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).
Prediction of long-term recurrence-free and overall survival in early-onset colorectal cancer: the ENCORE multi-centre study / Mannucci, A.; Hernández, G.; Uetake, H.; Yamada, Y.; Balaguer, F.; Baba, H.; Chen, T.; Chen, J.; Boland, C. R.; Cavestro, G. M.; Quintero, E.; Goel, A.. - In: NPJ PRECISION ONCOLOGY. - ISSN 2397-768X. - 9:1(2025). [10.1038/s41698-025-00978-7]
Prediction of long-term recurrence-free and overall survival in early-onset colorectal cancer: the ENCORE multi-centre study
Mannucci A.;Cavestro G. M.;
2025-01-01
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).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
