Osteoarthritis (OA) incidence continues to increase and is expected to be one of the most prevalent diseases in developed countries in the coming decades. 1 Severe pain and loss of physical function are common symptoms associated with OA and are among the leading cause of disability and time off work worldwide. 2 To date, there are no available disease-modifying treatments to revert OA, and the usual pharmacological management is limited to non-steroidal anti-inflammatory drugs (NSAIDs) that palliate its symptoms. 3 These drugs, however, have demonstrated modest benefits on pain and functional outcomes and might lead to adverse effects in elders and people with comorbidities. 3 All this, reinforce the need to investigate further pharmacological treatments that are both effective and safe against OA.
Colchicine is a medication extracted from the Colchicum autummale plant that has been used to treat ailments related to joint swelling for thousands of years. Nowadays, it is one of the main treatment options against some rheumatic diseases such as gout and familial Mediterranean fever. 4 Its anti-inflammatory effects seems promising in the treatment of OA. A systematic review and meta-analysis revealed the positive effects of Comparator/control (C): Active control or placebo control group.
Pain, physical function, imaging biomarkers (xray and/or MRI structural measures), biochemical markers, medication change, quality of life (QoL), and adverse events.
Randomised control trials, quasi-randomised, and non-randomised control trials with blinded or non-blinded design.
Scopus®, Web of Science®, Medline®, and Cochrane Library® databases will be searched for this systematic review. The abstracts of last two year s key conferences in the field of OA and rheumatology [e.g., European League Against Rheumatism (EULAR), Osteoarthritis Research Society International (OARSI), American Academy of Orthopaedic Surgeons (AAOS), and American College of Rheumatology (ACR)], as well as the reference list of included studies, and related systematic reviews and meta-analysis will be hand searched.
Scopus®, Web of Science®, Medline®, and Cochrane Library® databases will be searched using the following representative search strategy.
Population TITLE-ABS-KEY ( ( osteoarthr* OR "arthrosis" OR "artrosis" ) ) Intervention TITLE-ABS-KEY ( ( "colchicine" OR "colchicina" ) )
Population TS=(osteoarthr* OR "arthrosis" OR "artrosis") Intervention TS=("colchicine" OR "colchicina" )
All Fields (osteoarthr* OR "arthrosis" OR "artrosis") Intervention All Fields ("colchicine" OR "colchicina" )
All Text (osteoarthr* OR "arthrosis" OR "artrosis") Intervention All Text ("colchicine" OR "colchicina" )
Two reviewers will individually perform the study selection process, and any discrepancy will be resolved through discussions and consensus. The systematic review software Covidence (Veritas Health Innovation) will be used in order to facilitate the study selection process.
Relevant data of included studies will be extracted by one researcher and double-checked by a second reviewer. Information will be extracted as follow: 1) author s name and year of publication, 2) study design 3) sample size and population characteristics, 4) method used to identify/grade OA, 5) colchicine treatment (i.e., dose, administration manner, frequency, duration and follow up) 6) description of placebo/control, 7) outcomes included (e.g., pain, physical functioning, and QoL), 8) main findings.
The risk of bias of included studies will be individually tested by two researchers, according to the Cochrane Handbook for Intervention Studies guidelines. The criteria applied will be the following: 1) random sequence generation, 2) allocation concealment, 3) blinding of participants and personnel, 4) blinding of outcome assessment, 5) incomplete outcome data, 6) selection reporting, 7) attention, 8) compliance and 9) other potential sources of bias. Review Manager software (v. 5.4) will be used to guide the risk of bias assessment, and any disagreement will be resolved by the discussion with senior authors.
A meta-analysis of dichotomous (e.g., pain reduction or physical function improvement) or continuous data (e.g., mean difference in pain scale or physical function score) will be performed depending on how most studies report the data. In the case of a meta-analysis of dichotomous data, results will be summarized by means of the pooled relative risks (RR) estimate (and 95% CI interval) and number needed to treat (NNT), 7 while for the metaanalysis of continuous data, the standard mean differences (i.e., Hedges g or Cohen's d effect sizes depending on the sample size) will be used. Heterogeneity will be assessed with the Higgins I 2 statistic and p values, being classified as not important (0-40%), moderate (30-50%), substantial (50-75%), or considerable (75-100%). 8 In the presence of substantial or considerable heterogeneity (I 2 > 50%), the random-effects model will be used, while if not important or moderate heterogeneity is found (I 2 < 50%), the fixed-effects model will be used. 9 Sensitivity analyses will be performed by removing studies one at a time and testing whether the overall effect size (e.g., z-value) is significantly modified in magnitude or direction. This approach will provide information about the robustness of the synthesis of the evidence. A funnel plot and the Egger regression asymmetry test (a level of <0.10) will be used to assess publication bias. 10 In the case that ten or more studies will be included, meta-regression analysis will be performed to test how the study characteristics (e.g., sex and age of participants, colchicine dose or treatment duration) are associated with the colchicine treatment effects. Analyses will be performed using the Review Manager is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted November 20, 2020. ; https://doi.org/10.1101/2020.11.20.20226589 doi: medRxiv preprint