Evidence map›Paper›PMID 42543918›Full record

ArticleBrain and behavior2026

Latent Class Analysis of Negative Emotion Subtypes and Their Association With Quality of Life in Patients With Pituitary Neuroendocrine Tumors.

Lei Jin, FangYuan Yao, JinHua Yang, Jing Gong, JingHua Sheng, ShuYa Chen, Li Ji, Chen Wei

Abstract read
In one paragraph

Article in Brain and behavior, 2026. 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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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Lei JinDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0007-1432-0397
FangYuan YaoDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0009-2509-9020
JinHua YangDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0008-7139-7320
Jing GongDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0002-8626-8915
JingHua ShengDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0000-6238-2014
ShuYa ChenDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0009-2854-0328
Li JiDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0008-3868-546X
Chen WeiDepartment of Nursing, Huashan Hospital of Fudan University, Shanghai, China.ORCID https://orcid.org/0009-0007-3394-3450

Funding

Shanghai Municipal Commission of Health General Scientific Research Program 202340168
6 · The paper itself

Abstract

introductionPituitary neuroendocrine tumors (PitNETs) account for up to 15% of intracranial tumors. Patients commonly present with various emotional and cognitive impairments, including a high prevalence of anxiety and depression. Therefore, this study aimed to identify the latent subtypes of negative emotions in patients with PitNETs and examine their associations with quality of life.

methodsA total of 422 patients diagnosed with PitNETs who were scheduled for neurosurgical treatment at a tertiary hospital between September 2023 and September 2025 were enrolled. Multidimensional assessments were conducted, including a general information questionnaire, the Hospital Anxiety and Depression Scale (HADS), the 12-Item Short Form Health Survey (SF-12), the Pittsburgh Sleep Quality Index (PSQI), and neuroendocrine hormonal function classification. Latent class analysis was applied to identify subtypes of negative emotions, and multivariable regression was performed to compare psychological and clinical characteristics across classes.

resultsThree distinct latent subtypes of negative emotions were identified: the low negative-emotion class (C1; n = 75, 18%); moderate-distress class (C2; n = 218, 52%); and high dual-negative-emotion class (C3; n = 129, 30%). Multivariable regression showed significant differences between C1 and C3 in educational level, employment status, alcohol consumption, headache symptoms, and PSQI scores (p < 0.05). Significant differences were also found between C2 and C3 in pituitary hormone function, headache symptoms, and PSQI scores (p < 0.05).

conclusionNegative emotions in patients with PitNETs demonstrated marked heterogeneity. Therefore, identifying the distinct emotional subtypes may facilitate more precise psychological interventions, thereby improving quality of life and perioperative management.

Indexed as

EmotionsNeuroendocrine TumorsPituitary NeoplasmsQuality of LifeAdultAgedAnxietyDepressionFemaleHumansLatent Class AnalysisMaleMiddle Agedlatent class analysisnegative emotionspituitary neuroendocrine tumorsquality of life

Identifiers

PMID42543918
PMCPMC13430273

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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.