Pharmacological management of fibromyalgia: a Bayesian network meta-analysis
Filippo Migliorini, Nicola Maffulli, Jörg Eschweiler, Matthias Knobe, Markus Tingart, Giorgia Colarossi
Abstract
INTRODUCTION: The identification of the most effective therapy for patients with fibromyalgia (FM) remains controversial. Thus, we conducted a Bayesian network meta-analysis to compare several drugs employed as pharmacological management for FM. AREAS COVERED: The following databases were accessed in October 2021: PubMed, Google Scholar, Embase, and Scopus. All the randomized clinical trials (RCTs) that compare two or more pharmacological management for fibromyalgia were accessed. Only studies involving a minimum of 10 patients with a length of follow-up longer than 4 weeks were included. The data from the fibromyalgia impact questionnaire (FIQ) and the physical and mental subscales short form 36 (SF36) were extracted at last follow-up. Additionally, the number of adverse events leading to the study of discontinuation was extracted. The compounds of interests were duloxetine, pregabalin, fluoxetine, gabapentin, milnacipran, trazodone, placebo, nortriptyline, IGF-I, amitriptyline, and the combination of fluoxetine and amitriptyline, pregabalin, and trazodone. EXPERT OPINION: According to published evidence, pregabalin, and duloxetine evidenced the greatest improvement of the FIQ and SF36 Physical and Mental subscales, along with the lowest rate of adverse events leading to study discontinuation. The results must be interpreted in light of possible adverse events associated with the use of these drugs.