INTRODUCTION
Cross-walking is a method of mapping scores on different patient-reported outcome instruments that measure similar domains. It requires that changes in outcomes from two measures in the same individuals should be correlated and similarly responsive to change. The Oswestry Disability Index (ODI) and the Core Outcome Measures Index (COMI) are two commonly used self-rating outcome instruments in patients with spinal disorders. However, there is currently no formal cross-walk between the two that would otherwise allow the scores of one to be interpreted in terms of the other. This study aimed to create such a cross-walk.
METHODS
We performed a secondary analysis of data from conservative and operative patients with spinal disorders, from 2 observational studies and a registry (N = 3324 patients; 57±17y; 60% female), that had completed both an ODI and COMI at baseline and 1-year follow-up (FU). Correlations between the two instruments' baseline scores, FU scores and change-scores (baseline and 1y FU) were computed, and linear regression equations were created to allow calculation of one score in terms of the other. The Cohen’s κappa for agreement (κ) was calculated with respect to achievement of the minimal clinically important change (MCIC) score on each instrument (ODI, 12.8 (Copay et al 2008) points; COMI, 2.2 points (Mannion et al 2006)). It was hypothesized that, for the cross-walk to be meaningful (Morris et al 2015), baseline, FU, and change-scores for the two instruments should be at least moderately correlated (r>0.5) and have moderately similar responsiveness (kappa >0.4 for agreement in % reaching MCIC).
RESULTS
All pairs of measures were significantly positively correlated (baseline, 0.73; 1yr FU, 0.84; change-scores, 0.73). Overall, 53.9% patients achieved MCIC based on COMI change-scores and 52.4%, based on ODI change-scores; on an individual basis, there was 78% agreement between them regarding whether MCIC had been achieved or not, with a kappa coefficient of 0.56. Regression equations for predicting ODI from COMI were: baseline, ODI=COMI x 7.1 – 4.2;  1yr FU, ODI=COMI x 6.3 + 2.7; change-scores, ODIchange = COMIchange x 5.1 + 1.9; those for predicting COMI from ODI were: baseline, COMI=ODI x 0.08 + 3.6; 1yr FU, COMI=ODI x 0.11 + 1.0; change-scores, COMIchange = ODIchange x 0.10 + 1.1). The standard errors for the regression slopes were low, but the RMSresiduals were relatively high (COMI predicting ODI, 11-14; ODI predicting COMI, 1.42-1.96) when compared with the MCICs for the instruments.
DISCUSSION
Many institutions exhibit a preference for the use of one outcome instrument over another, and have a history of data collection with their chosen instrument; the ability to share data via the developed crosswalk, to convert mean scores between the two scales, should open up more centres/registries for collaboration and facilitate the pooling of data in meta-analyses. However, caution is advised if using the conversions for individual treatment decisions, due to the relatively large individual error of prediction.

1) Copay AG et al (2008)  Spine J 8:968-974; 2) Mannion AF et al (2009) Eur Spine J 18:374-379;  3) Morris T et al (2015) Spine 40:734-739