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[Systemic Inflammatory Markers Can Improve Survival Prediction of Patients with Diffuse Large B-Cell Lymphoma: Model
Ya-Jiao Liu1,2, Li Sheng1,2, Jing-Fen Zhou1,2
1Department of Hematology, The Affiliated Hospital of Jiangnan University, Wuxi 214000, Jiangsu Province, China.
Objective:
To establish a model to predict the overall survival (OS) rate of patients with diffuse large B-cell lymphoma (DLBCL) based on systemic inflammatory indicators, and study whether the new model combined with inflammatory related parameters is more effective than the conventional model using only clinical factors to predict the OS of patients with DLBCL.
Methods:
The clinical data of 213 patients with DLBCL were analyzed retrospectively. Backward stepwise Cox regression analysis was used to screen independent prognostic factors related to OS, and a nomogram for predicting OS was constructed based on these factors. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to evaluate the fitting of the model, the consistency index (C-index), area under receiver operating characteristic (ROC) curve (AUC) and calibration curve were used to evaluate the prediction accuracy of nomogram, and decision curve analysis (DCA) and Kaplan Meier curve were used to evaluate the clinical practicability of nomogram.
Results:
Multivariate analysis confirmed that age, ECOG PS score, serum lactate dehydrogenase (LDH) level, systemic immune inflammatory index (SII), and prognostic nutritional index (PNI) were used to construct the nomogram. The AIC and BIC of the nomogram were lower than the International Prognostic Index (IPI) and the National Comprehensive Cancer Network (NCCN)-IPI, indicating that the nomogram had better goodness of fit. The C-index and AUC of the nomogram were higher than IPI and NCCN-IPI, indicating that the prediction accuracy of the nomogram had been significantly improved, and the calibration curve showed that the prediction results were in good agreement with the actual survival results. DCA showed that the nomogram had better clinical net income. Kaplan Meier curve showed that patients could be well divided into low-risk, medium-risk and high-risk groups according to the nomogram score (P < 0.001).
Conclusion:
The nomogram combined with inflammatory indicators can accurately predict the individual survival probability of DLBCL patients.
