Fortunato Morabito1,2, Giovanni Tripepi3, Giovanni Del Poeta4, Francesca Romana Mauro5, Gianluigi Reda6, Paolo Sportoletti7, Luca Laurenti8, Marta Coscia9, Yair Herishanu10, Sabrina Bossio1, Marzia Varettoni11, Roberta Murru12, Annalisa Chiarenza13, Andrea Visentin14, Adalgisa Condoluci15, Riccardo Moia16, Daniela Pietrasanta17, Giacomo Loseto18, Ugo Consoli19, Ilaria Scortechini20, Francesca Maria Rossi21, Antonella Zucchetto21, Hamdi Al-Janazreh2, Ernesto Vigna1,22, Enrica Antonia Martino22, Francesco Mendicino22, Ramona Cassin6, Graziella D'Arrigo3, Sara Galimberti23, Angela Rago24, Ilaria Angeletti25, Annalisa Biagi4, Ilaria Del Giudice5, Riccardo Bomben21, Antonino Neri6, Gilberto Fronza26, Paola Monti26, Paola Menichini26, Giovanna Cutrona27, Ozren Jaksic28, Davide Rossi15, Francesco Di Raimondo13, Antonio Cuneo29, Gianluca Gaidano16, Aaron Polliack30, Livio Trentin14, Robin Foà5, Manlio Ferrarini31, Valter Gattei21, Massimo Gentile1,22. 1. Biothecnology Research Unit, AO of Cosenza, Cosenza, Italy. 2. Hematology and Bone Marrow Transplant Unit, Hemato-Oncology Department, Augusta Victoria Hospital, East Jerusalem, Israel. 3. CNR-IFC, Research Unit of Reggio Calabria, Reggio Calabria, Italy. 4. Division of Hematology, S. Eugenio Hospital and University of Tor Vergata, Rome, Italy. 5. Department of Translational and Precision Medicine, 'Sapienza' University, Rome, Italy. 6. Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico di Milano, Milano, Italy. 7. Centro di Ricerca Emato-Oncologica (CREO), University of Perugia, Perugia, Italy. 8. Fondazione Universitaria Policlinico A Gemelli di Roma, Roma, Italy. 9. Division of Hematology, A.O.U. Città della Salute e della Scienza di Torino, Torino, Italy. 10. Sourasky Medical Center, Institute of Hematology and Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. 11. Division of Haematology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. 12. Hematology and Stem Cell Transplantation Unit, Ospedale A. Businco, Cagliari, Italy. 13. Division of Hematology, Policlinico, Department of Surgery and Medical Specialties, University of Catania, Catania, Italy. 14. Department of Medicine, Hematology and Clinical Immunology Branch, University of Padova, Padova, Italy. 15. Oncology Institute of Southern Switzerland, Bellinzona, Switzerland. 16. Division of Hematology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy. 17. Division of Hematology, Azienda Ospedaliera SS Arrigo e Biagio e Cesare Arrigo, Alessandria, Italy. 18. Hematology and Cell Therapy Unit, IRCCS-Istituto Tumori 'Giovanni Paolo II', Bari, Italy. 19. Hematology Department, G. Garibaldi Hospital, Catania, Italy. 20. Clinica di Ematologia Ospedali Riuniti, Ancona, Italy. 21. Clinical and Experimental Onco-Hematology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy. 22. Hematology Unit AO of Cosenza, Cosenza, Italy. 23. Section of Hematology, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy. 24. UOSD Ematologia ASL Roma 1, Roma, Italy. 25. Reparto di Oncoematologia Azienda Ospedaliera Santa Maria di Terni, Terni, Italy. 26. Mutagenesis and Cancer Prevention Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy. 27. Molecular Pathology Unit, IRCCS Ospedale Policlinico San Martino, Genova, Italy. 28. Department of Hematology, Dubrava Univerisity Hospital, Zagreb, Croatia. 29. Hematology Section, Department of Medical Sciences, University of Ferrara, Cona, Italy. 30. Department of Hematology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel. 31. Department of Experimental Medicine, University of Genoa, Genoa, Italy.
Abstract
OBJECTIVES: To compare the capacity of ibrutinib (IB) and idelalisib-rituximab (IDELA-R) of prolonging overall survival (OS) as in CLL patients, previously treated with chemotherapy only. METHODS: A real-life cohort of 675 cases has been identified and investigated in the database of the groups participating in the study. RESULTS: At an unadjusted univariate analysis, a significant death risk reduction was observed favoring IB (IDELA-R vs IB HR = 0.5, 95% CI = 0.36-0.71) although with some limitations due to the non-randomized and retrospective nature of the study and to the lower number of patients in the IDELA-R group (112 cases) related to the current prescribing practice. To overcome the potential problem of confounding by indication, we adjusted the association between the type of therapy and mortality for all variables significantly associated with OS at Cox univariate analysis. Furthermore, those variables, differently distributed between the two study groups, were introduced into the multivariate Cox model to improve the effectiveness of the analysis. By introducing all these variables into the multiple Cox regression model, we confirmed the protective effect of IB vs IDELA-R (HR = 0.67, 95% CI = 0.45-0.98, P = .04) independent of potential confounders. CONCLUSIONS: Although our analysis presents some constraints, that is, the unavailability of additional potential confounders, and the retrospective nature of the study, this observation may be of help for the daily clinical practice, particularly in the absence of randomized trials comparing the two schedules.
OBJECTIVES: To compare the capacity of ibrutinib (IB) and idelalisib-rituximab (IDELA-R) of prolonging overall survival (OS) as in CLL patients, previously treated with chemotherapy only. METHODS: A real-life cohort of 675 cases has been identified and investigated in the database of the groups participating in the study. RESULTS: At an unadjusted univariate analysis, a significant death risk reduction was observed favoring IB (IDELA-R vs IB HR = 0.5, 95% CI = 0.36-0.71) although with some limitations due to the non-randomized and retrospective nature of the study and to the lower number of patients in the IDELA-R group (112 cases) related to the current prescribing practice. To overcome the potential problem of confounding by indication, we adjusted the association between the type of therapy and mortality for all variables significantly associated with OS at Cox univariate analysis. Furthermore, those variables, differently distributed between the two study groups, were introduced into the multivariate Cox model to improve the effectiveness of the analysis. By introducing all these variables into the multiple Cox regression model, we confirmed the protective effect of IB vs IDELA-R (HR = 0.67, 95% CI = 0.45-0.98, P = .04) independent of potential confounders. CONCLUSIONS: Although our analysis presents some constraints, that is, the unavailability of additional potential confounders, and the retrospective nature of the study, this observation may be of help for the daily clinical practice, particularly in the absence of randomized trials comparing the two schedules.
Authors: Monia Marchetti; Candida Vitale; Gian Matteo Rigolin; Alessandra Vasile; Andrea Visentin; Lydia Scarfò; Marta Coscia; Antonio Cuneo Journal: J Clin Med Date: 2022-04-07 Impact factor: 4.964