CAR-T(CAR-T)细胞疗法在非肿瘤性疾病中的应用
Chimeric antigen receptor T (CAR-T) cell therapy in non-oncological diseases.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Establishment and evaluation of a nomogram for predicting the survival outcomes of patients with diffuse large B-cell lymphoma based on International Prognostic Index scores and clinical indicators.
Establishment and evaluation of a nomogram for predicting the survival outcomes of patients with diffuse large B-cell lymphoma based on International Prognostic Index scores and clinical indicators.
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我们的研究确定了新诊断 DLBCL 患者的预后因素,以构建个体化风险预测模型,将 IPI 与常见临床指标相结合。我们的模型可能是一个有价值的工具,可用于预测接受标准一线治疗方案的 DLBCL 患者的预后。它使临床医生能够快速识别一些可能预后不良的患者,并为患者选择更积极的治疗,如 CAR-T 细胞免疫治疗和其他新药治疗,从而延长患者的 PFS 和 OS。
弥漫性大B细胞淋巴瘤(DLBCL)是最常见的侵袭性淋巴瘤,患者治疗结局差异很大。目前的国际预后指数(IPI)不足以区分预后不良的患者,而基因检测非常昂贵,因此应开发一种廉价的风险预测工具,供临床医生快速识别DLBCL患者的不良预后。
2008年至2017年在本院接受环磷酰胺、阿霉素、长春新碱和泼尼松(CHOP)联合或不联合利妥昔单抗(R-CHOP)治疗的DLBCL患者(n=420;18-80岁)被纳入研究。通过单因素和多因素Cox回归分析确定潜在的生存预测因素,并使用显著变量构建预测列线图。使用一致性指数(C-indexes)、校准曲线评估新的预测模型,并通过决策曲线分析(DCAs)评估其临床实用性。
5年总生存期(OS)率为70.62%,5年无进展生存期(PFS)率为59.02%。多因素Cox分析表明,IPI、Ki-67、淋巴细胞/单核细胞比值以及一线利妥昔单抗治疗与生存显著相关。C指数结果表明,包含这些变量的预测模型对OS(0.73 vs 0.67)和PFS(0.68 vs 0.63)的区分能力优于基于IPI的模型。校准图显示与观察结果和列线图预测具有良好的一致性。DCA证明了列线图的临床价值。
Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma, treatment outcomes of patients vary greatly. The current International Prognostic Index (IPI) is not enough to distinguish patients with poor prognosis, and genetic testing is very expensive, so a inexpensive risk prediction tool should be developed for clinicians to quickly identify the poor prognosis of DLBCL patients.
DLBCL patients (n=420; 18-80 years old) who received a combination of cyclophosphamide, adriamycin, vincristine, and prednisone (CHOP) with or without rituximab (R-CHOP) at our hospital between 2008 and 2017 were included in the study. Potential predictors of survival were determined by univariate and multivariate Cox regression analyses, and significant variables were used to construct predictive nomograms. The new prediction models were assessed using concordance indexes (C-indexes), calibration curves, and their clinical utility was assessed by decision curve analyses (DCAs).
The 5-year overall survival (OS) rate was 70.62% and the 5-year progression-free survival (PFS) rate was 59.02%. The multivariate Cox analysis indicated that IPI, Ki-67, the lymphocyte/monocyte ratio, and first-line treatment with rituximab were significantly associated with survival. The C-index results indicated that a predictive model that included these variables had better discriminability for OS (0.73 vs . 0.67) and PFS (0.68 vs . 0.63) than the IPI-based model. The calibration plots showed good agreement with observations and nomogram predictions. The DCAs demonstrated the clinical value of the nomograms.
Our study identified prognostic factors in patients who were newly diagnosed with DLBCL to construct an individualized risk prediction model, combined IPI with common clinical indicators. Our model might be a valuable tool that could be used to predict the prognosis of DLBCL patients who receive standard first-line treatment regimens. It enables clinicians to quickly identify some patients with possible poor prognosis and choose more active treatment for patients, such as chimeric antigen receptor T-cell (CART) Immunotherapy and other new drugs therapy, so as to prolong the PFS and OS of patients.
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