Six Externally Validated Prognostic Models Have Potential Clinical Value to Predict Patient Health Outcomes in the Rehabilitation of Musculoskeletal Conditions: A Systematic Review

• Published in: Physical therapy Vol. 103; no. 5
• Main Authors: Naye, Florian, Décary, Simon, Houle, Catherine, LeBlanc, Annie, Cook, Chad, Dugas, Michèle, Skidmore, Becky, Tousignant-Laflamme, Yannick
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.05.2023
• Subjects: Clinical outcomes; Disabled Persons; Humans; Musculoskeletal Diseases; Outcome Assessment, Health Care; Pain; Prognosis; Rehabilitation; Systematic review; Physical Therapy Modalities; Pain; Prognosis; Musculoskeletal Pain; Rehabilitation
• ISSN: 0031-9023; 1538-6724
• DOI: 10.1093/ptj/pzad021

Abstract Objective The purpose of this systematic review was to identify and appraise externally validated prognostic models to predict a patient’s health outcomes relevant to physical rehabilitation of musculoskeletal (MSK) conditions. Methods We systematically reviewed 8 databases and reported our findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020. An information specialist designed a search strategy to identify externally validated prognostic models for MSK conditions. Paired reviewers independently screened the title, abstract, and full text and conducted data extraction. We extracted characteristics of included studies (eg, country and study design), prognostic models (eg, performance measures and type of model) and predicted clinical outcomes (eg, pain and disability). We assessed the risk of bias and concerns of applicability using the prediction model risk of bias assessment tool. We proposed and used a 5-step method to determine which prognostic models were clinically valuable. Results We found 4896 citations, read 300 full-text articles, and included 46 papers (37 distinct models). Prognostic models were externally validated for the spine, upper limb, lower limb conditions, and MSK trauma, injuries, and pain. All studies presented a high risk of bias. Half of the models showed low concerns for applicability. Reporting of calibration and discrimination performance measures was often lacking. We found 6 externally validated models with adequate measures, which could be deemed clinically valuable [ie, (1) STart Back Screening Tool, (2) Wallis Occupational Rehabilitation RisK model, (3) Da Silva model, (4) PICKUP model, (5) Schellingerhout rule, and (6) Keene model]. Despite having a high risk of bias, which is mostly explained by the very conservative properties of the PROBAST tool, the 6 models remain clinically relevant. Conclusion We found 6 externally validated prognostic models developed to predict patients’ health outcomes that were clinically relevant to the physical rehabilitation of MSK conditions. Impact Our results provide clinicians with externally validated prognostic models to help them better predict patients’ clinical outcomes and facilitate personalized treatment plans. Incorporating clinically valuable prognostic models could inherently improve the value of care provided by physical therapists.