Prediction of Oswestry Disability Index and Numeric Rating Scale scores after lumbar spine surgery: machine learning model development and fairness assessment

Background One-third of patients operated for degenerative conditions in the lumbar spine do not report substantial improvement after 12 months. Most previous outcome prediction models are classifiers.

This constrains nuances in prediction and use for decision support. Objectives To develop and test models for the prediction of continuous outcome scores and retrieval of similar patients’ outcomes, and to evaluate the models’ fairness.

Participants and data source All cases recorded with an elective operation for lumbar disc herniation (LDH, n=18 377) or lumbar spinal stenosis (LSS, n=24 540) in the Norwegian Registry for Spine Surgery from 1 January 2007 to 23 May 2023. Outcome measures All outcomes were patient-reported 12 months after the operation.

The primary outcome was the Oswestry disability index (ODI), modelled on a scale ranging from 0 to 100. Numeric Rating Scale scores (range 0–10) for back and leg pain were secondary outcomes.

Model building and performance We selected 22 predictors recorded preoperatively by patients and clinicians based on Shapley Additive Explanations values. Data were split into 80%/20% training/test samples for LDH and LSS.