Evidence map›Paper›PMID 41836223›Full record

ArticleFrontiers in oncology2026

Symptom networks in breast cancer patients during chemotherapy and their impact on daily living status.

Yuxuan Zhang, Huoling Pan, Jinyu Zhang, Fengjing Wan, Minqi Ma, Wei Zheng

Abstract read
In one paragraph

Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yuxuan ZhangSchool of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Huoling PanSchool of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Jinyu ZhangSchool of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Fengjing WanSchool of Nursing, Hainan Medical University, Haikou, China.
Minqi MaSchool of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Wei ZhengDepartment of Breast Diseases, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Few current studies explore the relationships among chemotherapy - related symptoms in breast cancer patients from different perspectives, and the link between symptoms and daily life is unclear. Objective: To construct a symptom network for breast cancer patients during chemotherapy and explore symptom - symptom relationships from multiple perspectives. Methods: The Anderson Symptom Inventory was used to collect symptom data and daily - life interference of 480 patients. R software built the symptom network, and edge - weight and centrality difference tests identified core symptom clusters. Results: The 480 female patients had a mean age of 52.46 years. Symptoms were common during chemotherapy, like fatigue and restless sleep. Fatigue was the core symptom in the overall network, but it varied among groups with different chemotherapy cycles and BMI. Distress had the greatest impact on daily life. Conclusion: Attention should be paid to psychological and emotional symptoms, and priority symptoms for intervention should be selected based on the symptom network. Future research should develop dynamic symptom networks and centrality index trajectories using longitudinal data. Implications for practice: Nurses can implement precise symptom management based on the symptom network. Meanwhile, comprehensive assessments of patients' psychological and emotional problems should be initiated from the early stage of chemotherapy, and symptom management methods should be selected according to the severity of patients' conditions to improve their psychological and emotional well - being.

Indexed as

breast cancerchemotherapydaily living statussubgroup network analysissymptom networks

Identifiers

PMID41836223
PMCPMC12982111

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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.