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预测新辅助帕博利珠单抗治疗肌层浸润性膀胱癌后的病理完全缓解。

Predicting the Pathologic Complete Response After Neoadjuvant Pembrolizumab in Muscle-Invasive Bladder Cancer.

机构信息

San Raffaele Hospital and Scientific Institute, Milan, Italy.

Foundation Medicine, Cambridge, MA, USA.

出版信息

J Natl Cancer Inst. 2021 Jan 4;113(1):48-53. doi: 10.1093/jnci/djaa076.

Abstract

BACKGROUND

In the PURE-01 study (NCT02736266), we aimed to evaluate the ability to predict the pathologic complete response (pT0N0) after pembrolizumab by using clinical and tumor biomarkers.

METHODS

In an open-label, single-arm, phase 2 study, 3 courses of 200 mg pembrolizumab preceding radical cystectomy were administered in patients with T2-4aN0M0 muscle-invasive bladder cancer. The analyses included a comprehensive genomic profiling and programmed cell-death-ligand-1 (PD-L1)-combined positive score assessment (CPS; Dako 22C3 antibody) of pre- and posttherapy samples. Multivariable logistic regression analyses evaluated baseline clinical T stage and tumor biomarkers in association with pT0N0 response. Corresponding coefficients were used to develop a calculator of pT0N0 response based on the tumor mutational burden (TMB), CPS, and the clinical T stage. Decision-curve analysis was also performed. All statistical tests were 2-sided.

RESULTS

From February 2017 to June 2019, 112 patients with biomarker data were enrolled (105 with complete TMB and CPS data). Increasing TMB and CPS values featured a linear association with logistic pT0N0 probabilities (P = .02 and P = .004, respectively). For low TMB values (≤11 mut/Mb, median value, n = 53), pT0N0 probability was not associated with increasing CPS. Conversely, for high TMB values (>11 mut/Mb, n = 52), pT0N0 was statistically significantly associated with higher CPS (P = .004). The C index of the pT0N0 probability calculator was 0.77. On decision-curve analysis, the net benefit of the model was higher than the "treat-all" option within the clinically meaningful threshold probabilities of 40%-50%.

CONCLUSIONS

The study presents a composite biomarker-based pT0N0 probability calculator that reveals the complex interplay between TMB and CPS, added to the clinical T stage.

摘要

背景

在 PURE-01 研究(NCT02736266)中,我们旨在通过使用临床和肿瘤生物标志物来评估帕博利珠单抗治疗后病理完全缓解(pT0N0)的预测能力。

方法

在一项开放标签、单臂、2 期研究中,3 个疗程的 200mg 帕博利珠单抗在 T2-4aN0M0 肌肉浸润性膀胱癌患者行根治性膀胱切除术之前给予。分析包括综合基因组分析和程序性细胞死亡配体-1(PD-L1)联合阳性评分(CPS;Dako 22C3 抗体)的治疗前和治疗后样本。多变量逻辑回归分析评估了与 pT0N0 反应相关的基线临床 T 期和肿瘤生物标志物。相应的系数用于开发基于肿瘤突变负担(TMB)、CPS 和临床 T 期的 pT0N0 反应计算器。还进行了决策曲线分析。所有统计检验均为双侧检验。

结果

从 2017 年 2 月至 2019 年 6 月,入组了 112 名有生物标志物数据的患者(105 名患者有完整的 TMB 和 CPS 数据)。TMB 和 CPS 值的增加与逻辑 pT0N0 概率呈线性相关(P=.02 和 P=.004)。对于低 TMB 值(≤11 mut/Mb,中位数,n=53),pT0N0 概率与 CPS 的增加无关。相反,对于高 TMB 值(>11 mut/Mb,n=52),pT0N0 与更高的 CPS 统计学显著相关(P=.004)。pT0N0 概率计算器的 C 指数为 0.77。在决策曲线分析中,在 40%-50%的临床有意义阈值概率范围内,该模型的净获益高于“治疗所有”选项。

结论

该研究提出了一种基于复合生物标志物的 pT0N0 概率计算器,揭示了 TMB 和 CPS 与临床 T 期之间的复杂相互作用。

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