[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) 患者的生命。然而，区分可能和不可能做出反应的患者仍然是一个临床挑战。我们提出了第一个使用 177Lu-PSMA-617 建立的多变量结果模型，该模型使用 VISION 的数据构建，VISION 是一项旨在提高总体生存率的大型前瞻性 3 期临床试验。具有渐进性后雄激素受体途径抑制剂和紫杉烷前列腺特异性膜抗原 (PSMA) 的成人-阳性 mCRPC 接受 177Lu-PSMA-617 加上协议允许的护理标准 (SoC) 或单独的 SoC。在这项事后分析中，构建并评估了总生存期 (OS) 和放射学无进展生存期 (rPFS) 的多变量 Cox 比例风险模型，以及前列腺特异性抗原反应（下降≥50%；PSA50）的逻辑回归模型使用 C 指数或接受者操作特征 (ROC) 分析和引导验证。构建列线图用于可视化。患者在 2018 年 6 月至 2019 年 10 月期间被随机分组​​。177Lu-PSMA-617 组所有 551 名患者的数据均在多变量模型中进行了分析。 OS 列线图（C 指数，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)、自诊断以来的时间、阿片类镇痛药的使用、天冬氨酸转氨酶、血红蛋白、淋巴细胞计数、淋巴结、乳酸脱氢酶 (LDH)、碱性磷酸酶 (ALP) 和中性粒细胞计数中存在 PSMA 阳性病变。 rPFS 列线图（C 指数，0.68；0.65-0.72）包括 SUVmax、自诊断以来的时间、阿片类镇痛药的使用、淋巴细胞计数、计算机断层扫描显示的肝转移、LDH 和 ALP。 PSA50 列线图（ROC 曲线下面积，0.72；95% CI，0.68-0.77）包括 SUVmax、淋巴细胞计数和 ALP。 OS 和 rPFS 模型的性能在重建时不包括 SUVmax。这些使用 177Lu-PSMA-617 的结果模型是首次使用前瞻性 3 期数据构建的。他们表明，反映患者和肿瘤状态的治疗前实验室、临床和成像参数的组合会影响结果。这些模型对于帮助治疗选择、患者管理和临床试验设计非常重要。Novartis.© 2024 作者。

[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.© 2024 The Authors.