Eur J Pain. 2022 Mar 9. doi: 10.1002/ejp.1937. Online ahead of print.
ABSTRACT
BACKGROUND: The objective of this study was to develop prediction models and explore the external validity of the models in a large sample of patients with chronic widespread pain (CWP) and fibromyalgia (FM).
METHODS: Patients with CWP and FM referred to rehabilitation services in Norway (n=986) self-reported data on potential predictors prior to entering rehabilitation, and self-reported outcomes at one-year follow-up. Logistic regression models of improvement, worsening and work status, and a linear regression model of health-related quality of life (HRQoL), were developed using lasso regression. Externally validated estimates of model performance were obtained from the validation set.
RESULTS: The number of participants in the development and the validation sets was 771 and 215 respectively; only participants with outcome data (n = 519-532 and 185, respectively) were included in the analyses. On average, HRQoL and work status changed little over one year. The prediction models included 10-11 predictors. Discrimination (AUC statistic) for prediction of outcome at follow-up was 0.71 for improvement, 0.67 for worsening, and 0.87 for working. The median absolute error of predictions of HRQoL was 0.36 (0.22-0.51). Reasonably good predictions of working at follow-up and HRQoL could be obtained using only the baseline scores as predictors.
CONCLUSIONS: Moderately complex predictions models (10-11 predictors) generated poor to excellent predictions of patient-relevant outcomes. Simple prediction models of working and HRQoL at follow-up may be nearly as accurate and more practical.
PMID:35263480 | DOI:10.1002/ejp.1937
