Cargando…

Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors

BACKGROUND: The efficacy of immune checkpoint inhibitors (ICIs) in patients with microsatellite instability (MSI)-high metastatic colorectal cancer (mCRC) is unprecedented. A relevant proportion of subjects achieving durable disease control may be considered potentially ‘cured’, as opposed to patien...

Descripción completa

Detalles Bibliográficos
Autores principales: Pietrantonio, Filippo, Lonardi, Sara, Corti, Francesca, Infante, Gabriele, Elez, Maria Elena, Fakih, Marwan, Jayachandran, Priya, Shah, Aakash Tushar, Salati, Massimiliano, Fenocchio, Elisabetta, Salvatore, Lisa, Curigliano, Giuseppe, Cremolini, Chiara, Ambrosini, Margherita, Ros, Javier, Intini, Rossana, Nappo, Floriana, Damian, Silvia, Morano, Federica, Fucà, Giovanni, Overman, Michael, Miceli, Rosalba
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386222/
https://www.ncbi.nlm.nih.gov/pubmed/34429334
http://dx.doi.org/10.1136/jitc-2021-003370
_version_ 1783742219127095296
author Pietrantonio, Filippo
Lonardi, Sara
Corti, Francesca
Infante, Gabriele
Elez, Maria Elena
Fakih, Marwan
Jayachandran, Priya
Shah, Aakash Tushar
Salati, Massimiliano
Fenocchio, Elisabetta
Salvatore, Lisa
Curigliano, Giuseppe
Cremolini, Chiara
Ambrosini, Margherita
Ros, Javier
Intini, Rossana
Nappo, Floriana
Damian, Silvia
Morano, Federica
Fucà, Giovanni
Overman, Michael
Miceli, Rosalba
author_facet Pietrantonio, Filippo
Lonardi, Sara
Corti, Francesca
Infante, Gabriele
Elez, Maria Elena
Fakih, Marwan
Jayachandran, Priya
Shah, Aakash Tushar
Salati, Massimiliano
Fenocchio, Elisabetta
Salvatore, Lisa
Curigliano, Giuseppe
Cremolini, Chiara
Ambrosini, Margherita
Ros, Javier
Intini, Rossana
Nappo, Floriana
Damian, Silvia
Morano, Federica
Fucà, Giovanni
Overman, Michael
Miceli, Rosalba
author_sort Pietrantonio, Filippo
collection PubMed
description BACKGROUND: The efficacy of immune checkpoint inhibitors (ICIs) in patients with microsatellite instability (MSI)-high metastatic colorectal cancer (mCRC) is unprecedented. A relevant proportion of subjects achieving durable disease control may be considered potentially ‘cured’, as opposed to patients experiencing primary ICI refractoriness or short-term clinical benefit. We developed and externally validated a nomogram to estimate the progression-free survival (PFS) and the time-independent event-free probability (EFP) in patients with MSI-high mCRC receiving ICIs. METHODS: The PFS and EFP were estimated using a cure model fitted on a developing set of 163 patients and validated on a set of 146 patients with MSI-high mCRC receiving anti-programmed death (ligand)1 (PD-(L)1) ± anticytotoxic T-lymphocyte antigen 4 (CTLA-4) agents. A total of 23 putative prognostic factors were chosen and then selected using a random survival forest (RSF). The model performance in estimating PFS probability was evaluated by assessing calibration (internally—developing set and externally—validating set) and quantifying the discriminative ability (Harrell C index). RESULTS: RFS selected five variables: ICI type (anti-PD-(L)1 monotherapy vs anti-CTLA-4 combo), ECOG PS (0 vs >0), neutrophil-to-lymphocyte ratio (≤3 vs >3), platelet count, and prior treatment lines. As both in the developing and validation series most PFS events occurred within 12 months, this was chosen as cut-point for PFS prediction. The combination of the selected variables allowed estimation of the 12-month PFS (focused on patients with low chance of being cured) and the EFP (focused on patients likely to be event-free at a certain point of their follow-up). ICI type was significantly associated with disease control, as patients receiving the anti-CTLA-4-combination experienced the best outcomes. The calibration of PFS predictions was good both in the developing and validating sets. The median value of the EFP (46%) allowed segregation of two prognostic groups in both the developing (PFS HR=3.73, 95% CI 2.25 to 6.18; p<0.0001) and validating (PFS HR=1.86, 95% CI 1.07 to 3.23; p=0.0269) sets. CONCLUSIONS: A nomogram based on five easily assessable variables including ICI treatment was built to estimate the outcomes of patients with MSI-high mCRC, with the potential to assist clinicians in their clinical practice. The web-based system ‘MSI mCRC Cure’ was released.
format Online
Article
Text
id pubmed-8386222
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BMJ Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-83862222021-09-09 Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors Pietrantonio, Filippo Lonardi, Sara Corti, Francesca Infante, Gabriele Elez, Maria Elena Fakih, Marwan Jayachandran, Priya Shah, Aakash Tushar Salati, Massimiliano Fenocchio, Elisabetta Salvatore, Lisa Curigliano, Giuseppe Cremolini, Chiara Ambrosini, Margherita Ros, Javier Intini, Rossana Nappo, Floriana Damian, Silvia Morano, Federica Fucà, Giovanni Overman, Michael Miceli, Rosalba J Immunother Cancer Clinical/Translational Cancer Immunotherapy BACKGROUND: The efficacy of immune checkpoint inhibitors (ICIs) in patients with microsatellite instability (MSI)-high metastatic colorectal cancer (mCRC) is unprecedented. A relevant proportion of subjects achieving durable disease control may be considered potentially ‘cured’, as opposed to patients experiencing primary ICI refractoriness or short-term clinical benefit. We developed and externally validated a nomogram to estimate the progression-free survival (PFS) and the time-independent event-free probability (EFP) in patients with MSI-high mCRC receiving ICIs. METHODS: The PFS and EFP were estimated using a cure model fitted on a developing set of 163 patients and validated on a set of 146 patients with MSI-high mCRC receiving anti-programmed death (ligand)1 (PD-(L)1) ± anticytotoxic T-lymphocyte antigen 4 (CTLA-4) agents. A total of 23 putative prognostic factors were chosen and then selected using a random survival forest (RSF). The model performance in estimating PFS probability was evaluated by assessing calibration (internally—developing set and externally—validating set) and quantifying the discriminative ability (Harrell C index). RESULTS: RFS selected five variables: ICI type (anti-PD-(L)1 monotherapy vs anti-CTLA-4 combo), ECOG PS (0 vs >0), neutrophil-to-lymphocyte ratio (≤3 vs >3), platelet count, and prior treatment lines. As both in the developing and validation series most PFS events occurred within 12 months, this was chosen as cut-point for PFS prediction. The combination of the selected variables allowed estimation of the 12-month PFS (focused on patients with low chance of being cured) and the EFP (focused on patients likely to be event-free at a certain point of their follow-up). ICI type was significantly associated with disease control, as patients receiving the anti-CTLA-4-combination experienced the best outcomes. The calibration of PFS predictions was good both in the developing and validating sets. The median value of the EFP (46%) allowed segregation of two prognostic groups in both the developing (PFS HR=3.73, 95% CI 2.25 to 6.18; p<0.0001) and validating (PFS HR=1.86, 95% CI 1.07 to 3.23; p=0.0269) sets. CONCLUSIONS: A nomogram based on five easily assessable variables including ICI treatment was built to estimate the outcomes of patients with MSI-high mCRC, with the potential to assist clinicians in their clinical practice. The web-based system ‘MSI mCRC Cure’ was released. BMJ Publishing Group 2021-08-24 /pmc/articles/PMC8386222/ /pubmed/34429334 http://dx.doi.org/10.1136/jitc-2021-003370 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See https://creativecommons.org/licenses/by/4.0/.
spellingShingle Clinical/Translational Cancer Immunotherapy
Pietrantonio, Filippo
Lonardi, Sara
Corti, Francesca
Infante, Gabriele
Elez, Maria Elena
Fakih, Marwan
Jayachandran, Priya
Shah, Aakash Tushar
Salati, Massimiliano
Fenocchio, Elisabetta
Salvatore, Lisa
Curigliano, Giuseppe
Cremolini, Chiara
Ambrosini, Margherita
Ros, Javier
Intini, Rossana
Nappo, Floriana
Damian, Silvia
Morano, Federica
Fucà, Giovanni
Overman, Michael
Miceli, Rosalba
Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors
title Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors
title_full Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors
title_fullStr Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors
title_full_unstemmed Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors
title_short Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors
title_sort nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors
topic Clinical/Translational Cancer Immunotherapy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386222/
https://www.ncbi.nlm.nih.gov/pubmed/34429334
http://dx.doi.org/10.1136/jitc-2021-003370
work_keys_str_mv AT pietrantoniofilippo nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT lonardisara nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT cortifrancesca nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT infantegabriele nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT elezmariaelena nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT fakihmarwan nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT jayachandranpriya nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT shahaakashtushar nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT salatimassimiliano nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT fenocchioelisabetta nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT salvatorelisa nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT curiglianogiuseppe nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT cremolinichiara nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT ambrosinimargherita nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT rosjavier nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT intinirossana nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT nappofloriana nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT damiansilvia nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT moranofederica nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT fucagiovanni nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT overmanmichael nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors
AT micelirosalba nomogramtopredicttheoutcomesofpatientswithmicrosatelliteinstabilityhighmetastaticcolorectalcancerreceivingimmunecheckpointinhibitors