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Osteoporotic fracture risk assessment

Osteoporotic fracture risk assessment
Author:
E Michael Lewiecki, MD
Section Editors:
Clifford J Rosen, MD
Kenneth E Schmader, MD
Deputy Editor:
Katya Rubinow, MD
Literature review current through: Dec 2022. | This topic last updated: Dec 02, 2021.

INTRODUCTION — Osteoporosis is a common disease that is characterized by low bone mass with microarchitectural disruption and skeletal fragility, resulting in an increased risk of fracture, particularly at the spine, hip, wrist, humerus, and pelvis [1]. Osteoporotic fractures (fragility fractures, low-trauma fractures) are those occurring from a fall from a standing height or less, without major trauma such as a motor vehicle accident. There were an estimated nine million osteoporotic fractures worldwide in 2000, of which 1.6 million were hip, 1.7 million forearm, and 1.4 million clinical vertebral fractures [2]. Fractures of the hip and spine are associated with an increased mortality rate of 10 to 20 percent [1,3]. Fractures may result in limitation of ambulation, depression, loss of independence, and chronic pain [4,5].

Properties that contribute to bone strength include bone mineral density (BMD), bone geometry (size and shape of bone), degree of mineralization, microarchitecture, and bone turnover [6]. BMD measurements are available to many patients, and fracture risk has been demonstrated to increase with decreasing BMD [6]. Assessment of bone microarchitecture requires methodologies such as high-resolution peripheral quantitative computed tomography (HR-pQCT), high-resolution magnetic resonance imaging (HR-MRI) or microMRI, or double tetracycline-labeled transiliac bone biopsy with histomorphometry, which are not routinely used in clinical practice.

Non-BMD factors that contribute to fracture risk include advancing age, previous fracture, falls, glucocorticoid therapy, family history of hip fracture and current smoking (table 1) [7-10]. Incorporating risk factors that are independent of BMD increases the sensitivity of fracture risk assessment and thereby improves treatment intervention strategies [11]. Uni- and multivariate analyses suggest that age, prior fracture history, and BMD are the strongest predictors of fracture risk [12].

Risk assessment for osteoporotic fracture will be reviewed here. Detailed information regarding screening, prevention, diagnosis, and treatment is found elsewhere. (See "Screening for osteoporosis in postmenopausal women and men" and "Prevention of osteoporosis" and "Clinical manifestations, diagnosis, and evaluation of osteoporosis in postmenopausal women" and "Clinical manifestations, diagnosis, and evaluation of osteoporosis in men" and "Overview of the management of osteoporosis in postmenopausal women" and "Treatment of osteoporosis in men".)

ASSESSMENT OF FRACTURE RISK — Low bone mineral density (BMD) is associated with increased risk of fracture. However, methodologies for combining BMD with clinical risk factors to quantify fracture probability offer attractive alternatives to relying on BMD testing alone [13]. Thus, assessment of fracture risk should include evaluation of both:

BMD

Clinical risk factors

Fracture risk should be expressed as absolute, rather than relative, risk. Absolute risk (AR) provides a better assessment of the probability of fracture and is more useful clinically for identifying patients most likely to benefit from therapy. The use of a fracture risk prediction tool is helpful in identifying the probability of fracture over a specified period of time, typically 10 years. (See 'Expression of fracture risk' below and 'Fracture risk assessment tool' below.)

Bone mineral density — In 1994, the World Health Organization (WHO) established a classification of BMD according to the standard deviation (SD) difference between a patient's BMD and that of a young-adult reference population. This value is now commonly expressed as a "T-score." A T-score that is equal to or less than -2.5 is consistent with a diagnosis of osteoporosis, a T-score between -1.0 and -2.5 is classified as low bone mass (osteopenia), and a T-score of -1.0 or higher is normal [14]. (See 'Dual-energy x-ray absorptiometry (DXA)' below.)

Many studies have demonstrated that low BMD is associated with an increased risk of fracture [12,15-21]. Individuals with T-scores of ≤-2.5 have the highest risk of fracture. However, because there are more individuals with osteopenia than osteoporosis, the absolute number of fractures in subjects with T-scores in the osteopenia range is greater than in those with T-scores in the osteoporosis range [7-9,22]. Since most fractures occur in patients with T-scores better than -2.5, treatment strategies relying solely on BMD testing will miss many patients at risk for fracture who might benefit from interventions to reduce fracture risk.

Clinical risk factors — Assessment of clinical risk factors that are independent of BMD is important for fracture prediction. In addition to BMD, advancing age, prior history of fragility fracture, chronic glucocorticoid use, low body mass index (BMI), parental history of hip fracture, cigarette smoking, and excess alcohol intake are the risk factors that have been demonstrated to be most predictive of fracture (table 1). (See 'Clinical risk factor assessment' below.)

Clinical risk factor assessment alone may be considered for fracture prediction in world regions without access to any BMD measurement technologies [13,23]. The Fracture Risk Assessment Tool (FRAX) model allows estimation of 10-year probability of hip fracture and major osteoporotic fracture with clinical risk factors alone when BMD is not known, although performance is better when BMD is included [24-26]. (See 'Fracture risk assessment tool' below.)

Expression of fracture risk — Absolute risk (AR) is the probability of fracture, usually expressed as a percentage, over a specified period of time. Relative risk (RR) is the ratio of absolute risks of two populations [21]. RR tends to overestimate fracture risk in some populations and underestimate it in others [27]. As an example, a 50-year-old and an 80-year-old woman with a hip T-score of -2.5 each have the same RR for hip fracture compared with an age-matched population with normal BMD [21], while the 10-year probability of hip fracture is much higher in the 80-year-old woman (table 2) [28]. For this reason, AR provides a better assessment of fracture risk and is a more useful clinical tool for identifying patients most likely to benefit from therapy. The preferred fracture risk expression for use in clinical practice is AR denoted as the 10-year probability of fracture.

Fracture risk assessment tool — In 2008, the University of Sheffield launched a Fracture Risk Assessment Tool (FRAX) that estimates the 10-year probability of hip fracture and major osteoporotic fracture (hip, clinical spine, proximal humerus, or forearm) for untreated patients from age 40 to 90 years using easily obtainable clinical risk factors for fracture (table 1) and femoral neck BMD (g/cm2, using dual-energy x-ray absorptiometry [DXA]), when available [24,25]. DXA-equivalent femoral neck BMD derived from quantitative computed tomography (QCT) measurements may also be used with FRAX [29]; however, this is not recommended for use in clinical practice unless DXA is not available, due to greater radiation exposure and higher cost.

FRAX is based upon data collected from large, prospective, observational studies of females and males of different ethnicities and from different world regions in which clinical risk factors, BMD, and fractures were evaluated [12,28]. FRAX has been validated in approximately 26 independent cohorts, mainly comprised of women [30]. The statistical power of this large dataset allows estimation of fracture probability from an individual's set of risk factors. The country-specific FRAX prediction algorithms are available for many countries online (FRAX); click on Calculation Tool [25]. The FRAX calculator is also available on current versions of DXA software and as an app for smartphones [31].

Results from a large, prospective cohort study suggest that FRAX can similarly predict fracture in women currently or previously treated for osteoporosis [32]. In this analysis, the FRAX-predicted risk and observed incidence of major osteoporotic fracture in both untreated and treated women were concordant. Only in the subset of women who were at highest risk for fracture and who were highly adherent to their osteoporosis treatment was the observed hip fracture incidence significantly less than the predicted risk. Thus, osteoporosis therapy may not preclude the use of FRAX for fracture prediction. However, FRAX does not appear to capture the change in fracture risk associated with therapy and should not be used to monitor individuals on therapy [33].

Other fracture risk assessment models are available (eg, QFracture, Garvan), but most have not been validated in diverse populations, and they are not in widespread use [30,34,35]. The thresholds for intervention vary with the individual models. The selection of a particular assessment tool may best be determined by country-specific guidelines for treatment thresholds.

Clinical application of fracture risk assessment — When country-specific fracture data, life-expectancy data, and economic assumptions are used with FRAX, thresholds for cost-effective pharmacologic intervention can be calculated [28,36-41], allowing clinicians to identify patients likely to benefit from therapy better than qualitative methods. Treatment guidelines based upon FRAX are likely to lead to more drug treatment in older patients with slightly low T-scores and high risk of fracture, with less use of drugs to treat younger patients with low T-scores and low risk of fracture.

In the United States, cost-effectiveness modeling suggests that the 10-year hip fracture probability at which treatment becomes cost effective (intervention threshold) ranges from 2.5 to 4.7 percent for females and from 2.4 to 4.9 percent in males, depending upon age, assuming annual treatment costs of USD $600 and a willingness-to-pay threshold of USD $60,000 per quality-adjusted life-year gained [36]. For a 70-year-old woman initiating therapy, the intervention threshold is approximately 4 percent. Using similar willingness-to-pay thresholds but country-specific intervention costs, the intervention threshold in 70-year-old women from other countries ranges from 4 to 9.1 percent [42].

Intervention thresholds vary based upon country-specific health economic data, such as fracture-related treatment costs and willingness-to-pay thresholds [24]. In most countries, the analysis is based upon five years of treatment with a bisphosphonate. The analysis in the United States was based upon the incidence of hip fracture in White, postmenopausal women and the expected cost of generic alendronate (before the actual cost was known) [36,43]. Since the current cost of generic alendronate in the United States is less than the estimated cost, the fracture probability at which this treatment is cost effective is presumably less than what was calculated. Conversely, the use of more expensive nongeneric drugs increases the fracture probability at which treatment becomes cost effective.

Guidelines for pharmacologic intervention based upon 10-year absolute fracture risk are reviewed in detail separately. (See "Treatment of osteoporosis in men", section on 'Candidates for therapy' and "Overview of the management of osteoporosis in postmenopausal women", section on 'Patient selection'.)

Limitations — FRAX is a useful clinical tool for assessment of fracture risk. As with all clinical tools, however, there are some limitations. Limitations include lack of extensive validation in treated patients, limitation to four ethnicities in the United States (White, Black, Hispanic, and Asian Americans), uncertainty regarding the range of error with fracture risk, and lack of validation with BMD measurements by technologies other than DXA [44,45] and QCT [29].

The FRAX algorithm uses femoral neck BMD (g/cm2) for calculation of fracture probability in untreated patients. BMD input from non-hip sites and other hip regions of interest has not been validated with FRAX and is therefore not recommended [24]. For patients who have lumbar spine BMD that is much lower than femoral neck BMD, FRAX is likely to underestimate fracture risk. It is noteworthy that the FRAX estimation of major osteoporotic fracture does not include all osteoporotic fractures, since a substantial portion of fragility fractures are not at the four "major" skeletal sites used in the FRAX algorithm [46]. Additional limitations, which may result in over- or underestimation of fracture risk in an individual patient, include dichotomous (yes or no) input for clinical risk factors that are associated with variable risk depending on dose and duration of exposure (eg, glucocorticoids) and lack of consideration of all risk factors (eg, multiple fractures, recent fractures, severity of fractures, falls, bone turnover). While there is evidence that hip, vertebral, and humeral fractures appear to confer greater risk of subsequent fracture than fractures at other sites, quantification of this incremental risk in FRAX is not possible.

Thus, FRAX may underestimate fracture probability in individuals with [44,45,47]:

Lumbar spine BMD much lower than femoral neck BMD

Multiple or recent fractures

High-dose glucocorticoid exposure (prednisolone >7.5 mg/day or equivalent)

Prevalent, severe vertebral fractures

A parental history of non-hip fragility fracture

Diabetes mellitus

The magnitude by which FRAX may over- or underestimate fracture risk has been studied using large population databases, and procedures for adjusting FRAX probability have been proposed [48,49]. As an example, an analysis of the Canadian Manitoba BMD database shows that when there is discordance between lumbar spine and femoral neck BMD, the FRAX estimate for major osteoporotic fracture may be increased or decreased by one-tenth for each rounded T-score difference or offset between lumbar spine and femoral neck (eg, when the lumbar spine T-score is 1.0 less than the femoral neck T-score, the 10-year probability of major osteoporotic fracture can be increased by one-tenth) [48]. Another analysis using the United Kingdom General Practice Research Database showed that for patients exposed to high dose glucocorticoids (prednisolone >7.5 mg/day or equivalent), the 10-year probability of major osteoporotic fracture may be increased by 15 percent and the 10-year probability of hip increased by 20 percent [49]. The increase in fracture risk associated with type 2 diabetes mellitus may be captured by entering "yes" for rheumatoid arthritis in the FRAX algorithm [50]. With modifications such as these, the FRAX probability of fracture can be refined [31]. However, these correction factors have not been computed for the majority of countries represented by FRAX, including the United States. Thus, they should be applied to United States populations with caution.

The clinician should appreciate that intervention guidelines with or without the use of FRAX provide only general clinical guidance. Osteoporosis treatment should remain individualized through shared decision-making between patient and clinician. (See "Treatment of osteoporosis in men", section on 'Candidates for therapy' and "Overview of the management of osteoporosis in postmenopausal women", section on 'Patient selection'.)

METHODS OF MEASUREMENT OF BMD — Low bone mineral density (BMD) is associated with increased risk of fracture, regardless of the technique used for measurement [12,15-21,51-62]. However, there are discrepancies in T-score values at different skeletal sites and with different technologies. The increase in fracture risk per 1.0 standard deviation (SD) decrease in BMD (fracture gradient) varies with the technique used and the skeletal site measured. Therefore, T-scores derived from different skeletal sites with different technologies are not interchangeable [10,63].

In clinical practice, dual-energy x-ray absorptiometry (DXA) is the main technology for diagnostic classification and is the most useful technology for monitoring serial BMD changes. However, other techniques measuring different skeletal sites have demonstrated the ability to predict the likelihood of fractures. Therefore, when BMD testing by DXA is not available, then fracture risk assessment may be made using other technologies (measuring lumbar spine, hip, or peripheral skeletal sites) in combination with consideration of clinical risk factors.

Dual-energy x-ray absorptiometry (DXA) — DXA measures bone mineral content (BMC, in grams) and bone area (BA, in square centimeters), then calculates "areal" BMD (aBMD) in g/cm2 by dividing BMC by BA. DXA is the most widely used method for measuring BMD because it gives very precise and accurate measurements at clinically relevant skeletal sites (ie, those with major clinical consequences when a fracture occurs) and can be used for diagnostic classification, input with FRAX, and monitoring the response to therapy. The major disadvantages of DXA are that the instrument is large (not portable); more expensive than most peripheral technologies; and uses ionizing radiation, albeit in a very low dose.

Detailed information about DXA is found elsewhere. (See "Overview of dual-energy x-ray absorptiometry".)

Fracture prediction — Many studies have demonstrated that low BMD measured by DXA at any skeletal site (lumbar spine, hip, or forearm) can predict osteoporotic (fragility) fracture [15-18]. Overall, there is an approximately twofold increase in risk of such fractures for each SD decrease in BMD (table 3). As examples:

In a prospective study of 9700 older women, 2680 of whom were followed for an average of 15 years, the risk of vertebral fracture was inversely related to bone density at all measurement sites [64]. The age-adjusted odds ratio (OR) of vertebral fracture for each SD decrease in DXA-measured BMD of the lumbar spine and total hip was 2.1 (95% CI 1.8-2.3) and 1.8 (95% CI 1.6-2.0), respectively.

In a historical cohort study (mean observation 3.2±1.5 years) of 16,505 Canadian women, each SD decrease in DXA-measured BMD of the hip or lumbar spine was associated with an increased risk of osteoporotic fracture at any site (hazard ratio 1.8 [95% CI 1.7-2.0] for total hip and 1.5 [95% CI 1.4-1.6] for spine) [17].

Although low BMD at any skeletal site can predict osteoporotic fracture, site-specific measurements are generally better for their respective sites. As an example, hip BMD is superior to BMD measured at other skeletal sites in predicting hip fracture [12,15,17,19,20]. A meta-analysis of prospective cohort studies with over 90,000 person-years of observation found that every 1 SD decrease in BMD at the femoral neck in women was associated with a relative risk of 2.6 (95% CI 2.0-3.5) for hip fracture and 1.6 (95% CI 1.4-1.8) for all fractures. A 1 SD decrease in lumbar spine BMD was associated with a relative risk (RR) of 2.3 (95% CI 1.9-2.8) for vertebral fracture and 1.5 (95% CI 1.4-1.7) for all fractures [21].

There is a similar relationship between overall fracture, hip fracture, and femoral neck BMD [9,16,65].

High-trauma fractures (generally defined as fractures from motor vehicle accidents, sporting accidents, or falls from ladders or other raised surfaces) have traditionally been excluded from observational studies and clinical osteoporosis trials. Although the force to which bone is subjected varies with the level of trauma, the conventional view has been that even normal bone would fracture under most high-trauma conditions [66]. (See 'Clinical risk factor assessment' below.)

However, evidence suggests that low BMD also increases the risk of high-trauma fractures [67,68]. As an example, in two large, prospective cohort studies of community-dwelling older adults, a 1 SD decrease in total hip BMD was associated with similarly increased risks of high- or low-trauma fractures (age-adjusted relative hazard [RH] 1.4 [95% CI 1.2-1.7] and 1.5 [95% CI 1.4-1.6] for high- and low-trauma fractures, respectively, in females and 1.5 [95% CI 1.2-2.0] and 1.7 [95% CI 1.5-1.9], for high- and low-trauma fractures, respectively, in males) [68]. It has also been shown that the risk of future fractures with older adults is similar after high- and low-trauma fractures [69] (see 'Personal history of fracture as an adult' below). Although the relationship between BMD and fracture appears to be similar regardless of the cause of fracture, the studies are limited by the broad definition of high-trauma fracture [66].

Older adults with a fracture, regardless of the perceived level of trauma, should be considered for skeletal health evaluation and appropriate interventions. (See "Screening for osteoporosis in postmenopausal women and men" and "Clinical manifestations, diagnosis, and evaluation of osteoporosis in postmenopausal women" and "Clinical manifestations, diagnosis, and evaluation of osteoporosis in men".)

Follow-up BMD testing — DXA is commonly used to monitor the effects of pharmacologic therapy. Stability or an increase in bone mineral density (BMD) has traditionally been considered to be a good response to therapy, whereas significant loss of BMD is cause for evaluation of factors contributing to suboptimal therapeutic effect and consideration of a change in treatment strategies. (See "Screening for osteoporosis in postmenopausal women and men", section on 'Repeat BMD measurements' and "Overview of the management of osteoporosis in postmenopausal women", section on 'Monitoring'.)

Follow-up DXA may also be used in treated patients to aid in determining whether an acceptable level of fracture risk has been achieved, according to the concept of treat-to-target (treat-to-goal). Response to therapy is necessary, but not always sufficient, to achieve an acceptable level of fracture risk. Treat-to-target has been described in a report of a working group of the American Society for Bone and Mineral Research and the National Osteoporosis Foundation [70] and supported by subsequent data showing a robust correlation between the magnitude of BMD increase with treatment and reduction of fracture risk (ie, greater increases in BMD are associated with greater reduction in fracture risk) [71]. As an example, treat-to-target suggests that for a patient started on treatment because of T-score -2.5 or below, it would be desirable to at least reach a T-score >-2.5, and perhaps better >-2.0.

The value of repeat DXA in predicting fracture risk may be lower in older patients who are unlikely to experience further dramatic declines in BMD [72-74]. In the Study of Osteoporotic Fractures (SOF), a repeat BMD measurement performed a mean of eight years after the initial measurement did not improve the overall predictive value of hip, spine, or non-spine fracture risk in 4124 healthy, community-dwelling women 65 years and older [74]. However, these findings do not necessarily apply to younger women who may have accelerated bone loss (as in the early menopause), women being treated for osteoporosis or low BMD, anyone treated with medications known to be harmful to bone (eg, glucocorticoids, aromatase inhibitors, androgen deprivation therapy), or men [75,76].

Trabecular bone score — Trabecular bone score (TBS) is a commercially available software add-on for late-generation DXA systems that has been cleared by the US Food and Drug Administration (FDA) for use as a complement to DXA analysis and clinical examination for assessment of fracture risk and monitoring the effects of therapy. TBS uses data derived from lumbar spine DXA images to generate a gray-level textural index. TBS is associated with vertebral, hip, and major osteoporotic fracture risk in postmenopausal women, with major osteoporotic fracture risk in postmenopausal women with type 2 diabetes mellitus, and with hip fracture risk and major osteoporotic fracture risk in men over age 50 years [77,78]. It can be included in the FRAX algorithm to estimate fracture risk [79].

TBS cannot diagnose osteoporosis and should not be used alone to initiate therapy. TBS does not appear to be clinically useful to monitor the skeletal effects of bisphosphonates and denosumab, but it is potentially useful as a component of monitoring the skeletal effects of teriparatide and abaloparatide, provided precision assessment has been done and the least significant change (LSC) has been calculated [78].

Peripheral DXA (pDXA) — pDXA devices are dedicated portable instruments that use the same technology as DXA to measure BMD at peripheral sites, such as the forearm, calcaneus, or finger. Evaluation of fracture risk prediction with these devices is confounded by technical differences, variation in the definitions of the bone regions of interest measured, and lack of standardized reference databases for calculating T-scores. Nevertheless, low T-score values at peripheral skeletal sites measured by pDXA devices are associated with increased fracture risk [21,51].

Peripheral DXA cannot be used for diagnostic classification, other than with measurement at the distal 33 percent (one-third) radius site, since the WHO criteria for BMD classification do not apply to BMD at skeletal sites other than the lumbar spine, hip, and forearm [80]. Despite generally good precision with pDXA, it is not clinically useful to monitor therapy, since changes in BMD at peripheral skeletal sites in response to therapy are very slow [80].

Quantitative ultrasonography (QUS) — QUS appears to be a good predictor of fractures in females and males [59], and it is at least as good as clinical risk factors for identifying patients at high risk for osteoporosis. However, QUS cannot be used for diagnostic classification, since the WHO criteria were established based upon BMD measurement by DXA and cannot be used with FRAX. In addition, there are no studies showing reduction in fracture risk for patients selected for therapy based on QUS measurements, and QUS cannot be used to monitor response to therapy, because changes are too slow to be clinically useful. (See "Screening for osteoporosis in postmenopausal women and men" and "Clinical manifestations, diagnosis, and evaluation of osteoporosis in postmenopausal women".)

QUS does not measure BMD, but instead measures the transmission of ultrasound through accessible limb bones or the reflectance of the ultrasound waves from the bone surface. Parameters assessed by transmission ultrasound include broadband ultrasound attenuation (BUA), speed of sound (SOS), and calculated values such as quantitative ultrasound index (QUI) or stiffness index (SI). Reflectance ultrasound reports only SOS.

Potential advantages of QUS compared with measurement of BMD include lower expense, portability, and lack of radiation exposure. Measurements are most commonly made at the calcaneus (heel), a skeletal site that is composed primarily of cancellous bone, similar to the spine.

QUS is a good predictor of osteoporotic fracture risk [51-59,81]. As examples:

In a large, prospective study of 6189 postmenopausal women over age 65 years, QUS of the calcaneus predicted hip fracture as accurately as DXA of the calcaneus or femoral neck [54]. Each SD reduction in calcaneal BUA was associated with a doubling of the risk for hip fractures (relative risk [RR], 2.0; 95% CI 1.5-2.7).

In a larger study of 14,824 patients that included younger women as well as men ages 42 to 82 years, calcaneal QUS also was a good predictor of total and hip fracture risk [53]. BUA predicted fracture risk in all subgroups of patients, with a relative risk similar to the study above.

In addition to predicting fracture risk, other studies have found that QUS is at least as good as (and possibly better than) clinical risk factors for predicting women at risk for osteoporosis [82,83]. However, a limitation of ultrasound is that it does not reliably exclude or confirm DXA-determined osteoporosis. A meta-analysis of 25 studies that evaluated the sensitivity and specificity of calcaneal ultrasound for identifying patients with DXA T-scores ≤-2.5 concluded that currently used ultrasound cutoff thresholds do not have sufficiently high sensitivity or specificity to definitively exclude or confirm DXA-diagnosed osteoporosis [84].

Quantitative computed tomography — Quantitative computed tomography (QCT) measures volumetric BMD (vBMD) in mg/cm3 at the spine and hip. Unlike DXA, QCT can isolate trabecular bone from its envelope of cortical bone. Some studies have suggested that QCT of the spine may be a slightly better predictor of fracture risk of the spine than anterior-posterior spine DXA [85,86], perhaps because of the important contribution of trabecular bone to vertebral body strength [87]. However, another study suggested that QCT of the spine is not superior to DXA of the hip in predicting non-spine fracture [88].

QCT-derived, DXA-equivalent T-scores of the hip have been validated for diagnosing osteoporosis and osteopenia with the WHO criteria for BMD classification [29] but are not recommended for use in clinical practice unless DXA is not available, due to the level of radiation exposure and cost. A calculated aBMD of the hip derived from QCT measurements may be used for estimation of fracture risk with FRAX [89]. QCT may be clinically useful to monitor changes in BMD over time for some patients with structural abnormalities of the spine that preclude the use of DXA. It has a potential role in monitoring the therapeutic effects of anabolic agents or other types of drugs with novel mechanisms of action. At the present time, QCT is primarily a research tool that has been very helpful in improving our understanding of the pathogenesis of osteoporosis and the skeletal effects of drugs used to treat osteoporosis. It is more expensive, less reproducible, and requires a higher radiation dose than DXA.

New and emerging technologies — Although BMD measured by DXA is the most common method for assessing fracture risk in clinical practice, it has some limitations. DXA measures aBMD, rather than vBMD. In addition, it cannot distinguish between cortical and trabecular bone, cannot assess bone microarchitecture, and is not the only predictor of fractures. Thus, new technologies and non-BMD DXA measurements have been developed that allow noninvasive assessment of bone strength. As examples:

High-resolution peripheral QCT (HR-pQCT), high-resolution MRI (HR-MRI), and microMRI measure structural bone properties at peripheral sites (distal radius, tibia) in vivo. Alterations in microarchitecture as detected by these techniques have been associated with increases in fracture risk [90-93].

Trabecular attenuation can be measured on a standard clinical computed tomographic (CT) scan obtained for another clinical indication by manually drawing a region of interest. As an example, in abdominal CT exams of patients aged ≥65 years, trabecular attenuation measured at L1 is a predictor of fracture risk at any skeletal site [94].

Hip structural analysis (HSA) uses information about bone geometry and mass distribution obtained from DXA scans of the hip to calculate parameters that include hip axis length (HAL), neck-shaft angle (NSA), cross-sectional area (CSA), outer width (OD), section modulus (SM), cross-sectional moment of inertia (CSMI), and buckling ratio (BR) [95]. HAL derived from DXA is associated with hip fracture risk in postmenopausal women, while NSA, CSA, OD, SM, and CSMI derived from DXA should not be used to assess hip fracture risk [96]. None of these parameters should be used to initiate or monitor treatment.

Structural engineering models (SEMs) of the hip integrate DXA-derived hip data with applied forces to estimate hip fracture risk [95].

Finite element analysis (FEA) uses computer models of images and data from QCT of the spine or hip to assess bone strength [97]. QCT-based FEA can be used to predict vertebral fracture in postmenopausal females and is comparable with spine DXA in predicting vertebral fractures in males [98]; it is also comparable with hip DXA in predicting hip fractures in postmenopausal females and older males. FEA cannot be used to diagnose osteoporosis, initiate therapy, or monitor therapy.

Radiofrequency echographic multispectrometry (REMS) is a nonionizing technology for the densitometric assessment of osteoporosis. In a large, multicenter European study, REMS was able discriminate patients with and without osteoporosis (DXA T-score equal to or less than -2.5) at the femoral neck with sensitivity and specificity of 90.4 and 95.5 percent, respectively; for the lumbar spine scans, sensitivity was 90.9 percent and specificity was 95.1 percent [99].

Pulse-echo ultrasonography (PEUS) is a novel ultrasound method that measures the thickness of cortical bone at peripheral skeletal sites with a handheld device connected to a personal computer using proprietary software. In a study of ambulatory, older females with a previous hip fracture, there was a good correlation between PEUS-derived values expressed as density index (DI) at the proximal tibia and DXA BMD at the femoral neck [100].

While all of these technologies have provided insight into skeletal properties other than BMD that determine bone strength, their role in clinical practice has not been defined. These techniques are used primarily in research settings.

SKELETAL SITE TO MEASURE — We follow International Society for Clinical Densitometry (ISCD) recommendations and measure BMD using dual-energy x-ray absorptiometry (DXA; hip and lumbar spine). When either the hip or lumbar spine is not a valid skeletal site for BMD measurement, then the 33 percent (one-third) radius should be measured. In some patients, measurement of the hip alone could be sufficient.

Fracture risk can be predicted by measurement or estimation of bone mineral density (BMD) at many skeletal sites with a variety of technologies. Although BMD measurements at peripheral skeletal sites predict global fracture risk (ie, the risk of fracture at any skeletal site) as well as BMD measurement at the hip or spine [18,101], the risk for fracture at a particular skeletal site is best estimated by measuring BMD at that skeletal site [102-105].

The ISCD recommends that the World Health Organization (WHO) criteria be applied to BMD measured by dual-energy x-ray absorptiometry (DXA), using the lowest T-score of the lumbar spine (preferably L1-L4), femoral neck, or total proximal femur. If BMD cannot be measured at either of these skeletal sites due to structural abnormalities, such as osteoarthritis or surgical artifact, then the distal 33 percent (one-third) radius should also be measured and considered for diagnostic classification [80].

The lumbar spine is less useful for BMD measurement in older individuals, in whom structural abnormalities such as degenerative arthritis and disc disease commonly result in BMD increases. In such patients, measurement of the hip and forearm are recommended. (See "Clinical manifestations, diagnosis, and evaluation of osteoporosis in postmenopausal women", section on 'Site of measurement' and "Treatment of osteoporosis in men".)

In addition, it is important to note that Fracture Risk Assessment Tool (FRAX) was designed to calculate fracture probability with femoral neck BMD measured by DXA. The validity of FRAX with BMD measured at other skeletal sites and using other technologies (other than quantitative computed tomography [QCT] when DXA is not available) has not been determined and therefore is not recommended. (See 'Clinical application of fracture risk assessment' above.)

CLINICAL RISK FACTOR ASSESSMENT — Most fractures occur in patients who do not have a World Health Organization (WHO) classification of osteoporosis according to a T-score of -2.5 or less. Although patients with osteoporosis are at the highest risk of fracture, there are more fractures in patients with low bone mass or osteopenia (T-score between -1.0 and -2.5) because there are so many more patients in this category [7,106,107]. Therefore, assessment of clinical risk factors that are independent of bone mineral density (BMD) is important for fracture prediction.

Some of these factors in White adults include advancing age, previous fracture, glucocorticoid therapy, a family history of hip fracture, poor visual capacity, low body weight, neuromuscular disorders, and smoking (table 1) [10,108,109]. Similar risk factors were identified in a prospective study of 1435 Chinese women [23].

Many of these risk factors are easily discernible from a routine history and physical examination; taken together, they are predictive of future hip fracture, even in the absence of BMD measurement [110,111]. Advancing age and previous personal history of fracture are two of the most important BMD-independent risk factors for fracture.

Clinical risk factor assessment alone may be considered for fracture prediction in world regions without access to any BMD technologies. The Fracture Risk Assessment Tool (FRAX) model allows estimation of 10-year probability of hip fracture and major osteoporotic fractures using clinical risk factors alone or in combination with femoral neck BMD. (See 'Fracture risk assessment tool' above.)

Advanced age — For any given T-score, the risk of fracture is higher with advancing age (figure 1) [112].

Personal history of fracture as an adult — A history of a fragility (low-trauma) fracture is another important risk factor for subsequent fracture in both females and males [64,113-117]:

A meta-analysis of 11 prospective cohort studies of fracture risk in females or males with prior fracture reported increased risks of any fracture (relative risk [RR] 1.8, 95% CI 1.6-1.9), osteoporotic fracture (RR 1.8, 95% CI 1.6-1.9), and hip fracture (RR 1.6, 95% CI 1.3-2.0) in both females and males, even after adjustment for BMD [115].

In a prospective cohort study of 4005 Australian individuals (≥60 years of age) followed for 16 years, the RR of subsequent fracture in females with any initial low-trauma fracture (after age 60 years) was 2.0 (95% CI 1.7-2.2) and for males was 3.5 (95% CI 2.7-4.5) [113].

In a longitudinal study (Study of Osteoporotic Fractures [SOF]) of 9700 older (age >65 years at baseline) females, 2680 of whom were followed for an average of 15 years, the absolute risk (AR) of a new vertebral fracture in females with previous vertebral fracture ranged from 25 to 50 percent, depending upon T-score [64]. The risk of new vertebral fracture was greatest in those with a total hip T-score ≤-2.5 and a previous vertebral fracture (AR 56 percent, 95% CI 44-69). (See 'Expression of fracture risk' above.)

Prior fracture is associated with a particularly high risk of a subsequent fracture in the following one to five years ("imminent fracture risk") [118-122]. When recency of fracture is held constant, the risk of a second fracture soon after a prior fracture varies according to age, sex, and site of the prior fracture [123].

Studies have also shown that older adults with high-trauma fractures (eg, motor vehicle accident) have low BMD and increased risk of future fractures that is similar to those with fragility fractures [68,69,124]. This suggests that older adults with a fracture, regardless of the perceived level of trauma, should be considered for skeletal health evaluation and appropriate interventions. (See "Clinical manifestations, diagnosis, and evaluation of osteoporosis in postmenopausal women", section on 'Evaluation' and "Clinical manifestations, diagnosis, and evaluation of osteoporosis in men", section on 'Evaluation'.)

Glucocorticoid therapy — A retrospective cohort study in 244,235 oral glucocorticoid users in the United Kingdom General Practice Research Database showed a dose-dependent relationship between chronic glucocorticoid use and fracture risk, with high doses (prednisolone 7.5 mg/day or greater) having the highest risk [125]. Low doses of glucocorticoids (prednisolone less than 2.5 mg/day) were also associated with increased fracture risk. (See "Clinical features and evaluation of glucocorticoid-induced osteoporosis" and "Prevention and treatment of glucocorticoid-induced osteoporosis".)

History of fragility fracture in a first-degree relative — Parental history of hip fracture is associated with a twofold increased risk of hip fracture in women, regardless of BMD [110].

Low body weight — Low body weight (less than 58 kg [127 lb]) is associated with increased risk of osteoporosis and fractures, possibly related to small bone size [126-129]. Weight loss after age 50 years in women and increased height also raise the risk of hip fracture, while weight gain decreases it [127,130,131].

The mechanism of weight loss may influence the effect on bone physiology. In one small, randomized trial, subjects who lost weight by calorie restriction had decreases in total hip BMD, whereas subjects who lost the same amount of weight via exercise without reduced caloric intake had no changes in BMD [132].

Cigarette smoking — Meta-analyses have shown that cigarette smoking is associated with reduced BMD and increased risk of fracture [133,134]. The risk of fracture was increased with a smoking history and current smoking, but was higher for current smokers.

Excessive alcohol consumption — The risk of fracture with excessive alcohol intake is dose dependent [135]. A meta-analysis of case-control and prospective cohort studies showed that alcohol consumption in excess of two drinks (approximately 28 g of pure alcohol) per day is associated with an increased risk of hip fracture (RR 1.39, 95% CI 1.08-1.79) [136].

Medical diseases — Many medical diseases are associated with low BMD and an increased risk of fracture, either due to underlying inflammation, malabsorption, renal excretion of calcium, or medications used to treat the diseases. As examples:

Rheumatoid arthritis. (See "Overview of the systemic and nonarticular manifestations of rheumatoid arthritis".)

Inflammatory bowel disease. (See "Metabolic bone disease in inflammatory bowel disease".)

Celiac disease. (See "Epidemiology, pathogenesis, and clinical manifestations of celiac disease in adults", section on 'Metabolic bone disorders'.)

Cystic fibrosis. (See "Cystic fibrosis: Clinical manifestations and diagnosis", section on 'Musculoskeletal disorders'.)

Previous hyperthyroidism. (See "Bone disease with hyperthyroidism and thyroid hormone therapy".)

Type 1 and 2 diabetes. (See "Bone disease in diabetes mellitus".)

Renal disease. (See "Overview of chronic kidney disease-mineral and bone disorder (CKD-MBD)".)

End-stage kidney disease is associated with an increased risk of fracture. In addition, moderate degrees of renal insufficiency (as estimated in patients with a stable serum creatinine) have been reported to be associated with an increased fracture risk in one study [137], but not in another [138].

Sickle cell disease. (See "Acute and chronic bone complications of sickle cell disease".)

Other risk factors — Risk factors in addition to those described above (table 1) include the following:

Vitamin D deficiency.

Reduced functional mobility, recurrent falls, or use of walking aids. (See "Falls in older persons: Risk factors and patient evaluation".)

Many drugs, including androgen deprivation agents, aromatase inhibitors, proton pump inhibitors, selective serotonin reuptake inhibitors (SSRIs), thiazolidinediones, and anticonvulsants. (See "Side effects of androgen deprivation therapy", section on 'Osteoporosis and bone fractures' and "Drugs that affect bone metabolism".)

Dementia.

Poor health/frailty.

Previous fracture between the ages of 20 and 50 years. (See "Epidemiology and etiology of premenopausal osteoporosis", section on 'Fractures'.)

A previous history of breast cancer. (See "Overview of long-term complications of therapy in breast cancer survivors and patterns of relapse", section on 'Musculoskeletal complications'.)

Possible risk factors

Depression has been associated with an increased risk of fracture in some studies [139]. However, the relationship between depression and fracture is likely complex. Individuals with depression tend to have other risk factors for fracture, including medication use (SSRIs), increased frequency of falling, hypercortisolism, and lifestyle factors (smoking, alcohol). (See 'Other risk factors' above.)

Mild asymptomatic hyponatremia (serum sodium <135 mEq/L) was associated with an increased risk of fall-related fractures (adjusted odds ratio [OR] for fracture 4.2, 95% CI 2.2-7.7) in a case-control study [140]. In the majority of cases, hyponatremia was either drug-induced (diuretics, SSRIs, and antiseizure medications) or was due to the syndrome of inappropriate antidiuretic hormone secretion. (See "Drugs that affect bone metabolism".)

Aortic calcification on computed tomography (CT) scan (a marker of atherosclerosis) [141].

Elevated markers of inflammation [142,143].

High dietary retinol intake, which some, but not all, studies suggest increases fracture risk. (See "Drugs that affect bone metabolism".)

Sedentary lifestyle [144].

Vitamin B12 deficiency (pernicious anemia). (See "Treatment of vitamin B12 and folate deficiencies".)

High homocysteine concentrations, which are associated with an increased risk of fracture in some, but not all, studies [145-151].

Consumption of large amounts of caffeine. The association between excess caffeine and increased fracture risk has been variably reported as a definite association [110], no association [152,153], and an association only if the patient does not drink milk [154].

Carbonated beverages may be associated with adverse skeletal effects in adolescents, possibly due to the displacement of nutritious foods and beverages, but the impact in older women is unclear. In one report, modest intake of carbonated beverages did not have adverse effects on BMD [155], while in another, cola drinks (but not other carbonated beverages), were associated with lower bone density [156]. (See "Bone health and calcium requirements in adolescents".)

Bone turnover markers (BTMs) — Measurements of BTMs may provide information about expected rates of bone loss and fracture risk that cannot be obtained from measurements of BMD (figure 2) [157,158]. Elevated BTMs have been demonstrated to be associated with increased risk of vertebral and nonvertebral fracture, independently of BMD, suggesting that BMD combined with a BTM may improve fracture prediction (figure 3) [159,160]. (See "Use of biochemical markers of bone turnover in osteoporosis".)

However, the relationship between BTMs and fracture risk has not been validated in all studies. As examples:

In a subset of placebo patients in the Multiple Outcomes of Raloxifene (MORE) study, none of the BTMs (bone-specific alkaline phosphatase, osteocalcin, or urinary C-telopeptide) that were measured influenced fracture risk [161].

In an observational study of 225 postmenopausal women followed for a median of 16.2 years, BTMs (osteocalcin, alkaline phosphatase, and urinary hydroxyproline) did not predict any type of osteoporotic fracture [73].

While the use of BTMs in clinical trials has been helpful in understanding the mechanism of action of therapeutic agents, their role in the care of individual patients is not well established. Potential roles of BTMs in clinical practice include prediction of fracture risk, monitoring response to therapy, and as an aid in selection of drug for treatment [162]. It is not clear which specific BTM is most useful for specific clinical situations. Biologic and within individual variability in BTM values have confounded their widespread use in clinical practice.

SOCIETY GUIDELINE LINKS — Links to society and government-sponsored guidelines from selected countries and regions around the world are provided separately. (See "Society guideline links: Osteoporosis" and "Society guideline links: Clinical densitometry".)

SUMMARY AND RECOMMENDATIONS

Fracture risk assessment – Bone mineral density (BMD) and clinical risk factors may be combined to provide a better estimate of fracture risk than BMD or clinical risk factors alone. (See 'Assessment of fracture risk' above.)

Fracture risk assessment models – The Fracture Risk Assessment Tool (FRAX) estimates the 10-year probability of hip fracture and major osteoporotic fracture for an untreated patient (40 to 90 years of age) using femoral neck BMD (g/cm2), when available, and easily obtainable clinical risk factors for fracture (table 1). Other fracture risk assessment models are available (eg, QFracture, Garvan), but most have not been validated in diverse populations. The thresholds for intervention vary with the individual models. The selection of a particular assessment tool may best be determined by country-specific guidelines for treatment thresholds. (See 'Fracture risk assessment tool' above.)

FRAX – FRAX may be calibrated for each country using country-specific fracture data and mortality data (when available), then used with country-specific economic assumptions to develop treatment guidelines with thresholds for cost-effective pharmacologic intervention. (See 'Clinical application of fracture risk assessment' above.)

Clinical application – With the use of the fracture risk assessment models, it is anticipated that intervention will be more effectively targeted to those at highest risk of fracture (ie, older patients with slightly low T-scores and high risk of fracture will be selected for drug therapy), while fewer younger patients with low T-scores and low risk of fracture will be treated. (See 'Clinical application of fracture risk assessment' above.)

BMD assessment – We measure BMD using dual-energy x-ray absorptiometry (DXA; hip and lumbar spine). When either the hip or lumbar spine is not a valid skeletal site for BMD measurement, then the 33 percent (one-third) radius should be measured. In some patients, measurement of the hip alone could be sufficient. (See 'Skeletal site to measure' above.)

Other validated techniques measuring different skeletal sites have also demonstrated the ability to predict the likelihood of fractures. However, T-scores derived from different skeletal sites with different technologies are not interchangeable. (See 'Methods of measurement of BMD' above.)

Clinical risk factor assessment – Clinical risk factor assessment alone may be considered for fracture prediction in world regions without access to any BMD technologies. FRAX and other models allow estimation of 10-year probability of hip fracture and major osteoporotic fracture using clinical risk factors alone. (See 'Clinical risk factor assessment' above.)

The most robust, non-BMD risk factors are age and prevalent fracture. Other validated BMD-independent risk factors for fracture include long-term glucocorticoid therapy, parental history of hip fracture, cigarette smoking, and excess alcohol intake (table 1). (See 'Clinical risk factor assessment' above.)

  1. Riggs BL, Melton LJ 3rd. The worldwide problem of osteoporosis: insights afforded by epidemiology. Bone 1995; 17:505S.
  2. Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int 2006; 17:1726.
  3. Ioannidis G, Papaioannou A, Hopman WM, et al. Relation between fractures and mortality: results from the Canadian Multicentre Osteoporosis Study. CMAJ 2009; 181:265.
  4. Poole KE, Compston JE. Osteoporosis and its management. BMJ 2006; 333:1251.
  5. Adachi JD, Adami S, Gehlbach S, et al. Impact of prevalent fractures on quality of life: baseline results from the global longitudinal study of osteoporosis in women. Mayo Clin Proc 2010; 85:806.
  6. Ahlborg HG, Johnell O, Turner CH, et al. Bone loss and bone size after menopause. N Engl J Med 2003; 349:327.
  7. Wainwright SA, Marshall LM, Ensrud KE, et al. Hip fracture in women without osteoporosis. J Clin Endocrinol Metab 2005; 90:2787.
  8. Siris ES, Chen YT, Abbott TA, et al. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med 2004; 164:1108.
  9. Schuit SC, van der Klift M, Weel AE, et al. Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study. Bone 2004; 34:195.
  10. Kanis JA. Diagnosis of osteoporosis and assessment of fracture risk. Lancet 2002; 359:1929.
  11. Kanis JA, Johnell O, Oden A, et al. Ten-year risk of osteoporotic fracture and the effect of risk factors on screening strategies. Bone 2002; 30:251.
  12. Kanis JA, Borgstrom F, De Laet C, et al. Assessment of fracture risk. Osteoporos Int 2005; 16:581.
  13. Kanis JA, Oden A, Johnell O, et al. 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; 18:1033.
  14. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group. World Health Organ Tech Rep Ser 1994; 843:1.
  15. Stone KL, Seeley DG, Lui LY, et al. 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; 18:1947.
  16. Johnell O, Kanis JA, Oden A, et al. Predictive value of BMD for hip and other fractures. J Bone Miner Res 2005; 20:1185.
  17. Leslie WD, Tsang JF, Caetano PA, et al. Effectiveness of bone density measurement for predicting osteoporotic fractures in clinical practice. J Clin Endocrinol Metab 2007; 92:77.
  18. Black DM, Cummings SR, Genant HK, et al. Axial and appendicular bone density predict fractures in older women. J Bone Miner Res 1992; 7:633.
  19. Kanis JA, Glüer CC. An update on the diagnosis and assessment of osteoporosis with densitometry. Committee of Scientific Advisors, International Osteoporosis Foundation. Osteoporos Int 2000; 11:192.
  20. Cummings SR, Black DM, Nevitt MC, et al. Bone density at various sites for prediction of hip fractures. The Study of Osteoporotic Fractures Research Group. Lancet 1993; 341:72.
  21. Marshall D, Johnell O, Wedel H. Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 1996; 312:1254.
  22. Cranney A, Jamal SA, Tsang JF, et al. Low bone mineral density and fracture burden in postmenopausal women. CMAJ 2007; 177:575.
  23. Kung AW, Lee KK, Ho AY, et al. Ten-year risk of osteoporotic fractures in postmenopausal Chinese women according to clinical risk factors and BMD T-scores: a prospective study. J Bone Miner Res 2007; 22:1080.
  24. Kanis JA, Johnell O, Oden A, et al. FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int 2008; 19:385.
  25. WHO Fracture Risk Assessment Tool (FRAX). http://www.shef.ac.uk/FRAX (Accessed on June 05, 2012).
  26. Leslie WD, Morin S, Lix LM, et al. Fracture risk assessment without bone density measurement in routine clinical practice. Osteoporos Int 2012; 23:75.
  27. Kanis JA, Johnell O, Oden A, et al. Risk of hip fracture according to the World Health Organization criteria for osteopenia and osteoporosis. Bone 2000; 27:585.
  28. Kanis JA, Oden A, Johnell O, et al. The burden of osteoporotic fractures: a method for setting intervention thresholds. Osteoporos Int 2001; 12:417.
  29. Engelke K, Lang T, Khosla S, et al. Clinical Use of Quantitative Computed Tomography (QCT) of the Hip in the Management of Osteoporosis in Adults: the 2015 ISCD Official Positions-Part I. J Clin Densitom 2015; 18:338.
  30. Marques A, Ferreira RJ, Santos E, et al. The accuracy of osteoporotic fracture risk prediction tools: a systematic review and meta-analysis. Ann Rheum Dis 2015; 74:1958.
  31. McCloskey EV, Harvey NC, Johansson H, Kanis JA. FRAX updates 2016. Curr Opin Rheumatol 2016; 28:433.
  32. Leslie WD, Lix LM, Johansson H, et al. Does osteoporosis therapy invalidate FRAX for fracture prediction? J Bone Miner Res 2012; 27:1243.
  33. Leslie WD, Majumdar SR, Lix LM, et al. Can change in FRAX score be used to "treat to target"? A population‐based cohort study. J Bone Miner Res 2014; 29:1074.
  34. Rubin KH, Friis-Holmberg T, Hermann AP, et al. Risk assessment tools to identify women with increased risk of osteoporotic fracture: complexity or simplicity? A systematic review. J Bone Miner Res 2013; 28:1701.
  35. Hippisley-Cox J, Coupland C. Predicting risk of osteoporotic fracture in men and women in England and Wales: prospective derivation and validation of QFractureScores. BMJ 2009; 339:b4229.
  36. Tosteson AN, Melton LJ 3rd, Dawson-Hughes B, et al. Cost-effective osteoporosis treatment thresholds: the United States perspective. Osteoporos Int 2008; 19:437.
  37. Kanis JA, Burlet N, Cooper C, et al. European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int 2008; 19:399.
  38. Kanis JA, Borgstrom F, Zethraeus N, et al. Intervention thresholds for osteoporosis in the UK. Bone 2005; 36:22.
  39. Kanis JA, Borgström F, Johnell O, et al. Cost-effectiveness of raloxifene in the UK: an economic evaluation based on the MORE study. Osteoporos Int 2005; 16:15.
  40. Borgström F, Johnell O, Kanis JA, et al. Cost effectiveness of raloxifene in the treatment of osteoporosis in Sweden: an economic evaluation based on the MORE study. Pharmacoeconomics 2004; 22:1153.
  41. Kanis JA, Borgstrom F, Johnell O, Jonsson B. Cost-effectiveness of risedronate for the treatment of osteoporosis and prevention of fractures in postmenopausal women. Osteoporos Int 2004; 15:862.
  42. Borgström F, Johnell O, Kanis JA, et al. At what hip fracture risk is it cost-effective to treat? International intervention thresholds for the treatment of osteoporosis. Osteoporos Int 2006; 17:1459.
  43. Dawson-Hughes B, Tosteson AN, Melton LJ 3rd, et al. Implications of absolute fracture risk assessment for osteoporosis practice guidelines in the USA. Osteoporos Int 2008; 19:449.
  44. Leib ES, Saag KG, Adachi JD, et al. Official Positions for FRAX(®) clinical regarding glucocorticoids: the impact of the use of glucocorticoids on the estimate by FRAX(®) of the 10 year risk of fracture from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX(®). J Clin Densitom 2011; 14:212.
  45. The International Society for Clinical Densitometry, International Osteoporosis Foundation 2010 Official Positions on FRAX. http://www.iscd.org/wp-content/uploads/2012/10/Official-Positions-ISCD-IOF-FRAX.pdf.
  46. Sornay-Rendu E, Munoz F, Delmas PD, Chapurlat RD. The FRAX tool in French women: How well does it describe the real incidence of fracture in the OFELY cohort? J Bone Miner Res 2010; 25:2101.
  47. Giangregorio LM, Leslie WD, Lix LM, et al. FRAX underestimates fracture risk in patients with diabetes. J Bone Miner Res 2012; 27:301.
  48. Leslie WD, Lix LM, Johansson H, et al. Spine-hip discordance and fracture risk assessment: a physician-friendly FRAX enhancement. Osteoporos Int 2011; 22:839.
  49. Kanis JA, Johansson H, Oden A, McCloskey EV. Guidance for the adjustment of FRAX according to the dose of glucocorticoids. Osteoporos Int 2011; 22:809.
  50. Schacter GI, Leslie WD. DXA-Based Measurements in Diabetes: Can They Predict Fracture Risk? Calcif Tissue Int 2017; 100:150.
  51. Bauer DC, Glüer CC, Genant HK, Stone K. Quantitative ultrasound and vertebral fracture in postmenopausal women. Fracture Intervention Trial Research Group. J Bone Miner Res 1995; 10:353.
  52. Schott AM, Weill-Engerer S, Hans D, et al. Ultrasound discriminates patients with hip fracture equally well as dual energy X-ray absorptiometry and independently of bone mineral density. J Bone Miner Res 1995; 10:243.
  53. Khaw KT, Reeve J, Luben R, et al. Prediction of total and hip fracture risk in men and women by quantitative ultrasound of the calcaneus: EPIC-Norfolk prospective population study. Lancet 2004; 363:197.
  54. Bauer DC, Glüer CC, Cauley JA, et al. Broadband ultrasound attenuation predicts fractures strongly and independently of densitometry in older women. A prospective study. Study of Osteoporotic Fractures Research Group. Arch Intern Med 1997; 157:629.
  55. Hans D, Dargent-Molina P, Schott AM, et al. Ultrasonographic heel measurements to predict hip fracture in elderly women: the EPIDOS prospective study. Lancet 1996; 348:511.
  56. Glüer CC, Eastell R, Reid DM, et al. Association of five quantitative ultrasound devices and bone densitometry with osteoporotic vertebral fractures in a population-based sample: the OPUS Study. J Bone Miner Res 2004; 19:782.
  57. Stewart A, Torgerson DJ, Reid DM. Prediction of fractures in perimenopausal women: a comparison of dual energy x ray absorptiometry and broadband ultrasound attenuation. Ann Rheum Dis 1996; 55:140.
  58. Thompson P, Taylor J, Fisher A, Oliver R. Quantitative heel ultrasound in 3180 women between 45 and 75 years of age: compliance, normal ranges and relationship to fracture history. Osteoporos Int 1998; 8:211.
  59. Marín F, González-Macías J, Díez-Pérez A, et al. Relationship between bone quantitative ultrasound and fractures: a meta-analysis. J Bone Miner Res 2006; 21:1126.
  60. Seeley DG, Browner WS, Nevitt MC, et al. Which fractures are associated with low appendicular bone mass in elderly women? The Study of Osteoporotic Fractures Research Group. Ann Intern Med 1991; 115:837.
  61. Ross PD, Davis JW, Epstein RS, Wasnich RD. Pre-existing fractures and bone mass predict vertebral fracture incidence in women. Ann Intern Med 1991; 114:919.
  62. Cummings SR, Black DM, Nevitt MC, et al. Appendicular bone density and age predict hip fracture in women. The Study of Osteoporotic Fractures Research Group. JAMA 1990; 263:665.
  63. Picard D, Brown JP, Rosenthall L, et al. Ability of peripheral DXA measurement to diagnose osteoporosis as assessed by central DXA measurement. J Clin Densitom 2004; 7:111.
  64. Cauley JA, Hochberg MC, Lui LY, et al. Long-term risk of incident vertebral fractures. JAMA 2007; 298:2761.
  65. De Laet CE, Van Hout BA, Burger H, et al. Hip fracture prediction in elderly men and women: validation in the Rotterdam study. J Bone Miner Res 1998; 13:1587.
  66. Khosla S. High-trauma fractures and bone mineral density. JAMA 2007; 298:2418.
  67. Sanders KM, Pasco JA, Ugoni AM, et al. The exclusion of high trauma fractures may underestimate the prevalence of bone fragility fractures in the community: the Geelong Osteoporosis Study. J Bone Miner Res 1998; 13:1337.
  68. Mackey DC, Lui LY, Cawthon PM, et al. High-trauma fractures and low bone mineral density in older women and men. JAMA 2007; 298:2381.
  69. Leslie WD, Schousboe JT, Morin SN, et al. Fracture risk following high-trauma versus low-trauma fracture: a registry-based cohort study. Osteoporos Int 2020; 31:1059.
  70. Cummings SR, Cosman F, Lewiecki EM, et al. Goal-Directed Treatment for Osteoporosis: A Progress Report From the ASBMR-NOF Working Group on Goal-Directed Treatment for Osteoporosis. J Bone Miner Res 2017; 32:3.
  71. Bouxsein ML, Eastell R, Lui LY, et al. Change in Bone Density and Reduction in Fracture Risk: A Meta-Regression of Published Trials. J Bone Miner Res 2019; 34:632.
  72. Huang C, Ross PD, Wasnich RD. Short-term and long-term fracture prediction by bone mass measurements: a prospective study. J Bone Miner Res 1998; 13:107.
  73. Melton LJ 3rd, Crowson CS, O'Fallon WM, et al. Relative contributions of bone density, bone turnover, and clinical risk factors to long-term fracture prediction. J Bone Miner Res 2003; 18:312.
  74. Hillier TA, Stone KL, Bauer DC, et al. Evaluating the value of repeat bone mineral density measurement and prediction of fractures in older women: the study of osteoporotic fractures. Arch Intern Med 2007; 167:155.
  75. Kanis JA, Johnell O, Oden A, et al. Prediction of fracture from low bone mineral density measurements overestimates risk. Bone 2000; 26:387.
  76. Duppe H, Gardsell P, Nilsson B, Johnell O. A single bone density measurement can predict fractures over 25 years. Calcif Tissue Int 1997; 60:171.
  77. Silva BC, Broy SB, Boutroy S, et al. Fracture Risk Prediction by Non-BMD DXA Measures: the 2015 ISCD Official Positions Part 2: Trabecular Bone Score. J Clin Densitom 2015; 18:309.
  78. Shuhart CR, Yeap SS, Anderson PA, et al. Executive Summary of the 2019 ISCD Position Development Conference on Monitoring Treatment, DXA Cross-calibration and Least Significant Change, Spinal Cord Injury, Peri-prosthetic and Orthopedic Bone Health, Transgender Medicine, and Pediatrics. J Clin Densitom 2019; 22:453.
  79. Martineau P, Leslie WD. Trabecular bone score (TBS): Method and applications. Bone 2017; 104:66.
  80. Binkley N, Bilezikian JP, Kendler DL, et al. Official positions of the International Society for Clinical Densitometry and Executive Summary of the 2005 Position Development Conference. J Clin Densitom 2006; 9:4.
  81. Dobnig H, Piswanger-Sölkner JC, Obermayer-Pietsch B, et al. Hip and nonvertebral fracture prediction in nursing home patients: role of bone ultrasound and bone marker measurements. J Clin Endocrinol Metab 2007; 92:1678.
  82. Hodson J, Marsh J. Quantitative ultrasound and risk factor enquiry as predictors of postmenopausal osteoporosis: comparative study in primary care. BMJ 2003; 326:1250.
  83. Stewart A, Reid DM. Quantitative ultrasound or clinical risk factors--which best identifies women at risk of osteoporosis? Br J Radiol 2000; 73:165.
  84. Nayak S, Olkin I, Liu H, et al. Meta-analysis: accuracy of quantitative ultrasound for identifying patients with osteoporosis. Ann Intern Med 2006; 144:832.
  85. Yamada M, Ito M, Hayashi K, et al. Dual energy X-ray absorptiometry of the calcaneus: comparison with other techniques to assess bone density and value in predicting risk of spine fracture. AJR Am J Roentgenol 1994; 163:1435.
  86. Pacifici R, Rupich R, Griffin M, et al. Dual energy radiography versus quantitative computer tomography for the diagnosis of osteoporosis. J Clin Endocrinol Metab 1990; 70:705.
  87. Genant HK, Engelke K, Fuerst T, et al. Noninvasive assessment of bone mineral and structure: state of the art. J Bone Miner Res 1996; 11:707.
  88. Mackey DC, Eby JG, Harris F, et al. Prediction of clinical non-spine fractures in older black and white men and women with volumetric BMD of the spine and areal BMD of the hip: the Health, Aging, and Body Composition Study*. J Bone Miner Res 2007; 22:1862.
  89. Link TM, Lang TF. Axial QCT: clinical applications and new developments. J Clin Densitom 2014; 17:438.
  90. Sornay-Rendu E, Boutroy S, Munoz F, Delmas PD. Alterations of cortical and trabecular architecture are associated with fractures in postmenopausal women, partially independent of decreased BMD measured by DXA: the OFELY study. J Bone Miner Res 2007; 22:425.
  91. Boutroy S, Bouxsein ML, Munoz F, Delmas PD. In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab 2005; 90:6508.
  92. Majumdar S, Link TM, Augat P, et al. Trabecular bone architecture in the distal radius using magnetic resonance imaging in subjects with fractures of the proximal femur. Magnetic Resonance Science Center and Osteoporosis and Arthritis Research Group. Osteoporos Int 1999; 10:231.
  93. Link TM. Osteoporosis imaging: state of the art and advanced imaging. Radiology 2012; 263:3.
  94. Lee SJ, Graffy PM, Zea RD, et al. Future Osteoporotic Fracture Risk Related to Lumbar Vertebral Trabecular Attenuation Measured at Routine Body CT. J Bone Miner Res 2018; 33:860.
  95. Yang L, Peel N, Clowes JA, et al. Use of DXA-based structural engineering models of the proximal femur to discriminate hip fracture. J Bone Miner Res 2009; 24:33.
  96. Broy SB, Cauley JA, Lewiecki ME, et al. Fracture Risk Prediction by Non-BMD DXA Measures: the 2015 ISCD Official Positions Part 1: Hip Geometry. J Clin Densitom 2015; 18:287.
  97. Orwoll ES, Marshall LM, Nielson CM, et al. Finite element analysis of the proximal femur and hip fracture risk in older men. J Bone Miner Res 2009; 24:475.
  98. Zysset P, Qin L, Lang T, et al. Clinical Use of Quantitative Computed Tomography-Based Finite Element Analysis of the Hip and Spine in the Management of Osteoporosis in Adults: the 2015 ISCD Official Positions-Part II. J Clin Densitom 2015; 18:359.
  99. Cortet B, Dennison E, Diez-Perez A, et al. Radiofrequency Echographic Multi Spectrometry (REMS) for the diagnosis of osteoporosis in a European multicenter clinical context. Bone 2021; 143:115786.
  100. Karjalainen JP, Riekkinen O, Töyräs J, et al. Multi-site bone ultrasound measurements in elderly women with and without previous hip fractures. Osteoporos Int 2012; 23:1287.
  101. Siris ES, Miller PD, Barrett-Connor E, et al. Identification and fracture outcomes of undiagnosed low bone mineral density in postmenopausal women: results from the National Osteoporosis Risk Assessment. JAMA 2001; 286:2815.
  102. Blake GM, Fogelman I. Peripheral or central densitometry: does it matter which technique we use? J Clin Densitom 2001; 4:83.
  103. Eastell R, Wahner HW, O'Fallon WM, et al. Unequal decrease in bone density of lumbar spine and ultradistal radius in Colles' and vertebral fracture syndromes. J Clin Invest 1989; 83:168.
  104. Melton LJ 3rd, Atkinson EJ, O'Fallon WM, et al. Long-term fracture prediction by bone mineral assessed at different skeletal sites. J Bone Miner Res 1993; 8:1227.
  105. Cummings SR, Black D. Bone mass measurements and risk of fracture in Caucasian women: a review of findings from prospective studies. Am J Med 1995; 98:24S.
  106. Miller PD, Barlas S, Brenneman SK, et al. An approach to identifying osteopenic women at increased short-term risk of fracture. Arch Intern Med 2004; 164:1113.
  107. Miller PD, Siris ES, Barrett-Connor E, et al. Prediction of fracture risk in postmenopausal white women with peripheral bone densitometry: evidence from the National Osteoporosis Risk Assessment. J Bone Miner Res 2002; 17:2222.
  108. Robbins J, Aragaki AK, Kooperberg C, et al. Factors associated with 5-year risk of hip fracture in postmenopausal women. JAMA 2007; 298:2389.
  109. Liu H, Paige NM, Goldzweig CL, et al. Screening for osteoporosis in men: a systematic review for an American College of Physicians guideline. Ann Intern Med 2008; 148:685.
  110. Cummings SR, Nevitt MC, Browner WS, et al. Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. N Engl J Med 1995; 332:767.
  111. Sambrook PN, Flahive J, Hooven FH, et al. Predicting fractures in an international cohort using risk factor algorithms without BMD. J Bone Miner Res 2011; 26:2770.
  112. Kanis JA, Johnell O, Oden A, et al. Ten year probabilities of osteoporotic fractures according to BMD and diagnostic thresholds. Osteoporos Int 2001; 12:989.
  113. Center JR, Bliuc D, Nguyen TV, Eisman JA. Risk of subsequent fracture after low-trauma fracture in men and women. JAMA 2007; 297:387.
  114. Klotzbuecher CM, Ross PD, Landsman PB, et al. Patients with prior fractures have an increased risk of future fractures: a summary of the literature and statistical synthesis. J Bone Miner Res 2000; 15:721.
  115. Kanis JA, Johnell O, De Laet C, et al. A meta-analysis of previous fracture and subsequent fracture risk. Bone 2004; 35:375.
  116. Hodsman AB, Leslie WD, Tsang JF, Gamble GD. 10-year probability of recurrent fractures following wrist and other osteoporotic fractures in a large clinical cohort: an analysis from the Manitoba Bone Density Program. Arch Intern Med 2008; 168:2261.
  117. Gehlbach S, Saag KG, Adachi JD, et al. Previous fractures at multiple sites increase the risk for subsequent fractures: the Global Longitudinal Study of Osteoporosis in Women. J Bone Miner Res 2012; 27:645.
  118. Johansson H, Siggeirsdóttir K, Harvey NC, et al. Imminent risk of fracture after fracture. Osteoporos Int 2017; 28:775.
  119. Lindsay R, Silverman SL, Cooper C, et al. Risk of new vertebral fracture in the year following a fracture. JAMA 2001; 285:320.
  120. Banefelt J, Åkesson KE, Spångéus A, et al. Risk of imminent fracture following a previous fracture in a Swedish database study. Osteoporos Int 2019; 30:601.
  121. Balasubramanian A, Zhang J, Chen L, et al. Risk of subsequent fracture after prior fracture among older women. Osteoporos Int 2019; 30:79.
  122. Wong RMY, Wong PY, Liu C, et al. The imminent risk of a fracture-existing worldwide data: a systematic review and meta-analysis. Osteoporos Int 2022; 33:2453.
  123. Kanis JA, Johansson H, Harvey NC, et al. The effect on subsequent fracture risk of age, sex, and prior fracture site by recency of prior fracture. Osteoporos Int 2021; 32:1547.
  124. Muschitz C, Kocijan R, Baierl A, et al. Preceding and subsequent high- and low-trauma fracture patterns-a 13-year epidemiological study in females and males in Austria. Osteoporos Int 2017; 28:1609.
  125. Van Staa TP, Leufkens HG, Abenhaim L, et al. Use of oral corticosteroids and risk of fractures. J Bone Miner Res 2000; 15:993.
  126. Ensrud KE, Cauley J, Lipschutz R, Cummings SR. Weight change and fractures in older women. Study of Osteoporotic Fractures Research Group. Arch Intern Med 1997; 157:857.
  127. Ensrud KE, Lipschutz RC, Cauley JA, et al. Body size and hip fracture risk in older women: a prospective study. Study of Osteoporotic Fractures Research Group. Am J Med 1997; 103:274.
  128. Langlois JA, Visser M, Davidovic LS, et al. Hip fracture risk in older white men is associated with change in body weight from age 50 years to old age. Arch Intern Med 1998; 158:990.
  129. Green AD, Colón-Emeric CS, Bastian L, et al. Does this woman have osteoporosis? JAMA 2004; 292:2890.
  130. Langlois JA, Harris T, Looker AC, Madans J. Weight change between age 50 years and old age is associated with risk of hip fracture in white women aged 67 years and older. Arch Intern Med 1996; 156:989.
  131. Meyer HE, Falch JA, O'Neill T, et al. Height and body mass index in Oslo, Norway, compared to other regions of Europe: do they explain differences in the incidence of hip fracture? European Vertebral Osteoporosis Study Group. Bone 1995; 17:347.
  132. Villareal DT, Fontana L, Weiss EP, et al. Bone mineral density response to caloric restriction-induced weight loss or exercise-induced weight loss: a randomized controlled trial. Arch Intern Med 2006; 166:2502.
  133. Ward KD, Klesges RC. A meta-analysis of the effects of cigarette smoking on bone mineral density. Calcif Tissue Int 2001; 68:259.
  134. Kanis JA, Johnell O, Oden A, et al. Smoking and fracture risk: a meta-analysis. Osteoporos Int 2005; 16:155.
  135. Kanis JA, Johansson H, Johnell O, et al. Alcohol intake as a risk factor for fracture. Osteoporos Int 2005; 16:737.
  136. Berg KM, Kunins HV, Jackson JL, et al. Association between alcohol consumption and both osteoporotic fracture and bone density. Am J Med 2008; 121:406.
  137. Ensrud KE, Lui LY, Taylor BC, et al. Renal function and risk of hip and vertebral fractures in older women. Arch Intern Med 2007; 167:133.
  138. Jassal SK, von Muhlen D, Barrett-Connor E. Measures of renal function, BMD, bone loss, and osteoporotic fracture in older adults: the Rancho Bernardo study. J Bone Miner Res 2007; 22:203.
  139. Mezuk B, Eaton WW, Golden SH. Depression and osteoporosis: epidemiology and potential mediating pathways. Osteoporos Int 2008; 19:1.
  140. Gankam Kengne F, Andres C, Sattar L, et al. Mild hyponatremia and risk of fracture in the ambulatory elderly. QJM 2008; 101:583.
  141. Schulz E, Arfai K, Liu X, et al. Aortic calcification and the risk of osteoporosis and fractures. J Clin Endocrinol Metab 2004; 89:4246.
  142. Schett G, Kiechl S, Weger S, et al. High-sensitivity C-reactive protein and risk of nontraumatic fractures in the Bruneck study. Arch Intern Med 2006; 166:2495.
  143. Cauley JA, Danielson ME, Boudreau RM, et al. Inflammatory markers and incident fracture risk in older men and women: the Health Aging and Body Composition Study. J Bone Miner Res 2007; 22:1088.
  144. Gregg EW, Cauley JA, Seeley DG, et al. Physical activity and osteoporotic fracture risk in older women. Study of Osteoporotic Fractures Research Group. Ann Intern Med 1998; 129:81.
  145. van Meurs JB, Dhonukshe-Rutten RA, Pluijm SM, et al. Homocysteine levels and the risk of osteoporotic fracture. N Engl J Med 2004; 350:2033.
  146. McLean RR, Jacques PF, Selhub J, et al. Homocysteine as a predictive factor for hip fracture in older persons. N Engl J Med 2004; 350:2042.
  147. Dhonukshe-Rutten RA, Pluijm SM, de Groot LC, et al. Homocysteine and vitamin B12 status relate to bone turnover markers, broadband ultrasound attenuation, and fractures in healthy elderly people. J Bone Miner Res 2005; 20:921.
  148. Gerdhem P, Ivaska KK, Isaksson A, et al. Associations between homocysteine, bone turnover, BMD, mortality, and fracture risk in elderly women. J Bone Miner Res 2007; 22:127.
  149. Périer MA, Gineyts E, Munoz F, et al. Homocysteine and fracture risk in postmenopausal women: the OFELY study. Osteoporos Int 2007; 18:1329.
  150. McLean RR, Jacques PF, Selhub J, et al. Plasma B vitamins, homocysteine, and their relation with bone loss and hip fracture in elderly men and women. J Clin Endocrinol Metab 2008; 93:2206.
  151. Leboff MS, Narweker R, LaCroix A, et al. Homocysteine levels and risk of hip fracture in postmenopausal women. J Clin Endocrinol Metab 2009; 94:1207.
  152. Lloyd T, Rollings N, Eggli DF, et al. Dietary caffeine intake and bone status of postmenopausal women. Am J Clin Nutr 1997; 65:1826.
  153. Wu CH, Yang YC, Yao WJ, et al. Epidemiological evidence of increased bone mineral density in habitual tea drinkers. Arch Intern Med 2002; 162:1001.
  154. Barrett-Connor E, Chang JC, Edelstein SL. Coffee-associated osteoporosis offset by daily milk consumption. The Rancho Bernardo Study. JAMA 1994; 271:280.
  155. Kim SH, Morton DJ, Barrett-Connor EL. Carbonated beverage consumption and bone mineral density among older women: the Rancho Bernardo Study. Am J Public Health 1997; 87:276.
  156. Tucker KL, Morita K, Qiao N, et al. Colas, but not other carbonated beverages, are associated with low bone mineral density in older women: The Framingham Osteoporosis Study. Am J Clin Nutr 2006; 84:936.
  157. Christiansen C, Riis BJ, Rødbro P. Prediction of rapid bone loss in postmenopausal women. Lancet 1987; 1:1105.
  158. Hansen MA, Overgaard K, Riis BJ, Christiansen C. Role of peak bone mass and bone loss in postmenopausal osteoporosis: 12 year study. BMJ 1991; 303:961.
  159. Garnero P, Sornay-Rendu E, Claustrat B, Delmas PD. Biochemical markers of bone turnover, endogenous hormones and the risk of fractures in postmenopausal women: the OFELY study. J Bone Miner Res 2000; 15:1526.
  160. Delmas PD, Eastell R, Garnero P, et al. The use of biochemical markers of bone turnover in osteoporosis. Committee of Scientific Advisors of the International Osteoporosis Foundation. Osteoporos Int 2000; 11 Suppl 6:S2.
  161. Johnell O, Kanis JA, Black DM, et al. Associations between baseline risk factors and vertebral fracture risk in the Multiple Outcomes of Raloxifene Evaluation (MORE) Study. J Bone Miner Res 2004; 19:764.
  162. Srivastava AK, Vliet EL, Lewiecki EM, et al. Clinical use of serum and urine bone markers in the management of osteoporosis. Curr Med Res Opin 2005; 21:1015.
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