Network analysis of the Quick Inventory of Depressive Symptomatology: Reanalysis of the STAR*D clinical trial

Manisha Madhoo, Stephen Z. Levine

Research output: Contribution to journalArticlepeer-review

Abstract

Network analysis is yet to be used to examine patient-reported symptom severity and change during citalopram treatment for major depressive disorder. We aimed to identify: (I) network systems; (II) central symptoms; and (III) network differences, in patient-reported depression for baseline, endpoint and change scores. STAR*D data during citalopram treatment were reanalyzed to examine depression based on the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR). Network analyses were computed from the QIDS-SR item-level severity scores at baseline and endpoint, and from estimated change scores based on mixed models, adjusted for confounding by dose and baseline severity. Centrality indices for each symptom were computed. Networks were contrasted for connectivity with permutation tests. Network analyses grouped symptoms consistently as: Sleep disturbances, cognitive and physical avolition, Affect and Appetite. Symptom centrality was highest for Energy at baseline, Mood at endpoint, and Mood and Concentration on change scores. Generally, permutation tests showed that the networks all significantly (p<.05) differed. Results demonstrated: (I) a replicable network group of the symptoms of depression that modestly mapped onto well-known mechanisms for depression; (II) symptoms with high centrality that may be future treatment targets (e.g., mood); and (III) that the form of the networks differed across treatment time-points, thereby contributing centrality as a possible mechanism to the initial severity debate. These findings highlight the utility of focusing on symptoms rather than total scores to understand how treatment unfolds, and tentative mechanisms.

Original languageEnglish
Pages (from-to)1768-1774
Number of pages7
JournalEuropean Neuropsychopharmacology
Volume26
Issue number11
DOIs
StatePublished - 1 Nov 2016

Bibliographical note

Funding Information:
Data used in the preparation of this manuscript were obtained from the limited access datasets distributed from the NIH-supported “Sequenced Treatment Alternatives to Relieve Depression” (STAR*D). STAR*D focused on non-psychotic major depressive disorder in adults seen in outpatient settings. The primary purpose of this research study was to determine which treatments work best if the first treatment with medication does not produce an acceptable response. The study was supported by NIMH Contract # N01MH90003 to the University of Texas Southwestern Medical Center. The ClinicalTrials.gov identifier is NCT00021528. The views in this manuscript may or may not reflect the views of the STAR*D investigators and Shire.

Funding Information:
This manuscript was part of a research grant from Shire Development LLC (grant number 45031) to author Levine at the University of Haifa.

Publisher Copyright:
© 2016 Elsevier B.V. and ECNP

Keywords

  • Citalopram
  • Major depressive disorder
  • Psychometrics
  • Psychopharmacotherapy

ASJC Scopus subject areas

  • Pharmacology
  • Neurology
  • Clinical Neurology
  • Psychiatry and Mental health
  • Biological Psychiatry
  • Pharmacology (medical)

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