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A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients

BACKGROUNDS: Spontaneous ventilation-video-assisted thoracoscopic surgery (SV-VATS) has been applied to non-small cell lung cancer (NSCLC) patients in many centers. Since it remains a new and challenging surgical technique, only selected patients can be performed SV-VATS. We aim to conduct a retrosp...

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Autores principales: Wang, Runchen, Wang, Qixia, Liang, Hengrui, Ye, Zhiming, Qiu, Jiawen, Jiang, Yu, He, Jianxing, Zhao, Lei, Wang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10519124/
https://www.ncbi.nlm.nih.gov/pubmed/37743499
http://dx.doi.org/10.1186/s12893-023-02150-z
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author Wang, Runchen
Wang, Qixia
Liang, Hengrui
Ye, Zhiming
Qiu, Jiawen
Jiang, Yu
He, Jianxing
Zhao, Lei
Wang, Wei
author_facet Wang, Runchen
Wang, Qixia
Liang, Hengrui
Ye, Zhiming
Qiu, Jiawen
Jiang, Yu
He, Jianxing
Zhao, Lei
Wang, Wei
author_sort Wang, Runchen
collection PubMed
description BACKGROUNDS: Spontaneous ventilation-video-assisted thoracoscopic surgery (SV-VATS) has been applied to non-small cell lung cancer (NSCLC) patients in many centers. Since it remains a new and challenging surgical technique, only selected patients can be performed SV-VATS. We aim to conduct a retrospective single-center study to develop a clinical decision-making model to make surgery decision between SV-VATS and MV (mechanical ventilation) -VATS in NSCLC patients more objectively and individually. METHODS: Four thousand three hundred sixty-eight NSCLC patients undergoing SV-VATS or MV-VATS in the department of thoracic surgery between 2011 and 2018 were included. Univariate and multivariate regression analysis were used to identify potential factors influencing the surgical decisions. Factors with statistical significance were selected for constructing the Surgical Decision-making Scoring (SDS) model. The performance of the model was validated by area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). RESULTS: The Surgical Decision-making Scoring (SDS) model was built guided by the clinical judgment and statistically significant results of univariate and multivariate regression analyses of potential predictors, including smoking status (p = 0.03), BMI (p < 0.001), ACCI (p = 0.04), T stage (p < 0.001), N stage (p < 0.001), ASA grade (p < 0.001) and surgical technique (p < 0.001). The AUC of the training group and the testing group were 0.72 and 0.70, respectively. The calibration curves and the DCA curve revealed that the SDS model has a desired performance in predicting the surgical decision. CONCLUSIONS: This SDS model is the first clinical decision-making model developed for an individual NSCLC patient to make decision between SV-VATS and MV-VATS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12893-023-02150-z.
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spelling pubmed-105191242023-09-26 A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients Wang, Runchen Wang, Qixia Liang, Hengrui Ye, Zhiming Qiu, Jiawen Jiang, Yu He, Jianxing Zhao, Lei Wang, Wei BMC Surg Research Article BACKGROUNDS: Spontaneous ventilation-video-assisted thoracoscopic surgery (SV-VATS) has been applied to non-small cell lung cancer (NSCLC) patients in many centers. Since it remains a new and challenging surgical technique, only selected patients can be performed SV-VATS. We aim to conduct a retrospective single-center study to develop a clinical decision-making model to make surgery decision between SV-VATS and MV (mechanical ventilation) -VATS in NSCLC patients more objectively and individually. METHODS: Four thousand three hundred sixty-eight NSCLC patients undergoing SV-VATS or MV-VATS in the department of thoracic surgery between 2011 and 2018 were included. Univariate and multivariate regression analysis were used to identify potential factors influencing the surgical decisions. Factors with statistical significance were selected for constructing the Surgical Decision-making Scoring (SDS) model. The performance of the model was validated by area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). RESULTS: The Surgical Decision-making Scoring (SDS) model was built guided by the clinical judgment and statistically significant results of univariate and multivariate regression analyses of potential predictors, including smoking status (p = 0.03), BMI (p < 0.001), ACCI (p = 0.04), T stage (p < 0.001), N stage (p < 0.001), ASA grade (p < 0.001) and surgical technique (p < 0.001). The AUC of the training group and the testing group were 0.72 and 0.70, respectively. The calibration curves and the DCA curve revealed that the SDS model has a desired performance in predicting the surgical decision. CONCLUSIONS: This SDS model is the first clinical decision-making model developed for an individual NSCLC patient to make decision between SV-VATS and MV-VATS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12893-023-02150-z. BioMed Central 2023-09-25 /pmc/articles/PMC10519124/ /pubmed/37743499 http://dx.doi.org/10.1186/s12893-023-02150-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Wang, Runchen
Wang, Qixia
Liang, Hengrui
Ye, Zhiming
Qiu, Jiawen
Jiang, Yu
He, Jianxing
Zhao, Lei
Wang, Wei
A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients
title A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients
title_full A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients
title_fullStr A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients
title_full_unstemmed A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients
title_short A surgical Decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients
title_sort surgical decision-making scoring model for spontaneous ventilation- and mechanical ventilation-video-assisted thoracoscopic surgery in non-small-cell lung cancer patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10519124/
https://www.ncbi.nlm.nih.gov/pubmed/37743499
http://dx.doi.org/10.1186/s12893-023-02150-z
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