Dataset Information

Prognostic assessment of resected colorectal liver metastases integrating pathological features, RAS mutation and Immunoscore.

ABSTRACT: Surgical resection of colorectal liver metastases combined with systemic treatment aims to maximize patient survival. However, recurrence rates are very high postsurgery. In order to assess patient prognosis after metastasis resection, we evaluated the main patho-molecular and immune parameters of all surgical specimens. Two hundred twenty-one patients who underwent, after different preoperative treatment, curative resection of 582 metastases were analyzed. Clinicopathological parameters, RAS tumor mutation, and the consensus Immunoscore (I) were assessed for all patients. Overall survival (OS) and time to relapse (TTR) were estimated using the Kaplan-Meier method and compared by log-rank tests. Cox proportional hazard models were used for uni- and multivariate analysis. Immunoscore and clinicopathological parameters (number of metastases, surgical margin, histopathological growth pattern, and steatohepatitis) were associated with relapse in multivariate analysis. Overall, pathological score (PS) that combines relevant clinicopathological factors for relapse, and I, were prognostic for TTR (2-year TTR rate PS 0-1: 49.8.% (95% CI: 42.2-58.8) versus PS 2-4: 20.9% (95% CI: 13.4-32.8), hazard ratio (HR) = 2.54 (95% CI: 1.82-3.53), p?

SUBMITTER: Baldin P

PROVIDER: S-EPMC7737782 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Prognostic assessment of resected colorectal liver metastases integrating pathological features, RAS mutation and Immunoscore.

Baldin Pamela P Van den Eynde Marc M Mlecnik Bernhard B Bindea Gabriela G Beniuga Gabriela G Carrasco Javier J Haicheur Nacilla N Marliot Florence F Lafontaine Lucie L Fredriksen Tessa T Lanthier Nicolas N Hubert Catherine C Navez Benoît B Huyghe Nicolas N Pagès Franck F Jouret-Mourin Anne A Galon Jérôme J Komuta Mina M

The journal of pathology. Clinical research 20200909 1

Surgical resection of colorectal liver metastases combined with systemic treatment aims to maximize patient survival. However, recurrence rates are very high postsurgery. In order to assess patient prognosis after metastasis resection, we evaluated the main patho-molecular and immune parameters of all surgical specimens. Two hundred twenty-one patients who underwent, after different preoperative treatment, curative resection of 582 metastases were analyzed. Clinicopathological parameters, RAS tu ...[more]

PMID: 32902189

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Project description:BackgroundMost current models for predicting survival after resection of colorectal liver metastasis include largest diameter and number of colorectal liver metastases as dichotomous variables, resulting in underestimation of the extent of risk variation and substantial loss of statistical power. The aim of this study was to develop and validate a new prognostic model for patients undergoing liver resection including largest diameter and number of colorectal liver metastases as continuous variables.MethodsA prognostic model was developed using data from patients who underwent liver resection for colorectal liver metastases at MD Anderson Cancer Center and had RAS mutational data. A Cox proportional hazards model analysis was used to develop a model based on largest colorectal liver metastasis diameter and number of metastases as continuous variables. The model results were shown using contour plots, and validated externally in an international multi-institutional cohort.ResultsA total of 810 patients met the inclusion criteria. Largest colorectal liver metastasis diameter (hazard ratio (HR) 1.11, 95 per cent confidence interval 1.06 to 1.16; P < 0.001), number of colorectal liver metastases (HR 1.06, 1.03 to 1.09; P < 0.001), and RAS mutation status (HR 1.76, 1.42 to 2.18; P < 0.001) were significantly associated with overall survival, together with age, primary lymph node metastasis, and prehepatectomy chemotherapy. The model performed well in the external validation cohort, with predicted overall survival values almost lying within 10 per cent of observed values. Wild-type RAS was associated with better overall survival than RAS mutation even when liver resection was performed for larger and/or multiple colorectal liver metastases.ConclusionThe contour prognostic model, based on diameter and number of lesions considered as continuous variables along with RAS mutation, predicts overall survival after resection of colorectal liver metastasis.

Project description:OBJECTIVE:We aimed to improve prediction of outcome for patients with colorectal liver metastases, via prognostic models incorporating PET-derived measures, including radiomic features that move beyond conventional standard uptake value (SUV) measures. PATIENTS AND METHODS:A range of parameters including volumetric and heterogeneity measures were derived from FDG PET images of 52 patients with colorectal intrahepatic-only metastases (29 males and 23 females; mean age 62.9 years [SD 9.8; range 32-82]). The patients underwent PET/CT imaging as part of the clinical workup prior to final decision on treatment. Univariate and multivariate models were implemented, which included statistical considerations (to discourage false discovery and overfitting), to predict overall survival (OS), progression-free survival (PFS) and event-free survival (EFS). Kaplan-Meier survival analyses were performed, where the subjects were divided into high-risk and low-risk groups, from which the hazard ratios (HR) were computed via Cox proportional hazards regression. RESULTS:Commonly-invoked SUV metrics performed relatively poorly for different prediction tasks (SUVmax HR = 1.48, 0.83 and 1.16; SUVpeak HR = 2.05, 1.93, and 1.64, for OS, PFS and EFS, respectively). By contrast, the number of liver metastases and metabolic tumor volume (MTV) each performed well (with respective HR values of 2.71, 2.61 and 2.42, and 2.62, 1.96 and 2.29, for OS, PFS and EFS). Total lesion glycolysis (TLG) also resulted in similar performance as MTV. Multivariate prognostic modeling incorporating different features (including those quantifying intra-tumor heterogeneity) resulted in further enhanced prediction. Specifically, HR values of 4.29, 4.02 and 3.20 (p-values = 0.00004, 0.0019 and 0.0002) were obtained for OS, PFS and EFS, respectively. CONCLUSIONS:PET-derived measures beyond commonly invoked SUV parameters hold significant potential towards improved prediction of clinical outcome in patients with liver metastases, especially when utilizing multivariate models.

Dataset Information

Prognostic assessment of resected colorectal liver metastases integrating pathological features, RAS mutation and Immunoscore.

Publications

Prognostic assessment of resected colorectal liver metastases integrating pathological features, RAS mutation and Immunoscore.

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