Research Paper

External validation and updating of prognostic prediction models for nonrecovery among older adults seeking primary care for back pain

Vigdal, Ørjan Nesse^a,*; Storheim, Kjersti^a,b; Killingmo, Rikke Munk^a; Rysstad, Tarjei^a; Pripp, Are Hugo^a; van der Gaag, Wendelien^c; Chiarotto, Alessandro^c; Koes, Bart^c,d; Grotle, Margreth^a,b

Author Information

^aDepartment of Rehabilitation Science and Health Technology, Faculty of Health Science, OsloMet—Oslo Metropolitan University, Oslo, Norway

^bResearch and Communication Unit for Musculoskeletal Health (FORMI), Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway

^cDepartment of General Practice, Erasmus MC, University Medical Center, Rotterdam, the Netherlands

^dCenter for Muscle and Health, University of Southern Denmark, Odense, Denmark

^*Corresponding author. Address: OsloMet—Oslo Metropolitan University, Post Box 4, St. Olavs Plass, 0130 Oslo, Norway. Tel.: +47 414 59 314. E-mail address: [email protected] (Ø. N. Vigdal).

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

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PAIN 164(12):p 2759-2768, December 2023. | DOI: 10.1097/j.pain.0000000000002974

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Prognostic prediction models for 3 different definitions of nonrecovery were developed in the Back Complaints in the Elders study in the Netherlands. The models' performance was good (optimism-adjusted area under receiver operating characteristics [AUC] curve ≥0.77, R² ≥0.3). This study aimed to assess the external validity of the 3 prognostic prediction models in the Norwegian Back Complaints in the Elders study. We conducted a prospective cohort study, including 452 patients aged ≥55 years, seeking primary care for a new episode of back pain. Nonrecovery was defined for 2 outcomes, combining 6- and 12-month follow-up data: Persistent back pain (≥3/10 on numeric rating scale) and persistent disability (≥4/24 on Roland–Morris Disability Questionnaire). We could not assess the third model (self-reported nonrecovery) because of substantial missing data (>50%). The models consisted of biopsychosocial prognostic factors. First, we assessed Nagelkerke R², discrimination (AUC) and calibration (calibration-in-the-large [CITL], slope, and calibration plot). Step 2 was to recalibrate the models based on CITL and slope. Step 3 was to reestimate the model coefficients and assess if this improved performance. The back pain model demonstrated acceptable discrimination (AUC 0.74, 95% confidence interval: 0.69-0.79), and R² was 0.23. The disability model demonstrated excellent discrimination (AUC 0.81, 95% confidence interval: 0.76-0.85), and R² was 0.35. Both models had poor calibration (CITL <0, slope <1). Recalibration yielded acceptable calibration for both models, according to the calibration plots. Step 3 did not improve performance substantially. The recalibrated models may need further external validation, and the models' clinical impact should be assessed.