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Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence

BACKGROUND: Myasthenia gravis (MG) is one of the most common accessory syndromes for thymoma patients. To reduce MG exacerbation and guide clinical practice, we developed a nomogram for predicting MG exacerbation in patients with postoperative thymoma recurrence. METHODS: Retrospective study of 176...

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Autores principales: Cheng, Biqi, Xue, Yinping, Gu, Shanshan, Yang, Hongxia, Liu, Peng, Qi, Guoyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638789/
https://www.ncbi.nlm.nih.gov/pubmed/36353585
http://dx.doi.org/10.21037/gs-22-549
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author Cheng, Biqi
Xue, Yinping
Gu, Shanshan
Yang, Hongxia
Liu, Peng
Qi, Guoyan
author_facet Cheng, Biqi
Xue, Yinping
Gu, Shanshan
Yang, Hongxia
Liu, Peng
Qi, Guoyan
author_sort Cheng, Biqi
collection PubMed
description BACKGROUND: Myasthenia gravis (MG) is one of the most common accessory syndromes for thymoma patients. To reduce MG exacerbation and guide clinical practice, we developed a nomogram for predicting MG exacerbation in patients with postoperative thymoma recurrence. METHODS: Retrospective study of 176 patients with recurrence following thymoma resection who were admitted to the People’s Hospital of Shijiazhuang’s Center of Treatment of Myasthenia Gravis between 2013 and 2021. Among them, 120 patients with recurrent thymoma from 2013 to 2020 were selected as the training cohort, and 56 patients in 2021 as the validation cohort. Univariate and multivariate logical regression was used to determine the risk factors and draw the nomogram, and the parameters in the nomogram were proportionally assigned from 0 to 100 points. Finally, the performance of the model is evaluated by internal inspection and external inspection. RESULTS: Multivariate analysis revealed that postoperative treatment plan and the pathologic classification of the thymoma were independent predictors of MG exacerbation in the training cohort (n=120), so they were used to create the nomogram, which had a well-fit calibration curve and good concordance index of 0.77 [95% confidence interval (CI): 0.69–0.86] for the training cohort and 0.74 (95% CI: 0.58–0.91) for the validation cohort, respectively. Calculations were made to determine the nomogram’s sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV). The training cohort were 75.7% (95% CI: 66.1–83.4%), 64.7% (95% CI: 38.6–84.7%), 92.9% (95% CI: 84.5–97.1%) and 30.6% (95% CI: 16.9–48.3%) respectively, while the corresponding validation cohort were 84.1% (95% CI: 69.3–92.8%), 66.7% (95% CI: 35.4–88.7%), 90.2% (95% CI: 75.9–96.8%) and 53.3% (95% CI: 27.4–77.7%) respectively. CONCLUSIONS: We identified the risk factors for MG exacerbation in patients with postoperative recurrence of thymoma and drew a nomogram, which can be used to calculate the probability of MG exacerbation and guide clinicians to choose post-operative treatment.
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spelling pubmed-96387892022-11-08 Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence Cheng, Biqi Xue, Yinping Gu, Shanshan Yang, Hongxia Liu, Peng Qi, Guoyan Gland Surg Original Article BACKGROUND: Myasthenia gravis (MG) is one of the most common accessory syndromes for thymoma patients. To reduce MG exacerbation and guide clinical practice, we developed a nomogram for predicting MG exacerbation in patients with postoperative thymoma recurrence. METHODS: Retrospective study of 176 patients with recurrence following thymoma resection who were admitted to the People’s Hospital of Shijiazhuang’s Center of Treatment of Myasthenia Gravis between 2013 and 2021. Among them, 120 patients with recurrent thymoma from 2013 to 2020 were selected as the training cohort, and 56 patients in 2021 as the validation cohort. Univariate and multivariate logical regression was used to determine the risk factors and draw the nomogram, and the parameters in the nomogram were proportionally assigned from 0 to 100 points. Finally, the performance of the model is evaluated by internal inspection and external inspection. RESULTS: Multivariate analysis revealed that postoperative treatment plan and the pathologic classification of the thymoma were independent predictors of MG exacerbation in the training cohort (n=120), so they were used to create the nomogram, which had a well-fit calibration curve and good concordance index of 0.77 [95% confidence interval (CI): 0.69–0.86] for the training cohort and 0.74 (95% CI: 0.58–0.91) for the validation cohort, respectively. Calculations were made to determine the nomogram’s sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV). The training cohort were 75.7% (95% CI: 66.1–83.4%), 64.7% (95% CI: 38.6–84.7%), 92.9% (95% CI: 84.5–97.1%) and 30.6% (95% CI: 16.9–48.3%) respectively, while the corresponding validation cohort were 84.1% (95% CI: 69.3–92.8%), 66.7% (95% CI: 35.4–88.7%), 90.2% (95% CI: 75.9–96.8%) and 53.3% (95% CI: 27.4–77.7%) respectively. CONCLUSIONS: We identified the risk factors for MG exacerbation in patients with postoperative recurrence of thymoma and drew a nomogram, which can be used to calculate the probability of MG exacerbation and guide clinicians to choose post-operative treatment. AME Publishing Company 2022-10 /pmc/articles/PMC9638789/ /pubmed/36353585 http://dx.doi.org/10.21037/gs-22-549 Text en 2022 Gland Surgery. 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
Cheng, Biqi
Xue, Yinping
Gu, Shanshan
Yang, Hongxia
Liu, Peng
Qi, Guoyan
Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence
title Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence
title_full Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence
title_fullStr Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence
title_full_unstemmed Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence
title_short Developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence
title_sort developing and validating a nomogram to predict myasthenia gravis exacerbation in patients with postoperative thymoma recurrence
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638789/
https://www.ncbi.nlm.nih.gov/pubmed/36353585
http://dx.doi.org/10.21037/gs-22-549
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