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Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery

BACKGROUND: A specific risk-stratification tool is needed to facilitate safe and cost-effective approaches to the prophylaxis of acute pulmonary thromboembolism (PTE) in lung cancer surgery patients. This study aimed to develop and validate a simple nomogram model for the prediction of PTE after lun...

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Autores principales: Li, Yuping, Shen, Lei, Ding, Junrong, Xie, Dong, Yang, Jian, Zhao, Yanfeng, Carretta, Angelo, Petersen, René Horsleben, Gilbert, Sebastien, Hida, Yasuhiro, Bölükbas, Servet, Fernando, Hiran C., Jiang, Gening, Zhu, Yuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107740/
https://www.ncbi.nlm.nih.gov/pubmed/34012796
http://dx.doi.org/10.21037/tlcr-21-109
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author Li, Yuping
Shen, Lei
Ding, Junrong
Xie, Dong
Yang, Jian
Zhao, Yanfeng
Carretta, Angelo
Petersen, René Horsleben
Gilbert, Sebastien
Hida, Yasuhiro
Bölükbas, Servet
Fernando, Hiran C.
Jiang, Gening
Zhu, Yuming
author_facet Li, Yuping
Shen, Lei
Ding, Junrong
Xie, Dong
Yang, Jian
Zhao, Yanfeng
Carretta, Angelo
Petersen, René Horsleben
Gilbert, Sebastien
Hida, Yasuhiro
Bölükbas, Servet
Fernando, Hiran C.
Jiang, Gening
Zhu, Yuming
author_sort Li, Yuping
collection PubMed
description BACKGROUND: A specific risk-stratification tool is needed to facilitate safe and cost-effective approaches to the prophylaxis of acute pulmonary thromboembolism (PTE) in lung cancer surgery patients. This study aimed to develop and validate a simple nomogram model for the prediction of PTE after lung cancer surgery using readily obtainable clinical characteristics. METHODS: A total of 14,427 consecutive adult patients who underwent lung cancer surgery between January 2015 and July 2018 in our institution were retrospectively reviewed. Included in the cohort were 136 patients who developed PTE and 544 non-PTE patients. The patients were randomly divided into the derivation group (70%, 95 PTE patients and 380 non-PTE patients) and the validation group (30%, 41 PTE patients and 164 non-PTE patients). A nomogram model was developed based on the results of multivariate logistic analysis in the derivation group. The cut-off values were defined using Youden’s index. The prognostic accuracy was measured by area under the curve (AUC) values. RESULTS: In the derivation group, multivariate logistic analysis was carried out to evaluate the risk score. The risk assessment model contained five variables: age [95% confidence interval (CI): 1.008–1.083, P=0.016], body mass index (95% CI: 1.077–1.319, P=0.001), operation time (95% CI: 1.002–1.014, P=0.008), the serum level of cancer antigen 15-3 (CA15-3) before surgery (95% CI: 1.019–1.111, P=0.005), and the abnormal results of compression venous ultrasonography before surgery (95% CI: 2.819–18.838, P<0.001). All of them were independent risk factors of PTE. To simplify the risk assessment model, a nomogram model was established, which showed a good predictive performance in the derivation group (AUC 0.792, 95% CI: 0.734–0.853) and in the validation group (AUC 0.813, 95% CI: 0.737–0.890). CONCLUSIONS: A high-performance nomogram was established on the risk factors for PTE in patients undergoing lung cancer surgery. The nomogram could be used to provide an individual risk assessment and guide prophylaxis decisions for patients. Further external validation of the model is needed in lung cancer surgery patients in other clinical centers.
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spelling pubmed-81077402021-05-18 Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery Li, Yuping Shen, Lei Ding, Junrong Xie, Dong Yang, Jian Zhao, Yanfeng Carretta, Angelo Petersen, René Horsleben Gilbert, Sebastien Hida, Yasuhiro Bölükbas, Servet Fernando, Hiran C. Jiang, Gening Zhu, Yuming Transl Lung Cancer Res Original Article BACKGROUND: A specific risk-stratification tool is needed to facilitate safe and cost-effective approaches to the prophylaxis of acute pulmonary thromboembolism (PTE) in lung cancer surgery patients. This study aimed to develop and validate a simple nomogram model for the prediction of PTE after lung cancer surgery using readily obtainable clinical characteristics. METHODS: A total of 14,427 consecutive adult patients who underwent lung cancer surgery between January 2015 and July 2018 in our institution were retrospectively reviewed. Included in the cohort were 136 patients who developed PTE and 544 non-PTE patients. The patients were randomly divided into the derivation group (70%, 95 PTE patients and 380 non-PTE patients) and the validation group (30%, 41 PTE patients and 164 non-PTE patients). A nomogram model was developed based on the results of multivariate logistic analysis in the derivation group. The cut-off values were defined using Youden’s index. The prognostic accuracy was measured by area under the curve (AUC) values. RESULTS: In the derivation group, multivariate logistic analysis was carried out to evaluate the risk score. The risk assessment model contained five variables: age [95% confidence interval (CI): 1.008–1.083, P=0.016], body mass index (95% CI: 1.077–1.319, P=0.001), operation time (95% CI: 1.002–1.014, P=0.008), the serum level of cancer antigen 15-3 (CA15-3) before surgery (95% CI: 1.019–1.111, P=0.005), and the abnormal results of compression venous ultrasonography before surgery (95% CI: 2.819–18.838, P<0.001). All of them were independent risk factors of PTE. To simplify the risk assessment model, a nomogram model was established, which showed a good predictive performance in the derivation group (AUC 0.792, 95% CI: 0.734–0.853) and in the validation group (AUC 0.813, 95% CI: 0.737–0.890). CONCLUSIONS: A high-performance nomogram was established on the risk factors for PTE in patients undergoing lung cancer surgery. The nomogram could be used to provide an individual risk assessment and guide prophylaxis decisions for patients. Further external validation of the model is needed in lung cancer surgery patients in other clinical centers. AME Publishing Company 2021-04 /pmc/articles/PMC8107740/ /pubmed/34012796 http://dx.doi.org/10.21037/tlcr-21-109 Text en 2021 Translational Lung Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Li, Yuping
Shen, Lei
Ding, Junrong
Xie, Dong
Yang, Jian
Zhao, Yanfeng
Carretta, Angelo
Petersen, René Horsleben
Gilbert, Sebastien
Hida, Yasuhiro
Bölükbas, Servet
Fernando, Hiran C.
Jiang, Gening
Zhu, Yuming
Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery
title Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery
title_full Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery
title_fullStr Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery
title_full_unstemmed Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery
title_short Derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery
title_sort derivation and validation of a nomogram model for pulmonary thromboembolism in patients undergoing lung cancer surgery
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107740/
https://www.ncbi.nlm.nih.gov/pubmed/34012796
http://dx.doi.org/10.21037/tlcr-21-109
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