Prognostic Value of a Clinical Biochemistry-Based Nomogram for Coronavirus Disease 2019 - Yu, Jing; Nie, Lei; Wu, Dongde; Chen, Jian; Yang, Zhifeng; Zhang, Ling; Li, Dongqing; Zhou, Xia (Frontiers in Medicine, 2021)
Background: This study aimed to explore the predictive value of a clinical biochemistry-based Nomogram in COVID-19. Methods: The plasma or serum concentrations/levels of carcinoembryonic antigen (CEA) and other biomarkers (C-reactive protein (CRP), white blood cell (WBC), interleukin-6 (IL-6), ferritin (Fer), procalcitonin (PCT), lymphocyte percentage (L%), D-dimer (D2), and neutrophils percentage (N%)) were assessed in 314 hospitalized patients with confirmed COVID-19. The area under curves was used to estimate the diagnostic and prognostic value for COVID-19. Cox and logistic regression analysis were used to estimate the independent prognostic risk factors for the survival of patients with COVID-19. Results: Receiver operating characteristic (ROC) curves were used to determine the area under the curve (AUC) values for CEA, IL-6, CRP, PCT, Fer, D-dimer levels and L%, N% and WBC to assess disease classification. The critical values for these markers above to predict severe disease type were then determined. The hazard ratio of prognosis for risk of COVID-19, identified CEA, WBC, CRP, PCT, Fer, D-dimer, Neu%, and L% as independent prognostic factors. For the nomogram of overall survival (OS), the C-index was 0.84, demonstrating the good discriminative performance. Conclusions: An OS Nomogram for the clinical diagnosis and treatment of COVID-19 was constructed using biomarkers. These data will be useful for the diagnosis, management, and therapy of COVID-19.