Patient-reported outcome measures such as the Oxford-12 Hip Score and Hip Disability and Osteoarthritis Outcome Score (HOOS) are used in daily orthopaedic practice to evaluate patients. Because different studies use different scores, it would be important to build conversion tables between scores (crosswalk) to compare the results of one study with those of another study. Various mapping methods can be used to develop crosswalk tables that convert Oxford-12 scores to the HOOS (and its derivatives, including the HOOS physical function short form, HOOS joint replacement, and HOOS-12) and vice versa. Although prior studies have investigated this issue, they are limited to short forms of the HOOS score. Consequently, they cannot be applied to hip preservation surgery and do not include quality-of-life items, whereas the Oxford-12 Hip Score is used for all hip evaluations.
We prospectively studied the Oxford-12 and HOOS and its derivatives to (1) determine which version of the HOOS has the best mapping with the Oxford-12, (2) define the most-appropriate mapping method using selected indicators, and (3) generate crosswalk tables between these two patient-reported outcome measures.
The study enrolled 500 adult patients before primary THA (59% men [294 of 500 patients]) with hip osteoarthritis or avascular necrosis of the femoral head who completed the HOOS and Oxford-12. Patients were recruited from January 2018 to September 2019 in a tertiary-care university hospital, and we included all primary THAs in patients older than 18 years with a BMI lower than 35 kg/m2 and greater than 18 kg/m2. After a minimum of 6 months of follow-up, 39% (195 of 500) of the patients were assessed using the same tools. To determine which version of the HOOS mapped best to the Oxford-12 and what the most-appropriate mapping method was, we used preoperative data from all 500 patients. Because there is no consensus on the method to establish crosswalk, various mapping methods (linear regression, tobit regression, and quantile regression) and equating methods (linear equating and equipercentile method) were applied along with cross-validation to determine which method was the most suitable and which form of the HOOS provided the best result according to different criteria (mean absolute error, r2, and Kolmogorov-Smirnov distance).To generate crosswalk tables, we created a conversion table (between the Oxford-12 and the HOOS form that was chosen after answering our first research question and the method chosen after answering our second question) using preoperative and postoperative data (n = 695). This table was meant to be simple to use and allows easy conversions from one scoring system to another.
The Oxford-12 and HOOS were strongly correlated (Pearson correlation coefficient range 0.586-0.842) for the HOOS subcategories and HOOS physical function, HOOS joint replacement, and HOOS-12. The correlation between the HOOS-12 and Oxford-12 was the strongest (r = 0.825). According to the three different criteria and five methods, the HOOS-12 was the best suited for mapping. The goal was to minimize the mean absolute error (perfect model = 0), have a Kolmogorov-Smirnov distance as close as possible to 0, and have the r2 as close as possible to 1. Regarding the most-suitable method for the crosswalk mapping (research question 2), the five methods generated similar results for the r2 (range 0.63-0.67) and mean absolute error (range 6-6.2). For the Kolmogorov-Smirnov distance, the equipercentile method was the best (Kolmogorov-Smirnov distance 0.04), with distance reduced by 43% relative to the regression methods (Kolmogorov-Smirnov distance 0.07). A graphical comparison of the predicted and observed scores showed that the equipercentile method provided perfect superposition of predicted and observed values after mapping. Finally, crosswalk tables were produced between the HOOS-12 and Oxford-12.
The HOOS-12 is the most complete and suitable form of the HOOS for mapping with the Oxford-12, while the equipercentile method is the most suitable for predicting values after mapping. This study provides clinicians with a reliable tool to crosswalk between these scores not only for joint arthroplasty but also for all types of hip surgeries while also assessing quality of life. Our findings should be confirmed in additional studies.
The resulting crosswalk tables can be used in meta-analyses, systematic reviews, or clinical practice to compare clinical studies that did not include both outcome scores. In addition, with these tools, the clinician can collect only one score while still being able to compare his or her results with those obtained in other databases and registries, and to add his or her results to other databases and joint registries.