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

Abstract

BackgroundThe 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.MethodsThe 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).ResultsRFS 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.ConclusionsA 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.

Metastatic sites and lesion numbers cooperated to predict efficacy of PD‐1 inhibitor‐based combination therapy for patients with metastatic colorectal cancer

“…According to a lesion‐based study including 78 patients with dMMR solid tumors treated with PD‐1 monotherapy, 27 most lesions responded irrespective of organ sites and no significant difference was observed. In another study constructing a nomogram to predict the efficacy of immunotherapy in patients with MSI‐H mCRC, 31 only five variates (regimen, Eastern Cooperative Oncology Group Performance Status, prior lines, neutrophil‐to‐lymphocytes ratio, and palates) from 23 characteristics were demonstrated to independently predict the 12‐month PFS. Unexpectedly, liver metastases showed no significant negative impact on survival, implying that hypermutated genomic status significantly reshaped the tumor microenvironment even in immune privilege organ.…”

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“… 8 , 10 , 32 In addition, several hematological indicators reflecting the systematic inflammation, including hemoglobin, platelet, globulin, and PLR, were associated with NAC.NICB efficacy. 34 , 35 These pretreatment hematological indicators were more accessible, economical, and repeatable than biomarkers derived from cancer tissues. In order to develop an efficacy prediction model without overfitting, we defined a new comprehensive indicator, named PLR.GHR, based on four hematological indicators.…”

Characteristics of Prognostic Programmed Cell Death–Related Long Noncoding RNAs Associated With Immune Infiltration and Therapeutic Responses to Colon Cancer

“…The results of the external database analysis provided further evidence that our model could accurately assess the prognosis of CC. The nomogram is a quantitative tool that can predict a certain clinical outcome or the probability of a certain type of event based on the values of several variables ( 32 ). The DCA decision and ROC curves showed a better net profit rate and diagnostic ability for the nomogram than those for a single indicator in terms of assessing patient prognosis.…”