Guru Sonpavde1, Juliane Manitz2, Chen Gao3, Darren Tayama4, Constanze Kaiser4, Daniel Hennessy2, Doris Makari3, Ashok Gupta3, Shaad Essa Abdullah3, Guenter Niegisch5, Jonathan E Rosenberg6, Dean F Bajorin6, Petros Grivas7, Andrea B Apolo8, Robert Dreicer9, Noah M Hahn10, Matthew D Galsky11, Andrea Necchi12, Sandy Srinivas13, Thomas Powles14, Toni K Choueiri1, Gregory R Pond15. 1. Dana-Farber Cancer Institute, Boston, Massachusetts. 2. EMD Serono, Inc., Billerica, Massachusetts. 3. AstraZeneca, Gaithersburg, Maryland. 4. Genentech, South San Francisco, California. 5. Department of Urology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany. 6. Memorial Sloan Kettering Cancer Center, New York, New York. 7. University of Washington, Seattle, Washington. 8. National Cancer Institute, National Institutes of Health, Bethesda, Maryland. 9. University of Virginia, Charlottesville, Virginia. 10. Johns Hopkins University School of Medicine, Baltimore, Maryland. 11. Department of Medicine, Icahn School of Medicine at Mount Sinai, Tisch Cancer Institute, New York, New York. 12. Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy. 13. Stanford University Medical Center, Palo Alto, California. 14. Royal Free Hospital, London, United Kingdom. 15. McMaster University, Hamilton, Ontario.
Abstract
PURPOSE: A prognostic model for overall survival of post-platinum patients with metastatic urothelial carcinoma receiving PD-1/PD-L1 inhibitors is necessary as existing models were constructed in the chemotherapy setting. MATERIALS AND METHODS: Patient level data were used from phase I/II trials evaluating PD-L1 inhibitors following platinum based chemotherapy for metastatic urothelial carcinoma. The derivation data set consisted of 2 phase I/II trials evaluating atezolizumab (405). Two phase I/II trials that evaluated avelumab (242) and durvalumab (198) comprised the validation data sets. Cox regression analyses evaluated the association of candidate prognostic factors with overall survival. Stepwise selection was used to select an optimal model using the derivation data set. Discrimination and calibration were assessed in the avelumab and durvalumab data sets. RESULTS: The 5 prognostic factors identified in the optimal model using the atezolizumab derivation data set were ECOG-PS (1 vs 0, HR 1.80, 95% CI 1.36-2.36), liver metastasis (HR 1.55, 95% CI 1.20-2.00), platelet count (HR 2.22; 95% CI 1.54-3.18), neutrophil-to-lymphocyte ratio (HR 1.94, 95% CI 1.57-2.40) and lactate dehydrogenase (HR 1.60, 95% CI 1.28-1.99). There was robust discrimination of survival between low, intermediate and high risk groups. The c-statistic was 0.692 in the derivation and 0.671 and 0.773 in the avelumab and durvalumab validation data sets, respectively. A web based interactive tool was developed to calculate the expected survival probabilities based on risk factors. CONCLUSIONS: A validated 5-factor model has satisfactory prognostic performance for survival across 3 PD-L1 inhibitors to treat metastatic urothelial carcinoma after platinum therapy and may assist in stratification, interpreting and designing trials incorporating PD-1/PD-L1 inhibitors in the post-platinum setting.
PURPOSE: A prognostic model for overall survival of post-platinumpatients with metastatic urothelial carcinoma receiving PD-1/PD-L1 inhibitors is necessary as existing models were constructed in the chemotherapy setting. MATERIALS AND METHODS:Patient level data were used from phase I/II trials evaluating PD-L1 inhibitors following platinum based chemotherapy for metastatic urothelial carcinoma. The derivation data set consisted of 2 phase I/II trials evaluating atezolizumab (405). Two phase I/II trials that evaluated avelumab (242) and durvalumab (198) comprised the validation data sets. Cox regression analyses evaluated the association of candidate prognostic factors with overall survival. Stepwise selection was used to select an optimal model using the derivation data set. Discrimination and calibration were assessed in the avelumab and durvalumab data sets. RESULTS: The 5 prognostic factors identified in the optimal model using the atezolizumab derivation data set were ECOG-PS (1 vs 0, HR 1.80, 95% CI 1.36-2.36), liver metastasis (HR 1.55, 95% CI 1.20-2.00), platelet count (HR 2.22; 95% CI 1.54-3.18), neutrophil-to-lymphocyte ratio (HR 1.94, 95% CI 1.57-2.40) and lactate dehydrogenase (HR 1.60, 95% CI 1.28-1.99). There was robust discrimination of survival between low, intermediate and high risk groups. The c-statistic was 0.692 in the derivation and 0.671 and 0.773 in the avelumab and durvalumab validation data sets, respectively. A web based interactive tool was developed to calculate the expected survival probabilities based on risk factors. CONCLUSIONS: A validated 5-factor model has satisfactory prognostic performance for survival across 3 PD-L1 inhibitors to treat metastatic urothelial carcinoma after platinum therapy and may assist in stratification, interpreting and designing trials incorporating PD-1/PD-L1 inhibitors in the post-platinum setting.
Entities:
Keywords:
carcinoma; drug therapy; neoplasm metastasis; platinum; prognosis; transitional cell
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