A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia
Abstract Background The morbidity and mortality of community-acquired pneumonia (CAP) remain high among infectious diseases. It was reported that angiopoietin-like 4 (ANGPTL4) could be a diagnostic biomarker and a therapeutic target for pneumonia. This study aimed to develop a more objective, specif...
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| Format: | Article |
| Language: | English |
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BMC
2023-10-01
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| Series: | BMC Infectious Diseases |
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| Online Access: | https://doi.org/10.1186/s12879-023-08648-4 |
| _version_ | 1797577880713035776 |
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| author | Siqin Chen Jia Jiang Minhong Su Ping Chen Xiang Liu Wei Lei Shaofeng Zhang Qiang Wu Fu Rong Xi Li Xiaobin Zheng Qiang Xiao |
| author_facet | Siqin Chen Jia Jiang Minhong Su Ping Chen Xiang Liu Wei Lei Shaofeng Zhang Qiang Wu Fu Rong Xi Li Xiaobin Zheng Qiang Xiao |
| author_sort | Siqin Chen |
| collection | DOAJ |
| description | Abstract Background The morbidity and mortality of community-acquired pneumonia (CAP) remain high among infectious diseases. It was reported that angiopoietin-like 4 (ANGPTL4) could be a diagnostic biomarker and a therapeutic target for pneumonia. This study aimed to develop a more objective, specific, accurate, and individualized scoring system to predict the severity of CAP. Methods Totally, 31 non-severe community-acquired pneumonia (nsCAP) patients and 14 severe community-acquired pneumonia (sCAP) patients were enrolled in this study. The CURB-65 and pneumonia severity index (PSI) scores were calculated from the clinical data. Serum ANGPTL4 level was measured by enzyme-linked immunosorbent assay (ELISA). After screening factors by univariate analysis and receiver operating characteristic (ROC) curve analysis, multivariate logistic regression analysis of ANGPTL4 expression level and other risk factors was performed, and a nomogram was developed to predict the severity of CAP. This nomogram was further internally validated by bootstrap resampling with 1000 replications through the area under the ROC curve (AUC), the calibration curve, and the decision curve analysis (DCA). Finally, the prediction performance of the new nomogram model, CURB-65 score, and PSI score was compared by AUC, net reclassification index (NRI), and integrated discrimination improvement (IDI). Results A nomogram for predicting the severity of CAP was developed using three factors (C-reactive protein (CRP), procalcitonin (PCT), and ANGPTL4). According to the internal validation, the nomogram showed a great discrimination capability with an AUC of 0.910. The Hosmer–Lemeshow test and the approximately fitting calibration curve suggested a satisfactory accuracy of prediction. The results of DCA exhibited a great net benefit. The AUC values of CURB-65 score, PSI score, and the new prediction model were 0.857, 0.912, and 0.940, respectively. NRI comparing the new model with CURB-65 score was found to be statistically significant (NRI = 0.834, P < 0.05). Conclusion A robust model for predicting the severity of CAP was developed based on the serum ANGPTL4 level. This may provide new insights into accurate assessment of the severity of CAP and its targeted therapy, particularly in the early-stage of the disease. |
| first_indexed | 2024-03-10T22:14:15Z |
| format | Article |
| id | doaj.art-5ebc8afec7014d318aeb0ece90d5797c |
| institution | Directory Open Access Journal |
| issn | 1471-2334 |
| language | English |
| last_indexed | 2024-03-10T22:14:15Z |
| publishDate | 2023-10-01 |
| publisher | BMC |
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| series | BMC Infectious Diseases |
| spelling | doaj.art-5ebc8afec7014d318aeb0ece90d5797c2023-11-19T12:29:12ZengBMCBMC Infectious Diseases1471-23342023-10-0123111110.1186/s12879-023-08648-4A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumoniaSiqin Chen0Jia Jiang1Minhong Su2Ping Chen3Xiang Liu4Wei Lei5Shaofeng Zhang6Qiang Wu7Fu Rong8Xi Li9Xiaobin Zheng10Qiang Xiao11Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical UniversityPulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical UniversityPulmonary and Critical Care Medicine, Zhujiang Hospital, Southern Medical UniversityGMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Medical UniversityDepartments of Hematology, Shunde Hospital, Southern Medical UniversityPulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical UniversityPulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical UniversityDepartment of Cardiology, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People’s Hospital, Second Hospital Affiliated to Southern University of Science and TechnologyPulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical UniversityPulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical UniversityPulmonary and Critical Care Medicine, The Fifth Affiliated Hospital of Sun Yat-Sen UniversityPulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical UniversityAbstract Background The morbidity and mortality of community-acquired pneumonia (CAP) remain high among infectious diseases. It was reported that angiopoietin-like 4 (ANGPTL4) could be a diagnostic biomarker and a therapeutic target for pneumonia. This study aimed to develop a more objective, specific, accurate, and individualized scoring system to predict the severity of CAP. Methods Totally, 31 non-severe community-acquired pneumonia (nsCAP) patients and 14 severe community-acquired pneumonia (sCAP) patients were enrolled in this study. The CURB-65 and pneumonia severity index (PSI) scores were calculated from the clinical data. Serum ANGPTL4 level was measured by enzyme-linked immunosorbent assay (ELISA). After screening factors by univariate analysis and receiver operating characteristic (ROC) curve analysis, multivariate logistic regression analysis of ANGPTL4 expression level and other risk factors was performed, and a nomogram was developed to predict the severity of CAP. This nomogram was further internally validated by bootstrap resampling with 1000 replications through the area under the ROC curve (AUC), the calibration curve, and the decision curve analysis (DCA). Finally, the prediction performance of the new nomogram model, CURB-65 score, and PSI score was compared by AUC, net reclassification index (NRI), and integrated discrimination improvement (IDI). Results A nomogram for predicting the severity of CAP was developed using three factors (C-reactive protein (CRP), procalcitonin (PCT), and ANGPTL4). According to the internal validation, the nomogram showed a great discrimination capability with an AUC of 0.910. The Hosmer–Lemeshow test and the approximately fitting calibration curve suggested a satisfactory accuracy of prediction. The results of DCA exhibited a great net benefit. The AUC values of CURB-65 score, PSI score, and the new prediction model were 0.857, 0.912, and 0.940, respectively. NRI comparing the new model with CURB-65 score was found to be statistically significant (NRI = 0.834, P < 0.05). Conclusion A robust model for predicting the severity of CAP was developed based on the serum ANGPTL4 level. This may provide new insights into accurate assessment of the severity of CAP and its targeted therapy, particularly in the early-stage of the disease.https://doi.org/10.1186/s12879-023-08648-4Angiopoietin-like 4 (ANGPTL4)Severe community-acquired pneumoniaBiomarkerPrecision medicinePrediction model |
| spellingShingle | Siqin Chen Jia Jiang Minhong Su Ping Chen Xiang Liu Wei Lei Shaofeng Zhang Qiang Wu Fu Rong Xi Li Xiaobin Zheng Qiang Xiao A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia BMC Infectious Diseases Angiopoietin-like 4 (ANGPTL4) Severe community-acquired pneumonia Biomarker Precision medicine Prediction model |
| title | A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia |
| title_full | A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia |
| title_fullStr | A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia |
| title_full_unstemmed | A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia |
| title_short | A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia |
| title_sort | nomogram based on the expression level of angiopoietin like 4 to predict the severity of community acquired pneumonia |
| topic | Angiopoietin-like 4 (ANGPTL4) Severe community-acquired pneumonia Biomarker Precision medicine Prediction model |
| url | https://doi.org/10.1186/s12879-023-08648-4 |
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