Prediction of outcome after spinal surgery—using The Dialogue Support based on the Swedish national quality register

Abstract

Purpose To evaluate the predictive precision of the Dialogue Support, a tool for additional help in shared decision-making before surgery of the degenerative spine. Methods Data in Swespine (Swedish national quality registry) of patients operated between 2007 and 2019 found the development of prediction algorithms based on logistic regression analyses, where socio-demographic and baseline variables were included. The algorithms were tested in four diagnostic groups: lumbar disc herniation, lumbar spinal stenosis, degenerative disc disease and cervical radiculopathy. By random selection, 80% of the study population was used for the prediction of outcome and then tested against the actual outcome of the remaining 20%. Outcome measures were global assessment of pain (GA), and satisfaction with outcome. Results Calibration plots demonstrated a high degree of concordance on a group level. On an individual level, ROC curves showed moderate predictive capacity with AUC (area under the curve) values 0.67–0.68 for global assessment and 0.6–0.67 for satisfaction. Conclusion The Dialogue Support can serve as an aid to both patient and surgeon when discussing and deciding on surgical treatment of degenerative conditions in the lumbar and cervical spine. Level of evidence I.

Validating the predictive precision of the dialogue support tool on Danish patient cohorts

“…Our results show overall comparable ROC curves and AUC values with Fritzell et al. for both GA pain and satisfaction [11] . Fritzell et al.…”

“…The underlying prediction models were based on pre- and postoperative data on 77.743 patients enrolled in the Swedish national spine surgery registry from 2007 to 2019 (Swespine). Included diagnosis groups were lumbar disc herniation (LDH), lumbar spinal stenosis (LSS), lumbar degenerative disc disease (DDD) and cervical radiculopathy (CR) [11] . Swespine collects patient self-reported data on demographics, comorbidity and PROMs by questionnaires.…”

Non-respondents do not bias outcome assessment after cervical spine surgery: a multicenter observational study from the Norwegian registry for spine surgery (NORspine)

“…Registries are particularly appropriate where there is variation in provider performance and clinical practice and when provider-specific outcomes are benchmarked and compared transparently [ 16 ]. Data from registries that produce patient-specific predictors of outcomes can be utilized to develop decision support tools and thus facilitate shared decision-making between patients and providers [ 9 , 29 ]. Integration between clinical-quality registries and electronic health records entails a potential to leverage the complete experience from all previously registered cases to advise decisions about subsequent patients.…”

Does the strategic use of Big Data alter outcomes in degenerative spine surgery? A study protocol for a multicenter clinical trial testing the Swespine Dialogue Support

“…during development (7). An external validation on Danespine register data found similar AUC values for LSS (9).…”

“…The correlation between the baseline characteristics has previously been examined during the creation of the Dialogue Support (7). The relative difference between the groups will then be calculated using a multivariable logistic regression model where the GA and Satisfaction will be set as dependent variables and the covariates as independent variables together with group variable as the main effect variable.…”