Abstract
Objective
Comparison of performances of 5 (semi)automated methods in measuring joint space width (JSW) in rheumatoid arthritis.
Methods
Change in JSW was determined by 5 measurement methods on 4 radiographs per patient from 107 patients included in the COBRA trial (comparing sulfasalazine alone or in combination with methotrexate and corticosteroids). For each method the number of patients with sufficient available results was assessed (efficiency). An independent repeated measurement was carried out on a random sample of 30 patients’ baseline and 1-year radiographs, to evaluate within-method reliability of change scores. Discriminatory ability (DA) of the measurement methods (between the 2 treatment arms) was compared with the DA of the Sharp-van der Heijde score (SHS) and its 2 components (erosion and JSW scores).
Results
The overall success rate varied widely between methods. Applying the chosen threshold of a minimum of 50% available joints with a change score per patient resulted in a success rate > 92% in 4/5 methods. Repeatability of measurements was good for most methods (intraclass correlation coefficient ≥ 0.80 in 4/5 methods). Almost all measurement methods in 3 followup periods (12/14) showed a lower mean loss of JSW in patients from the intensive treatment group, although this was rarely statistically significant, confirming the known difference in structural damage. JSW as measured by the (semi)automated systems often showed higher DA than the JSW score of the SHS, but was lower than the total SHS and erosion scores.
Conclusion
Although efficiency of the methods should be improved further, results already show good reliability and encouraging DA of most methods. Optimal information may be obtained with a combination of scoring of erosions and (semi)automated measurement of JSW.
Key Indexing Terms:Footnotes
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C. Lukas, MD, Rheumatologist, Universiteit Maastricht; J.T. Sharp, MD, Affiliate Professor of Medicine, University of Washington; J. Angwin, MA, Research Associate, Biology, Respiratory and Inflammation Centre of Excellence in Drug Discovery, GlaxoSmithKline; M. Boers, MD, Professor of Medicine, Department of Clinical Epidemiology, VU University Medical Center, Amsterdam, The Netherlands; D.M.F.M. van der Heijde, MD, PhD, Professor of Rheumatology, Leiden University Medical Center; J. Duryea, PhD, Assistant Professor, Brigham and Women’s Hospital, Harvard University; J.R. Hall, Software Engineer, Snoqualmie, WA, USA; J.A. Kauffman, MSc, Signals and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente; R.B. Landewé, MD, PhD, Universiteit Maastricht; H.J. Bernelot Moens, MD, Rheumatologist, Ziekenhuis Groep Twente; P. Peloschek, MD, Department of Radiology, Vienna Medical University; G. Langs, MSc, PhD, Institute for Computer Graphics and Vision, Graz University of Technology, and Pattern Recognition and Image Processing Group, Vienna University of Technology.
- Accepted for publication February 16, 2008.
