dc.contributor.author | Richards, Derek | |
dc.date.accessioned | 2023-11-28T10:46:48Z | |
dc.date.available | 2023-11-28T10:46:48Z | |
dc.date.issued | 2023 | |
dc.date.submitted | 2023 | en |
dc.identifier.citation | Lee, Chi Tak, Kelley, Sean W., Palacios, Jorge, Richards, Derek, Gillan, Claire M., Estimating the prognostic value of cross-sectional network connectivity for treatment response in depression, Psychological Medicine, 2023 Jun 7:1-10 | en |
dc.identifier.issn | 0033-2917 | |
dc.identifier.other | Y | |
dc.description | PUBLISHED | en |
dc.description.abstract | Background: Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small-sample studies comparing single responder v. 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: N = 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 (N = 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, n = 250 per sample).
Results: The baseline non-responder network was more connected than responders (3.15 v. 2.70, S = 0.44, p < 0.001), but effects were small, requiring n = 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 (r = 0.20-0.58, all p < 0.001). Both PHQ-9 sum score mean (β = -1.79, s.e. = 0.07, p < 0.001), and PHQ-9 sum score variance (β = -1.67, s.e. = 0.09, p < 0.001) had larger effect sizes for predicting response than connectivity (β = -1.35, s.e. = 0.12, p < 0.001). The association between connectivity and response disappeared when PHQ-9 sum score variance was accounted for (β = -0.28, s.e. = 0.19, p = 0.14). We replicated these results in patients completing longer treatment (8-12 weeks, N = 22 952) and using anxiety symptom networks (N = 70 620).
Conclusions: The association between baseline network connectivity and treatment response may be largely due to differences in baseline score variance. | en |
dc.format.extent | 1-10 | en |
dc.language.iso | en | en |
dc.relation.ispartofseries | Psychological Medicine; | |
dc.rights | Y | en |
dc.subject | Treatment response | en |
dc.subject | Treatment prognosis | en |
dc.subject | Treatment prediction | en |
dc.subject | Real-world | en |
dc.subject | Network connectivity | en |
dc.subject | Anxiety | en |
dc.subject | Centrality | en |
dc.subject | Depression | en |
dc.subject | Internet-delivered cognitive behavioural therapy | en |
dc.subject | Network analysis | en |
dc.title | Estimating the prognostic value of cross-sectional network connectivity for treatment response in depression | en |
dc.type | Journal Article | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/drichard | |
dc.identifier.rssinternalid | 259105 | |
dc.identifier.doi | http://dx.doi.org/10.1017/S0033291723001368 | |
dc.rights.ecaccessrights | openAccess | |
dc.subject.TCDTag | Clinical Psychology | en |
dc.subject.TCDTag | Psychology | en |
dc.identifier.orcid_id | 0000-0003-0871-4078 | |
dc.status.accessible | N | en |
dc.identifier.uri | http://hdl.handle.net/2262/104209 | |