Université de Paris, IAME, INSERM, F-75018 Paris, France.
UMR 1246, Université de Tours, Université de Nantes, Inserm SPHERE, Tours, France.
Clin Pharmacol Ther. 2019 Oct;106(4):810-820. doi: 10.1002/cpt.1450. Epub 2019 Jul 5.
We characterized the association between tumor size kinetics and survival in patients with advanced urothelial carcinoma treated with atezolizumab (anti-programmed death-ligand 1, Tecentriq) using a joint model. The model, developed on data from 309 patients of a phase II clinical trial, identified the time-to-tumor growth and the instantaneous changes in tumor size as the best on-treatment predictors of survival. On the validation dataset containing data from 457 patients from a phase III study, the model predicted individual survival probability using 3-month or 6-month tumor size follow-up data with an area under the receptor-occupancy curve between 0.75 and 0.84, as compared with values comprised between 0.62 and 0.75 when the model included only information available at treatment initiation. Including tumor size kinetics in a relevant statistical framework improves the prediction of survival probability during immunotherapy treatment and may be useful to identify most-at-risk patients in "real-time."
我们使用联合模型来描述接受阿替利珠单抗(抗程序性死亡配体 1,Tecentriq)治疗的晚期尿路上皮癌患者的肿瘤大小变化动力学与生存之间的关系。该模型基于一项 II 期临床试验的 309 名患者的数据建立,结果表明肿瘤生长时间和肿瘤大小的瞬时变化是生存的最佳治疗预测因素。在包含来自 III 期研究的 457 名患者数据的验证数据集上,该模型使用 3 个月或 6 个月的肿瘤大小随访数据来预测个体的生存概率,受体占有率曲线下面积在 0.75 至 0.84 之间,而当模型仅包含治疗开始时可用的信息时,该值在 0.62 至 0.75 之间。在相关的统计框架中纳入肿瘤大小变化动力学可提高免疫治疗期间生存概率的预测能力,并可能有助于实时识别风险最高的患者。