S Aeppli1, M Schmaus2, T Eisen3, B Escudier4, V Grünwald5, J Larkin6, D McDermott7, J Oldenburg8, C Porta9, B I Rini10, M Schmidinger11, C N Sternberg12, C Rothermundt13, P M Putora14. 1. Division of Oncology and Haematology, Kantonsspital St. Gallen, St. Gallen, Switzerland. Electronic address: Stefanie.aeppli@kssg.ch. 2. Department of Radiotherapy and Radiation Oncology, University Medical Centre Hamburg Eppendorf, Hamburg, Germany. 3. Department of Oncology, Cambridge University Hospitals National Health Service Foundation, Cambridge, UK. 4. Gustave Roussy, Villejuif, France. 5. Interdisciplinary GU Oncology, Clinic for Urology and Clinic for Tumour Research, University Hospital Essen, Essen, Germany. 6. The Royal Marsden Hospital, London, UK. 7. Beth Israel Deaconess Medical Centre, Boston, USA. 8. Department of Oncology, Akershus University Hospital and Medical Faculty of University of Oslo, Oslo, Norway. 9. Department of Biomedical Sciences and Human Oncology, University of Bari 'A. Moro', Bari, Italy. 10. Division of Hematology and Oncology, Vanderbilt University Medical Centre, Nashville, USA. 11. Department of Medicine I, Clinical Division of Oncology and Comprehensive Cancer Centre, Medical University of Vienna, Austria. 12. Division of Hematology and Oncology, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, USA. 13. Division of Oncology and Haematology, Kantonsspital St. Gallen, St. Gallen, Switzerland. 14. Department of Radiation Oncology, Kantonsspital St. Gallen, St. Gallen, Switzerland; Department of Radiation Oncology, University of Bern, Bern, Switzerland.
Abstract
BACKGROUND: The treatment landscape of metastatic clear cell renal cell carcinoma (mccRCC) has been transformed by targeted therapies with tyrosine kinase inhibitors (TKI) and more recently by the incorporation of immune checkpoint inhibitors (ICI). Today, a spectrum of single agent TKI to TKI/ICI and ICI/ICI combinations can be considered and the choice of the best regimen is complex. MATERIALS AND METHODS: We performed an updated decision-making analysis among 11 international kidney cancer experts. Each expert provided their treatment strategy and relevant decision criteria in the first line treatment of mccRCC. After the collection of all input a list of unified decision criteria was determined and compatible decision trees were created. We used a methodology based on diagnostic nodes, which allows for an automated cross-comparison of decision trees, to determine the most common treatment recommendations as well as deviations. RESULTS: Diverse parameters were considered relevant for treatment selection, various drugs and drug combinations were recommended by the experts. The parameters, chosen by the experts, were performance status, International Metastatic renal cell carcinoma Database Consortium (IMDC) risk group, PD-L1 status, zugzwang and contraindication to immunotherapy. The systemic therapies selected for first line treatment were sunitinib, pazopanib, tivozanib, cabozantinib, ipilimumab/nivolumab or pembrolizumab/axitinib. CONCLUSION: A wide spectrum of treatment recommendations based on multiple decision criteria was demonstrated. Significant inter-expert variations were observed. This demonstrates how data from randomized trials are implemented differently when transferred into daily practice.
BACKGROUND: The treatment landscape of metastatic clear cell renal cell carcinoma (mccRCC) has been transformed by targeted therapies with tyrosine kinase inhibitors (TKI) and more recently by the incorporation of immune checkpoint inhibitors (ICI). Today, a spectrum of single agent TKI to TKI/ICI and ICI/ICI combinations can be considered and the choice of the best regimen is complex. MATERIALS AND METHODS: We performed an updated decision-making analysis among 11 international kidney cancer experts. Each expert provided their treatment strategy and relevant decision criteria in the first line treatment of mccRCC. After the collection of all input a list of unified decision criteria was determined and compatible decision trees were created. We used a methodology based on diagnostic nodes, which allows for an automated cross-comparison of decision trees, to determine the most common treatment recommendations as well as deviations. RESULTS: Diverse parameters were considered relevant for treatment selection, various drugs and drug combinations were recommended by the experts. The parameters, chosen by the experts, were performance status, International Metastatic renal cell carcinoma Database Consortium (IMDC) risk group, PD-L1 status, zugzwang and contraindication to immunotherapy. The systemic therapies selected for first line treatment were sunitinib, pazopanib, tivozanib, cabozantinib, ipilimumab/nivolumab or pembrolizumab/axitinib. CONCLUSION: A wide spectrum of treatment recommendations based on multiple decision criteria was demonstrated. Significant inter-expert variations were observed. This demonstrates how data from randomized trials are implemented differently when transferred into daily practice.
Authors: Ameish Govindarajan; Daniela V Castro; Zeynep B Zengin; Sabrina K Salgia; Jalen Patel; Sumanta K Pal Journal: Cancers (Basel) Date: 2022-04-19 Impact factor: 6.575
Authors: Samuel M Miller; Lauren E Wilson; Melissa A Greiner; Jessica E Pritchard; Tian Zhang; Deborah R Kaye; Harvey Jay Cohen; Robert D Becher; Linda L Maerz; Michaela A Dinan Journal: J Geriatr Oncol Date: 2022-01-05 Impact factor: 3.929
Authors: Sara García-Alonso; Inés Romero-Pérez; Lucía Gandullo-Sánchez; Luis Chinchilla; Alberto Ocaña; Juan Carlos Montero; Atanasio Pandiella Journal: J Exp Clin Cancer Res Date: 2021-08-16