Clinical risk factors for fracture risk prediction in patients with type 2 diabetes using adjusted FRAX / 中华内分泌外科杂志

Objective:To study the clinical risk factors for osteoporotic fracture (OF) risk prediction in patients with type 2 diabetes mellitus (T2DM) using adjusted fracture risk assessment tool (FRAX) .Methods:A cross-sectional study of 429 patients with T2DM who were hospitalized in the Department of Endocrinology and Geriatrics of the Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University from Sep. 2019 to Sep. 2020 was conducted. Participants were divided into OF low-risk group and OF high-risk group. Participant characteristics (age, gender, height, weight, waist, blood pressure, history of drug treatment, serum glucose, glycosylated hemoglobin, total cholesterol, low-density lipoprotein cholesterol (LDL-C) , high-density lipoprotein cholesterol (HDL-C) , triglyceride, serum uric acid, alkaline phosphatase, and thyroid stimulating hormone levels, urine protein/creatinine ratio, urea, creatinine and TPOAB) and dual energy x-ray absorptiometry results were obtained and analyzed. Logistic regression model was used to investigate the relationship between the OF risk of T2DM assessed by adjusted FRAX and clinical risk factors.Results:Patients in the OF high-risk group accounted for 9.09% of the subjects. After adjustment for other variables, the duration of diabetes was still positively associated with significantly elevated risk of OF assessed by adjusted FRAX ( OR 7.660, 95% CI 1.661-35.334, P=0.009) , whereas the blood uric acid was negatively associated with significantly elevated risk of OF assessed by adjusted FRAX ( OR 0.345, 95 % CI 0.128-0.928, P=0.035) .Likewise, LDL-C levels decreased the odds of the risk of OF assessed by adjusted FRAX ( OR 0.316, 95 % CI 0.114-0.881, P=0.028) . There was no significant relationship between alkaline phosphatase ( OR 1.902, 95 % CI 0.904-4.004, P=0.090) as well as total cholesterol ( OR 0.297, 95% CI 0.056~1.560, P=0.151) levels and the elevated risk of OF assessed by adjusted FRAX. Conclusion:Diabetes duration could be a risk factor for OF risk prediction in patients with T2DM using adjusted FRAX, and serum uric acid and LDL-C could be protective factors for OF risk prediction in patients with T2DM using adjusted FRAX.

Unadjusted and adjusted fracture risk assessment tool and the hip fracture risk in patients with type 2 diabetes / 中华内分泌代谢杂志

Objective:To evaluate and compare the clinical value of unadjusted fracture risk assessment tool(FRAX) and adjusted FRAX in predicting the risk of hip fracture in patients with type 2 diabetes(T2DM).Methods:In this 10-year retrospective cohort study, 1 730 patients with T2DM were collected from August 2009 to July 2013. The 10-year risk of hip fracture was calculated using the China FRAX model. Hip fracture events during the follow-up period were collected through electronic medical records and telephone interviews. The value of FRAX and adjusted FRAX in predicting the risk of hip fracture in T2DM patients was evaluated from two aspects of discrimination and calibration. Cox regression model was used to investigate the relationship between diabetes related factors and hip fracture.Results:A total of 39 participants(2.3%) experienced hip fracture during a median follow-up of 10 years. The area under the curve of unadjusted FRAX was 0.760, but the calibration ability was poor [calibration χ2: 75.78, P<0.001; calibration ratio(observation/prediction): 3.97(95% CI 2.76~5.17)]. There was no significant improvement in calibration ability of adjusted FRAX. After adjustment for unadjusted or adjusted hip fracture probability calculated by FRAX(FRAX-HF), duration, estimated glomerular filtration rate, insulin use, cerebrovascular diseases, and diabetic peripheral neuropathy were significantly associated with an increased risk of hip fracture( P<0.05). Conclusion:The FRAX tool significantly underestimated the risk of hip fracture in T2DM patients, and there was still significantly underestimation after adjustment due to the failure to eliminate the influence of diabetes-related factors such as disease duration and peripheral neuropathy.

Patients Risk Stratification in the Management of Osteoporosis: the Latest International Guidelines

@#Assessment of risk of a fragility fracture is a vital step a physician needs to undertake in every patient suspected of osteoporosis, as this will influence the decisions on whether to treat with a pharmacological agent, with which drug, and for how long. After risk stratification, patients deemed Very High-Risk should be considered for an anabolic agent, or if this is not feasible, a parenteral anti-resorptive. High- Risk or Moderate-Risk patients may be considered for oral bisphosphonates.

Advances in Predicting Fracture Risk Based on Hip Bone Properties / 医用生物力学

With the increasing life span of the population and the increasing proportion of the elderly population, the elderly with osteoporosis are prone to hip fractures, which brings heavy economic burdens to the family and society. The progress in predicting hip fractures from the aspects of the proximal femur geometry, bone mineral density (BMD), fracture risk assessment tool (FRAX) and finite element analysis (FEA) based on computed tomography (CT) imaging was reviewed, in order to understand the influencing factors of fracture risk, improve the accuracy of hip fracture risk prediction for the elderly, detect the high fracture risk group at an early stage, and hence to reduce the occurrence of fractures with appropriate preventing measures, and provide theoretical references for the prevention and treatment of hip fractures.

Individualized fracture risk assessment: State-of-the-art and room for improvement

Fragility fracture is a serious clinical event, because it is associated with increased risk of mortality and reduced quality of life. The risk of fracture is determined by multiple risk factors, and their effects may be interactional. Over the past 10 years, a number of predictive models (e.g., FRAX, Garvan Fracture Risk Calculator, and Qfracture) have been developed for individualized assessment of fracture risk. These models use different risk profiles to estimate the probability of fracture over 5- and 10-year period. The ability of these models to discriminate between those individuals who will and will not have a fracture (i.e., area under the receiver operating characteristic curve [AUC]) is generally acceptable-to-good (AUC, 0.6 to 0.8), and is highly variable between populations. The calibration of existing models is poor, particularly in Asian populations. There is a strong need for the development and validation of new prediction models based on Asian data for Asian populations. We propose approaches to improve the accuracy of existing predictive models by incorporating new markers such as genetic factors, bone turnover markers, trabecular bone score, and time-variant factors. New and more refined models for individualized fracture risk assessment will help identify those most likely to sustain a fracture, those most likely to benefit from treatment, and encouraging them to modify their risk profile to decrease risk.

Feasibility of FRAX for Prediction of Osteoporotic Vertebral Fractures in Korea

STUDY DESIGN: Retrospective study. PURPOSE: To assess the feasibility and limitations of fracture risk assessment tool (FRAX) for osteoporotic vertebral fractures in the Korean population. OVERVIEW OF LITERATURE: The FRAX algorithm is country specific and uses clinical risk factor data to calculate an individual patient's 10-year probability of hip fracture and 10-year probability of major osteoporotic fracture. However, it has not been adequately investigated for Korean. METHODS: One hundred ninety four patients who had all risk factor data for the calculation of FRAX were divided into two groups depending on the existence of vertebral fractures: the fracture group was comprised of 88 patients and the non-facture group comprised of 105 patients. We analyzed prediction of the fracture by applying respectively the Korean, Japanese, USA and UK model, and compared their FRAX results by calculating lumbar bone mineral density (BMD) instead of femoral neck BMD. RESULTS: The prediction of vertebral fracture using FRAX was 10.9 +/- 6.2% in the fracture group, 9.5 +/- 5.5% of the non-fracture group in the Korean model (p = 0.108); 17.9 +/- 10.2% in the fracture group, 14.6 +/- 9.0% in the non-fracture group in the Japanese model (p = 0.017). Only the Japanese model exhibited significant difference in vertebral fracture risk. The prediction of vertebral fracture using lumbar BMD instead of femoral neck BMD was 19.5 +/- 12.1% in the fracture group, 16.0 +/- 10.3% in the non-fracture group in the Korean model (p = 0.029). All models had statistically significant differences for the prediction of osteoporotic vertebral fracture. CONCLUSIONS: The 10-year probability of osteoporotic vertebral fracture had underestimation of the risk considering treatment eligibility based on the National Osteoporosis Foundation guidelines. BMD that accurately reflects the contribution of each result to fracture risk should be preferred for the prediction of fracture using FRAX, when lumbar spine and hip BMD measurements are both performed for clinical purposes in Korean.

Osteoporosis Medication Treatment Thresholds for Patients with a Distal Radius Fracture as Determined using Bone Mineral Density and the Fracture Risk Assessment Tool

OBJECTIVE: To compare the treatment thresholds for osteoporosis medication based on bone mineral density (BMD) results and fracture risk assessment tool (FRAX) risks in patients with a distal radius fracture. METHODS: The data of 116 consecutive women aged 50~89 years (mean 64.5 years) with a distal radius fracture were collated to identify clinical risk factors, which were inserted into the FRAX algorithm to calculate 10-year fracture risks. Proportions of patients indicated for osteoporosis medication based on BMD alone and based on FRAX risks were determined. Sensitivity estimation was done with FRAX plus BMD as a gold standard measurement for osteoporosis treatment. RESULTS: Of the 116 patients, 38% needed osteoporosis medication based on BMD alone, and 41% were indicated for treatment based on FRAX plus BMD. These proportions were not significantly different (P = 0.481). However, 56% of patients were indicated for treatment based on FRAX excluding BMD, which was significantly larger than the proportion determined by BMD alone (P = 0.001) or FRAX plus BMD (P = 0.003). Sensitivity, specificity, positive predictive value, negative predictive value for BMD alone were 75%, 93%, 90%, 82% and those for FRAX without BMD were 83%, 70%, 69%, 84%. CONCLUSION: No difference was found in the proportion of patients that need osteoporosis medication based on BMD results alone and FRAX plus BMD risks, suggesting BMD measurement can be sufficient to detect candidates for osteoporosis medication in patients with a distal radius fracture. FRAX excluding BMD may include too many patients that do not need osteoporosis treatment.