Evidence map›Paper›PMID 41495551›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2026

Association of peripheral inflammatory cell counts with depression among cancer survivors: a cross-sectional study based on the NHANES dataset.

Ziwei Wang, Wenkai Wang, Chaowei Wang, Yingru Zhang, Xueqing Hu, Yuanyuan Feng, Haoran Li, Yun-Chuan Sun, Xinying He, Ling Bi and 1 more

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Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

  1. Comment on "Association of peripheral inflammatory cell counts with depression among cancer survivors: a cross-sectional study based on the NHANES dataset".Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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5 · Who and what money

Authors and funding

11 authors.

Ziwei WangDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China.
Wenkai WangDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China.
Chaowei WangDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China.
Yingru ZhangDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China.
Xueqing HuDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China.
Yuanyuan FengDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China.
Haoran LiDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China.
Yun-Chuan SunOncology Department of Cangzhou Hospital of Integrated TCM-WM, Hebei Province, 061000, China.
Xinying HeOncology Department of Cangzhou Hospital of Integrated TCM-WM, Hebei Province, 061000, China.
Ling BiDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China. ling_bi@126.com.
Yan WangDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Rd528 Zhangheng, Shanghai, 201203, China. yanwang@shutcm.edu.cn.

Funding

National Natural Science Foundation of China 82474230Shanghai Oriental Talents Program (LB), Shanghai Frontier Research Base of Disease and Syndrome Biology of Inflammatory Cancer Trans-formation 2021KJ03-12Special Funds for High-level Creative Talents Cultivation in Guizhou Province Qian Ke He XKBF (2025)027
6 · The paper itself

Abstract

backgroundDepression occur more frequently in cancer patients than in the general population. However, the association between inflammatory biomarkers and depression in cancer survivors is not well understood. This study aimed to examine the correlation between inflammatory biomarkers and depression in patients with solid tumors and to identify clinical and biological factors related to this association.

methodsThe cross-sectional cohort study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018, including 2,926 cancer survivors aged 20 years and older. Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), and inflammatory biomarkers were derived from blood count measurements. Prevalence and regression analyses were conducted to evaluate the associations between inflammatory biomarkers and depression in patients with solid tumors, and the robustness of the models was assessed through sensitivity analyses.

resultAmong the 2,926 cancer survivors, 25.80% exhibited depression, including mild (15.52%), moderate (8.95%), and severe (1.33%) cases. Patients with digestive system cancers (OR = 1.63, 95% CI: 1.18-2.24, P = 0.003) and those with reproductive system cancers (OR = 1.47, 95% CI: 1.12-1.93, P = 0.005) were significantly associated with a higher prevalence of depression. Further subgroup analysis revealed that, in colorectal cancer patients, female (OR = 2.33, 95% CI [1.15-4.74], P = 0.020), neutrophil (NE) counts above 6.4 (OR = 4.02, 95% CI [1.36-11.90], P = 0.012) and monocyte (MO) counts above 0.8 (OR = 3.21, 95% CI [1.03-10.00], P = 0.045) were positively associated with depression, whereas age under 45 years (OR = 1.826, 95% CI [1.073-3.106], P = 0.026) was associated with depression in patients with uterine tumors. In addition, sensibility analysis conducted in the subgroup of colorectal cancer patients with mild depressive symptoms indicated that the observed associations were robust.

conclusionDepression is common among cancer survivors, particularly in those with digestive and reproductive system cancers. In colorectal cancer patients, female sex and elevated neutrophil and monocyte counts were associated with higher prevalence of depression, while younger age was associated with depression in uterine cancer patients. These findings highlight the potential relevance of inflammatory biomarkers in understanding depression among cancer survivors. Future longitudinal studies are warranted to further explore the temporal and biological relationships underlying these associations.

Indexed as

Cancer SurvivorsDepressionInflammationNeoplasmsAdultAgedBiomarkersCross-Sectional StudiesFemaleHumansMaleMiddle AgedNutrition SurveysPrevalenceUnited StatesYoung AdultBiomarkersColorectal cancerDepressionNeutrophilsNHANES datasetSolid tumor

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.