Predictors of treatment response trajectories to cognitive behavioral therapy for chronic fatigue syndrome: A cohort study

Background

The response to cognitive behavioral therapy (CBT) for chronic fatigue syndrome (CFS) varies greatly between patients, but predictors of treatment success remain to be elucidated. We aimed to identify patient subgroups based on fatigue trajectory during CBT, identify pre-treatment predictors of subgroup membership, and disentangle the direction of predictor – outcome relationships over time.

Methods

297 individuals with CFS were enrolled in a standardized CBT program consisting of 17 sessions, with session timing variable between participants. Self-reported levels of fatigue, depressive, anxiety, and somatic symptoms, perceived stress, and positive affect were collected pre-treatment, and after 3, 10, and 15 sessions. Latent Class Growth Analysis (LCGA) was used to identify subgroups based on fatigue trajectories and baseline predictors of group membership. Cross-lagged structural equation models were used to disentangle predictor-outcome relationships.

Results

LCGA identified four fatigue trajectory subgroups, which were labelled as “no improvement” (23 %), “weak improvement” (45 %), “moderate improvement” (23 %), and “strong improvement” (9 %) classes. Higher pre-treatment levels of depressive, anxiety, and somatic symptoms, stress, and lower levels of positive affect predicted membership of the “no improvement” subgroup. Reductions in anxiety preceded reductions in fatigue, while the depressive symptoms – fatigue relationship was bidirectional.

Conclusions

On a group level, there were statistically significant reductions in fatigue after 15 sessions of CBT, with important individual differences in treatment response. Higher pre-treatment levels of anxious, depressive, and somatic symptoms and perceived stress are predictors of lack of response, with reductions in anxiety and stress preceding improvements in fatigue.