Nomogram for predicting cardiovascular mortality in patients with gastrointestinal stromal tumor: A population-based study.

Autor:	Wang H; Department of Cardiology, Affiliated Hospital 2 of Nantong University, Nantong, China.; Nantong Clinical Medical College of Kangda College, Nanjing Medical University, Nantong, China., Zheng K; Department of Cardiology, Affiliated Hospital 2 of Nantong University, Nantong, China., Tai C; Department of Cardiology, Affiliated Hospital 2 of Nantong University, Nantong, China., Sun Y; Office of the Dean, Affiliated Hospital 2 of Nantong University, Nantong, China., Feng S; Nantong Clinical Medical College of Kangda College, Nanjing Medical University, Nantong, China.; Department of Nephrology, Affiliated Hospital 2 of Nantong University, Nantong, China., Zhang Y; Nantong Clinical Medical College of Kangda College, Nanjing Medical University, Nantong, China.; Department of Neurosurgery, Affiliated Hospital 2 of Nantong University, Nantong, China., Gao YD; Nantong Clinical Medical College of Kangda College, Nanjing Medical University, Nantong, China.; Department of Gastroenterology, Affiliated Hospital 2 of Nantong University, Nantong, China.
Jazyk:	angličtina
Zdroj:	Medicine [Medicine (Baltimore)] 2024 Sep 27; Vol. 103 (39), pp. e39835.
DOI:	10.1097/MD.0000000000039835
Abstrakt:	This research aimed to develop and validate a clinical nomogram for predicting the probability of cardiovascular death (CVD) in patients with gastrointestinal stromal tumors (GIST). Information regarding patients diagnosed with GIST was extracted from the surveillance, epidemiology, and end results database. The multivariable competing risk model and multivariable Cox regression model were utilized to determine the independent predictive factors. A comparison was made between the results obtained from the 2 models. A nomogram was built to visualize the competing risk model. The nomogram's performance was assessed utilizing concordance index, calibrate curve, decision curve analysis, and risk stratification. A total of 9028 cases were enrolled for final analysis, with CVD accounting for 12.8% of all deaths since GIST diagnosis. The multivariate analysis of competing risks revealed that age, chemotherapy and marital status were identified as independent risk factors for CVD in GIST individuals. The nomogram model exhibited good calibration and strong discriminative ability, indicating its effectiveness in predicting outcomes, with a concordance index of 0.788 (95% confidence interval: 0.753-0.823) in the training set, and 0.744 (95% confidence interval: 0.673-0.815) in the validation set. Decision curve analysis indicated that the prediction model had good clinical practicability. Additionally, risk stratification analysis efficiently divided GIST individuals into high- and low-risk populations for CVD. This was the first research to construct and validate a predictive nomogram using a competing risk model to estimate the individual probabilities of CVD in GIST patients. The nomogram can assist clinicians in making personalized treatment and monitoring plans. Competing Interests: The authors have no conflicts of interest to disclose. (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)
Databáze:	MEDLINE
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