Evaluation of Quantitative Computed Tomography Cortical Hip Quadrant in a Clinical Trial With Rosiglitazone: A Potential New Study Endpoint

Effects of metformin on bone mineral density and bone turnover markers: a systematic review and meta-analysis

OBJECTIVES

Metformin is associated with osteoblastogenesis and osteoclastogenesis. This study aims to investigate the impacts of metformin therapy on bone mineral density (BMD) and bone turnover markers.

DESIGN

Systematic review and meta-analysis of randomised controlled trials.

METHODS

Searches were carried out in PubMed, EMBASE, Web of science, Cochrane library, ClinicalTrials.gov from database inception to 26 September 2022. Two review authors assessed trial eligibility in accordance with established inclusion criteria. The risk of bias was assessed using the Cochrane Risk of Bias tool (RoB V.2.0). Data analysis was conducted with Stata Statistical Software V.16.0 and Review Manager Software V.5.3.

RESULTS

A total of 15 studies with 3394 participants were identified for the present meta-analysis. Our pooled results indicated that metformin had no statistically significant effects on BMD at lumbar spine (SMD=-0.05, 95% CI=-0.19 to 0.09, p=0.47, participants=810; studies=7), at femoral (MD=-0.01 g/cm2, 95% CI=-0.04 to 0.01 g/cm2, p=0.25, participants=601; studies=3) and at hip (MD=0.01 g/cm2, 95% CI=-0.02 to 0.03 g/cm2, p=0.56, participants=634; studies=4). Metformin did not lead to significant change in osteocalcin, osteoprotegerin and bone alkaline phosphatase. Metformin induced decreases in N-terminal propeptide of type I procollagen (MD=-6.09 µg/L, 95% CI=-9.38 to -2.81 µg/L, p=0.0003, participants=2316; studies=7) and C-terminal telopeptide of type I collagen (MD=-55.80 ng/L, 95% CI=-97.33 to -14.26 ng/L, p=0.008, participants=2325; studies=7).

CONCLUSION

This meta-analysis indicated that metformin had no significant effect on BMD. Metformin decreased some bone turnover markers as N-terminal propeptide of type I procollagen and C-terminal telopeptide of type I collagen. But the outcomes should be interpreted with caution due to several limitations.

Comparison of the Effects of Metformin and Thiazolidinediones on Bone Metabolism: A Systematic Review and Meta-Analysis

OBJECTIVES

Studies have shown that people with diabetes have a high risk of osteoporosis and fractures. The effect of diabetic medications on bone disease cannot be ignored. This meta-analysis aimed to compare the effects of two types of glucose-lowering drugs, metformin and thiazolidinediones (TZD), on bone mineral density and bone metabolism in patients with diabetes mellitus.

METHODS

This systematic review and meta-analysis were prospectively registered on PROSPERO, and the registration number is CRD42022320884. Embase, PubMed, and Cochrane Library databases were searched to identify clinical trials comparing the effects of metformin and thiazolidinediones on bone metabolism in patients with diabetes. The literature was screened by inclusion and exclusion criteria. Two assessors independently assessed the quality of the identified studies and extracted relevant data.

RESULTS

Seven studies involving 1656 patients were finally included. Our results showed that the metformin group had a 2.77% (SMD = 2.77, 95%CI [2.11, 3.43]; p < 0.00001) higher bone mineral density (BMD) than the thiazolidinedione group until 52 weeks; however, between 52 and 76 weeks, the metformin group had a 0.83% (SMD = -0.83, 95%CI: [-3.56, -0.45]; p = 0.01) lower BMD. The C-terminal telopeptide of type I collagen (CTX) and procollagen type I N-terminal propeptide (PINP) were decreased by 18.46% (MD = -18.46, 95%CI: [-27.98, -8.94], p = 0.0001) and 9.94% (MD = -9.94, 95%CI: [-16.92, -2.96], p = 0.005) in the metformin group compared with the TZD group.

Update on: effects of anti-diabetic drugs on bone metabolism

INTRODUCTION

Preclinical, clinical, and population-based studies have provided evidence that anti-diabetic drugs affect bone metabolism and may affect the risk of fracture in diabetic patients.

AREAS COVERED

An overview of the skeletal effects of anti-diabetic drugs used in type 2 diabetes is provided. Searches on AdisInsight, PubMed, and Medline databases were conducted up to 1^st July 2020. The latest evidence from randomized clinical trials and population-based studies on the skeletal safety of the most recent drugs (DPP-4i, GLP-1RA, and SGLT-2i) is provided.

EXPERT OPINION

Diabetic patients present with a higher risk of fracture for a given bone mineral density suggesting a role of bone quality in the etiology of diabetic fracture. Bone quality is difficult to assess in human clinical practice and the use of preclinical models provides valuable information on diabetic bone alterations. As several links have been established between bone and energy homeostasis, it is interesting to study the safety of anti-diabetic drugs on the skeleton. So far, evidence for the newest molecules suggests a neutral fracture risk, but further studies, especially in different types of patient populations (patients at risk or with history of cardiovascular disease, renal impairment, neuropathy) are required to fully appreciate this matter.

Metformin monotherapy for adults with type 2 diabetes mellitus

BACKGROUND

Worldwide, there is an increasing incidence of type 2 diabetes mellitus (T2DM). Metformin is still the recommended first-line glucose-lowering drug for people with T2DM. Despite this, the effects of metformin on patient-important outcomes are still not clarified.

OBJECTIVES

To assess the effects of metformin monotherapy in adults with T2DM.

SEARCH METHODS

We based our search on a systematic report from the Agency for Healthcare Research and Quality, and topped-up the search in CENTRAL, MEDLINE, Embase, WHO ICTRP, and ClinicalTrials.gov. Additionally, we searched the reference lists of included trials and systematic reviews, as well as health technology assessment reports and medical agencies. The date of the last search for all databases was 2 December 2019, except Embase (searched up 28 April 2017).

SELECTION CRITERIA

We included randomised controlled trials (RCTs) with at least one year's duration comparing metformin monotherapy with no intervention, behaviour changing interventions or other glucose-lowering drugs in adults with T2DM.

DATA COLLECTION AND ANALYSIS

Two review authors read all abstracts and full-text articles/records, assessed risk of bias, and extracted outcome data independently. We resolved discrepancies by involvement of a third review author. For meta-analyses we used a random-effects model with investigation of risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes, using 95% confidence intervals (CIs) for effect estimates. We assessed the overall certainty of the evidence by using the GRADE instrument.

MAIN RESULTS

We included 18 RCTs with multiple study arms (N = 10,680). The percentage of participants finishing the trials was approximately 58% in all groups. Treatment duration ranged from one to 10.7 years. We judged no trials to be at low risk of bias on all 'Risk of bias' domains. The main outcomes of interest were all-cause mortality, serious adverse events (SAEs), health-related quality of life (HRQoL), cardiovascular mortality (CVM), non-fatal myocardial infarction (NFMI), non-fatal stroke (NFS), and end-stage renal disease (ESRD). Two trials compared metformin (N = 370) with insulin (N = 454). Neither trial reported on all-cause mortality, SAE, CVM, NFMI, NFS or ESRD. One trial provided information on HRQoL but did not show a substantial difference between the interventions. Seven trials compared metformin with sulphonylureas. Four trials reported on all-cause mortality: in three trials no participant died, and in the remaining trial 31/1454 participants (2.1%) in the metformin group died compared with 31/1441 participants (2.2%) in the sulphonylurea group (very low-certainty evidence). Three trials reported on SAE: in two trials no SAE occurred (186 participants); in the other trial 331/1454 participants (22.8%) in the metformin group experienced a SAE compared with 308/1441 participants (21.4%) in the sulphonylurea group (very low-certainty evidence). Two trials reported on CVM: in one trial no CVM was observed and in the other trial 4/1441 participants (0.3%) in the metformin group died of cardiovascular reasons compared with 8/1447 participants (0.6%) in the sulphonylurea group (very low-certainty evidence). Three trials reported on NFMI: in two trials no NFMI occurred, and in the other trial 21/1454 participants (1.4%) in the metformin group experienced a NFMI compared with 15/1441 participants (1.0%) in the sulphonylurea group (very low-certainty evidence). One trial reported no NFS occurred (very low-certainty evidence). No trial reported on HRQoL or ESRD. Seven trials compared metformin with thiazolidinediones (very low-certainty evidence for all outcomes). Five trials reported on all-cause mortality: in two trials no participant died; the overall RR was 0.88, 95% CI 0.55 to 1.39; P = 0.57; 5 trials; 4402 participants). Four trials reported on SAE, the RR was 0,95, 95% CI 0.84 to 1.09; P = 0.49; 3208 participants. Four trials reported on CVM, the RR was 0.71, 95% CI 0.21 to 2.39; P = 0.58; 3211 participants. Three trial reported on NFMI: in two trials no NFMI occurred and in one trial 21/1454 participants (1.4%) in the metformin group experienced a NFMI compared with 25/1456 participants (1.7%) in the thiazolidinedione group. One trial reported no NFS occurred. No trial reported on HRQoL or ESRD. Three trials compared metformin with dipeptidyl peptidase-4 inhibitors (one trial each with saxagliptin, sitagliptin, vildagliptin with altogether 1977 participants). There was no substantial difference between the interventions for all-cause mortality, SAE, CVM, NFMI and NFS (very low-certainty evidence for all outcomes). One trial compared metformin with a glucagon-like peptide-1 analogue (very low-certainty evidence for all reported outcomes). There was no substantial difference between the interventions for all-cause mortality, CVM, NFMI and NFS. One or more SAEs were reported in 16/268 (6.0%) of the participants allocated to metformin compared with 35/539 (6.5%) of the participants allocated to a glucagon-like peptide-1 analogue. HRQoL or ESRD were not reported. One trial compared metformin with meglitinide and two trials compared metformin with no intervention. No deaths or SAEs occurred (very low-certainty evidence) no other patient-important outcomes were reported. No trial compared metformin with placebo or a behaviour changing interventions. Four ongoing trials with 5824 participants are likely to report one or more of our outcomes of interest and are estimated to be completed between 2018 and 2024. Furthermore, 24 trials with 2369 participants are awaiting assessment.

AUTHORS' CONCLUSIONS

There is no clear evidence whether metformin monotherapy compared with no intervention, behaviour changing interventions or other glucose-lowering drugs influences patient-important outcomes.

QCT of the femur: Comparison between QCTPro CTXA and MIAF Femur

QCT is commonly employed in research studies and clinical trials to measure BMD at the proximal femur. In this study we compared two analysis software options, QCTPro CTXA and MIAF-Femur, using CT scans of the semi-anthropometric European Proximal Femur Phantom (EPFP) and in vivo data from 130 Chinese elderly men and women aged 60-80 years. Integral (Int), cortical (Cort) and trabecular (Trab) vBMD, volume, and BMC of the neck (FN), trochanter (TR), inter-trochanter (IT), and total hip (TH) VOIs were compared. Accuracy was determined in the 5 mm wide central portion of the femoral neck of the EPFP. Nominal values were: cross-sectional area (CSA) 4.9 cm², cortical thickness (C.Th) 2 mm, CortBMD 723 mg/cm³ and TrabBMD 100 mg/cm³. In MIAF the so-called peeled trabecular VOI was analyzed, which excludes subcortical bone to avoid partial volume artefacts at the endocortical border that artificially increase TrabBMD. For CTXA uncorrected, so called raw cortical values were used for the analysis. QCTPro and MIAF phantom results were: CSA 5.9 cm² versus 5.1 cm²; C.Th 1.68 mm versus 1.92 mm; CortBMD 578 mg/cm³ versus 569 mg/cm³; and TrabBMD 154 mg/cm³ versus 104 mg/cm³. In vivo correlations (R²) of integral and trabecular bone parameters ranged from 0.63 to 0.96. Bland-Altman analysis for TH and FN TrabBMD showed that lower mean values were associated with higher differences, which means that TrabBMD differences between MIAF and CTXA are larger for osteoporotic than for normal patients, which can be largely explained by the inclusion of subcortical BMD in the trabecular VOI analyzed by CTXA in combination with fixed thresholds used to separate cortical from trabecular bone compartments. Correlations between CTXA corrected CortBMD and MIAF were negative, whereas raw data correlated positively with MIAF measurements for all VOIs questioning the validity of the CTXA corrections. The EPFP results demonstrated higher MIAF accuracy of cortical thickness and TrabBMD. Integral and trabecular bone parameters were highly correlated between CTXA and MIAF. Partial volume artefacts at the endocortical border artificially increased trabecular BMD by CTXA, especially for osteoporosis patients. With respect to volumetric cortical measurements with CTXA, the use raw data is recommended, because corrected data cause a negative correlation with MIAF CortBMD.

Diabetes pharmacotherapy and effects on the musculoskeletal system

Persons with type 1 or type 2 diabetes have a significantly higher fracture risk than age-matched persons without diabetes, attributed to disease-specific deficits in the microarchitecture and material properties of bone tissue. Therefore, independent effects of diabetes drugs on skeletal integrity are vitally important. Studies of incretin-based therapies have shown divergent effects of different agents on fracture risk, including detrimental, beneficial, and neutral effects. The sulfonylurea class of drugs, owing to its hypoglycemic potential, is thought to amplify the risk of fall-related fractures, particularly in the elderly. Other agents such as the biguanides may, in fact, be osteo-anabolic. In contrast, despite similarly expected anabolic properties of insulin, data suggests that insulin pharmacotherapy itself, particularly in type 2 diabetes, may be a risk factor for fracture, negatively associated with determinants of bone quality and bone strength. Finally, sodium-dependent glucose co-transporter 2 inhibitors have been associated with an increased risk of atypical fractures in select populations, and possibly with an increase in lower extremity amputation with specific SGLT2I drugs. The role of skeletal muscle, as a potential mediator and determinant of bone quality, is also a relevant area of exploration. Currently, data regarding the impact of glucose lowering medications on diabetes-related muscle atrophy is more limited, although preclinical studies suggest that various hypoglycemic agents may have either aggravating (sulfonylureas, glinides) or repairing (thiazolidinediones, biguanides, incretins) effects on skeletal muscle atrophy, thereby influencing bone quality. Hence, the therapeutic efficacy of each hypoglycemic agent must also be evaluated in light of its impact, alone or in combination, on musculoskeletal health, when determining an individualized treatment approach. Moreover, the effect of newer medications (potentially seeking expanded clinical indication into the pediatric age range) on the growing skeleton is largely unknown. Herein, we review the available literature regarding effects of diabetes pharmacotherapy, by drug class and/or by clinical indication, on the musculoskeletal health of persons with diabetes.

Practical considerations for obtaining high quality quantitative computed tomography data of the skeletal system

Quantitative CT (QCT) analysis involves the calculation of specific parameters such as bone volume and density from CT image data, and can be a powerful tool for understanding bone quality and quantity. However, without careful attention to detail during all steps of the acquisition and analysis process, data can be of poor- to unusable-quality. Good quality QCT for research requires meticulous attention to detail and standardization of all aspects of data collection and analysis to a degree that is uncommon in a clinical setting. Here, we review the literature to summarize practical and technical considerations for obtaining high quality QCT data, and provide examples of how each recommendation affects calculated variables. We also provide an overview of the QCT analysis technique to illustrate additional opportunities to improve data reproducibility and reliability. Key recommendations include: standardizing the scanner and data acquisition settings, minimizing image artifacts, selecting an appropriate reconstruction algorithm, and maximizing repeatability and objectivity during QCT analysis. The goal of the recommendations is to reduce potential sources of error throughout the analysis, from scan acquisition to the interpretation of results.