# A data-driven analysis of lumbar steroid injection satisfaction in patients with chronic low back pain

## TL;DR

This study uses patient data to predict satisfaction with lumbar steroid injections for chronic low back pain, identifying key factors like coping mechanisms and pain reduction thresholds.

## Contribution

A predictive framework using Random Forest and SHAP analysis to identify key predictors of treatment satisfaction in CLBP patients.

## Key findings

- A Random Forest model achieved 0.865 precision in predicting treatment satisfaction.
- Pain self-efficacy features like coping mechanisms and household activities were key predictors.
- Clinically significant pain reduction thresholds were identified at an absolute change of 2.09 and 30% relative change on the NRS.

## Abstract

Chronic low back pain (CLBP) is a prevalent condition significantly reducing quality of life. Lumbar steroid injections are a widely used conservative treatment option, but their effectiveness varies among patients. This study aimed to develop a predictive framework that integrates clinical variables and patient demographics to evaluate post-treatment pain satisfaction in CLBP patients undergoing lumbar injection therapy. We performed a retrospective analysis of 212 CLBP patients to evaluate the treatment satisfaction and pain intensity changes using the Numerical Rating Scale (NRS). A Random Forest model, validated through nested cross-validation, achieved an average precision of 0.865 in predicting treatment satisfaction. SHapley Additive exPlanations (SHAP) analysis revealed pain self-efficacy features, particularly coping mechanisms and household activities, as key outcome predictors of post-treatment pain satisfaction. Clinically significant pain reduction thresholds were identified at an absolute change of 2.09 and a relative change of 30 % on the NRS. Our findings reveal the biological and social factors influencing post-treatment pain in CLBP patients. The identified pain reduction thresholds and predictors may help clinicians to develop individualized management strategies, optimizing treatment outcomes and improving patient care. Future research should refine the predictive model by incorporating additional multimodal variables to better capture CLBP heterogeneity.