
A network meta-analysis of osteoporotic vertebral compression fracture treatments

A network meta-analysis of osteoporotic vertebral compression fracture treatments
Comparative Efficacy and Tolerability of Three Treatments in Old People with Osteoporotic Vertebral Compression Fracture: A Network Meta-Analysis and Systematic Review
PLoS One. 2015 Apr 13;10(4):e0123153Did you know you're eligible to earn 0.5 CME credits for reading this report? Click Here
Synopsis
Five randomized controlled trials (RCT) with a total of 777 patients were included in this meta-analysis to analyze the efficacy of percutaneous vertebroplasty (PVP), balloon kyphoplasty (BK), and conservative treatment (CT) in elderly patients with an osteoporotic vertebral compression fracture. Visual analogue scale (VAS), the risk of all-cause discontinuation, and the incidence of new fractures were used to assess and compare the three treatments options. Pooled results demonstrated PVP to be more beneficial for pain relief, and BK correlated with lower risk of all-cause discontinuation, although additional, larger-scale studies longer duration follow-ups are needed for a more conclusive analysis.
Were the search methods used to find evidence (original research) on the primary question or questions stated?
Was the search for evidence reasonably comprehensive?
Were the criteria used for deciding which studies to include in the overview reported?
Was the bias in the selection of studies avoided?
Were the criteria used for assessing the validity of the included studies reported?
Was the validity of all of the studies referred to in the text assessed with use of appropriate criteria (either in selecting the studies for inclusion or in analyzing the studies that were cited)?
Were the methods used to combine the findings of the relevant studies (to reach a conclusion) reported?
Were the findings of the relevant studies combined appropriately relative to the primary question that the overview addresses?
Were the conclusions made by the author or authors supported by the data and or analysis reported in the overview?
How would you rate the scientific quality of this evidence?
Yes = 1
Uncertain = 0.5
Not Relevant = 0
No = 0
The Reporting Criteria Assessment evaluates the transparency with which authors report the methodological and trial characteristics of the trial within the publication. The assessment is divided into five categories which are presented below.
4/4
Introduction
4/4
Accessing Data
4/4
Analysing Data
4/4
Results
3/4
Discussion
Detsky AS, Naylor CD, O'Rourke K, McGeer AJ, L'Abbé KA. J Clin Epidemiol. 1992;45:255-65
The Fragility Index is a tool that aids in the interpretation of significant findings, providing a measure of strength for a result. The Fragility Index represents the number of consecutive events that need to be added to a dichotomous outcome to make the finding no longer significant. A small number represents a weaker finding and a large number represents a stronger finding.
Why was this study needed now?
Patients with osteoporosis, mainly the elderly, often suffer vertebral compression fractures. Common treatments for these fractures are percutaneous vertebroplasty (PVP), balloon kyphoplasty (BK), and conservative treatment (CT). Previous meta-analyses have been limited in the number comparisons that can be made between the three treatments and the number of trials included. As a result, there is an ongoing discussion surrounding comparative efficacy of these treatments. This network meta-analysis was synthesized to provide a hierarchy of the three treatments based on pain, the risk of all-cause discontinuation, and the incidence of new fractures.
What was the principal research question?
Which of the three treatments: percutaneous vertebroplasty (PVP), balloon kyphoplasty (BK), and conservative treatment (CT), is the most effective and tolerable treatment in elderly patients with osteoporotic vertebral compression fractures?
What were the important findings?
- A total of 5 randomized clinical trials were included in the network meta-analysis.
- Direct and indirect comparisons on visual analogue scale (VAS) scores indicated greater reduction in pain with PVP (3/5 studies; p>0.0001, p=0.028, p>0.0001) and BK (1/5 studies; p<0.0001) treatments compared to CT; according to SUCRA, PVP ranked first, BK second, and CT placed third
- Direct comparisons evaluating the risk of all-cause discontinuation were significantly lower in BK (1/5 studies; p=0.036) compared to CT; according to SUCRA, BK ranked first, PVP second, and CT was third
- Studies assessing the incidence of new fractures (36/5 studies) demonstrated no significant differences between treatments (p=0.22, 0.769, 0.065); according to SUCRA, CT had the lowest probability of new fractures, BK in second place, and PVP ranked third
- One study demonstrated PVP to be the suggested treatment when measured by cost-effectiveness
What should I remember most?
Pooled results demonstrated that PVP may be more beneficial for pain relief, and BK may demonstrate a lower risk of all-cause discontinuation in elderly osteoporotic vertebral compression fracture patients. However, definitive conclusions cannot be made based on these findings as this study was limited by the number of available trials and the number of patients included; further studies are needed to strengthen the body of evidence from which clinical decisions can be made with regards to the management of compression fractures in the elderly.
How will this affect the care of my patients?
Few clinical recommendations can be made based on the results of this research. While PVP treatment showed greater beneficial outcomes for pain relief, and BK was shown to have the lowest risk of all-cause discontinuation in elderly patients with an osteoporotic vertebral compression fracture, the overall body of evidence was limited quantity and quality. Future studies with larger and more uniform patient population are needed to combat heterogeneity and longer follow-up durations in studies are needed to examine the effects of these three management options.
Learn about our AI Driven
High Impact Search Feature

The OE High Impact metric uses AI to determine the impact a study will have by considering the content of the article itself. Built using the latest advances of natural language processing techniques. OE High Impact predicts an article’s future number of citations than impact factor alone.
Continue
Join the Conversation
Please Login or Join to leave comments.