scholarly journals Safety and Activity of Sorafenib in Addition to Vinflunine in Post‐Platinum Metastatic Urothelial Carcinoma (Vinsor): Phase I Trial

2018 ◽  
Vol 24 (6) ◽  
pp. 745
Author(s):  
Carl‐Henrik Shah ◽  
Helle Pappot ◽  
Mads Agerbæk ◽  
Karin Holmsten ◽  
Fredrik Jäderling ◽  
...  
2018 ◽  
Vol 17 (14) ◽  
pp. e3001 ◽  
Author(s):  
C.-H. Shah ◽  
H. Pappot ◽  
M. Agerbæk ◽  
K. Holmsten ◽  
F. Jäderling ◽  
...  

2019 ◽  
Vol 38 (4) ◽  
pp. 1056-1066 ◽  
Author(s):  
Shunji Takahashi ◽  
Motohide Uemura ◽  
Tomokazu Kimura ◽  
Yoshihide Kawasaki ◽  
Atsushi Takamoto ◽  
...  

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. e15527-e15527
Author(s):  
Andrea Borghese Apolo ◽  
Howard L. Parnes ◽  
Ravi Amrit Madan ◽  
James L. Gulley ◽  
Jane B. Trepel ◽  
...  

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4552-4552 ◽  
Author(s):  
Guru Sonpavde ◽  
Juliane Manitz ◽  
Chen Gao ◽  
Daniel Hennessy ◽  
Doris Makari ◽  
...  

4552 Background: A prognostic model for overall survival (OS) of metastatic urothelial carcinoma (mUC) was previously reported in the setting of post-platinum atezolizumab (Pond GR, GU ASCO 2018). This model was limited by employing only atezolizumab treated patients (pts), small size of the validation dataset and unclear applicability to other PD-1/L1 inhibitors. Hence, we constructed a robust prognostic model utilizing the combined atezolizumab cohort as the discovery dataset and used 2 separate validation datasets comprised of post-platinum avelumab or durvalumab treated pts. Methods: The discovery dataset consisted of pt level data from 2 phase I/II trials (IMvigor210 and PCD4989g) evaluating atezolizumab (n = 405). Pts enrolled on 2 separate phase I/II trials, EMR 100070-001 that evaluated post-platinum avelumab (n = 242) and CD1108 that evaluated durvalumab (n = 189) comprised the validation datasets. Cox regression analyses evaluated the association of candidate prognostic factors with OS. Factors were dichotomized and laboratory values were normalized by logarithmic transformation. Stepwise selection was employed to propose an optimal model using the discovery dataset. Discrimination and calibration were assessed in the avelumab and durvalumab datasets following the validation procedure by Royston and Altman (2013). Results: The 5 factors included in the optimal prognostic model in the discovery dataset were ECOG-PS (1 vs. 0; HR 1.80; 95% CI [1.36-2.36]), presence/absence of liver metastasis (HR 1.55; 95% CI [1.20-2.00]), number of platelets (HR 2.22; 95% CI [1.54-3.18]), neutrophil-lymphocyte ratio (NLR; HR 1.94; 95% CI [1.57-2.40]) and lactate dehydrogenase (LDH; HR 1.60; 95% CI [1.28-1.99]). There was robust discrimination of survival between low, intermediate and high-risk groups based on 0-1, 2-3 and 4 factors. The concordance of survival was 0.692 in the discovery and 0.671 and 0.775 in the avelumab and durvalumab validation datasets, respectively. Acceptable or good calibration of expected 1-year survival rate was observed. Conclusions: A 5-factor prognostic model is prognostic for survival across 3 different PD-L1 inhibitors (atezolizumab, avelumab, durvalumab) in this large study totaling 836 pts overall in the setting of post-platinum therapy for mUC. This model may assist in prognostic stratification and interpreting nonrandomized trials of post-platinum PD1/L1 inhibitors.


2021 ◽  
Vol 32 ◽  
pp. S718-S719
Author(s):  
C.J. Pobel ◽  
D. Teyssonneau ◽  
A. Procureur ◽  
L. Verlingue ◽  
F. Facchinetti ◽  
...  

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