Objective: What model development and external validation studies exist that focus on the prognosis of patients with recent-onset low back pain (LBP)? What is the performance (in terms of discrimination and calibration) of these clinical prediction models?
Methods: Systematic searches on MEDLINE, Embase and CINAHL were conducted. Model development and/or external validation studies of patients with recent-onset LBP were selected. Models predicting outcomes of pain, disability, sick leave, work absence and self-reported recovery, with at least 12 weeks of follow-up, were included. Risk of bias was assessed using the PROBAST instrument.
Results: We identified 17 prognostic models developed to predict outcomes in people with recent-onset LBP: six models were in the development phase and 11 were in the validation phase. The most assessed prediction model was the Original Örebro Musculoskeletal Pain Questionnaire. The Da Silva Clinical Prediction Model was the only model, from a study with low risk of bias, that presented acceptable discrimination, demonstrating 'good' performance in predicting recovery from pain (C-statistic 0.71, 95% CI 0.63 to 0.78) and overall acceptable agreement in calibration.
Conclusion: Most prediction models for prognosis of patients with recent-onset LBP did not perform well at discrimination, few studies reported calibration and their performance varied across studies. It seems premature to advocate use of the available models, at their current state of development and validation, for low back pain in primary care, considering their generally poor methods and performance.
Registration: CRD42020160988.
Keywords: Clinical prediction model; Low back pain; Physical therapy; Prognosis; Systematic review.
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