Comparative responsiveness and minimal change for the Oxford Elbow Score following surgery. - Dawson, J; Doll, H; Boller, I; Fitzpatrick, R; Little, C; Rees, J; Carr, A (2008)
PURPOSE: To assess the responsiveness and minimal change for the Oxford Elbow Score (OES) using anchor- and distribution-based approaches. METHODS: A prospective observational study of 104 patients undergoing elbow surgery at a specialist orthopaedic hospital was carried out. Patients completed the OES and the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaires (both scored on a 0 to 100 scale) pre- and 6 months post-surgery. Transition items (used as anchors) assessed perceived changes following surgery. Indicators of responsiveness were the effect size; the anchor-based minimal clinically important difference (MCID) and best cut-point on the receiver operator characteristic (ROC) curve; and the distribution-based minimal detectable change (MDC). RESULTS: The three elbow-specific OES scales (Function, Pain, Social-Psychological) produced generally larger effect sizes (0.79, 1.14 and 1.18, respectively) than the upper-limb-specific DASH scale (0.76). Clear associations were observed between transition items and all OES and DASH scores (all r > |0.35|). The MCIDs for the OES Function scale and the DASH were similar (approximately 10), but were larger for the OES Pain and Social-Psychological scales (approximately 18), reflecting their lower (i.e. poorer) baseline scores and larger effect sizes. The MCIDs were, however, only consistently larger than the MDCs for the OES Pain domain. The OES Function scale and the DASH performed similarly on ROC analysis, but with the OES Pain and Social-Psychological scales demonstrating superior efficiency. CONCLUSIONS: For elbow surgery, the 12-item three-scale OES is highly responsive to 6-month post-operative outcomes, with its performance being generally better than that of the 30-item one-scale DASH. Study estimates of minimal change for the OES may be useful for informing sample size calculations and interpreting outcomes in future clinical trials.