Return to Work in a Cohort of Low Back Pain Patients: Development and Validation of a Clinical Prediction Rule

Background From the viewpoint of cost prevention, it is necessary to identify patients that are of high risk for long-term work disability, production loss and sick-leave. Methods Secondary data analysis in a cohort of 628 workers on sick-leave between 3 and 6 weeks due to low back pain (LBP). The association of a broad set of demographic, work, LBP and psychosocial related factors on lasting return to work was studied using Cox regression analysis with backward selection. The most relevant factors were used to derive a clinical prediction rule to determine the risk of sick-leave of more than 6 months. Variable and model selection and clinical model performance were performed with bootstrapping techniques. Also the test characteristics of the clinical model were considered. Results Longer work absence is related to “moderate” to “poor” job satisfaction, a higher score of fear avoidance beliefs, higher pain intensity at baseline, a longer duration of complaints and being of female gender. Calibration and discrimination of the clinical prediction rule were 0.90 (slope) and 0.63 (c-index), respectively. The explained variance of 6% of the prediction rule was low and the clinical performance in terms of sensitivity, specificity, positive and negative predictive values at specific cut-off points was moderate. Conclusions Our study confirmed the importance of demographic, work, LBP and psychosocial related factors on the prediction of long-term sick-leave. When these factors were used to derive a clinical prediction rule the performance was moderate. As a consequence, prudence has to be taken when using the prediction rule in practice.