The prognostic analysis and a machine-learning based disease-specific survival state model in pulmonary large-cell neuroendocrine carcinomas.
Xiongye XuBaomo LiuYan SuPeixin DongShuaishuai WangJiating DengZiying LinLixia HuangShaoli LiJincui GuYanbin ZhouPublished in: Journal of thoracic disease (2024)
Male, age ≥65 years, distant metastasis to the bone, liver, and brain are associated with a worse prognosis in PLCNEC patients, while surgery and chemotherapy are associated with improved prognosis. GBDT showed promising performance in predicting 2-year survival, which can serve as a valuable reference for clinical diagnosis and treatment of PLCNEC.
Keyphrases
- machine learning
- end stage renal disease
- ejection fraction
- newly diagnosed
- minimally invasive
- chronic kidney disease
- pulmonary hypertension
- lymph node
- single cell
- prognostic factors
- free survival
- white matter
- squamous cell carcinoma
- bone mineral density
- stem cells
- coronary artery disease
- patient reported outcomes
- postmenopausal women
- body composition
- brain injury