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Related Experiment Video

Updated: Jul 16, 2026

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder
05:19

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Published on: July 7, 2023

Changes in Symptom Networks During Inpatient Cancer Rehabilitation: A Retrospective Bayesian Gaussian Graphical Model

Christina Kirchhoff1, Thomas Licht2,3, Samuel Eke1

  • 1Department of Psychiatry, Psychotherapy, Psychosomatics and Medical Psychology, University Hospital of Psychiatry II, Medical University of Innsbruck, 6020 Innsbruck, Austria.

Cancers
|July 15, 2026
PubMed
Summary

Cancer rehabilitation significantly improves physical and psychological symptoms, but the underlying symptom network structure remains largely unchanged. Emotional functioning and anxiety are key targets for future network-informed interventions.

Keywords:
Bayesian networksGaussian Graphical Modelsanxietycancer survivorshipdepressionnetwork analysisoutcomestructural change

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Last Updated: Jul 16, 2026

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder
05:19

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Published on: July 7, 2023

Area of Science:

  • Oncology
  • Rehabilitation Medicine
  • Psychosocial Oncology
  • Network Science

Background:

  • Cancer survivors experience complex, interrelated physical and psychological symptoms.
  • Inpatient rehabilitation improves symptom scores, but its effect on symptom network structure is unknown.

Purpose of the Study:

  • To characterize symptom network structure in cancer survivors before and after inpatient rehabilitation.
  • To compare network topology changes and identify central treatment targets.
  • To assess the generalizability of findings across cancer types.

Main Methods:

  • Secondary analysis of electronic patient-reported outcome data from 5066 cancer survivors.
  • Utilized EORTC QLQ-C30 and Hospital Anxiety and Depression Scale (HADS) questionnaires.
  • Employed Bayesian Gaussian Graphical Models to analyze symptom networks at admission and discharge.

Main Results:

  • Significant improvements observed in all 17 symptom and functioning domains, notably emotional functioning, global health, and fatigue.
  • Emotional functioning and anxiety were the most central nodes in the symptom network.
  • Symptom network architecture remained largely stable, with 83% of connections unchanged, despite clinical improvements.

Conclusions:

  • Inpatient cancer rehabilitation leads to substantial symptom improvement while maintaining a stable underlying symptom network structure.
  • Emotional functioning and anxiety are critical, structurally central domains for network-informed rehabilitation strategies.
  • Findings offer a novel structural perspective and framework for targeted oncological rehabilitation interventions.