Predicting the course of persistent physical symptoms: Development and internal validation of prediction models for symptom severity and functional status during 2 years of follow-up: Development and internal validation of prediction models for symptom severity and functional status during 2 years of follow-up

Objective: Increased knowledge about predictors of the course of persistent physical symptoms (PPS) is needed to identify patients at risk for long-term PPS in clinical settings. Therefore, we developed prediction models for the course of PPS in terms of symptom-severity and related functional status during a 2-year follow-up period. Methods: We used data of the PROSPECTS cohort study, consisting of 325 PPS patients from several health care settings. Symptom severity (PHQ-15), physical functioning (RAND 36 PCS) and mental functioning (RAND 36 MCS) were assessed at baseline and 6, 12 and 24 months afterwards. We applied mixed model analyses to develop prediction models for all outcomes, using all follow-up measurements. Potential predictors were based on empirical and theoretical literature and measured at baseline. Results: For symptom severity, physical functioning and mental functioning we identified predictors for the adverse course of PPS included physical comorbidity, higher severity and longer duration of PPS at baseline, anxiety, catastrophizing cognitions, embarrassment and fear avoidance cognitions, avoidance or resting behaviour and neuroticism. Predictors of a favourable course included limited alcohol use, higher education, higher levels of physical and mental functioning at baseline, symptom focusing, damage cognitions and extraversion. Explained interpersonal variance for all three models varied between 70.5 and 76.0%. Performance of the models was comparable in primary and secondary/tertiary care. Conclusion: The presented prediction models identified several relevant demographic, medical, psychological and behavioural predictors for adverse and favourable courses of PPS. External validation of the presented models is needed prior to clinical implementation.