Estimating the prognostic value of cross-sectional network connectivity for treatment response in depression.

Background: Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small-sample studies comparing single responder non-responder networks. We aimed to estimate the association between baseline network connectivity and treatment response in a large sample and benchmark its prognostic value against baseline symptom severity and variance.

Methods: = 40 518 patients receiving treatment for depression in routine care in England from 2015-2020 were analysed. Cross-sectional networks were constructed using the Patient Health Questionnaire-9 (PHQ-9) for responders and non-responders ( = 20 259 each). To conduct parametric tests investigating the contribution of PHQ-9 sum score mean and variance to connectivity differences, networks were constructed for 160 independent subsamples of responders and non-responders (80 each, = 250 per sample).

Results: The baseline non-responder network was more connected than responders (3.15 2.70, = 0.44, < 0.001), but effects were small, requiring = 750 per group to have 85% power. Parametric analyses revealed baseline network connectivity, PHQ-9 sum score mean, and PHQ-9 sum score variance were correlated ( = 0.20-0.58, all < 0.001). Both PHQ-9 sum score mean ( = -1.79, s.e. = 0.07, < 0.001), and PHQ-9 sum score variance ( = -1.67, s.e. = 0.09, < 0.001) had larger effect sizes for predicting response than connectivity ( = -1.35, s.e. = 0.12, < 0.001). The association between connectivity and response disappeared when PHQ-9 sum score variance was accounted for ( = -0.28, s.e. = 0.19, = 0.14). We replicated these results in patients completing longer treatment (8-12 weeks, = 22 952) and using anxiety symptom networks ( = 70 620).

Conclusions: The association between baseline network connectivity and treatment response may be largely due to differences in baseline score variance.