. There was a small improvement in vertebral fracture prediction under the hybrid model [0.731 (0.212)] compared with the femoral neck model [0.7235 (0.217), p < .001]. No significant difference was seen between these prediction models for nonvertebral fractures or all fractures combined. When analysis was restricted to 6434 women from the validation subgroup with a T-score difference between the lumbar spine and femoral neck exceeding 1 SD, there was a small improvement in overall fracture prediction with the hybrid model versus the femoral neck model (p = .025).
|FN model||Hybrid model||p Value,a FN versus hybrid model|
|Overall data set, n = 37,032|
|Nonvertebral fracture||0.687 (.007)||0.687 (.007)||.18|
|Vertebral fracture||0.719 (.016)||0.727 (.016)||< .001|
|Any fracture||0.695 (.007)||0.695 (.007)||.42|
|Validation data set, n = 18,585|
|Nonvertebral fracture||0.693 (.010)||0.692 (.010)||.24|
|Vertebral fracture||0.723 (.022)||0.731 (.021)||< .001|
|Any fracture||0.701 (.009)||0.701 (.009)||.75|
|Discordance subgroup, n = 6434b|
|Nonvertebral fracture||0.671 (.018)||0.672 (.018)||.46|
|Vertebral fracture||0.729 (.040)||0.750 (.038)||< .001|
|Any fracture||0.682 (.016)||0.687 (.016)||.025|
The effect of including lumbar spine in the risk assessment algorithm was assessed in terms of reclassification and fracture risk stratification (Table 4). Based on predefined 10-year fracture risk categories (low < 10%, moderate 10% to 20%, high > 20%), there was a low level (6.4%) of categorical reclassification that was greatest for those at moderate risk under the femoral neck system (8.0%), followed by the low-risk group (6.1%) and least for the high-risk group (<0.1%). Among women in the moderate-risk category under the femoral neck system, those who were reclassified to low risk had mean lumbar spine T-scores of +0.2, those who remained in the moderate-risk category had mean lumbar spine T-scores of –2.2, and those who moved into the high-risk category had mean lumbar spine T-scores of –3.4. Ten-year fracture risk for women in the moderate-risk category under the femoral neck system estimated by the Kaplan-Meier method was 18.2% for the validation data set. After reclassification under the hybrid system, 10-year fracture estimates were 6.3% for those reclassified as low risk, 18.6% for those reclassified as moderate risk, and 25.5% for those reclassified as high risk (p < .001 for trend). Similar results were seen for the overall data set and for the discordance subgroup. Table 4 shows that 675 (39%) of the major osteoporotic fractures occurred in women designated as low risk under FRAX, of whom 67 (10%) were appropriately reclassified to a higher-risk category under the hybrid system.
|Femoral neck model||Hybrid model|
|Overall||Low risk (< 10%)||Moderate risk (10% to 20%)||High risk (> 20%)||p Trend|
|Low risk (< 10%)|
|% Fractures at 10 years (SE)||6.9 (0.3)||6.4 (0.3)||14.9 (1.9)||N/A|
|Moderate risk (10% to 20%)|
|% Fractures at 10 years (SE)||17.5 (0.7)||11.0 (6.0)||16.9 (0.7)||25.5 (2.4)|
|High risk (> 20%)|
|% Fractures at 10 years (SE)||40.3 (2.7)||N/A||N/A||46.4 (4.9)|
|% Fractures at 10 years (SE)||11.2 (0.3)||6.4 (0.3)||16.8 (0.7)||35.2 (2.0)|
This analysis provides proof of concept that incorporation of lumbar spine BMD in fracture risk assessment provides a small but demonstrable improvement in fracture risk stratification compared with femoral neck BMD alone. The improvement was more evident among those with discordance between the lumbar spine and femoral neck T-scores exceeding 1 SD. When analyzed according to fracture site, all the gain in fracture prediction under the hybrid system was enhanced risk prediction for vertebral fractures, whereas nonvertebral fracture prediction was unchanged.
At first glance, the minimal changes in AUC could be used to argue that the more complex two-site risk assessment system offers little advantage over the single-site femoral neck system and is not worth the trouble. Although there is truth to this statement, it must be acknowledged that lumbar spine BMD measurements are performed routinely in clinical practice both for baseline risk assessment and for monitoring purposes. When confronted with highly discordant measurements (lumbar spine worse than femoral neck), clinicians are in a quandary about how this should be integrated into the decision-making process. Under some guidelines, such as those from the National Osteoporosis Foundation, treatment would be recommended for a lumbar spine T-score in the osteoporotic range regardless of the estimated risk.25 Other national guidelines, such as those from the United Kingdom, do not have specific treatment recommendations for individuals with osteoporotic lumbar spine BMD when 10-year fracture risk prediction from the femoral neck does not achieve the intervention threshold.26 Previous 2005 Canadian guidelines attempted to address the issue of site discordance by substituting the minimum T-score for the femoral neck T-score,23 but this systematically overestimates fracture risk27 and does not consider site-specific differences in fractures or the way BMD declines with age.7, 28 Where lumbar spine and hip measurements are both performed for clinical purposes, using a procedure that accurately reflects the contribution of each measurement site to fracture risk clearly is preferred.
FRAX is a work in progress, and there is active discussion about changes and enhancements that will improve its clinical performance. Incorporating the lumbar spine in the FRAX algorithm is one such option, whereas inclusion of additional clinical risk factors (eg, falls) also has been proposed. Although not the primary focus of this analysis, it is worth noting that the improvement in fracture prediction from including the FRAX clinical risk factors in fracture risk assessment over BMD alone has been an area of uncertainty. FRAX with BMD outperformed FRAX without BMD or BMD alone in a pooled analysis from Kanis and colleagues.5 Attempts to confirm this in additional cohorts have met with mixed results. Trémollieres and colleagues29 did not demonstrate value in using FRAX over BMD alone, but a recent report from Manitoba did find that FRAX with BMD provided better stratification for major osteoporotic and hip fractures than BMD or FRAX clinical risk factors alone.21
Limitations to this analysis are acknowledged. Although a split-cohort derivation/validation procedure was used, completely independent validation in different populations and contexts would be preferred. A major challenge in the study of the epidemiology of osteoporotic fractures concerns the difficulty in ascertaining vertebral fractures. The protean definitions that have been applied clinically, morphometrically, and administratively speak to this challenge. Notwithstanding these legitimate difficulties, administrative definitions for vertebral fractures have been developed and tested with acceptable results.30 Since the predominant difficulty is underrecognition of vertebral fractures, this actually would introduce a bias against the hybrid system, as noted earlier. Furthermore, it does not seriously undermine the conceptual framework of this analysis. The actual improvement in risk stratification under the hybrid system is likely underestimated owing to the intentional use of a highly restrictive definition of clinical vertebral fracture. Larger gains would be expected with better vertebral fracture recognition. Whether the existing FRAX formulation would admit to inclusion of multiple BMD measurement sites is also unclear. FRAX already considers a multitude of interactions, and inclusion of additional interactions with lumbar spine BMD and/or higher-order interactions may not be feasible. The calculations described are also unsuitable for clinical practice because the risk calculations require computerization. A simple, clinician-friendly approach that has face validity to clinicians probably would meet with greater acceptance. Referral bias in this clinical population is likely responsible for the higher than expected prevalence of rheumatoid arthritis. Despite this, mean Z-scores for the spine and hip were very close to the manufacturer's age-matched mean reference values (ie, Z-score close to zero).
In summary, we have shown that it is feasible to create a hybrid 10-year absolute fracture risk assessment system that combines lumbar spine and femoral neck BMD information. Risk reclassification under this hybrid system is responsive to lumbar spine measurements and provides a small improvement in risk stratification that is most evident in those at moderate risk under the femoral neck system and where there is discordance between the two BMD measurement sites. This supports clinical interest in a system that quantitatively integrates lumbar spine BMD in the fracture risk assess paradigm. Although it cannot be quantified, clinicians are likely to have greater confidence in a risk assessment system that has face validity by adjusting risk in the setting of discordant lumbar spine measurements.
WL: Speaker bureau and unrestricted research grants: Merck Frosst Canada; research honoraria and unrestricted educational grants: Sanofi-Aventis, Procter & Gamble Pharmaceuticals Canada; unrestricted research grants: Novartis, Amgen Pharmaceuticals Canada; unrestricted educational grants: Genzyme Canada; Advisory boards: Genzyme Canada, Novartis, Amgen Pharmaceuticals Canada. LL: Unrestricted research grant: Amgen. Both the authors state that they have no conflicts of interest.
We are indebted to Manitoba Health for providing data (HIPC File No. 2007/2008–35). The results and conclusions are those of the authors, and no official endorsement by Manitoba Health is intended or should be inferred. This article has been reviewed and approved by the members of the Manitoba Bone Density Program Committee.
- 18WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATC classification and DDD assignment. Oslo, 2005.