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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-9866143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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