Jean Sanderson1, Marrissa Martyn-St James2, John Stevens3, Edward Goka4, Ruth Wong5, Fiona Campbell6, Peter Selby7, Neil Gittoes8, Sarah Davis9. 1. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom. Electronic address: jean.sanderson@sheffield.ac.uk. 2. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom. Electronic address: m.martyn-stjames@sheffield.ac.uk. 3. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom. Electronic address: j.w.stevens@sheffield.ac.uk. 4. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom. Electronic address: e.a.goka@sheffield.ac.uk. 5. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom. Electronic address: ruth.wong@sheffield.ac.uk. 6. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom. Electronic address: f.campbell@sheffield.ac.uk. 7. Department of Medicine, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL, United Kingdom. Electronic address: peter.selbly@manchester.ac.uk. 8. Centre for Endocrinology, Diabetes and Metabolism, University of Birmingham & University Hospitals Birmingham Health Partners, B15 2TH, United Kingdom. Electronic address: Neil.Gittoes@uhb.nhs.uk. 9. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom. Electronic address: s.davis@sheffield.ac.uk.
Abstract
OBJECTIVES: To assess the relative efficacy of bisphosphonates (alendronate, risedronate, ibandronate and zoledronic acid) for the treatment of osteoporosis using network meta-analysis (NMA). METHODS: A systematic review of the literature was conducted using PRISMA guidelines. A network meta-analysis was used to determine the relative efficacy of treatments on four fracture outcomes (vertebral, non-vertebral, hip and wrist) and percentage change in femoral neck bone mineral density (BMD). Treatment effects were modelled using an exchangeable treatment effects model. Heterogeneity in treatment effects was explored by considering potential treatment effect modifiers using meta-regression. Where appropriate, inconsistency between direct and indirect evidence was assessed using node-splitting. RESULTS: 46 randomised controlled trials (RCTs) were identified. Twenty seven RCTs provided fracture data and 35 RCTs provided BMD data for analysis. Zoledronic acid was associated with the greatest treatment effect on vertebral fractures (HR 0.41, 95% CrI: 0.28, 0.56) and percentage change in BMD (3.21, 95%: CrI 2.52, 3.86) compared to placebo. The greatest treatment effect on non-vertebral and wrist fractures was given by risedronate (HR 0.72, 95%: CrI 0.53, 0.89 and HR 0.77, 95%: CrI 0.44, 1.24, respectively). For hip fractures the greatest treatment effect was given by alendronate (HR 0.78, 95% CrI: 0.44, 1.30). CONCLUSIONS: All treatments examined were associated with beneficial effects on fractures and femoral neck BMD relative to placebo. For vertebral fractures and percentage change in femoral neck BMD the treatment effects were statistically significant for all treatments. Pairwise comparisons between treatments indicated that no active treatment was statistically significantly more effective than any other active treatment for fracture outcomes. There was some heterogeneity in treatment effects between studies suggesting differential treatment effects according to study characteristics; however, there was no evidence of differential treatment effects with respect to gender and age.
OBJECTIVES: To assess the relative efficacy of bisphosphonates (alendronate, risedronate, ibandronate and zoledronic acid) for the treatment of osteoporosis using network meta-analysis (NMA). METHODS: A systematic review of the literature was conducted using PRISMA guidelines. A network meta-analysis was used to determine the relative efficacy of treatments on four fracture outcomes (vertebral, non-vertebral, hip and wrist) and percentage change in femoral neck bone mineral density (BMD). Treatment effects were modelled using an exchangeable treatment effects model. Heterogeneity in treatment effects was explored by considering potential treatment effect modifiers using meta-regression. Where appropriate, inconsistency between direct and indirect evidence was assessed using node-splitting. RESULTS: 46 randomised controlled trials (RCTs) were identified. Twenty seven RCTs provided fracture data and 35 RCTs provided BMD data for analysis. Zoledronic acid was associated with the greatest treatment effect on vertebral fractures (HR 0.41, 95% CrI: 0.28, 0.56) and percentage change in BMD (3.21, 95%: CrI 2.52, 3.86) compared to placebo. The greatest treatment effect on non-vertebral and wrist fractures was given by risedronate (HR 0.72, 95%: CrI 0.53, 0.89 and HR 0.77, 95%: CrI 0.44, 1.24, respectively). For hip fractures the greatest treatment effect was given by alendronate (HR 0.78, 95% CrI: 0.44, 1.30). CONCLUSIONS: All treatments examined were associated with beneficial effects on fractures and femoral neck BMD relative to placebo. For vertebral fractures and percentage change in femoral neck BMD the treatment effects were statistically significant for all treatments. Pairwise comparisons between treatments indicated that no active treatment was statistically significantly more effective than any other active treatment for fracture outcomes. There was some heterogeneity in treatment effects between studies suggesting differential treatment effects according to study characteristics; however, there was no evidence of differential treatment effects with respect to gender and age.
Authors: Hai-Jun Wang; Yu Liu; Bao-Jun Zhou; Zhan-Xue Zhang; Ai-Ying Li; Ran An; Bin Yue; Li-Qiao Fan; Yong Li Journal: J Int Med Res Date: 2018-03-23 Impact factor: 1.671
Authors: Claudia Martini; Fernando Nicolas Sosa; Ricardo Malvicini; Natalia Pacienza; Gustavo Yannarelli; María Del C Vila Journal: J Physiol Biochem Date: 2021-07-24 Impact factor: 4.158