多变量模型分析[177Lu]Lu-PSMA-617的临床结局：VISION Ⅲ期试验的分析

[177Lu]Lu-PSMA-617（177Lu-PSMA-617）在VISION（NCT03511664）中延长了转移性去势抵抗性前列腺癌（mCRPC）患者的生存期。然而，区分可能响应与不太可能响应的患者仍是临床挑战。本文首次提出基于VISION这项大规模前瞻性Ⅲ期临床试验数据构建的多变量结局模型，此试验为总生存期提供统计支持。成人患者在接受抗雄激素受体通路抑制剂和紫杉醇治疗后病情进展，且肿瘤表现出PSMA阳性，随机接受177Lu-PSMA-617联合协议允许的标准治疗（SoC）或单一SoC。在这项事后分析中，构建并评估了全生存期（OS）、影像学无进展生存期（rPFS）的多变量Cox比例风险模型，以及前列腺特异性抗原（PSA）反应（≥50%的下降，PSA50）的逻辑回归模型，使用C-index或受试者工作特征（ROC）曲线分析并通过自助法验证。采用列线图进行可视化。患者于2018年6月至2019年10月随机分配，分析了177Lu-PSMA-617组全部551例患者数据。OS列线图（C-index为0.73；95%置信区间[CI]，0.70-0.76）包括全身最大标准化摄取值（SUVmax）、诊断起始时间、阿片类镇痛药使用、天冬氨酸氨基转移酶、血红蛋白、淋巴细胞计数、淋巴结中PSMA阳性病灶的存在、乳酸脱氢酶（LDH）、碱性磷酸酶（ALP）及中性粒细胞数。rPFS列线图（C-index为0.68；0.65-0.72）包括SUVmax、诊断起始时间、阿片类镇痛药使用、淋巴细胞计数、肝转移（CT检测）、LDH及ALP。PSA50列线图（ROC曲线下面积为0.72；95% CI，0.68-0.77）包括SUVmax、淋巴细胞计数和ALP。当排除SUVmax后，OS和rPFS模型的性能依然保持。该类模型是首个利用前瞻性Ⅲ期数据构建的与177Lu-PSMA-617相关的结局模型，它们显示预处理的实验室、临床和影像参数的结合，反映患者和肿瘤状态，共同影响治疗结局。这些模型对于辅助治疗选择、患者管理及临床试验设计具有重要意义。诺华公司。

[177Lu]Lu-PSMA-617 (177Lu-PSMA-617) prolonged life in patients with metastatic castration-resistant prostate cancer (mCRPC) in VISION (NCT03511664). However, distinguishing between patients likely and unlikely to respond remains a clinical challenge. We present the first multivariable models of outcomes with 177Lu-PSMA-617 built using data from VISION, a large prospective phase 3 clinical trial powered for overall survival.Adults with progressive post androgen receptor pathway inhibitor and taxane prostate-specific membrane antigen (PSMA)-positive mCRPC received 177Lu-PSMA-617 plus protocol-permitted standard of care (SoC) or SoC alone. In this post hoc analysis, multivariable Cox proportional hazards models of overall survival (OS) and radiographic progression-free survival (rPFS), and a logistic regression model of prostate-specific antigen response (≥50% decline; PSA50) were constructed and evaluated using C-index or receiver operating characteristic (ROC) analyses with bootstrapping validation. Nomograms were constructed for visualisation.Patients were randomised between June 2018 and October 2019. Data from all 551 patients in the 177Lu-PSMA-617 arm were analysed in multivariable modelling. The OS nomogram (C-index, 0.73; 95% confidence interval [CI], 0.70-0.76) included whole-body maximum standardised uptake value (SUVmax), time since diagnosis, opioid analgesic use, aspartate aminotransferase, haemoglobin, lymphocyte count, presence of PSMA-positive lesions in lymph nodes, lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and neutrophil count. The rPFS nomogram (C-index, 0.68; 0.65-0.72) included SUVmax, time since diagnosis, opioid analgesic use, lymphocyte count, presence of liver metastases by computed tomography, LDH, and ALP. The PSA50 nomogram (area under ROC curve, 0.72; 95% CI, 0.68-0.77) included SUVmax, lymphocyte count and ALP. Performances of the OS and rPFS models were maintained when they were reconstructed excluding SUVmax.These models of outcomes with 177Lu-PSMA-617 are the first built using prospective phase 3 data. They show that a combination of pretreatment laboratory, clinical, and imaging parameters, reflecting both patient and tumour status, influences outcomes. These models are important for aiding treatment selection, patient management, and clinical trial design.Novartis.