Previous fracture and subsequent fracture risk: a meta-analysis to update FRAX.

A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX. INTRODUCTION: The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD). METHODS: We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture, and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD, and duration of follow-up. The results of the different studies were merged by using the weighted ß-coefficients. RESULTS: A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06), or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination. CONCLUSION: A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies.

Update of the fracture risk prediction tool FRAX: a systematic review of potential cohorts and analysis plan.

We describe the collection of cohorts together with the analysis plan for an update of the fracture risk prediction tool FRAX with respect to current and novel risk factors. The resource comprises 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. INTRODUCTION: The availability of the fracture risk assessment tool FRAX® has substantially enhanced the targeting of treatment to those at high risk of fracture with FRAX now incorporated into more than 100 clinical osteoporosis guidelines worldwide. The aim of this study is to determine whether the current algorithms can be further optimised with respect to current and novel risk factors. METHODS: A computerised literature search was performed in PubMed from inception until May 17, 2019, to identify eligible cohorts for updating the FRAX coefficients. Additionally, we searched the abstracts of conference proceedings of the American Society for Bone and Mineral Research, European Calcified Tissue Society and World Congress of Osteoporosis. Prospective cohort studies with data on baseline clinical risk factors and incident fractures were eligible. RESULTS: Of the 836 records retrieved, 53 were selected for full-text assessment after screening on title and abstract. Twelve cohorts were deemed eligible and of these, 4 novel cohorts were identified. These cohorts, together with 60 previously identified cohorts, will provide the resource for constructing an updated version of FRAX comprising 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. For each known and candidate risk factor, multivariate hazard functions for hip fracture, major osteoporotic fracture and death will be tested using extended Poisson regression. Sex- and/or ethnicity-specific differences in the weights of the risk factors will be investigated. After meta-analyses of the cohort-specific beta coefficients for each risk factor, models comprising 10-year probability of hip and major osteoporotic fracture, with or without femoral neck bone mineral density, will be computed. CONCLUSIONS: These assembled cohorts and described models will provide the framework for an updated FRAX tool enabling enhanced assessment of fracture risk (PROSPERO (CRD42021227266)).

Repurposing a fracture risk calculator (FRAX) as a screening tool for women at risk for sarcopenia.

Osteoporosis and sarcopenia share risk profiles, so we tested a fracture risk assessment tool (FRAX) as a screening tool for sarcopenia. FRAX probabilities without bone mineral density predicted sarcopenia with high sensitivity and reasonable specificity. There is potential to use this FRAX as a screening tool for sarcopenia. PURPOSE: There is a need for simple screening tools for sarcopenia. As osteoporosis and sarcopenia share risk profiles, we tested the performance of a fracture risk assessment tool for discriminating individuals at risk for sarcopenia. METHODS: In this longitudinal study, FRAX (Australia) probabilities were calculated for 354 women (ages 40-90 years) in the Geelong Osteoporosis Study. Sarcopenia was assessed a decade later using DXA-derived low appendicular lean mass (Lunar; ALM/height2 < 5.5 kg/m2) and low handgrip strength (Jamar; HGS < 16 kg), according to EWGSOP2. We determined FRAX probabilities (%) for hip fracture (HF-FRAX) and major osteoporotic fracture (MOF-FRAX), with and without BMD. Area under the receiver operator characteristic (AUROC) curves quantified the performance of FRAX for predicting sarcopenia. RESULTS: Baseline median (IQR) values for HF-FRAX without BMD were 0.4 (0.1-1.3) and for MOF-FRAX without BMD, 2.4 (1.2-5.2); comparable figures for HF-FRAX with BMD were 0.2 (0.0-0.7) and for MOF-FRAX with BMD, 2.1 (1.1-4.4). At follow-up, sarcopenia was identified for 11 (3.1%) women. When FRAX was calculated without BMD, the AUROC was 0.90 for HF-FRAX and 0.88 for MOF-FRAX. Optimal thresholds were 0.9 for HF-FRAX (sensitivity 90.9%, specificity 62.4%) and 5.3 for MOF-FRAX (sensitivity 81.8%, specificity 71.7%). Calculating FRAX with BMD did not improve the predictive performance of FRAX for sarcopenia. CONCLUSION: Here we provide preliminary evidence to suggest that FRAX probabilities without BMD might predict sarcopenia with high sensitivity and reasonable specificity. Given that FRAX clinical risk factors are identified without equipment, there is potential to use this or a modified version of the FRAX tool to screen for individuals at risk of sarcopenia.

Bone mineral density in diabetes and impaired fasting glucose.

We report that compared with normoglycaemia, post-menopausal women (non-obese and obese) with diabetes had higher lumbar spine bone mineral density (LSBMD). Femoral neck bone mineral density (FNBMD) was higher in obese post-menopausal women with diabetes. Only non-obese post-menopausal women with impaired fasting glucose (IFG) had a higher LSBMD than normoglycaemia. No other associations with IFG were observed. INTRODUCTION: Individuals with diabetes have a higher or normal bone mineral density (BMD) compared with those without diabetes. However, paradoxically, they also have a higher fracture risk. It is not clear whether those with IFG also have altered BMD. This study aimed to determine whether individuals with IFG have elevated or normal BMD. METHODS: Women (n = 858) and men (n = 970) (aged 20-80 years) from the Geelong Osteoporosis Study were included. IFG was defined as fasting plasma glucose (FPG) 5.5-6.9 mmol/L and diabetes as FPG ≥ 7.0 mmol/L, use of antihyperglycaemic medication and/or self-report. Using multivariable linear regression, the relationships between glycaemia and BMD at the femoral neck and lumbar spine were examined, and adjusted for age, body mass index (BMI), and other variables. In women, two interaction terms were identified: menopause × glycaemia and BMI × glycaemia, and thus, the analyses were stratified by menopause and obesity status (BMI cut point ≥ 30 kg/m2). RESULTS: There were no associations between glycaemic status and BMD for pre-menopausal women. For non-obese post-menopausal women, there was no association between FNBMD and glycaemic status, but women with IFG or diabetes had higher LSBMD than those with normoglycaemia (7.1% and 9.7%, respectively, both p < 0.01). Obese post-menopausal women with diabetes had a higher FNBMD (8.8%, p = 0.008) and LSBMD (12.2%, p < 0.001), but those with IFG were not different from the normoglycaemia group. There were no associations detected between glycaemic status and BMD in men. CONCLUSIONS: In this study, we report that compared with normoglycaemia, post-menopausal women (non-obese and obese) with diabetes had higher LSBMD. FNBMD was higher in obese post-menopausal women with diabetes. Only non-obese post-menopausal women with IFG had a higher LSBMD than normoglycaemia. No other associations with IFG were observed.

How well do the FRAX (Australia) and Garvan calculators predict incident fractures? Data from the Geelong Osteoporosis Study.

This study reports that both FRAX and Garvan calculators underestimated fractures in Australian men and women, particularly in those with osteopenia or osteoporosis. Major osteoporotic fractures were poorly predicted, while both calculators performed acceptably well for hip fractures. INTRODUCTION: This study assessed the ability of the FRAX (Australia) and Garvan calculators to predict fractures in Australian women and men. METHODS: Women (n = 809) and men (n = 821) aged 50-90 years, enrolled in the Geelong Osteoporosis Study, were included. Fracture risk was estimated using FRAX and Garvan calculators with and without femoral neck bone mineral density (BMD) (FRAXBMD, FRAXnoBMD, GarvanBMD, GarvannoBMD). Incident major osteoporotic (MOF), fragility, and hip fractures over the following 10 years were verified radiologically. Differences between observed and predicted numbers of fractures were assessed using a chi-squared test. Diagnostics indexes were calculated. RESULTS: In women, 115 MOF, 184 fragility, and 42 hip fractures occurred. For men, there were 73, 109, and 17 fractures, respectively. FRAX underestimated MOFs, regardless of sex or inclusion of BMD. FRAX accurately predicted hip fractures, except in women with BMD (20 predicted, p = 0.004). Garvan underestimated fragility fractures except in men using BMD (88 predicted, p = 0.109). Garvan accurately predicted hip fractures except for women without BMD (12 predicted, p < 0.001). Fractures were underestimated primarily in the osteopenia and osteoporosis groups; MOFs in the normal BMD group were only underestimated by FRAXBMD and fragility fractures by GarvannoBMD, both in men. AUROCs were not different between scores with and without BMD, except for fragility fractures predicted by Garvan in women (0.696, 95% CI 0.652-0.739 and 0.668, 0.623-0.712, respectively, p = 0.008) and men, which almost reached significance (0.683, 0.631-0.734, and 0.667, 0.615-0.719, respectively, p = 0.051). Analyses of sensitivity and specificity showed overall that MOFs and fragility fractures were poorly predicted by both FRAX and Garvan, while hip fractures were acceptably predicted. CONCLUSIONS: Overall, the FRAX and Garvan calculators underestimated MOF and fragility fractures, particularly in individuals with osteopenia or osteoporosis. Hip fractures were predicted better by both calculators. AUROC analyses suggest that GarvanBMD performed better than GarvannoBMD for prediction of fragility fractures.

Prediction of major osteoporotic and hip fractures in Australian men using FRAX scores adjusted with trabecular bone score.

There was no significant difference between the areas under receiver operating characteristics (AUROCs) and diagnostic indexes (sensitivity, specificity, positive predictive value, negative predictive value) for either major osteoporotic or hip fracture FRAX scores when comparing the unadjusted and trabecular bone score (TBS)-adjusted scores. INTRODUCTION: FRAX 10-year probability of fracture can be calculated with adjustment for the TBS. Studies have shown that TBS can improve FRAX assessments in some populations. This study aimed to determine if TBS-adjusted FRAX score is better than the unadjusted score for predicting major osteoporotic fracture (MOF) and hip fracture in Australian men. METHODS: This study involved 591 men aged 40-90 years, enrolled in the Geelong Osteoporosis Study. Incident MOF (n = 50) and hip fractures (n = 14) were ascertained using radiological reports. Median follow-up time was 9.5 years (IQR7.5-11.4). Diagnostic indexes were calculated using cut points of ≥20% for MOF and ≥3% for the hip. AUROC curves were also determined for adjusted and unadjusted scores as continuous variables. RESULTS: Sensitivity was higher in the TBS-adjusted scores (MOF 4%, hip 78.6%) than the unadjusted scores (MOF 2%, hip 57.1%), with a decrease in specificity (MOF 98.9 vs 99.3%; hip 79.9 vs 83.9%). When considering TBS-adjusted and unadjusted FRAX as continuous scores, AUROCs were 0.738 and 0.740, respectively, for MOF and 0.849 and 0.848 for the hip. CONCLUSIONS: Prediction of fractures by MOF or hip FRAX was not substantially improved by TBS adjustment. There was no difference in AUROCs or diagnostic indexes for cut-off points of ≥20 for MOF and ≥3% for hip FRAX.

Lower limb fracture presentations at a regional hospital.

We found that lower limb fractures, which were largely the result of minimal trauma, had high levels of hospitalisation, length of stay and surgery. It is therefore important to prevent fractures at all sites to avoid the associated morbidity and mortality. PURPOSE: Hip fractures are a major cause of morbidity and mortality, particularly in older women. In comparison, less is known about the epidemiology and burden of other lower limb fractures. The study aimed to investigate the epidemiology and burden of these fractures. METHODS: Incident fractures of the hip, femur, tibia/fibula, ankle and foot in women (≥ 20 years) managed through the University Hospital Geelong, Australia, were ascertained from 1 Jan. 2014 to 31 Dec. 2014 from radiology reports. Age, cause of fracture, post-fracture hospitalisation, surgery, length of stay and discharge location were ascertained from medical records. RESULTS: We identified 585 fractures of the lower limb (209 hip, 42 femur, 41 tibia/fibula, 162 ankle, 131 foot). Most fractures were sustained by women aged ≥ 50 years. Fractures were largely a result of minimal trauma. Most women with hip or femur fractures were hospitalised; fewer were hospitalised for fractures at other sites. Surgery for fracture followed the same pattern as hospitalisations. Length of stay was the highest for hip and femur fractures and the lowest for foot fractures. Women with hip or femur fractures were discharged to rehabilitation more often than home. Fractures at other sites were most commonly discharged home. CONCLUSIONS: Fractures of the lower limb occurred frequently in older women. Hospitalisation and subsequent surgery were common in cases of hip and femur fractures. It is important for prevention strategies to target fractures at a range of skeletal sites to reduce costs, hospitalisations, loss of independence and reduced quality of life.

Anxiety disorders and falls among older adults.

BACKGROUND: Falls are common among older adults and can lead to serious injuries, including fractures. We aimed to determine associations between anxiety disorders and falls in older adults. METHODS: Participants were 487 men and 376 women aged ≥60 years enrolled in the Geelong Osteoporosis Study, Australia. Using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Non-patient edition (SCID-I/NP), lifetime history of anxiety disorders was determined. Falls were determined by self-report. In men, a falls-risk score (Elderly Falls Screening Test (EFST)) was also calculated. RESULTS: Among fallers, 24 of 299 (8.0%) had a lifetime history of anxiety disorder compared to 36 of 634 (5.7%) non-fallers (p=0.014). Examination of the association between anxiety and falls suggested differential relationships for men and women. In men, following adjustment for psychotropic medications, mobility and blood pressure, lifetime anxiety disorder was associated with falling (OR 2.96; 95%CI 1.07-8.21) and with EFST score (OR 3.46; 95%CI 1.13-10.6). In women, an association between lifetime anxiety disorder and falls was explained by psychotropic medication use, poor mobility and socioeconomic status. LIMITATIONS: Sub-group analyses involving types of anxiety and anxiety disorders over the past 12-months were not performed due to power limitations. CONCLUSION: Although anxiety disorders were independently associated with a 3-fold increase in likelihood of reported falls and high falls risk among men, an independent association was not detected among women. These results may aid in prevention of falls through specific interventions aimed at reducing anxiety, particularly in men.

Physical health comorbidities in women with personality disorder: Data from the Geelong Osteoporosis Study.

BACKGROUND: Associations between common psychiatric disorders, psychotic disorders and physical health comorbidities are frequently investigated. The complex relationship between personality disorders (PDs) and physical health is less understood, and findings to date are varied. This study aims to investigate associations between PDs with a number of prevalent physical health conditions. METHODS: This study examined data collected from women (n=765;≥ 25 years) participating in a population-based study located in south-eastern Australia. Lifetime history of psychiatric disorders was assessed using the semi-structured clinical interviews (SCID-I/NP and SCID-II). The presence of physical health conditions (lifetime) were identified via a combination of self-report, medical records, medication use and clinical data. Socioeconomic status, and information regarding medication use, lifestyle behaviors, and sociodemographic information was collected via questionnaires. Logistic regression models were used to investigate associations. RESULTS: After adjustment for sociodemographic variables (age, socioeconomic status) and health-related factors (body mass index, physical activity, smoking, psychotropic medication use), PDs were consistently associated with a range of physical health conditions. Novel associations were observed between Cluster A PDs and gastro-oesophageal reflux disease (GORD); Cluster B PDs with syncope and seizures, as well as arthritis; and Cluster C PDs with GORD and recurrent headaches. CONCLUSIONS: PDs were associated with physical comorbidity. The current data contribute to a growing evidence base demonstrating associations between PDs and a number of physical health conditions independent of psychiatric comorbidity, sociodemographic and lifestyle factors. Longitudinal studies are now required to investigate causal pathways, as are studies determining pathological mechanisms.

Non-hip and non-vertebral fractures: the neglected fracture sites.

SUMMARY: Non-hip, non-vertebral fractures (NHNVF) were compared with hip, vertebral and controls. NHNVF were younger and heavier than controls and hip/vertebral fractures in both men and women, respectively. Falls and prior fractures were less common in NHNVF than hip fractures. Glucocorticoid use was lower in NHNVF compared to vertebral fracture (VF) in men. INTRODUCTION: Although hip fracture (HF) and vertebral fractures (VF) receive the most attention in the literature and are the targeted sites for fracture prevention, non-hip, non-vertebral fracture (NHNVF) sites account for a greater proportion of fractures than the hip or vertebrae. This study aimed to assess risk factors for NHNVF and compare them with those for HF, VF and controls. METHODS: Incident fractures during 2005-2007 for men and 1994-1996 for women were identified using computerised keyword searches of radiological reports, and controls were selected at random from electoral rolls for participation in the Geelong Osteoporosis Study. Participants aged 60+ years were included in this study. RESULTS: Compared to controls, men and women with NHNVF were younger (ORs, 0.90, 95% CI 0.86-0.94; and 0.96, 0.93-0.98, respectively) and had a lower femoral neck bone mineral density (BMD) T-score (age-adjusted; difference [men] 0.383, P = 0.002; [women] 0.287, P = 0.001). Compared to HF, men and women with NHNVF were heavier (difference [men] 9.0 kg, P = 0.01; [women] 7.6 kg, P < 0.001). Heavier weight was also a risk factor for women with NHNVF compared to VF (1.03, 1.01-1.06). In men with NHNVF, falls (0.37, 0.14-0.97) and prior fractures (0.38, 0.15-0.98) were less common compared to HF; and glucocorticoid use was less common for NHNVF (0.30, 0.11-0.85) compared to VF. CONCLUSIONS: Given the high numbers of NHNVF sustained by men and women in this study, fracture prevention strategies should focus on individuals with high risk of sustaining these types of fractures, as well as on individuals who are more likely to sustain a HF or VF.

The social gradient of fractures at any skeletal site in men and women: data from the Geelong Osteoporosis Study Fracture Grid.

UNLABELLED: Age-specific and age-standardized associations between socioeconomic status (SES) and fractures in adults showed a social gradient of fracture, irrespective of fracture site. Compared to the highest SES, males in the lowest SES group had a sixfold increased odds for any fracture, whilst females had a twofold increased odds. INTRODUCTION: The effective identification of predisposing risk factors for fracture requires understanding any association with SES. These investigations should consider both sexes, span the adult age range and include any fractures. We investigated age- and sex-specific and age-standardized associations between SES and fractures at any skeletal site in Australians aged ≥ 50 years. METHODS: Incident fractures that occurred 2006-2007 for adults aged ≥ 50 years were identified from radiological reports extracted for the Barwon Statistical Division, in south-eastern Australia. SES was determined by cross-referencing residential addresses with Australian Bureau of Statistics census data and then categorized in quintiles. We compared frequencies of observed vs. expected fractures for SES quintiles using χ (2) comparison, calculated age-specific fracture incidence across SES and compared age-standardized fracture rates in SES quintile 1 to quintile 5. RESULTS: We identified 3943 incident fractures (69.4 % female); 47.4 % had occurred at major osteoporotic fracture (MOF) sites (hip, humerus, spine and forearm/wrist). Differences existed in observed vs. expected fractures across SES quintiles (p ≤ 0.001, sexes combined); all fractures showed an inverse association with SES (p ≤ 0.001, sexes combined). Compared to the highest SES quintile, individuals from the lowest SES quintile had between two to six times greater standardized fracture rates. CONCLUSIONS: Disadvantaged men and women have an increased fracture incidence compared to their less disadvantaged counterparts. The large differences in fracture rates between SES groups warrant further research into designing appropriate, targeted interventions for those demographics at most risk.

Is there an interaction between socioeconomic status and FRAX 10-year fracture probability determined with and without bone density measures? Data from the Geelong Osteoporosis Study of female cohort.

FRAX(©) evaluates 10-year fracture probabilities and can be calculated with and without bone mineral density (BMD). Low socioeconomic status (SES) may affect BMD, and is associated with increased fracture risk. Clinical risk factors differ by SES; however, it is unknown whether aninteraction exists between SES and FRAX determined with and without the BMD. From the Geelong Osteoporosis Study, we drew 819 females aged ≥50 years. Clinical data were collected during 1993-1997. SES was determined by cross-referencing residential addresses with Australian Bureau of Statistics census data and categorized in quintiles. BMD was measured by dual energy X-ray absorptiometry at the same time as other clinical data were collected. Ten-year fracture probabilities were calculated using FRAX (Australia). Using multivariable regression analyses, we examined whether interactions existed between SES and 10-year probability for hip and any major osteoporotic fracture (MOF) defined by use of FRAX with and without BMD. We observed a trend for a SES * FRAX(no-BMD) interaction term for 10-year hip fracture probability (p = 0.09); however, not for MOF (p = 0.42). In women without prior fracture (n = 518), we observed a significant SES * FRAX(no-BMD) interaction term for hip fracture (p = 0.03) and MOF (p = 0.04). SES does not appear to have an interaction with 10-year fracture probabilities determined by FRAX with and without BMD in women with previous fracture; however, it does appear to exist for those without previous fracture.

Prior fracture as a risk factor for future fracture in an Australian cohort.

SUMMARY: This study investigated the influence of prior fracture on the risk of subsequent fracture. There was a higher risk of subsequent fracture in both young and older adult age groups when Australian males or females had already sustained a prior fracture. Fracture prevention is important throughout life for both sexes. INTRODUCTION: The purpose of this study was to determine the impact of prior fracture on the risk of subsequent fracture across the adult age range in Australian males and females. METHODS: All-cause fractures were grouped into age categories for males and females enrolled in the Geelong Osteoporosis Study (Australia) using retrospective self-report data and prospective radiology-confirmed data. For all age categories, the relative risk (RR and 95% confidence interval (CI)) of subsequent fracture in a later age category was compared between those with prior fracture and those without. RESULTS: For both sexes, childhood fracture increased the risk of subsequent fracture in adolescence (males: RR 21.7; 95% CI 16.0, 27.4; females: RR 8.1; 3.5, 12.8). Males with adolescent fracture had increased risk of subsequent fracture in early adulthood (RR 11.5; 5.7, 17.3) and mid-adulthood (RR 13.0; 6.3, 19.7). Additionally, males with young adulthood or mid-adulthood fracture had increased risk of subsequent fracture in the following age group (RR 11.2; 4.4, 17.9, and RR 6.2; 0.8, 11.7, respectively). Mid-adult fractures increased the risk of subsequent fracture in older adulthood (RR 6.2; 0.8, 11.7). Females with childhood or adolescent fracture had an increased risk of fracture in young adulthood (RR 4.3; 0.7, 7.9, and RR 10.5; 4.4, 16.6), and prior fracture in older adult life increased the risk of subsequent fracture in old age (RR 14.9; 6.4. 23.3). CONCLUSIONS: Fracture prevention strategies may be more effective if attention is directed towards individuals with prior fracture at any age as they have a higher likelihood of sustaining a subsequent fracture later in life.

Fracture risk among older men: osteopenia and osteoporosis defined using cut-points derived from female versus male reference data.

SUMMARY: We explored the effect of using male and female reference data in a male sample to categorise areal bone mineral density (BMD). Using male reference data, a large proportion of fractures arose from osteopenia, whereas using female reference data shifted the fracture burden into normal BMD. INTRODUCTION: The purpose of this study was to describe fracture risk associated with osteopenia and osteoporosis in older men, defined by areal BMD and using cut-points derived from male and female reference data. METHODS: As part of the Geelong Osteoporosis Study, we followed 619 men aged 60-93 years after BMD assessments (performed 2001-2006) until 2010, fracture, death or emigration. Post-baseline fractures were radiologically confirmed, and proportions of fractures in each BMD category were age-standardised to national profiles. RESULTS: Based on World Health Organization criteria, and using male reference data, 207 men had normal BMD at the femoral neck, 357 were osteopenic and 55 were osteoporotic. Using female reference data, corresponding numbers were 361, 227 and 31. During the study, 130 men died, 15 emigrated and 63 sustained at least one fracture. Using male reference data, most (86.5 %) of the fractures occurred in men without osteoporosis on BMD criteria (18.4 % normal BMD, 68.1 % osteopenia). The pattern differed when female reference data were used; while most fractures arose from men without osteoporosis (88.2 %), the burden shifted from those with osteopenia (34.8 %) to those with normal BMD (53.4 %). CONCLUSIONS: Decreasing BMD categories defined increasing risk of fracture. Although men with osteoporotic BMD were at greatest risk, they made a relatively small contribution to the total burden of fractures. Using male reference data, two-thirds of the fractures arose from men with osteopenia. However, using female reference data, approximately half of the fractures arose from those with normal BMD. Using female reference data to define osteoporosis in men does not appear to be the optimal approach.

Examining the impact of reimbursement on referral to bone density testing for older adults: 8 years of data from the Barwon Statistical Division, Australia.

UNLABELLED: In 2007, Medicare Australia revised rei:mbursement guidelines for dual energy X-ray absorptiometry (DXA) for Australians aged ≥70 years; we examined whether these changes increased DXA referrals in older adults. Proportions of DXA referrals doubled for men and tripled for women from 2003 to 2010; however, rates of utilization remained low. INTRODUCTION: On April 1, 2007 Medicare Australia revised reimbursement guidelines for DXA for Australians aged ≥70 year; changes that were intended to increase the proportion of older adults being tested. We examined whether changes to reimbursement increased DXA referrals in older adults, and whether any sex differences in referrals were observed in the Barwon Statistical Division. METHODS: Proportions of DXA referrals 2003-2010 based on the population at risk ascertained from Australian Census data and annual referral rates and rate ratios stratified by sex, year of DXA, and 5-year age groups. Persons aged ≥70 years referred to the major public health service provider for DXA clinical purposes (n = 6,096; 21 % men). RESULTS: DXA referrals. Proportions of DXA referrals for men doubled from 0.8 % (2003) to 1.8 % (2010) and tripled from 2.0 to 6.3 % for women (all p < 0.001). For 2003-2006, referral ratios of men/women ranged between 1:1.9 and 1:3.0 and for 2007-2010 were 1:2.3 to 1:3.4. Referral ratios <2007:≥2007 were 1:1.7 for men aged 70-79 years (p < 0.001), 1:1.2 for men aged 80-84 years (p = 0.06), and 1:1.3 for men 85+ years (p = 0.16). For women, the ratios <2007:≥2007 were 1:2.1 (70-79 years), 1.1.5 (80-84 years), and 1:1.4 (85+ years) (all p < 0.001). CONCLUSIONS: DXA referral ratios were 1:1.6 (men) and 1:1.8 (women) for 2007-2010 vs. 2003-2006; proportions of referrals doubled for men and tripled for women from 2003 to 2010. Overall, rates of DXA utilization remained low. Policy changes may have had minimal influence on referral; thus, ongoing evaluation over time is warranted.

Age-related reference intervals for bone turnover markers from an Australian reference population.

BACKGROUND: This study was performed to establish age-related serum reference intervals for procollagen type I N-propeptide (P1NP) and type I collagen C-telopeptide (CTx) in the Australian population. METHODS: Fasting sera from 1143 males (mean age 60 years; range 20-97 years) and 1246 females (mean age 53 years; range 20-93 years) who participated in the Geelong Osteoporosis Study were analysed for CTx and P1NP using the automated Roche Modular Analytics E170 analyser. RESULTS: Optimal age-related reference intervals were based on the central 90% of the distribution. The male CTx reference interval was divided into three age groups. For men aged 25 to 40 years, the interval was 170-600 ng/L; 40 to 60 years, the interval was 130-600 ng/L; and for men aged greater 60 years the interval was 100-600 ng/L. For P1NP the male reference interval was 15-80 µg/L for men aged between 25 to 70 years. In men greater than 70 years of age values were higher possibly due to increased bone turnover. High values are frequently seen for both CTx and P1NP in males aged younger than 25 years. This is probably due to bone growth that is not completely finalised. The female CTx reference interval was divided into four age groups. For women aged less than 30 years, the interval was 150-800 ng/L; 30-39 years, the interval was 100-700 ng/L; 40-49 years, the interval was 100-600 ng/L; and for women aged 50 years or more the interval was 100-700 ng/L. The female P1NP reference interval was divided into four age groups. For women aged less than 30 years, the interval was 25-90 µg/L; 30-39 years, the interval was 15-80 µg/L; 40-49 years, the interval was 15-60 µg/L; and for women aged 50-69 years the interval was 15-75 µg/L. In women greater than 70 years of age values were higher possibly due to increased bone turnover. CONCLUSION: Values obtained from this large study provide sound age-related reference intervals for serum P1NP and CTx values in the Australian population.

Associations between measures of adiposity over 10 years and patella cartilage in population-based asymptomatic women.

OBJECTIVE: Osteoarthritis (OA) most commonly affects the patellofemoral compartment of the knee, and is a major cause of pain and disability. Structural changes that evolve prior to the onset of symptoms can be visualised using magnetic resonance imaging (MRI). There is little known information about the role of adiposity on the early structural changes in the patella cartilage in younger, asymptomatic adult females. METHODS: One hundred and sixty asymptomatic women (20-49 years) participating in the Geelong Osteoporosis Study underwent knee MRI (2006-8). Weight and body mass index (BMI) were measured 10 years prior (1994-7, baseline) and at the time of MRI (current), with change over the period calculated (current-baseline). Relationships between measures of adiposity and patella cartilage volume and defects were examined. RESULTS: After adjustment for age and patella bone volume, there was a reduction of 13 ml (95% confidence interval (95% CI), -25.7, -0.55) in patella cartilage volume for every 1 unit increase in current BMI, and a reduction of 27 ml (95% CI -52.6, -1.5) per BMI unit increase over 10 years (P=0.04 for both). No significant association was observed between baseline BMI and patella cartilage volume (P=0.16). Increased baseline and current weight and BMI were associated with increased prevalence of patella cartilage defects (all P<0.001). CONCLUSIONS: Adiposity and weight gain during midlife are associated with detrimental structural change at the patella in young to middle-aged healthy non-osteoarthritic women. Maintaining a healthy weight and avoiding weight gain in younger asymptomatic women may be important in the prevention of patellofemoral OA.

Calcaneal ultrasound reference ranges for Australian men and women: the Geelong Osteoporosis Study.

UNLABELLED: Heel ultrasound is a more portable modality for assessing fracture risk than dual-energy X-ray absorptiometry and does not use ionising radiation. Fracture risk assessment requires appropriate reference data to enable comparisons. This study reports the first heel ultrasound reference ranges for the Australian population. INTRODUCTION: This study aimed to develop calcaneal (heel) ultrasound reference ranges for the Australian adult population using a population-based random sample. METHODS: Men and women aged≥20 years were randomly selected from the Barwon Statistical Division in 2001-2006 and 1993-1997, respectively, using the electoral roll. Broadband ultrasound attenuation (BUA), speed of sound (SOS) and stiffness index (SI) were measured at the heel using a Lunar Achilles Ultrasonometer. Gender-specific means and standard deviations for BUA, SOS and SI were calculated for the entire sample (men 20-93 years, n=1,104; women 20-92 years, n=914) and for participants aged 20-29 years (men, n=157; women, n=151). Associations between ultrasound measures and age were examined using linear regression. RESULTS: For men, mean±standard deviation BUA, SOS and SI were 118.7±15.8 dB/MHz, 1,577.0±43.7 m/s and 100.5±20.7, respectively; values for women were consistently lower (111.0±16.4 dB/MHz, P<0.001; 1,571.0±39.0 m/s, P=0.001; and 93.7±20.3, P<0.001, respectively). BUA was higher in young men compared with young women (124.5±14.4 vs 121.0±15.1 dB/MHz), but SOS (1,590.1±43.1 vs 1,592.5±35.0 m/s) and SI (108.0±19.9 vs 106.3±17.7) were not. The relationships between age and each ultrasound measure were linear and negative across the age range in men; associations were also negative in women but non-linear. CONCLUSION: These data provide reference standards to facilitate the assessment of fracture risk in an Australian population using heel ultrasound.

Bone mineral density is cross sectionally associated with cartilage volume in healthy, asymptomatic adult females: Geelong Osteoporosis Study.

INTRODUCTION: The association between osteoporosis and osteoarthritis (OA) is controversial. Although previous studies have shown total body, lower limb, spinal and knee BMD and knee cartilage volume to be positively associated, the relationship between other distant site-specific measures of BMD and other knee structures is unknown. The aim of this study was to determine the associations between BMD at eight skeletal sites, and knee structure in asymptomatic young to middle-aged females without any clinical signs of OA. METHODS: One hundred and sixty healthy, asymptomatic females (29-50 yr) underwent magnetic resonance imaging of the knee. BMD was measured at the spine, hip, total body and forearm by dual energy X-ray absorptiometry, and at the calcaneus by quantitative ultrasound. BMD was tested for an association with cartilage volume, defects, and bone marrow lesions (BMLs). RESULTS: Medial cartilage volume was positively associated with BMD at the spine, total body, femoral neck, and Ward's triangle (all p<0.05), with non-significant associations in the same direction at the trochanter (p=0.07). Findings in the lateral compartment were similar. The presence of medial cartilage knee defects were also associated with BMD at the spine; defects in the lateral compartment were associated with BMD at the forearm (both p=0.05). BMD was not associated with the presence of BMLs. No associations were observed with calcaneus BMD. CONCLUSIONS: Site-specific BMD is associated with cartilage volume at the knee in asymptomatic young to middle-aged adults, with the direction and effects trending in the same direction. The magnitude of changes correlates with clinically relevant changes. QUS defined calcaneus BMD, showed no associations with knee structure. Although systemic factors may underlie the association between knee cartilage volume and axial/lower limb BMD, these data suggest that common local, possibly biomechanical factors may also play a role.

Overreporting of vitamin D deficiency with the Roche Elecsys Vitamin D3 (25-OH) method.

BACKGROUND: Vitamin D deficiency is common. Recently Roche Diagnostics removed their Elecsys Vitamin D3 (25OH) electrochemiluminescence immunoassay (ECLIA) from use, citing deteriorating traceability to the reference method (liquid chromatography tandem mass spectrometry; LCMSMS). We investigated the performance of the Roche assay (2 assay formulations) against an LCMSMS method and the widely used DiaSorin radioimmunoassay (RIA) method. METHODS: Two sets of samples from separate populations were assayed for vitamin D. The first set was assayed using three different methods: RIA (DiaSorin) in 2004, polyclonal ECLIA (Roche) in early 2009 and LCMSMS in early 2010. The second set was assayed using polyclonal and monoclonal ECLIA (Roche) and LCMSMS in mid-2010. RESULTS: The correlation of the polyclonal ECLIA with the RIA was poor (ECLIA = 0.45 × RIA + 19, r(2) = 0.59, n = 773). LCMSMS results correlated with RIA (RIA = 0.86 × LCMSMS + 4, r(2) = 0.69, n = 49) better than with polyclonal ECLIA (polyclonal ECLIA = 0.55 × LCMSMS + 6, r(2) = 0.62, n = 55) despite a storage interval of 6 years.In recently collected samples monoclonal and polyclonal immunoassays gave similar results (monoclonal ECLIA = 0.93 polyclonal ECLIA -3, r(2) = 0.60, n = 153). The correlation between monoclonal Roche ECLIA and LCMSMS in these samples was very poor (monoclonal ECLIA = 0.31 × LCMSMS + 23, r(2) = 0.27). CONCLUSIONS: At the time of its removal from the market, the Roche Elecsys Vitamin D3 (25OH) assay showed unacceptable performance, underestimating vitamin D levels. It seems that this bias preceded the introduction of the monoclonal assay. The worldwide distribution of the assay and the duration of this bias likely led to a significant number of patients starting supplementation unnecessarily.