Development and internal validation of prognostic models for recovery in patients with non-specific neck pain presenting in primary care

Objectives Development and internal validation of prognostic models for post-treatment and 1-year recovery in patients with neck pain in primary care. Design Prospective cohort study. Setting Primary care manual therapy practices. Participants Patients with non-specific neck pain of any duration (n = 1193). Intervention Usual care manual therapy. Outcome measures Recovery defined in terms of pain intensity, disability, and global perceived improvement directly post-treatment and at 1-year follow-up. Results All post-treatment models exhibited acceptable discriminative performance after derivation (AUC = 0.7). The developed post-treatment disability model exhibited the best overall performance (R2 = 0.24; IQR, 0.220.26), discrimination (AUC = 0.75; 95% CI, 0.630.84), and calibration (slope 0.92; IQR, 0.910.93). After internal validation and penalization, this model retained acceptable discriminative performance (AUC = 0.74). The five other models, including those predicting 1-year recovery, did not reach acceptable discriminative performance after internal validation. Baseline pain duration, disability, and pain intensity were consistent predictors across models. Conclusion A post-treatment prognostic model for disability was successfully developed and internally validated. This model has potential to inform primary care clinicians about a patients individual prognosis after treatment, but external validation is required before clinical use can be recommended. (C) 2021 The Authors. Published by Elsevier Ltd on behalf of Chartered Society of Physiotherapy. Contribution of the paper Existing prognostic models for patients with non-specific neck pain present substantial methodological shortcomings, which prevent their clinical use. We developed and internally validated prognostic models to predict recovery in patients with neck pain. The prognostic model for post-treatment disability exhibited good performance and calibration, showing promise for external validation and clinical