[Systemic Inflammatory Markers Can Improve Survival Prediction of Patients with Diffuse Large B-Cell Lymphoma: Model Development and Evaluation].

Ya-Jiao Liu, Li Sheng, Jing-Fen Zhou, Hai-Ying Hua
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Abstract

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.

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[全身炎症标志物可改善弥漫大 B 细胞淋巴瘤患者的生存预测:模型开发与评估]。
目的建立一个基于全身炎症指标预测弥漫大B细胞淋巴瘤(DLBCL)患者总生存率(OS)的模型,并研究结合炎症相关参数的新模型是否比仅使用临床因素的传统模型更有效地预测DLBCL患者的OS:方法:回顾性分析213例DLBCL患者的临床数据。方法:对 213 例 DLBCL 患者的临床数据进行回顾性分析,采用逆向逐步 Cox 回归分析筛选出与 OS 相关的独立预后因素,并根据这些因素构建了预测 OS 的提名图。采用阿凯克信息准则(AIC)和贝叶斯信息准则(BIC)评价模型的拟合程度,采用一致性指数(C-index)、接收者操作特征曲线下面积(AUC)和校正曲线评价提名图的预测准确性,采用决策曲线分析(DCA)和卡普兰-梅耶曲线评价提名图的临床实用性:多变量分析证实,年龄、ECOG PS评分、血清乳酸脱氢酶(LDH)水平、全身免疫炎症指数(SII)和预后营养指数(PNI)被用于构建提名图。提名图的AIC和BIC均低于国际预后指数(IPI)和美国国立综合癌症网络(NCCN)-IPI,表明提名图具有更好的拟合度。提名图的 C 指数和 AUC 均高于 IPI 和 NCCN-IPI,表明提名图的预测准确性显著提高,校准曲线显示预测结果与实际生存结果吻合良好。DCA显示,提名图具有更好的临床净收益。卡普兰-梅耶尔曲线显示,根据提名图评分,患者可以很好地被分为低危、中危和高危组(P < 0.001):结论:提名图结合炎症指标可准确预测DLBCL患者的个体生存概率。
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中国实验血液学杂志
中国实验血液学杂志 Medicine-Medicine (all)
CiteScore
0.40
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7331
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[Effect and Influencing Factors of Peripheral Blood Hematopoietic Stem Cells Collection from Unrelated Donors]. [Effect of Endothelial Activation and Stress Index(EASIX) on Prognosis of Peripheral T-Cell Lymphoma Patient]. [Effect of JMJD3-IRF4 Signaling Pathway-Mediated Macrophage Polarization on the Malignant Biological Behavior of Multiple Myeloma Cells]. [Effect of Tumor Suppressor Gene Kmt2c Heterozygous Deletion on Hematopoietic System in Mice]. [Effects of ATG5 and ATG7 Knockout on Ferroptosis Sensitivity of RPMI-8226 Cells].
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