The Use of Botulinum Toxin A as an Adjunctive Therapy in the Management of Chronic Musculoskeletal Pain: A Systematic Review with Meta-Analysis

Simone Battista, Luca Buzzatti, Marialuisa Gandolfi, Cinzia Finocchi, Luca Falsiroli Maistrello, Antonello Viceconti, Benedetto Giardulli, Marco Testa

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
11 Downloads (Pure)

Abstract

Several studies have investigated the effect of botulinum toxin A (BoNT-A) for managing chronic musculoskeletal pain, bringing contrasting results to the forefront. Thus far, however, there has been no synthesis of evidence on the effect of BoNT-A as an adjunctive treatment within a multimodal approach. Hence, Medline via PubMed, EMBASE, and the Cochrane Library-CENTRAL were searched until November 2020 for randomised controlled trials (RCTs) that investigated the use of BoNT-A as an adjunctive therapy for chronic musculoskeletal pain. The risk of bias (RoB) and the overall quality of the studies were assessed through RoB 2.0 and the GRADE approach, respectively. Meta-analysis was conducted to analyse the pooled results of the six included RCTs. Four were at a low RoB, while two were at a high RoB. The meta-analysis showed that BoNT-A as an adjunctive therapy did not significantly decrease pain compared to the sole use of traditional treatment (SDM −0.89; 95% CI −1.91; 0.12; p = 0.08). Caution should be used when interpreting such results, since the studies displayed very high heterogeneity (I = 94%, p < 0.001). The overall certainty of the evidence was very low. The data retrieved from this systematic review do not support the use of BoNT-A as an adjunctive therapy in treating chronic musculoskeletal pain.

Original languageEnglish
Article number640
Number of pages17
JournalToxins
Volume13
Issue number9
DOIs
Publication statusPublished - Sep 2021

Fingerprint

Dive into the research topics of 'The Use of Botulinum Toxin A as an Adjunctive Therapy in the Management of Chronic Musculoskeletal Pain: A Systematic Review with Meta-Analysis'. Together they form a unique fingerprint.

Cite this