Responder Criteria for Nonpharmalogical Treatment of Fibromyalgia. Save

Because of the subjective nature of fibromyalgia symptoms, tools for monitoring of disease activity and/or treatment assessment tools to evaluate effectiveness of nonpharmacological modalities are difficult to develop.
Due to the great variation in symptomatology among fibromyalgia patients, both pharmacological and nonpharmacological treatment for fibromyalgia are equally important while showing large individual variability in the long-term outcomes for fibromyalgia patients.

Responder criteria can help evaluate effectiveness of treatment and tailor to each individual patient, but no such criteria exists for nonpharmacological treatment per se.

Dr. Vervoort et al got on a mission to define responder criteria for multicomponent non-pharmacological treatment in FM.

In this project, candidate responder sets were identified in literature and tested for sensitivity and specificity in a cohort of 144 patients with FM receiving multicomponent non-pharmacological treatment. The therapist's judgement about patient's goal attainment and patients' perspective on health status change, assessed at 6 months after the start of treatment, were used as gold standard.

The groups defined 3 responder sets from the literature with the highest sensitivity and specificity. An additional 4 sets were formulated by expert group consensus: All responder criteria were defined and comprised combinations of domains of 1) pain; 2) fatigue; 3) patient global assessment (PGA); 4) illness perceptions; 5) limitations in activities of daily living (ADL); 6) sleep.

Of the literature-based responder sets, the OMERACT-OARSI responder set with patient's gold standard performed best (sensitivity 63%, specificity 75% and ROC area = 0.69). The expert-based responder set comprising the domains illness perceptions and limitations in ADL performed best (sensitivity 47%, specificity 96% and ROC area = 0.71).

Based on presented results, the group suggests further research should focus on the validation of those sets with acceptable performance.