A Network Meta-Analysis of Randomized Controlled Trials Directed at Treating Lateral Epicondylalgia

Lateral epicondylosis is the most prevalent cause of lateral elbow pain, occurring in 4 per 1000 patients. The aim of most treatments is to reduce inflammation even with histological evidence demonstrating that lateral epicondylosis is a non-inflammatory condition. To determine the relative merits of the different regimens used to diminish lateral epicondylosis pain using a mixed treatment comparison/network meta-analysis (NMA). A thorough literature search was performed. The eligibility criteria for this mixed treatment comparison were: randomized controlled clinical trials; human subjects; working age population (16 to 70 years); the outcome measure was an objective pain assessment; measured at a 1- to 3-month follow-up. The NMA were performed using the GeMTC user interface for automated NMA utilizing a Bayesian Hierarchical Model of random effects. The evaluation of confidence in the findings from NMA was performed using a semi-automated platform called CINeMA (Confidence in Network Meta-Analysis). The model suggests that articulation technique is the most effective measure for decreasing lateral epicondylalgia followed by topical nitrates, acupuncture, kinesiology taping and low-level laser therapy, respectively. Muscle energy technique, local corticosteroid injection, prolotherapy and counterforce bracing displayed a trend toward being less effective than placebo. The results suggest that the most effective modalities for improving lateral epicondylalgia are those that decrease muscle tone and those that improve circulation, while measures meant to decrease inflammation appear to be of no or limited benefit.