■本研究试图了解临床因素和炎症生物标志物如何影响粘膜相关淋巴组织(MALT)淋巴瘤的预后,并开发预测性列线图以协助临床实践。
■我们对2011年1月至2021年10月的183例新诊断的MALT淋巴瘤患者进行了回顾性研究,随机分为两组:训练队列(75%)和验证队列(25%)。将最小绝对收缩和选择操作员(LASSO)回归分析与多变量Cox回归分析相结合,以构建用于预测MALT淋巴瘤患者无进展生存期(PFS)的列线图。要评估列线图模型的准确性,接收器工作特性(ROC)曲线下的面积,校正曲线,采用决策曲线分析(DCA)。
■PFS与安娜堡阶段显著相关,靶向治疗,放射治疗,MALT淋巴瘤的血小板淋巴细胞比率(PLR)。将这四个变量组合以建立列线图来预测三年和五年的PFS率。重要的是,对于3年和5年PFS,我们的列线图具有良好的预测价值,在训练队列中ROC曲线下面积(AUC)值为0.841和0.763,在验证队列中为0.860和0.879。分别。此外,3年和5年PFS校准曲线显示,预测与实际复发概率高度一致.此外,DCA证明了该列线图的净临床益处及其准确识别高风险患者的能力。
■新的列线图模型可以准确预测MALT淋巴瘤患者的预后,并帮助临床医生设计个体化治疗方案。
UNASSIGNED: The present study sought to understand how clinical factors and inflammatory biomarkers affected the prognosis of mucosa-associated lymphoid tissue (MALT) lymphoma and develop a predictive nomogram to assist in clinical practice.
UNASSIGNED: We conducted a retrospective study on 183 cases of newly diagnosed MALT lymphoma from January 2011 to October 2021, randomly divided into two groups: a training cohort (75%); and a validation cohort (25%). The least absolute shrinkage and selection operator (LASSO) regression analysis was combined with multivariate Cox regression analysis to construct a nomogram for predicting the progression-free survival (PFS) in patients with MALT lymphoma. To evaluate the accuracy of the nomogram model, the area under the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used.
UNASSIGNED: The PFS was significantly associated with the Ann Arbor Stage, targeted therapy, radiotherapy, and platelet-to-lymphocyte ratio (PLR) in MALT lymphoma. These four variables were combined to establish a nomogram to predict the PFS rates at three and five years. Importantly, our nomogram yielded good predictive value with area under the ROC curve (AUC) values of 0.841 and 0.763 in the training cohort and 0.860 and 0.879 in the validation cohort for the 3-year and 5-year PFS, respectively. Furthermore, the 3-year and 5-year PFS calibration curves revealed a high degree of consistency between the prediction and the actual probability of relapse. Additionally, DCA demonstrated the net clinical benefit of this nomogram and its ability to identify high-risk patients accurately.
UNASSIGNED: The new nomogram model could accurately predict the prognosis of MALT lymphoma patients and assist clinicians in designing individualized treatments.