Navigating specific targets of psychoneurological symptom cluster in breast cancer: a computer-simulated network analysis - Report - MDSpire

Navigating specific targets of psychoneurological symptom cluster in breast cancer: a computer-simulated network analysis

  • By

  • Jiyu Cai

  • Zhao Liu

  • Xianliang Liu

  • Chunzi Wan

  • Xia Duan

  • June 26, 2026

  • 0 min

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Clinical Report: Exploring Targeted Interventions for Psychoneurological Symptoms in Breast Cancer

Overview

This study investigates the interrelationships among psychoneurological symptoms in breast cancer patients.

Background

Breast cancer is a significant global health issue, with a high prevalence of psychoneurological symptoms such as fatigue, emotional distress, sleep disturbances, and pain. These symptoms can severely impact the quality of life for patients and often persist long after treatment. Understanding the relationships among these symptoms is crucial for developing effective interventions.

Data Highlights

SymptomExpected Influence (EI)Bridge Expected Influence (bEI)
Physical Fatigue1.8831.824
Sleep Latency0.940N/A
Depression0.794N/A
PainN/A1.558
Daytime DysfunctionN/A1.331

Key Findings

  • Physical fatigue, sleep latency, and depression were identified as core symptoms in breast cancer patients.
  • Physical fatigue, pain, and daytime dysfunction were found to be bridging symptoms.
  • Computer-simulated interventions indicated that targeting depression resulted in the largest reduction in symptom scores.
  • Poor sleep efficiency was associated with an increase in total symptom scores.
  • Physical fatigue was identified as a key node within the symptom network.

Clinical Implications

Clinicians should consider the identified symptoms when developing treatment plans for breast cancer patients experiencing psychoneurological symptoms.

Conclusion

Further research is warranted to validate these findings and their impact on clinical outcomes.

Related Resources & Content

  1. The ASCO Post, 2024 -- New Computational Tool May Predict Immunotherapy Outcomes in Patients With Metastatic Breast Cancer
  2. The ASCO Post, 2020 -- ASCO20 Virtual Scientific Program: Next-Generation Oncology Highlights
  3. BMC Cancer, 2026 -- Human factors validation study of an artificial neural network‑based preoperative decision‑support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer
  4. Frontiers in Oncology, 2026 -- A network analysis of symptom clusters and core symptoms in colorectal cancer patients undergoing postoperative chemotherapy
  5. NCCN Guidelines® Insights: Distress Management, Version 1.2026 - PubMed
  6. Adult Cancer Pain, Version 2.2025, NCCN Clinical Practice Guidelines In Oncology - PubMed
  7. NCCN Guidelines® Insights: Survivorship, Version 2.2025 - PubMed
  8. Effects of cognitive-behavioral therapy for insomnia compared with controls among cancer survivors: a systematic review and meta-analysis of randomized trials - PMC
  9. A randomized controlled trial of cognitive behavioral therapy and bright light therapy for insomnia and fatigue during breast cancer treatment: SleepCaRe trial. | Journal of Clinical Oncology
  10. Effectiveness of Acupressure in Managing the Pain-Fatigue-Sleep Disturbance-Depression Symptom Cluster in Patients with Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials - PubMed
  11. Symptom network analysis in breast cancer patients: A scoping review
  12. The interplay between sleep and cancer-related fatigue in breast cancer: A casual and computer-simulated network analysis - ScienceDirect
  13. NCCN Guidelines® Insights: Distress Management, Version 1.2026 - PubMed
  14. Adult Cancer Pain, Version 2.2025, NCCN Clinical Practice Guidelines In Oncology - PubMed
  15. NCCN Guidelines® Insights: Survivorship, Version 2.2025 - PubMed
  16. Effects of cognitive-behavioral therapy for insomnia compared with controls among cancer survivors: a systematic review and meta-analysis of randomized trials - PMC
  17. A randomized controlled trial of cognitive behavioral therapy and bright light therapy for insomnia and fatigue during breast cancer treatment: SleepCaRe trial. | Journal of Clinical Oncology
  18. Effectiveness of Acupressure in Managing the Pain-Fatigue-Sleep Disturbance-Depression Symptom Cluster in Patients with Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials - PubMed
  19. Symptom network analysis in breast cancer patients: A scoping review
  20. The interplay between sleep and cancer-related fatigue in breast cancer: A casual and computer-simulated network analysis - ScienceDirect

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