A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> 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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MDPI AG
2023-01-01
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| Series: | Tropical Medicine and Infectious Disease |
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| Online Access: | https://www.mdpi.com/2414-6366/8/1/33 |
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| author | Zhong Hong Shiqing Zhang Lu Li Yinlong Li Ting Liu Suying Guo Xiaojuan Xu Zhaoming Yang Haoyi Zhang Jing Xu |
| author_facet | Zhong Hong Shiqing Zhang Lu Li Yinlong Li Ting Liu Suying Guo Xiaojuan Xu Zhaoming Yang Haoyi Zhang Jing Xu |
| author_sort | Zhong Hong |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T11:04:54Z |
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| spelling | doaj.art-2c37413c18bd4e0db397453e90dbe9182023-12-01T00:58:09ZengMDPI AGTropical Medicine and Infectious Disease2414-63662023-01-01813310.3390/tropicalmed8010033A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> in Dongzhi County—A Case StudyZhong Hong0Shiqing Zhang1Lu Li2Yinlong Li3Ting Liu4Suying Guo5Xiaojuan Xu6Zhaoming Yang7Haoyi Zhang8Jing Xu9National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, ChinaDepartment of Schistosomiasis Control and Prevention, Anhui Institute of Parasitic Diseases, Hefei 230061, ChinaNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, ChinaNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, ChinaDepartment of Schistosomiasis Control and Prevention, Anhui Institute of Parasitic Diseases, Hefei 230061, ChinaNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, ChinaDepartment of Schistosomiasis Control and Prevention, Anhui Institute of Parasitic Diseases, Hefei 230061, ChinaDepartment of Clinical Treatment, Dongzhi Schistosomiasis Hospital, Chizhou 247230, ChinaDepartment of Clinical Treatment, Dongzhi Schistosomiasis Hospital, Chizhou 247230, ChinaNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, ChinaBackgrounds: 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.https://www.mdpi.com/2414-6366/8/1/33advanced schistosomiasisprognosisLASSO logistic regressionnomogram |
| spellingShingle | Zhong Hong Shiqing Zhang Lu Li Yinlong Li Ting Liu Suying Guo Xiaojuan Xu Zhaoming Yang Haoyi Zhang Jing Xu A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> in Dongzhi County—A Case Study Tropical Medicine and Infectious Disease advanced schistosomiasis prognosis LASSO logistic regression nomogram |
| title | A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> in Dongzhi County—A Case Study |
| title_full | A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> in Dongzhi County—A Case Study |
| title_fullStr | A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> in Dongzhi County—A Case Study |
| title_full_unstemmed | A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> in Dongzhi County—A Case Study |
| title_short | A Nomogram for Predicting Prognosis of Advanced <i>Schistosomiasis japonica</i> in Dongzhi County—A Case Study |
| title_sort | nomogram for predicting prognosis of advanced i schistosomiasis japonica i in dongzhi county a case study |
| topic | advanced schistosomiasis prognosis LASSO logistic regression nomogram |
| url | https://www.mdpi.com/2414-6366/8/1/33 |
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