ArticleAnnals of surgical oncology2023
A Competing Risk Model Nomogram to Predict the Long-Term Prognosis of Lung Carcinoid.
Article in Annals of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The value of nomogram analysis in predicting pulmonary metastasis in hepatic alveolar echinococcosis.Scientific reports · 2025Article
- Nomogram prediction of molecular characteristics in WHO grade 3-4 diffuse gliomas based on fractal analysis and VASARI features.Scientific reports · 2025Article
- Prediction of the prognosis of intrahepatic cholangiocarcinoma patients after hepatectomy via propensity score matching: a competitive risk model analysis.Translational cancer research · 2025Article
- Development of a machine learning-based predictive model for transitional cell carcinoma of the renal pelvis in White Americans: a SEER-based study.Translational andrology and urology · 2024Article
- Article
- Prognostic factors of recurrence and disease-free survival in radically resected pulmonary carcinoids: a real-world analysis.Journal of thoracic disease · 2024Article
- The presentation pattern and surgical strategies in bronchopulmonary carcinoid tumors: a multicenter experience in a low-income country.Frontiers in surgery · 2024Article
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9 authors.
Funding
Abstract
backgroundThe prediction of long-term, cancer-specific survival of lung carcinoid remains controversial. We aimed to build a prognostic model by using competing-risk analysis to predict the long-term, cancer-specific survival of lung carcinoid patients.
methodsPatients were retrospectively enrolled from the SEER database, and clinicopathological data were collected. Univariable and multivariable competing-risk analyses were conducted to identify prognostic factors. A competing-risk model and a nomogram were developed by using independent prognostic factors. The model was assessed by using concordance index and calibration curves.
resultsA total of 2496 patients were enrolled, of which 267 (10.7%) died of diagnosed carcinoma; 316 (12.7%) died because of other reasons. The 5-year, 10-year, and 15-year cancer-specific survival of carcinoid patients were 91.35%, 86.60%, and 84.39%, respectively. Multivariable analysis demonstrated that increasing age, male, larger tumor size, higher N stage, M1, atypical carcinoid, and undergoing no surgery were independent risk factors. A competing-risk model based on the risk factors and a corresponding nomogram were developed. Concordance index of the developed model for 5-year, 10-year, and 15-year were 0.891, 0.856, 0.836 respectively in the training cohort and 0.876, 0.841, 0.819 respectively in the validation cohort after bootstrap adjustment. The calibration curves of 5-year, 10-year, and 15-year showed good agreement.
conclusionsIncreasing age, male, larger tumor size, higher N stage, M1, atypical carcinoid, and undergoing no surgery were independent risk factors. A competing risk model of excellent performance in predicting long-term survival was developed, and a nomogram was established.
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