International multicenter real-world registry for patients with metastatic renal cell carcinoma: Meet-URO 33 study (REGAL study).
Authors: Rebuzzi Sara Elena , Fornarini Giuseppe , Signori Alessio , Buti Sebastiano , Procopio Giuseppe , De Giorgi Ugo , Pignata Sandro , Naglieri Emanuele , Maruzzo Marco , Banna Giuseppe Luigi , Rescigno Pasquale , Messina Carlo , Nasso Cecilia , Murianni Veronica , Cremante Malvina , Damassi Alessandra , Catalano Fabio , Mattana Alvise , Basso Umberto , Bimbatti Davide ,   Meet-URO group
Published: January 2024

TPS485 Background: Nowadays, different systemic treatments are available for the first-line setting of metastatic renal cell carcinoma (mRCC). Immuno-combinations are the standard first-line therapy in all mRCC patients regardless the IMDC risk category, even though TKI monotherapy is still a therapeutic option in selected patients. However, comparisons between the different first-line treatment strategies are lacking and few real-world data are available in this setting. For these reasons, the regimen choice represents an important issue in clinical practice and the optimal treatment sequence remains unclear. Methods: The Meet-URO 33 (REGAL) study is a multicentric prospective observational study enrolling mRCC patients treated with first-line systemic therapy according to clinical practice in a real-world setting. A retrospective cohort of mRCC patients who received first-line systemic therapy from 1st of January 2021 will also be included. The study includes 84 Italian centers and a study amendment will be submitted to include about 10 European centers. The Meet-URO 33 study aims to provide a large-scale real-world database on mRCC patients and the primary objective is to identify potential prognostic and predictive factors that could help guide the treatment choice. Secondary objectives include the comparison between treatment strategies in first-line and subsequent lines according to response and survival outcomes and toxicity profile; the assessment of the correlation between the clinical and tumor characteristics and the choice of the first line of treatment; the assessment of the prognostic performance of the Meet-URO score compared with the IMDC score. Moreover, given the registry nature of the study, further studies will be planned subsequently, both on the entire cohort (e.g. genomic analyses and artificial intelligence) and particular subgroups (e.g. poor-risk category, elderly, non-clear cell histology) to answer as many clinical questions as possible. The descriptive statistics will be used to summarize the clinical characteristics of patients and the distribution of prognostic factors. All time-to-event endpoints (PFS, OS) will be analyzed using the Kaplan-Meier method, the restricted mean survival time (RMST) and the Cox proportional hazard regression model. The binary endpoints (ORR, DCR) will be analyzed through relative frequencies and logistic regression. For all the comparisons between treatments, all causal inference techniques such as propensity scores and marginal structural models will be used. All the steps for a correct target trial emulation strategy will be followed to avoid potential biases deriving from the observational nature of the study. In particular, in comparing the different treatments, the principles of emulating a clinical trial will be applied, developing appropriate ad hoc protocols for each planned comparison. Clinical trial information: CESC IOV 2023-78 .