Fracture risk in type 2 diabetic patients: A clinical prediction tool based on a large population-based cohort

A simple fragility fracture risk score for type 2 diabetes patients: a derivation, validation, comparison, and risk stratification study

OBJECTIVES

The aims of this study were to develop and validate 2 simple scores for stratification of the risks of (1) any fragility (AF) and (2) major osteoporotic fracture (MOF) in type 2 diabetes (T2D) patients; we also compared the performance of these scores with that of the Fracture Risk Assessment Tool (FRAX) and its adjustments.

DESIGN AND METHODS

In this longitudinal cohort study, 1855 patients with T2D were enrolled from January 2015 to August 2019. Cox proportional hazard regression was used to model the 5-year risk of AF and MOF. These scores were internally validated using a bootstrap resampling method of 1000.

RESULTS

During a median follow-up of 5 years, 119 (6.42%) cases of AF and 92 (4.96%) cases of MOFs were identified. Both the concordance index (C-index) and calibration plots indicated improved identification performance using the newly established scores. Furthermore, these scores also showed improved outcomes regarding the decision curve analysis (DCA) and area under the curve (AUC) compared to the widely used FRAX and its derivatives. More importantly, these scores successfully separated T2D patients into risk groups according to significant differences in fracture incidence.

CONCLUSIONS

These novel scores enable simple and reliable fracture risk stratification in T2D patients. Future work is needed to validate these findings in external cohort(s).

Prediction models of diabetes complications: a scoping review

BACKGROUND

Diabetes often places a large burden on people with diabetes (hereafter 'patients') and the society, that is, in part attributable to its complications. However, evidence from models predicting diabetes complications in patients remains unclear. With the collaboration of patient partners, we aimed to describe existing prediction models of physical and mental health complications of diabetes.

METHODS

Building on existing frameworks, we systematically searched for studies in Ovid-Medline and Embase. We included studies describing prognostic prediction models that used data from patients with pre-diabetes or any type of diabetes, published between 2000 and 2020. Independent reviewers screened articles, extracted data and narratively synthesised findings using established reporting standards.

RESULTS

Overall, 78 studies reported 260 risk prediction models of cardiovascular complications (n=42 studies), mortality (n=16), kidney complications (n=14), eye complications (n=10), hypoglycaemia (n=8), nerve complications (n=3), cancer (n=2), fracture (n=2) and dementia (n=1). Prevalent complications deemed important by patients such as amputation and mental health were poorly or not at all represented. Studies primarily analysed data from older people with type 2 diabetes (n=54), with little focus on pre-diabetes (n=0), type 1 diabetes (n=8), younger (n=1) and racialised people (n=10). Per complication, predictors vary substantially between models. Studies with details of calibration and discrimination mostly exhibited good model performance.

CONCLUSION

This rigorous knowledge synthesis provides evidence of gaps in the landscape of diabetes complication prediction models. Future studies should address unmet needs for analyses of complications n> and among patient groups currently under-represented in the literature and should consistently report relevant statistics. SCOPING REVIEW REGISTRATION: https://osf.io/fjubt/.

Bone fragility in diabetes: novel concepts and clinical implications

Increased fracture risk represents an emerging and severe complication of diabetes. The resulting prolonged immobility and hospitalisations can lead to substantial morbidity and mortality. In type 1 diabetes, bone mass and bone strength are reduced, resulting in up to a five-times greater risk of fractures throughout life. In type 2 diabetes, fracture risk is increased despite a normal bone mass. Conventional dual-energy x-ray absorptiometry might underestimate fracture risk, but can be improved by applying specific adjustments. Bone fragility in diabetes can result from cellular abnormalities, matrix interactions, immune and vascular changes, and musculoskeletal maladaptation to chronic hyperglycaemia. This Review summarises how the bone microenvironment responds to type 1 and type 2 diabetes, and the mechanisms underlying fragility fractures. We describe the value of novel imaging technologies and the clinical utility of biomarkers, and discuss current and future therapeutic approaches that protect bone health in people with diabetes.

Bone fragility in patients with diabetes mellitus: A consensus statement from the working group of the Italian Diabetes Society (SID), Italian Society of Endocrinology (SIE), Italian Society of Gerontology and Geriatrics (SIGG), Italian Society of Orthopaedics and Traumatology (SIOT)

Bone fragility is one of the possible complications of diabetes, either type 1 (T1D) or type 2 (T2D). Bone fragility can affect patients of different age and with different disease severity depending on type of diabetes, disease duration and the presence of other complications. Fracture risk assessment should be started at different stages in the natural history of the disease depending on the type of diabetes and other risk factors. The risk of fracture in T1D is higher than in T2D, imposing a much earlier screening and therapeutic intervention that should also take into account a patient's life expectancy, diabetes complications etc. The therapeutic armamentarium for T2D has been enriched with drugs that may influence bone metabolism, and clinicians should be aware of these effects. Considering the complexity of diabetes and osteoporosis and the range of variables that influence treatment choices in a given individual, the Working Group on bone fragility in patients with diabetes mellitus has identified and issued recommendations based on the variables that should guide screening of bone fragility and management of diabetes and bone fragility: (A)ge, (B)MD, (C)omplications, (D)uration of disease, & (F)ractures (ABCD&F). Consideration of these parameters may help clinicians identify the best time for screening, the appropriate glycaemic target and anti-osteoporosis drug for patients with diabetes at risk of or with bone fragility.

Bone Turnover Markers Do Not Predict Fracture Risk in Type 2 Diabetes

Type 2 diabetes (T2D) is characterized by increased fracture risk despite higher BMD and reduced bone turnover. BMD underestimates fracture risk in T2D, but the predictive role of bone turnover markers (BTMs) on fracture risk in T2D has not been explored. Thus, we sought to determine whether BTMs predict incident fractures in subjects with T2D. For this case-cohort study, we used data from the Health, Aging, and Body Composition (Health ABC) Study of well-functioning older adults, aged 70 to 79 years at baseline (April 1997-June 1998). The case-cohort sample consisted of (i) the cases, composed of all 223 participants who experienced incident fractures of the hip, clinical spine, or distal forearm within the first 9 years of study follow-up; and (ii) the subcohort of 508 randomly sampled participants from three strata at baseline (T2D, prediabetes, and normoglycemia) from the entire Health ABC cohort. A total of 690 subjects (223 cases, of whom 41 were in the subcohort) were included in analyses. BTMs (C-terminal telopeptide of type I collagen [CTX], osteocalcin [OC], and procollagen type 1 N-terminal propeptide [P1NP]) were measured in archived baseline serum. Cox regression with robust variance estimation was used to estimate the adjusted hazard ratio (HR) for fracture per 20% increase in BTMs. In nondiabetes (prediabetes plus normoglycemia), fracture risk was increased with higher CTX (HR 1.10; 95% confidence interval [CI], 1.01 to 1.20 for each 20% increase in CTX). Risk was not increased in T2D (HR 0.92; 95% CI, 0.81 to 1.04; p for interaction .045). Similarly, both OC and P1NP were associated with higher risk of fracture in nondiabetes, but not in T2D, with p for interaction of .078 and .109, respectively. In conclusion, BTMs did not predict incident fracture risk in T2D but were modestly associated with fracture risk in nondiabetes. © 2020 American Society for Bone and Mineral Research.

Correlation Between Serum miR-154-5p and Osteocalcin in Males and Postmenopausal Females of Type 2 Diabetes With Different Urinary Albumin Creatinine Ratios

Purpose: To investigate the serum levels of miR-154-5p, osteocalcin (OC), and other clinical parameters in male and post-menopausal female type 2 diabetes mellitus (T2DM) patients with different urinary albumin creatinine ratio (UACR) levels and to discuss the relationship between miR-154-5p and glycolipid metabolism, bone metabolism, and different urinary albumin excretion rate in T2DM. Methods: Seven hundred thirty-eight T2DM patients were categorized into six groups, including 374 men and 364 post-menopausal women who were sub-divided into three groups based on albumin excretion that involved normal albuminuria, microalbuminuria, and large amount of albuminuria (138, 127, 109, 135, 125, and 104 cases, UACR<30, 30-300, and >300 mg/g, M1, M2, M3, F1, F2, and F3). Measurement of circulating miR-154-5p, OC, and other biochemical indicators were performed by real-time PCR, ELISA, and chemiluminescence assays in T2DM patients and in 141 M0 and 139 F0 control subjects. Results: There are few differences appeared between groups. Comparing with men, women had higher age, waist-to-hip ratio (WHR), adiponectin (ADPN), connective tissue growth factor (CTGF), UACR, procollagen type 1 N-terminal propeptide (P1NP), β-C-terminal telopeptide of type I collagen (β-CTx), OC, and miR-154-5p, but lower FPG, HOMA-IR, and HbA1c. T2DM patients with albuminuria (micro or macro) had lower bone turnover markers (P1NP, β-CTx, and OC) and adiponectin, but higher HbA1c, CTGF, and miR-154-5p. In addition, after regression analysis, UACR was positively correlated with CTGF, HbA1c, and miR-154-5p, and negatively correlated with ADPN and bone turnover markers (P1NP, β-CTx, and OC). However, OC showed a positive correlation with ADPN and other bone turnover markers (P1NP and β-CTx), but negative correlation with CTGF, UACR, and miR-154-5p in all three groups. Conclusion: These findings suggested that increased serum levels of miR-154-5p and decreased OC levels may influence osteogenesis and proteinuria in T2DM and may identify novel targets for diagnosis and treatment of diabetic kidney disease and osteoporosis.