Guo Yiwei, Lian Jie, Chen Yao, Quan Lina, Guo Xiuchen, Zhang Jingbo, Liu Zhiqiang, Liu Aichun
Hematology Department, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China.
Outpatient Chemotherapy Department, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China.
Hematology. 2025 Dec;30(1):2445395. doi: 10.1080/16078454.2024.2445395. Epub 2024 Dec 26.
Relapsed/Refractory (R/R) diffuse large B-cell lymphoma (DLBCL) represents a subgroup with a high incidence and dismal prognosis. Currently, there is a lack of robust models for predicting R/R DLBCL. Therefore, we conducted a retrospective study to identify key determinants to be incorporated into a novel nomogram to enhance the identification of DLBCL patients at elevated risk of refractoriness/recurrence.
We included 293 newly-diagnosed DLBCL patients from Harbin Medical University Cancer Hospital, collected from 2008-2017. Patients were randomly divided into a training cohort (n = 206) and a validation cohort (n = 87) at a 7:3 ratio. The training cohort underwent univariable analysis to select variables for a binary logistic regression model. These variables were also prioritized using a random forest algorithm. The developed nomogram was evaluated with the receiver-operator characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) for its clinical utility.
Univariable analysis pinpointed several factors significantly associated with refractoriness/recurrence, including pathological subtype, lactate dehydrogenase (LDH), International Prognostic Index (IPI), treatment, absolute lymphocyte count (ALC), lymphocyte/monocyte ratio (LMR), and prognostic nutritional index (PNI). Binary logistic regression highlighted pathological subtype, LDH, treatment, and ALC as key predictors, which were incorporated into the nomogram. The nomogram showed excellent calibration and accuracy in both cohorts, and comparative DCA and ROC analysis demonstrated its superior net benefit and area under the curve (AUC) compared to traditional indexes like IPI, R-IPI, and NCCN-IPI.
This nomogram serves as a valuable tool for predicting the likelihood of refractoriness or recurrence in DLBCL patients.
复发/难治性(R/R)弥漫性大B细胞淋巴瘤(DLBCL)是一个发病率高且预后不良的亚组。目前,缺乏可靠的模型来预测R/R DLBCL。因此,我们进行了一项回顾性研究,以确定关键决定因素,纳入一个新的列线图,以加强对难治性/复发风险升高的DLBCL患者的识别。
我们纳入了2008年至2017年期间从哈尔滨医科大学附属肿瘤医院收集的293例新诊断的DLBCL患者。患者按7:3的比例随机分为训练队列(n = 206)和验证队列(n = 87)。训练队列进行单变量分析,以选择二元逻辑回归模型的变量。这些变量也使用随机森林算法进行优先级排序。使用受试者操作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)评估所开发列线图的临床效用。
单变量分析确定了几个与难治性/复发显著相关的因素,包括病理亚型、乳酸脱氢酶(LDH)、国际预后指数(IPI)、治疗、绝对淋巴细胞计数(ALC)、淋巴细胞/单核细胞比率(LMR)和预后营养指数(PNI)。二元逻辑回归突出了病理亚型、LDH、治疗和ALC作为关键预测因素,并将其纳入列线图。列线图在两个队列中均显示出良好的校准和准确性,比较DCA和ROC分析表明,与IPI、R-IPI和NCCN-IPI等传统指标相比,其净效益和曲线下面积(AUC)更优。
该列线图是预测DLBCL患者难治性或复发可能性的有价值工具。