Use of WOMAC for the Assessment of Treatment Benefit for the Pain of Osteoarthritis of the Knee

Article type
Authors
Woolacott N1, Corbett M1, Slack R1, Rice S1
1CRD, University of York, UK
Abstract
Background: For the purposes of meta-analysis and network meta-analysis the use of standard outcome measures is ideal. In the field of osteoarthritis research The Western Ontario and McMaster University Osteoarthris Index (WOMAC) was developed as an osteoarthritis- specific measure of disability. It comprises three components: pain, stiffness, physical function, which can be reported separately or as an overall index. In 1994 a consensus meeting recommended the use of WOMAC as a primary measure of efficacy in osteoarthritis.

Objectives: Within the context of investigating the efficacy of physical interventions for the relief of the pain of osteoarthritis of the knee (OAK), we investigated to what extent WOMAC had been adopted.

Methods: We conducted a systematic review of physical therapies for pain relief in OAK. A range of sources were systematically searched in December 2009-January 2010.

Results: A total of 138 original trials formed the basis of the review. Pain was measured using a variety of scales, with WOMAC pain scores making up 41% of the studies: pain was recorded using a WOMAC Likert scale in 29 studies and using a WOMAC visual analog scale in 28 studies. However, in many cases unexplained modifications and transformations of the WOMAC scores had been used such that comparability across trials, purportedly using the same measure, could not be assumed. Only 26 studies reported an overall WOMAC index (19%); 25 reported (some if not all) individual WOMAC subscores in addition to pain.

Conclusions: The limited use of WOMAC, coupled with the wide range of other tools used in studies in our review, was a source of heterogeneity between studies. Further standardisation of the use of the WOMAC scoring system, with improved reporting of it, in trials of OAK is required. Caution in the pooling of the different pain scales and other similar score data is needed.