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 WeiABSTRACT
Introduction
Pituitary 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.
Methods
A 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.
Results
Three 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).
Conclusion
Negative 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.