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World J Psychiatry. Oct 19, 2026; 16(10): 116515
Published online Oct 19, 2026. doi: 10.5498/wjp.116515
Published online Oct 19, 2026. doi: 10.5498/wjp.116515
Toward a psychoneuroimmune interpretation of anxiety and depression risk in cervical cancer
Huan-Fang Fan, De-Hui Li, Department of Oncology II, The First Affiliated Hospital of Hebei University of Chinese Medicine (Hebei Province Hospital of Chinese Medicine), Shijiazhuang 050000, Hebei Province, China
Jia Yuan, Graduate School, Hebei University of Chinese Medicine, Shijiazhuang 050091, Hebei Province, China
De-Hui Li, Key Laboratory of Integrated Chinese and Western Medicine for Gastroenterology Research, Hebei Industrial Technology Institute for Traditional Chinese Medicine Preparation, Shijiazhuang 050000, Hebei Province, China
Co-first authors: Huan-Fang Fan and Jia Yuan.
Author contributions: Yuan J and Fan HF contributed equally to this manuscript and are co-first authors. Li DH and Fan HF designed the overall concept and outline of the manuscript; Yuan J contributed to the writing and editing of the manuscript, as well as drawing the figure; Fan HF reviewed the literature; Li DH directed and reviewed the paper. All authors have read and approved the final manuscript.
AI contribution statement: During the preparation of this manuscript, the authors used DeepSeek for supportive tasks including English language polishing, translation, and literature search and organization, in order to improve the readability and academic quality of the manuscript. It should be noted that the main text of the manuscript was independently written by the authors; AI was used solely for language-level polishing and translation, not for generative writing. All AI-assisted content was reviewed and verified word by word by the authors. The study design, data interpretation, and formulation of scientific conclusions were entirely based on the authors' professional judgment, without any AI involvement. All schematic figures in the manuscript were hand-drawn by the authors using Figdraw, and no AI-generated images were used. The authors assume full responsibility for the content and academic integrity of this manuscript.
Supported by the 2023 Government-Funded Project of the Outstanding Talents Training Program in Clinical Medicine, No. ZF2023165; Key Research and Development Projects of Hebei Province, No. 18277731D; Natural Science Foundation of Hebei Province, No. H2024423105; Hebei Provincial Administration of Traditional Chinese Medicine, Scientific Research Project, No. 2023045 and No. 2024023; Hebei Institute of Traditional Chinese Medicine Pharmaceutical Preparation Industry Technology Special Project, No. YJY2024006; and Scientific Research Project of Health Commission of Hebei Province, No. 20220962 and No. 20240282.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: De-Hui Li, Department of Oncology II, The First Affiliated Hospital of Hebei University of Chinese Medicine (Hebei Province Hospital of Chinese Medicine), No. 389 Zhongshan East Road, Chang‘an District, Shijiazhuang 050000, Hebei Province, China.
Received: November 13, 2025
Revised: January 10, 2026
Accepted: February 11, 2026
Published online: October 19, 2026
Processing time: 331 Days and 9 Hours
Revised: January 10, 2026
Accepted: February 11, 2026
Published online: October 19, 2026
Processing time: 331 Days and 9 Hours
Core Tip
Core Tip: This commentary elucidates the innovative “psycho-neuro-immune” axis mechanism underlying a predictive model for anxiety/depression in cervical cancer. The four distinct risk factors, such as advanced cancer, comprehensive therapy, low hope level, and low income level, converge via the psycho-neuro-immune axis: Physical stressors trigger an “outside-in” immune-to-brain pathway, while psychosocial stressors drive a “top-down” neuroendocrine-to-immune pathway. These pathways interact, creating a vicious cycle that sustains peripheral and central inflammation, ultimately leading to mood symptoms. This integrative framework transforms clinical risk prediction into a targetable biological model for future interventions.