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

彭布罗利珠单抗 膀胱癌 医学 膀胱切除术 内科学 逻辑回归 肿瘤科 阶段(地层学) 生物标志物 癌症 免疫疗法 古生物学 生物化学 生物 化学
作者
Marco Bandini,Jeffrey S. Ross,Daniele Raggi,Andrea Gallina,Maurizio Colecchia,Roberta Lucianò,Patrizia Giannatempo,Elena Farè,Filippo Pederzoli,Marco Bianchi,Renzo Colombo,Giorgio Gandaglia,Nicola Fossati,Laura Marandino,Umberto Capitanio,Federico Dehò,Siraj M. Ali,Russell W. Madison,Jon Chung,Andrea Salonia,Alberto Briganti,Francesco Montorsi,Andrea Necchi
出处
期刊:Journal of the National Cancer Institute [Oxford University Press]
卷期号:113 (1): 48-53 被引量:38
标识
DOI:10.1093/jnci/djaa076
摘要

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.

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