Evidence map›Paper›PMID 41699534›Full record

ArticleBMC cancer2026

Chemotherapy-related symptoms in colorectal cancer patients: A latent profile analysis.

Wangjie Xia, Zhen Luo, Shengnan Shan, Jing Chen, Daoxia Guo, Li Tian

Abstract read
In one paragraph

Article in BMC cancer, 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. Article
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.

Wangjie Xia *First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Zhen Luo *First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Shengnan ShanFirst Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Jing ChenSchool of Nursing, Suzhou Medical College of Soochow University, Suzhou, 215006, China.
Daoxia GuoSchool of Nursing, Suzhou Medical College of Soochow University, Suzhou, 215006, China.
Li TianFirst Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China. tianlisz@suda.edu.cn.

Funding

Major Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province 2023SJZD144
6 · The paper itself

Abstract

objectiveTo investigate chemotherapy-related symptoms in colorectal cancer patients and to identify population characteristics in different potential categories.

methodFrom November 2023 to September 2024, 710 colorectal cancer patients undergoing chemotherapy in a hospital in Suzhou were selected as the participants by cluster sampling method. The general data questionnaire and Memorial Symptom Assessment Scale were used to investigate the patients. Latent profile analysis was used to examine the patterns of symptom severity, and multinomial logistic regression was used to explore the influencing factors of potential categories of chemotherapy-related symptoms.

resultChemotherapy-related symptoms could be divided into three groups: high physical-low psychological symptom group (n = 74, 10.42%), mild symptom group (n = 565, 79.58%), and high psychological-low physical symptom group (n = 71, 10.00%). Regression analysis showed that patients with low education were more likely to fall into the high psychological-low physical symptom group. Patients who did not have a stoma and had ≤ 6 chemotherapy sessions would fall into the mild symptom group. Patients with lower BMI and did not undergo surgery before chemotherapy would be in the high physical-low psychological symptom group.

conclusionChemotherapy-related symptoms of colorectal cancer patients are heterogeneous and can be divided into three categories. Based on the above indicators, more attention could be paid to patients with low BMI, low education level, more chemotherapy sessions, and those did not undergo surgery before chemotherapy.

Indexed as

Antineoplastic AgentsColorectal NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedSurveys and QuestionnairesSymptom BurdenAntineoplastic AgentsChemotherapyColorectal cancerLatent profile analysisSymptom

Identifiers

PMID41699534
PMCPMC13014745

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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.