Objective: To retrospectively analyze clinical characteristics and survival time of patients with diffuse large B-cell lymphoma (DLBCL), detect prognosis-related markers, and establish a nomogram prognostic model of clinical factors combined with biomarkers.
Methods: One hundred and thirty-seven patients with DLBCL were included in this study from January 2014 to March 2019 in the First Affiliated Hospital of Nanchang University. The expression of GCET1, LMO2, BCL-6, BCL-2 and MYC protein were detected by immunohistochemistry (IHC), then the influences of these proteins on the survival and prognosis of the patients were analyzed. Univariate and multivariate Cox regression analysis were used to gradually screen the prognostic factors in nomogram model. Finally, nomogram model was established according to the result of multivariate analysis.
Results: The positive expression of GCET1 protein was more common in patients with Ann Arbor staging I/II (P =0.011). Compared with negative patients, patients with positive expression of LMO2 protein did not often show B symptoms (P =0.042), and could achieve better short-term curative effect (P =0.005). The overall survival (OS) time of patients with positive expression of LMO2 protein was significantly longer than those with negative expression of LMO2 protein (P =0.018), though the expression of LMO2 protein did not correlate with progression-free survival (PFS) (P >0.05). However, the expression of GCET1 protein had no significant correlation with OS and PFS. Multivariate Cox regression analysis showed that nomogram model consisted of 5 prognostic factors, including international prognostic index (IPI), LMO2 protein, BCL-2 protein, MYC protein and rituximab. The C-index applied to the nomogram model for predicting 4-year OS rate was 0.847. Moreover, the calibrated curve of 4-year OS showed that nomogram prediction had good agreement with actual prognosis.
Conclusion: The nomogram model incorporating clinical characteristics and IHC biomarkers has good discrimination and calibration, which provides a useful tool for the risk stratification of DLBCL.
题目: 基于IHC标志物和IPI评分的弥漫大B细胞淋巴瘤预后模型的建立和临床意义.
目的: 回顾性分析弥漫大B细胞淋巴瘤（DLBCL）患者的临床特征、生存期，检测预后相关标志物，建立临床因素与生物标志物相结合的Nomogram预后模型。.
方法: 选取南昌大学第一附属医院2014年1月至2019年3月收治的137例DLBCL患者，免疫组织化学染色检测GCET1、LMO2、BCL-6、BCL-2和MYC蛋白表达，并分析这些蛋白对患者生存和预后的影响，单因素和多因素分析用于逐步筛选Nomogram模型中的预后因素，最终根据多因素分析结果建立Nomogram模型。.
结果: GCET1蛋白表达阳性多见于Ann Arbor分期I/II期患者（P =0.011）。LMO2蛋白表达阳性患者与阴性患者相比较少出现B症状（P=0.042），且能获得更好的近期疗效（P =0.005）。LMO2蛋白表达阳性患者总生存（OS）时间显著长于阴性患者（P =0.018），但LMO2蛋白表达与无进展生存（PFS）时间无显著相关（P >0.05），而GCET1蛋白表达与OS、PFS时间均无显著相关。多因素分析结果显示，Nomogram模型包括IPI评分、BCL-2蛋白、MYC蛋白、LMO2蛋白和利妥昔单抗5个预后因素。Nomogram模型预测4年OS率的C指数为0.847，校准曲线显示列线图预测与实际预后有良好的一致性。.
结论: 结合临床因素和免疫组织化学染色标志物的Nomogram模型有较好的区分度和校准度，为DLBCL的预后评估提供了有效工具。.
Keywords: diffuse large B-cell lymphoma; immunohistochemistry; nomogram; prognosis.