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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
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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 |
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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 |
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