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A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study

Backgrounds: Advanced schistosomiasis is the late stage of schistosomiasis, seriously jeopardizing the quality of life or lifetime of infected people. This study aimed to develop a nomogram for predicting mortality of patients with advanced schistosomiasis japonica, taking Dongzhi County of China as...

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Autores principales: Hong, Zhong, Zhang, Shiqing, Li, Lu, Li, Yinlong, Liu, Ting, Guo, Suying, Xu, Xiaojuan, Yang, Zhaoming, Zhang, Haoyi, Xu, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866143/
https://www.ncbi.nlm.nih.gov/pubmed/36668940
http://dx.doi.org/10.3390/tropicalmed8010033
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author Hong, Zhong
Zhang, Shiqing
Li, Lu
Li, Yinlong
Liu, Ting
Guo, Suying
Xu, Xiaojuan
Yang, Zhaoming
Zhang, Haoyi
Xu, Jing
author_facet Hong, Zhong
Zhang, Shiqing
Li, Lu
Li, Yinlong
Liu, Ting
Guo, Suying
Xu, Xiaojuan
Yang, Zhaoming
Zhang, Haoyi
Xu, Jing
author_sort Hong, Zhong
collection PubMed
description Backgrounds: Advanced schistosomiasis is the late stage of schistosomiasis, seriously jeopardizing the quality of life or lifetime of infected people. This study aimed to develop a nomogram for predicting mortality of patients with advanced schistosomiasis japonica, taking Dongzhi County of China as a case study. Method: Data of patients with advanced schistosomiasis japonica were collected from Dongzhi Schistosomiasis Hospital from January 2019 to July 2022. Data of patients were randomly divided into a training set and validation set with a ratio of 7:3. Candidate variables, including survival outcomes, demographics, clinical features, laboratory examinations, and ultrasound examinations, were analyzed and selected by LASSO logistic regression for the nomogram. The performance of the nomogram was assessed by concordance index (C-index), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The calibration of the nomogram was evaluated by the calibration plots, while clinical benefit was evaluated by decision curve and clinical impact curve analysis. Results: A total of 628 patients were included in the final analysis. Atrophy of the right liver, creatinine, ascites level III, N-terminal procollagen III peptide, and high-density lipoprotein were selected as parameters for the nomogram model. The C-index, sensitivity, specificity, PPV, and NPV of the nomogram were 0.97 (95% [CI]: [0.95–0.99]), 0.78 (95% [CI]: [0.64–0.87]), 0.97 (95% [CI]: [0.94–0.98]), 0.78 (95% [CI]: [0.64–0.87]), 0.97 (95% [CI]: [0.94–0.98]) in the training set; and 0.98 (95% [CI]: [0.94–0.99]), 0.86 (95% [CI]: [0.64–0.96]), 0.97 (95% [CI]: [0.93–0.99]), 0.79 (95% [CI]: [0.57–0.92]), 0.98 (95% [CI]: [0.94–0.99]) in the validation set, respectively. The calibration curves showed that the model fitted well between the prediction and actual observation in both the training set and validation set. The decision and the clinical impact curves showed that the nomogram had good clinical use for discriminating patients with high risk of death. Conclusions: A nomogram was developed to predict prognosis of advanced schistosomiasis. It could guide clinical staff or policy makers to formulate intervention strategies or efficiently allocate resources against advanced schistosomiasis.
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spelling pubmed-98661432023-01-22 A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study Hong, Zhong Zhang, Shiqing Li, Lu Li, Yinlong Liu, Ting Guo, Suying Xu, Xiaojuan Yang, Zhaoming Zhang, Haoyi Xu, Jing Trop Med Infect Dis Article Backgrounds: Advanced schistosomiasis is the late stage of schistosomiasis, seriously jeopardizing the quality of life or lifetime of infected people. This study aimed to develop a nomogram for predicting mortality of patients with advanced schistosomiasis japonica, taking Dongzhi County of China as a case study. Method: Data of patients with advanced schistosomiasis japonica were collected from Dongzhi Schistosomiasis Hospital from January 2019 to July 2022. Data of patients were randomly divided into a training set and validation set with a ratio of 7:3. Candidate variables, including survival outcomes, demographics, clinical features, laboratory examinations, and ultrasound examinations, were analyzed and selected by LASSO logistic regression for the nomogram. The performance of the nomogram was assessed by concordance index (C-index), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The calibration of the nomogram was evaluated by the calibration plots, while clinical benefit was evaluated by decision curve and clinical impact curve analysis. Results: A total of 628 patients were included in the final analysis. Atrophy of the right liver, creatinine, ascites level III, N-terminal procollagen III peptide, and high-density lipoprotein were selected as parameters for the nomogram model. The C-index, sensitivity, specificity, PPV, and NPV of the nomogram were 0.97 (95% [CI]: [0.95–0.99]), 0.78 (95% [CI]: [0.64–0.87]), 0.97 (95% [CI]: [0.94–0.98]), 0.78 (95% [CI]: [0.64–0.87]), 0.97 (95% [CI]: [0.94–0.98]) in the training set; and 0.98 (95% [CI]: [0.94–0.99]), 0.86 (95% [CI]: [0.64–0.96]), 0.97 (95% [CI]: [0.93–0.99]), 0.79 (95% [CI]: [0.57–0.92]), 0.98 (95% [CI]: [0.94–0.99]) in the validation set, respectively. The calibration curves showed that the model fitted well between the prediction and actual observation in both the training set and validation set. The decision and the clinical impact curves showed that the nomogram had good clinical use for discriminating patients with high risk of death. Conclusions: A nomogram was developed to predict prognosis of advanced schistosomiasis. It could guide clinical staff or policy makers to formulate intervention strategies or efficiently allocate resources against advanced schistosomiasis. MDPI 2023-01-03 /pmc/articles/PMC9866143/ /pubmed/36668940 http://dx.doi.org/10.3390/tropicalmed8010033 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hong, Zhong
Zhang, Shiqing
Li, Lu
Li, Yinlong
Liu, Ting
Guo, Suying
Xu, Xiaojuan
Yang, Zhaoming
Zhang, Haoyi
Xu, Jing
A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study
title A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study
title_full A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study
title_fullStr A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study
title_full_unstemmed A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study
title_short A Nomogram for Predicting Prognosis of Advanced Schistosomiasis japonica in Dongzhi County—A Case Study
title_sort nomogram for predicting prognosis of advanced schistosomiasis japonica in dongzhi county—a case study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866143/
https://www.ncbi.nlm.nih.gov/pubmed/36668940
http://dx.doi.org/10.3390/tropicalmed8010033
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