Prediction of long-term recurrence-free and overall survival in early-onset colorectal cancer: the ENCORE multi-centre study

Survivors of early-onset colorectal cancer (EOCRC, i.e., diagnosed before age 50) are likely to experience recurrence after completing treatment. In this international, multi-centric, phase I-II-III EDRN biomarker study, we identified a panel of tumor-derived biomarkers of EOCRC recurrence. We then trained and independently validated a machine learning model (XGBoost) to predict 5-year recurrence-free and overall survival (RFS and OS) of patients with stage I-III EOCRC. Patients with "low-risk" EOCRC demonstrated statistically higher rates of 2-, 5-, and 10 year RFS in both the training cohort (51.0 vs. 92.4%; 34.4% vs. 92.4%; 25.8% vs. 92.4%, respectively; p < 0.0001) and the validation cohort (78.9% vs. 100.0%; 75.0% vs. 100.0%; 75.0% vs. 100.0%, respectively; p = 0.0019). We also report a significant reduction in both over-treatment and missed recurrences compared to current clinically available options. This tissue-based, machine learning-powered assay was prognostic of long-term RFS and OS outcomes after curative-intent treatment of EOCRC (ENCORE was first registered on ClinicalTrial.gov [ID: NCT06271980] on February 15th, 2024).

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Publication Details

Journal
npj Precision Oncology
Published
2025-06-21
DOI
https://doi.org/10.1038/s41698-025-00978-7
Citations
5
Primary Topic
Genetic factors in colorectal cancer
Type
article
Field-Weighted Citation Impact
7.36

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article

Prediction of long-term recurrence-free and overall survival in early-onset colorectal cancer: the ENCORE multi-centre study

Jinfei Chen, Hiroyuki Uetake, Giulia Martina Cavestro, Enrique Quintero et al.
5 citations
npj Precision Oncology
Genetic factors in colorectal cancer
7.36
article

Prediction of long-term recurrence-free and overall survival in early-onset colorectal cancer: the ENCORE multi-centre study

Jinfei Chen, Hiroyuki Uetake, Giulia Martina Cavestro, Enrique Quintero, Francesc Balaguer, Alessandro Mannucci, Yasuhide Yamada, Tianhui Chen, Goretti Hernández, Hideo Baba, Ajay Goel, C. Richard Boland
article en
5 citations

Abstract

Survivors of early-onset colorectal cancer (EOCRC, i.e., diagnosed before age 50) are likely to experience recurrence after completing treatment. In this international, multi-centric, phase I-II-III EDRN biomarker study, we identified a panel of tumor-derived biomarkers of EOCRC recurrence. We then trained and independently validated a machine learning model (XGBoost) to predict 5-year recurrence-free and overall survival (RFS and OS) of patients with stage I-III EOCRC. Patients with "low-risk" EOCRC demonstrated statistically higher rates of 2-, 5-, and 10 year RFS in both the training cohort (51.0 vs. 92.4%; 34.4% vs. 92.4%; 25.8% vs. 92.4%, respectively; p < 0.0001) and the validation cohort (78.9% vs. 100.0%; 75.0% vs. 100.0%; 75.0% vs. 100.0%, respectively; p = 0.0019). We also report a significant reduction in both over-treatment and missed recurrences compared to current clinically available options. This tissue-based, machine learning-powered assay was prognostic of long-term RFS and OS outcomes after curative-intent treatment of EOCRC (ENCORE was first registered on ClinicalTrial.gov [ID: NCT06271980] on February 15th, 2024).

npj Precision OncologyVol. 9(1)
Tokyo Medical and Dental University (JP), Vita-Salute San Raffaele University (IT), Chinese Academy of Sciences (CN), Wenzhou Medical University (CN), American Gastroenterological Association (US), Hospital Universitario de Canarias (ES), First Affiliated Hospital of Wenzhou Medical University (CN), Baylor University Medical Center (US), University of California San Diego (US), Zhejiang Cancer Hospital (CN), City of Hope (US), Baylor Medical Center at Garland (US), Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (ES), National Cancer Center Hospital East (JP), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele (IT), Beckman Research Institute, Kumamoto University (JP)
Fundación Mapfre, Università degli Studi di Padova, National Institutes of Health, National Cancer Institute
Good health and well-being
Openalex Percentile: Top 3%
Genetic factors in colorectal cancer
7.36
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