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

  • 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 Deho',
  • Siraj M Ali,
  • Russell Madison,
  • Jon H Chung,
  • Andrea Salonia,
  • Alberto Briganti,
  • Francesco Montorsi ,
  • Andrea Necchi

Publication: Journal of the National Cancer Institute, Volume 113, Issue 1, January 2021


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.


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.


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%.


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.

Commentary by Dr. Evanguelos Xylinas

Several recent phase 2 trials have investigated the potential benefit associated with immune checkpoint inhibitors administration in the neoadjuvant setting for muscle-invasive bladder cancer, showing rates of pathologic complete response (pCR) of 31% and 37% with 2 cycles of atezolizumab and 3 cycles of pembrolizumab, respectively. However, unlike neoadjuvant chemotherapy, biomarkers that predict pCR are needed in order to select the patients that are going to benefit the most from this therapeutic strategy.

A recently published biomarker analysis of the PURE-01 study in the Journal of the National Cancer Institute investigated the association of clinical and tumour biomarkers with pCR after pembrolizumab. PURE-01 was an open-label, single-arm, phase 2 study that enrolled patients scheduled for radical cystectomy (RC) for a clinical T2-4aN0M0 bladder cancer. The pCR (pT0N0) was defined as the absence of residual tumour in examined tissue from RC and pelvic lymph node dissection. The study included 112 patients who underwent comprehensive genomic profiling and PD-L1 combined positive score (CPS) assessment. 

The authors conducted multivariable logistic regression analyses (MVA) to evaluate baseline clinical T-stage and tumor biomarkers associated with pCR. Only CPS was a statistically significant predictor of pCR (odds ratio [OR]: 1.02, 95% CI: 1.01-1.04, p=0.005). A calculator for pCR probability was developed using the coefficients of the multivariable model, including TMB, CPS, and cT-stage (based on preoperative MRI). The c-index of the pCR probability calculator was 0.77. The study evaluated the contribution of TMB and CPS in determining the probability of pCR. Interestingly, very high TMB levels were found to be a statistically significant predictor for pCR regardless of the PD-L1 expression. Only in tumours with high TMB (>11 Mut/Mb), the CPS values had a linear impact on pCR probability. This impact was not observed in low-TMB tumors.