Fracture risk prediction: importance of age, BMD and spine fracture status.
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ABSTRACT:
SUBMITTER: Krege JH
PROVIDER: S-EPMC3789218 | biostudies-other | 2013
REPOSITORIES: biostudies-other
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Project description:Lumbar spine bone mineral density (BMD) and trabecular bone score (TBS) are both calculated on L1-L4 vertebrae. This study investigated the ability to predict osteoporotic fractures of BMD and TBS as calculated based on all possible adjacent L1-L4 vertebrae combinations. Present findings indicate that L1-L3 is an optimal combination to calculate LS-BMD or TBS.IntroductionLumbar spine (LS) BMD and TBS are both assessed in the LS DXA scans in the same region of interest, L1-L4. We aimed to investigate the ability to predict osteoporotic fractures of all the possible adjacent LS vertebrae combinations used to calculate BMD and TBS and to evaluate if any of these combinations performs better at osteoporotic fracture prediction than the traditional L1-L4 combination.MethodsThis study was embedded in OsteoLaus-women cohort in Switzerland. LS-DXA scans were performed using Discovery A System (Hologic). The incident vertebral fractures (VFs) and major osteoporotic fractures (MOFs) were assessed from VF assessments using Genant's method or questionnaires (non-VF MOF). We ran logistic models using TBS and BMD to predict MOF, VF, and non-VF MOF, combining different adjustment factors (age, fracture level, or BMD).ResultsOne thousand six hundred thirty-two women (mean ± SD) 64.4 ± 7.5 years, BMI 25.9 ± 4.5 kg/m2, were followed for 4.4 years and 133 experienced MOF. The association of one SD decrease L1-L3 BMD with the odds ratios (ORs) of MOF was OR 1.32 (95%CI 1.15-1.53), L2-L4 BMD was 1.25 (95%CI 1.09-1.42), and L1-L4 BMD was 1.30 (95%CI 1.14-1.48). One SD decrease in L1-L3 TBS was more strongly associated with the odds of having a MOF (OR 1.64, 95% CI 1.34-2.00), than one SD decrease in L2-L4 TBS (OR 1.48, 95% CI 1.21-1.81), or in L1-L4 TBS (OR 1.60, CI 95% 1.32-1.95).ConclusionCurrent findings indicate that L1-L3 is an optimal combination for the TBS or LS-BMD calculation.
| S-EPMC9184435 | biostudies-literature
Project description:Type 2 diabetes is a risk factor for fracture independent of FRAX (fracture risk assessment) probability. We directly compared four proposed methods to improve the performance of FRAX for type 2 diabetes by: (1) including the rheumatoid arthritis (RA) input to FRAX; (2) making a trabecular bone score (TBS) adjustment to FRAX; (3) reducing the femoral neck T-score input to FRAX by 0.5 SD; and (4) increasing the age input to FRAX by 10 years. We examined major osteoporotic fractures (MOFs) and hip fractures (HFs) over a mean of 8.3 years observation among 44,543 women and men 40 years of age or older (4136 with diabetes) with baseline lumbar spine and hip DXA from 1999 through 2016. Controlled for unadjusted FRAX probability, diabetes was associated with an increased risk for MOFs and HFs. All four FRAX adjustments attenuated the effect of diabetes, but a residual effect of diabetes was seen on MOF risk after TBS adjustment, and on HF risk after the RA and TBS adjustments. Among those with diabetes, unadjusted FRAX risk underestimated MOF (observed/predicted ratio 1.15; 95% CI, 1.03 to 1.28), but this was no longer significant after applying the diabetes adjustments. HF risk was more severely underestimated (observed/predicted ratio 1.85; 95% CI, 1.51 to 2.20) and was only partially corrected with the diabetes adjustments (still significant for the RA and TBS adjustments). Among those with diabetes, there was moderate reclassification based upon a fixed MOF cut-off of 20% (4.1% to 7.1%) or fixed HF cut-off of 3% (5.7% to 16.5%). Net reclassification improvement increased for MOF with each of the diabetes adjustments (range 3.9% to 5.6% in the diabetes subgroup). In conclusion, each of the proposed methods for addressing limitations in the ability of FRAX to assess fracture risk in individuals with diabetes was found to improve performance, though no single method was optimal in all settings. © 2018 American Society for Bone and Mineral Research.
| S-EPMC6193547 | biostudies-literature
Project description:Serum proteomics analysis may lead to the discovery of novel osteoporosis biomarkers. The Osteoporotic Fractures in Men (MrOS) study comprises men ≥65 years old in the US who have had repeated BMD measures and have been followed for incident fracture. High-throughput quantitative proteomic analysis was performed on baseline fasting serum samples from non-Hispanic white men using a multidimensional approach coupling liquid chromatography, ion-mobility separation, and mass spectrometry (LC-IMS-MS). We followed the participants for a mean of 4.6 years for changes in femoral neck bone mineral density (BMD) and for incident hip fracture. Change in BMD was determined from mixed effects regression models taking age and weight into account. Participants were categorized into three groups: BMD maintenance (no decline; estimated change ≥0 g/cm2 , n = 453); expected loss (estimated change 0 to 1 SD below the estimated mean change, -0.034 g/cm2 for femoral neck, n = 1184); and accelerated loss (estimated change ≥1 SD below mean change, n = 237). Differential abundance values of 3946 peptides were summarized by meta-analysis to determine differential abundance of each of 339 corresponding proteins for accelerated BMD loss versus maintenance. Using this meta-analytic standardized fold change at cutoffs of ≥1.1 or ≤0.9 (p < 0.10), 20 proteins were associated with accelerated BMD loss. Associations of those 20 proteins with incident hip fracture were tested using Cox proportional hazards models with age and BMI adjustment in 2473 men. Five proteins were associated with incident hip fracture (HR between 1.29 and 1.41 per SD increase in estimated protein abundance). Some proteins have been previously associated with fracture risk (eg, CD14 and SHBG), whereas others have roles in cellular senescence and aging (B2MG and TIMP1) and complement activation and innate immunity (CO7, CO9, CFAD). These findings may inform development of biomarkers for future research in bone biology and fracture prediction. © 2017 American Society for Bone and Mineral Research.
| S-EPMC5489383 | biostudies-literature
Project description:In women of ages 75-80 years, a low one leg standing time (OLST) was associated with an increased risk of incident fractures, independently of bone mineral density and clinical risk factors. OLST contributed substantially to fracture probability, indicating that the test should be considered when evaluating fracture risk in older women.IntroductionPhysical function and risk of falls are important risk factors for fracture. A few previous studies have suggested that a one leg standing time (OLST) less than 10 s predicts fracture risk, but the impact of OLST, in addition to known clinical risk factors, for fracture probability is unknown. The aim of this study was to determine the independent contribution of OLST to fracture probability in older women.MethodsThe Sahlgrenska University Hospital Prospective Evaluation of Risk of Bone Fractures (SUPERB) is a prospective population-based study of 3028 women 75-80 years old, recruited from the greater Gothenburg area in Sweden. At baseline, information on risk factors was collected using questionnaires, bone mineral density was measured with dual-energy X-ray absorptiometry (DXA), and OLST was performed.ResultsDuring a median follow-up of 3.6 years (IQR 1.5 years), X-ray-verified incident fractures were identified using health records. OLST was available in 2405 women. OLST less than 10 s was associated with an increased risk for incident hip fracture (Hazard Ratio (HR) 3.02, 95% Confidence Interval (CI) [1.49-6.10]), major osteoporotic fracture (HR 95% CI 1.76 [1.34-1.46]), and nonvertebral fracture (HR 95% CI 1.61 [1.26-2.05]) in Cox regression analyses adjusted for age, height, and weight. Depending on BMD, the 4-year fracture probability increased by a factor of 1.3 to 1.5 in a 75-year-old woman with a low OLST (<10 s).ConclusionA low OLST has a substantial impact on fracture probability and should be considered when evaluating fracture risk in older women.
| S-EPMC8758616 | biostudies-literature
Project description:ObjectiveTo evaluate the association between Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD) and risk for major osteoporotic fractures (MOF) in type 1 diabetes.MethodsSubjects with type 1 diabetes and without diabetes from the 'Coronary Artery Calcification in Type 1 Diabetes' study were included. Risk for MOF was calculated using FRAX-based clinical risk factors and without BMD at visit 3 (2006-2008). Incident fractures were defined as fractures that occurred between visit 3 and visit 4 (2013-2017). Survival models were used to study the predictability of new MOF by diabetes status.Results346 type 1 diabetes (mean age 43.3 ± 9, BMI 26.4 ± 5, diabetes duration 29.4 ± 8.6 years, A1c 7.8 ± 1.1) and 411 controls (mean age 46.9 ± 9 years, BMI 26.3 ± 5 kg/m2, A1c 5.5 ± 0.4) were analyzed in this study. In unadjusted survival analysis, the FRAX score without BMD was significantly associated with MOF (HR 1.08, 95% CI: 1.04-1.13, p < 0.0001), and remained significantly associated after adjustment for age and sex (HR 1.09, 95% CI: 1.04-1.15, p = 0.0007) and type 1 diabetes (HR 1.08, 95% CI: 1.04-1.12, p = 0.0002). In the fully adjusted model (adjusted for age, sex and type 1 diabetes), the FRAX score without BMD was the only variable significantly associated with risk of MOF (HR 1.08, 95% CI: 1.02-1.14, p = 0.006).ConclusionClinical use of FRAX without BMD is useful tool in identifying adults with type 1 diabetes at higher risk for MOF risk and may help clinicians to guide therapeutic decision-making in this high fracture risk population.
| S-EPMC7770010 | biostudies-literature
Project description:ObjectiveThrough the follow-up analysis of cervical spine fracture cases with ankylosing spondylitis (AS), a treatment-oriented fracture classification method is introduced to evaluate the clinical efficacy guided by this classification method.MethodA retrospective analysis was performed on 128 AS patients who underwent comprehensive treatment in the Spine Surgery Department of Qingdao University Hospital from January 2009 to May 2018. Statistics of patient demographic data, distribution of different fractures corresponding to surgical methods, 3-year follow-up outcomes, and summary of objective fracture classification methods were analyzed. A prospective 5-year follow-up study of 90 patients with AS cervical spine fractures from June 2015 to August 2020 was also included. Statistical differences on the distribution of factors such as case information, cervical spine sagittal sequence parameters, and fracture classification were assessed. Correlations between surgical information, American Spinal Injuries Association grade (ASIA), modified Japanese Orthopaedic Association scores (mJOA), and other factors were analyzed to establish a nomogram predictive model for curative effect outcomes. Overall, three major types and the four subtypes of AS cervical spine fractures were evaluated based on the clinical efficacy of the classification and the selection of surgical treatment methods.ResultThe most common type of fracture was type II (30 cases, 33.33%), most of the subtypes were A (37 cases), followed by B (36 cases) and C (17 cases). Twenty-four of 28 patients with type I underwent anterior surgery, and 47 of 62 patients with type II and III underwent posterior surgery. The average follow-up time was 25.76 ± 11.80 months. The results of predicting clinical variables are different but include factors such as fracture type and subtype, type of operation, and age. The predictor variables include the above-mentioned similar variables, but survival is more affected by the fracture type of the patient.ConclusionThis predictive model based on follow-up information delineation points out the impact of ankylosing spondylitis cervical spine fracture classification on surgical selection and clinical efficacy.
| S-EPMC8916892 | biostudies-literature
Project description:BackgruoundSince image-based fracture prediction models using deep learning are lacking, we aimed to develop an X-ray-based fracture prediction model using deep learning with longitudinal data.MethodsThis study included 1,595 participants aged 50 to 75 years with at least two lumbosacral radiographs without baseline fractures from 2010 to 2015 at Seoul National University Hospital. Positive and negative cases were defined according to whether vertebral fractures developed during follow-up. The cases were divided into training (n=1,416) and test (n=179) sets. A convolutional neural network (CNN)-based prediction algorithm, DeepSurv, was trained with images and baseline clinical information (age, sex, body mass index, glucocorticoid use, and secondary osteoporosis). The concordance index (C-index) was used to compare performance between DeepSurv and the Fracture Risk Assessment Tool (FRAX) and Cox proportional hazard (CoxPH) models.ResultsOf the total participants, 1,188 (74.4%) were women, and the mean age was 60.5 years. During a mean follow-up period of 40.7 months, vertebral fractures occurred in 7.5% (120/1,595) of participants. In the test set, when DeepSurv learned with images and clinical features, it showed higher performance than FRAX and CoxPH in terms of C-index values (DeepSurv, 0.612; 95% confidence interval [CI], 0.571 to 0.653; FRAX, 0.547; CoxPH, 0.594; 95% CI, 0.552 to 0.555). Notably, the DeepSurv method without clinical features had a higher C-index (0.614; 95% CI, 0.572 to 0.656) than that of FRAX in women.ConclusionDeepSurv, a CNN-based prediction algorithm using baseline image and clinical information, outperformed the FRAX and CoxPH models in predicting osteoporotic fracture from spine radiographs in a longitudinal cohort.
| S-EPMC9449110 | biostudies-literature
Project description:Femoral neck bone mineral density (BMD), age plus femoral neck BMD T score, and three externally generated fracture risk tools had similar accuracy to identify older men who developed osteoporotic fractures. Risk tools with femoral neck BMD performed better than those without BMD. The externally developed risk tools were poorly calibrated. INTRODUCTION:We compared the performance of fracture risk assessment tools in older men, accounting for competing risks including mortality. METHODS:A comparative ROC curve analysis assessed the ability of the QFracture, FRAX® and Garvan fracture risk tools, and femoral neck bone mineral density (BMD) T score with or without age to identify incident fracture in community-dwelling men aged 65 years or older (N = 4994) without hip or clinical vertebral fracture or antifracture treatment at baseline. RESULTS:Among risk tools calculated with BMD, the discriminative ability to identify men with incident hip fracture was similar for FRAX (AUC 0.77, 95% CI 0.73, 0.81), the Garvan tool (AUC 0.78, 95% CI 0.74, 0.82), age plus femoral neck BMD T score (AUC 0.79, 95% CI 0.75, 0.83), and femoral neck BMD T score alone (AUC 0.76, 95% CI 0.72, 0.81). Among risk tools calculated without BMD, the discriminative ability to identify hip fracture was similar for QFracture (AUC 0.69, 95% CI 0.66, 0.73), FRAX (AUC 0.70, 95% CI 0.66, 0.73), and the Garvan tool (AUC 0.71, 95% CI 0.67, 0.74). Correlated ROC curve analyses revealed better diagnostic accuracy for risk scores calculated with BMD compared with QFracture (P < 0.0001). Calibration was good for the internally generated BMD T score predictor with or without age and poor for the externally developed risk tools. CONCLUSION:In untreated older men without fragility fractures at baseline, an age plus femoral neck BMD T score classifier identified men with incident hip fracture as accurately as more complicated fracture risk scores.
| S-EPMC5695884 | biostudies-literature
Project description:A large number of SNPs significant for osteoporosis (OP) had been identified by genome-wide association studies. However, the underlying association mechanisms were largely unknown. From the perspective of protein phosphorylation, gene expression regulation, and bone cell activity, this study aims to illustrate association mechanisms for representative SNPs of interest. We utilized public databases and bioinformatics tool to identify OP-associated SNPs which potentially influence protein phosphorylation (phosSNPs). Associations with hip/spine BMD, as well as fracture risk, in human populations for one significant phosSNP, that is, rs227584 (major/minor allele: C/A, EAS population) located in C17orf53 gene, were suggested in prior meta-analyses. Specifically, carriers of allele C had significant higher BMD and lower risk of low-trauma fractures than carriers of A. We pursued to test the molecular and cellular functions of rs227584 in bone through osteoblastic cell culture and multiple assays. We identified five phosSNPs significant for OP (P < 0.01). The osteoblastic cells, which was transfected with wild-type C17orf53 (allele C at rs227584, P126), demonstrated specific interaction with NEK2 kinase, increased expression levels of osteoblastic genes significantly (OPN, OCN, COL1A1, P < 0.05), and promoted osteoblast growth and ALP activity, in contrast to those transfected with mutant C17orf53 (allele A at rs227584, T126). In the light of the consistent evidences between the present functional study in human bone cells and the prior association studies in human populations, we conclude that the SNP rs227584, via altering protein-kinase interaction, regulates osteoblastic gene expression, influences osteoblast growth and activity, hence to affect BMD and fracture risk in humans.
| S-EPMC6349212 | biostudies-literature
Project description:PurposeA major challenge in osteoporosis is to identify individuals at high fracture risk. We investigated six bone turnover markers (BTMs) to determine association with specific fracture types; the time-frame for risk prediction and whether these are influenced by age at assessment.MethodsPopulation-based OPRA cohort (n = 1044) was assessed at ages 75, 80, 85 and fractures documented for up to 15 years. Six BTMs were analyzed at each time-point (N-terminal propeptide of type I collagen, PINP; total osteocalcin, OC; bone-specific alkaline phosphatase, BALP; C-terminal telopeptide of type I collagen, CTX; tartrate-resistant acid phosphatase 5b, TRAcP5b; urinary osteocalcin). Hazard ratios (HR) for any, major osteoporotic, vertebral and hip fractures were calculated as short (1, 2, 3 years) and long-term risk (5, 10, 15 years).ResultsAt 75 year, high CTX levels were associated with an increased risk of all fractures, including major osteoporotic fractures, across most time-frames (HRs ranging: 1.28 to 2.28). PINP was not consistently associated. Urinary osteocalcin was consistently associated with elevated short-term risk (HRs ranging: 1.83-2.72). Other BTMs were directionally in accordance, though not all statistically significant. BTMs were not predictive for hip fractures. Association of all BTMs attenuated over time; at 80 year none were associated with an increased fracture risk.ConclusionCTX, urinary OC and TRAcP5b are predictive for fracture in a 1 to 3 year, perspective, whereas in the long-term or above age 80 years, BTMs appear less valuable. Resorption markers, particularly CTX, were more consistently associated with fracture risk than formation markers in the very elderly.
| S-EPMC9395308 | biostudies-literature