Evidence map›Paper›PMID 41454294›Full record

ArticleBMC neurology2025

Identification of distinct symptom profiles in primary brain tumor patients: a prospective longitudinal study.

Rongqing Li, Zikai Zhang, Xin Zhang, Jiefang Song, Yawen Wu, Linzhi Wu, Sailu Mao, Jinxia Jiang, Li Zeng

Abstract read
In one paragraph

Article in BMC neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Rongqing Li *Department of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China.
Zikai Zhang *Department of Science Administration, Tongji Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China.
Xin ZhangDepartment of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China.
Jiefang SongDepartment of Neurosurgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China.
Yawen WuDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China.
Linzhi WuDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China.
Sailu MaoDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China.
Jinxia JiangDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China. jiangjinxia99@163.com.
Li ZengDepartment of Nursing, Tongji Hospital, School of Medicine, Tongji University, Shanghai, People's Republic Of China. aiyinsinian1986@163.com.

Funding

Clinical Research Project of Tongji hospital of Tongji university No. ITJ(QN)2308NSFC Development Project of Shanghai Tongji hospital GJPY2338, GJPY2340
6 · The paper itself

Abstract

backgroundSymptom burden in primary brain tumor patients varies, emphasizing the need for comprehensive understanding to improve patient care. This study aims to identify distinct symptom clusters among brain tumor patients in Shanghai, China, using Latent Profile Analysis (LPA) to guide personalized diagnosis, treatment, and supportive care.

methodsA longitudinal study was conducted among 161 patients with primary brain tumors in Shanghai. Participants completed the MD Anderson Symptom Inventory Brain Tumor Module (MDASI-BT) at three intervals: the day of admission (T1), three days after surgery (T2), and two weeks after surgery (T3). Latent Profile Analysis (LPA) was used to identify subgroups with unique symptom patterns.

resultsSix distinct subgroups were identified (entropy = 0.964), ranging from low-burden to persistently severe patterns. Subgroup membership was partially associated with age, tumor grade, and diagnosis. These subgroups were: transient postoperative burden group, stable symptom with cognitive emergence group, distress-predominant, low burden group, elderly-high grade, persistently severe group, nausea-dominant recovery group, and distress-plus-nausea, younger urban group.

conclusionOur findings reveal substantial heterogeneity in perioperative symptom experiences among brain tumor patients. Identifying subgroups with high and persistent symptom burden may help clinicians target interventions such as enhanced education, proactive monitoring, rehabilitation, psychological support, and antiemetic management. This subgroup-based approach may improve quality of life, reduce morbidity, and guide precision supportive care in neuro-oncology.

Indexed as

Brain NeoplasmsAdultAgedChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedProspective StudiesYoung AdultLatent profile analysisPrimary brain tumorSymptom profile

Identifiers

PMID41454294
PMCPMC12849636

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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.