Developing clinical prediction models for nonrecovery in older patients seeking care for back pain: the back complaints in the elders prospective cohort study. Issue 6 (June 2021)

• Record Type: Journal Article
• Authors: van der Gaag, Wendelien H.; Chiarotto, Alessandro; Heymans, Martijn W.; Enthoven, Wendy T.M.; van Rijckevorsel-Scheele, Jantine; Bierma-Zeinstra, Sita M.A.; Bohnen, Arthur M.; Koes, Bart W.
• Is Part Of: Pain. Volume 162:Issue 6(2021)
• Publication Date: 2021-06
• Subjects: Back pain -- Older adults -- General practice -- Family practice -- Primary care -- Prospective studies -- Cohort studies -- Clinical prediction model -- Prognostic model -- Pain -- Prognosis -- Recovery -- Model development -- Internal validation; Pain -- Periodicals; Douleur -- Périodiques; Anesthésie -- Périodiques; Pain; Electronic journals; Periodicals; Electronic journals; 616.0472
• DOI: 10.1097/j.pain.0000000000002161
• Languages: English
• ISSNs: 0304-3959

Abstract

Abstract : Abstract: Back pain is a leading cause of disability worldwide and is common in older adults. No clinical prediction models for poor long-term outcomes have been developed in older patients with back pain. This study aimed to develop and internally validate 3 clinical prediction models for nonrecovery in this population. A prospective cohort study in general practice was conducted (Back Complaints in the Elders, Netherlands), including 675 patients >55 years with a new episode of care for back pain. Three definitions of nonrecovery were used combining 6-month and 12-month follow-up data: (1) persistent back pain, (2) persistent disability, and (3) perceived nonrecovery. Sample size calculation resulted in a maximum of 14 candidate predictors that were selected from back pain prognostic literature and clinical experience. Multivariable logistic regression was used to develop the models (backward selection procedure). Models' performance was evaluated with explained variance (Nagelkerke's R 2 ), calibration (Hosmer–Lemeshow test), and discrimination (area under the curve [AUC]) measures. The models were internally validated in 250 bootstrapped samples to correct for overoptimism. All 3 models displayed good overall performance during development and internal validation (ie, R 2 > 30%; AUC > 0.77). The model predicting persistent disability performed best, showing good calibration, discrimination (AUC 0.86, 95% confidence interval 0.83-0.89; optimism-adjusted AUC 0.85), and explained variance (R 2 49%, optimism-adjusted R 2 46%). Common predictors in all models were: age, chronic duration, disability, a recent back pain episode, and patients' recovery expectations. Spinal morning stiffness and pain during spinal rotation were included in 2 of 3 models. These models should be externally validated before being used in a clinical primary care setting. Abstract : Three clinical prediction models were developed for nonrecovery in older adults seeking care for back pain; the model predicting persistent disability performed best (optimism-adjusted R 2 46%, area under the curve 0.85).