Properties of SF-6D when longitudinal data from 16,398 spine surgery procedures is applied to 9 national SF-6D value sets

Background and purpose - There are several national value sets for SF-6D. For studies conducted in countries without a country-specific value set the authors may use a value set from a neighboring or culturally similar county. We evaluated the consequences of using different national value sets in SF-6D index-based outcome analyses. Patients and methods - Patients surgically treated for lumbar spinal stenosis or lumbar disk herniation between 2007 and 2017 were recruited from the national Swedish spine register. 16,398 procedures were eligible for analysis. The SF-6D health states were coded to SF-6D preference indices using value sets for 9 countries. The SF-6D index distributions were then estimated with kernel density estimation. The change in SF-6D index before and after treatment was evaluated with the standardized response mean (SRM). Results - There was a marked variability in mean and shape for the resulting SF-6D index distributions. There were considerable differences in SF-6D index distribution shape before and after treatment using the same value set. The effect sizes of 2-year change (SRM) were in most cases similar when the 9 value sets were applied on pre- and post-treatment data. Interpretation - We found a marked variability in SF-6D index distributions when a single large data set was applied to 9 national SF-6D value sets. Consequently, we recommend that SF-6D index data from studies conducted in countries without country-specific SF-6D value sets is interpreted with caution.

Automated summary

The study found that using different national value sets in SF-6D index-based outcome analyses may lead to significant variability and differences in SF-6D index distributions. There were considerable differences in SF-6D index distribution shape before and after treatment when the same value set was used. The effect sizes of 2-year change were mostly similar when 9 different national value sets were applied to pre- and post-treatment data.