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Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia
Zhang, Teng1,2; Zeng, Yifeng3; Lin, Runpei3; Xue, Mingshan3; Liu, Mingtao3; Li, Yusi1; Zhen, Yingjie3; Li, Ning3; Cao, Wenhan3; Wu, Sixiao3; Zhu, Huiqing3; Zhao, Qi1,2; Sun, Baoqing3
2022-10-01
Source PublicationJournal of Clinical Medicine
ISSN2077-0383
Volume11Issue:20
Abstract

(1) Background: Biomarker and model development can help physicians adjust the management of patients with community-acquired pneumonia (CAP) by screening for inpatients with a low probability of cure early in their admission; (2) Methods: We conducted a 30-day cohort study of newly admitted adult CAP patients over 20 years of age. Prognosis models to predict the short-term prognosis were developed using random survival forest (RSF) method; (3) Results: A total of 247 adult CAP patients were studied and 208 (84.21%) of them reached clinical stability within 30 days. The soluble form of suppression of tumorigenicity-2 (sST2) was an independent predictor of clinical stability and the addition of sST2 to the prognosis model could improve the performance of the prognosis model. The C-index of the RSF model for predicting clinical stability was 0.8342 (95% CI, 0.8086–0.8598), which is higher than 0.7181 (95% CI, 0.6933–0.7429) of CURB 65 score, 0.8025 (95% CI, 0.7776–8274) of PSI score, and 0.8214 (95% CI, 0.8080–0.8348) of cox regression. In addition, the RSF model was associated with adverse clinical events during hospitalization, ICU admissions, and short-term mortality; (4) Conclusions: The RSF model by incorporating sST2 was more accurate than traditional methods in assessing the short-term prognosis of CAP patients.

KeywordClinical Stability Community-acquired Pneumonia Random Survival Forests Suppression Of Tumorigenicity 2
DOI10.3390/jcm11206015
URLView the original
Language英語English
Scopus ID2-s2.0-85140921199
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Document TypeJournal article
CollectionFaculty of Health Sciences
Affiliation1.Cancer Centre, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, 999078, Macao
2.MoE Frontiers Science Center for Precision Oncology, University of Macau, 999078, Macao
3.Department of Allergy and Clinical Immunology, Department of Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, China
First Author AffilicationCancer Centre;  University of Macau
Recommended Citation
GB/T 7714
Zhang, Teng,Zeng, Yifeng,Lin, Runpei,et al. Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia[J]. Journal of Clinical Medicine,2022,11(20).
APA Zhang, Teng,Zeng, Yifeng,Lin, Runpei,Xue, Mingshan,Liu, Mingtao,Li, Yusi,Zhen, Yingjie,Li, Ning,Cao, Wenhan,Wu, Sixiao,Zhu, Huiqing,Zhao, Qi,&Sun, Baoqing.(2022).Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia.Journal of Clinical Medicine,11(20).
MLA Zhang, Teng,et al."Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia".Journal of Clinical Medicine 11.20(2022).
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