Broad External Validation and Update of a Prediction Model for Persistent Neck Pain After 12 Weeks

Abstract

Study Design. A prospective observational study. Objective. To externally validate the prediction model developed by Schellingerhout and colleagues predicting global perceived effect at 12 weeks in patients with neck pain and to update and internally validate the updated model. Summary of Background Data. Only one prediction model for neck pain has undergone some external validation with good promise. However, the model needs testing in other populations before implementation in clinical practice. Methods. Patients with neck pain (n ¼ 773) consulting Norwegian chiropractors were followed for 12 weeks. Parameters from the original prediction model were applied to this sample for external validation. Subsequently, two random samples were drawn from the full study sample. One sample (n ¼ 436) was used to update the model; by recalibration, removing noninformative covariates, and adding new possible predictors. The updated model was tested in the other sample (n ¼ 303) using stepwise logistic regression analysis. Main outcomes for performance of models were discrimination and calibration plots. Results. Three hundred seventy patients (47%) in the full study sample reported persistent pain at 12 weeks. The performance of the original model was poor, area under the receiver operating characteristics curve was 0.55 with a Confidence Interval of 0.51-0.59. The updated model included Radiating pain to shoulder and/or elbow, education level, physical activity, consultation-type (first-time, follow-up or maintenance consultation), expected course of neck pain, previous course of neck pain, number of pain sites, and the interaction term Physical activity##Number of pain sites. The area under the receiver operating characteristics curve was 0.65 with a 95% Confidence Interval of 0.58-0.71 for the updated model. Conclusion. The predictive accuracy of the original model performed insufficiently in the sample of patients from Norwegian chiropractors and the model is therefore not recommended for that setting. Only one predictor from the original model was retained in the updated model, which demonstrated reasonable good performance predicting outcome at 12 weeks. Before considering clinical use, a new external validation is required.

Visual trajectory pattern as prognostic factors for neck pain

“…This study was part of a one-year observational cohort study on neck pain patients in chiropractic practice in Norway (Myhrvold et al, 2019). Patients can both be referred or selfreferred to chiropractic treatment and qualify for partial refund from the Norwegian healthcare system.…”

“…The association between the subgroup variable and GPE as outcome was tested by univariate logistic regression analysis and reported as odds ratios (OR) with 95% confidence interval (CI). Further, a multivariable logistic regression model was formed to test the association between GPE and a set of previously identified predictors consisting of: Radiating pain to shoulder/elbow, Education level, Consultation type, musculoskeletal comorbidity (number of MSK pain sites), Physical activity and the interaction term "number of MSK pain sites#Physical activity" (Myhrvold et al, 2019). The predictive capacity in terms of Area Under the ROC curve (AUC) of that model was compared to the AUC of the univariate model.…”

“…It is well documented that patients pain history and outcome expectations are strongly associated with prognosis for several musculoskeletal conditions (Burgess, Mansell, Bishop, Lewis, & Hill, 2020;Mallen et al, 2007;Mondloch et al, 2001;Myhrvold et al, 2019). In studies of musculoskeletal conditions, pain history is assessed traditionally as pain duration and/or number of previous episodes (Mallen et al, 2007).…”

“…Visual trajectories that illustrate patterns of pain are simple to use, both for capturing individual experience of the course of pain in the past, and for assessing individual expectations regarding the course of future pain (Dunn, Campbell, & Jordan, 2017). In a recent study, we updated a prediction model for neck pain patients by including patients' self-reported visual trajectory pattern of neck pain the previous year and the expected pattern the following year (Myhrvold et al, 2019). These two variables had stronger association with outcome than traditional measures of pain history and psychological distress in a multivariable prediction model.…”

“…These two variables had stronger association with outcome than traditional measures of pain history and psychological distress in a multivariable prediction model. However, the predictive probability of the model was most accurate in identifying people with a low chance of persistent pain (Myhrvold et al, 2019). To further improve the prediction model for neck pain, there is a need to understand the patient groups reporting the various patterns and how previous and expected pain patterns are related.…”