Clinical parameters for first-line immuno-combinations choice in metastatic renal cell carcinoma (mRCC) patients (pts): the Meet-URO 33 study
Bimbatti 1, A. Signori 2, U. Basso 1, L. Fratino 3, E. Bronte 4, M. De Tursi 5, F. Pierantoni 6, C. Ortega 7, G. Zago 8, R. De Vivo 9, M. Buffoni 10, S. Bracarda 11, R. Iacovelli 12, S. Chiallino 13, S.E. Rebuzzi 14
(1) Oncology 1 unit, IOV – Istituto Oncologico Veneto IRCCS, Padova, Italy – Italy, (2) Department of Health Sciences – Section of Biostatistics, Università degli Studi di Genova, Genova, Italy – Italy, (3) Medical Oncology, CRO Aviano – Centro di Riferimento Oncologico – IRCCS, Aviano, Italy – Italy, (4) Medical Oncology, Azienda Ospedaliera Ospedali Riuniti Villa Sofia – Cervello, Palermo, Italy – Italy, (5) Medical Oncology Department, Ospedale Clinicizzato SS. Annunziata Chieti Policlinico, Chieti, Italy – Italy, (6) Oncology 3 unit, IOV – Istituto Oncologico Veneto IRCCS, Padova, Italy – Italy, (7) Medical Oncology Department, Ospedale Michele e Pietro Ferrero – ASL CN2 Alba e Bra, Verduno, Italy – Italy, (8) Medical Oncology, Ospedale Regionale di Treviso S.Maria di Cà Foncello ULSS2, Treviso, Italy – Italy, (9) Medical Oncology Department, Ospedale San Bortolo AULSS8 Berica Distretto EST, Vicenza, Italy – Italy, (10) Oncology Department, Spedali Civili di Brescia, Brescia, Italy – Italy, (11) OncoIogy Department, Azienda Ospedaliera Santa Maria Terni, Terni, Italy – Italy, (12) MedicaIOncology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy – Italy, (13) Oncologia Medica, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy – Italy, (14) Savona – Italy
Davide Bimbatti, Alessio Signori, Umberto Basso, Lucia Fratino, Enrico Bronte, Michele De Tursi, Francesco Pierantoni, Cinzia Ortega, Giulia Zago, Rocco De Vivo, Martina Buffoni, Sergio Bracarda, Roberto Iacovelli, Silvia Chiellino, Emanuela Fantinel, Pasquale Rescigno, Giuseppe Luigi Banna, Sebastiano Buti, Giuseppe Fornarini, Sara Elena Rebuzzi.
Objective:
Despite several first-line immuno-combinations in mRCC, there are no formal comparisons or biomarkers to guide the treatment choice. In this context, the ongoing Meet-URO 33 study will recruit pts in up to 80 Italian centers to answer many clinical unmet needs.
Methods:
The Meet-URO 33 study is a multicenter prospective/retrospective registry of a real-world mRCC population receiving first-line therapy from January 2021. As of April 2024, 421 pts from 25 Italian centers were included. We investigated which clinical parameters (age, ECOG PS, type/number of comorbidities, steroids, primary tumor surgery, histology, sarcomatoid features, type/number of metastases, IMDC and Meet-URO scores) influenced investigators’ choice.
Results:
Overall, 344 (81.7%) pts received an immuno-combo: 160 (46.5%) Pembro + Axi (P+A), 81 (23.6%) Nivo + Ipi (N+I), 63 (18.3%) Nivo + Cabo (N+C), 40 (11.6%) Pembro + Lenva (P+L). At univariate analysis, the IMDC and Met-URO scores, histology, bone and pancreatic metastases, and metabolic comorbidities significantly associated with an immuno-combo choice. Specifically, N+I population had a higher percentage of IMDC intermediate-risk pts while P+L poor-risk pts (p=0.002). According to the Meet-URO score, the worst prognostic group (group 5) was predominantly treated with P+A and N+C (p=0.043). Metabolic comorbidities correlated with a more frequent choice of N+I and less of P+L (p=0.019). P+L was significantly preferred in clear-cell histology, while N+C with the higher percentage of papillary histology (p=0.047). Bone metastases correlated with N+C and less with N+I and P+L (p=0.021), while pancreatic metastases were associated with P+L and less with N+I and N+C (p=0.006).
Conclusions:
Despite the bias linked to the different prescription indications over time, the associations observed from this real-world scenario confirmed the consideration of well-known prognostic factors in the therapeutic choice; these findings should be also interpreted as a general reflection of the oncologists experience. Associations of clinical parameters will be assessed within a larger sample size.