Alessandro Mannucci, Goretti Hernández, Hiroyuki Uetake, Yasuhide Yamada, Francesc Balaguer, Hideo Baba, Tianhui Chen, Jinfei Chen, C Richard Boland, Giulia Martina Cavestro, Enrique Quintero, Ajay Goel
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引用次数: 0
摘要
早发性结直肠癌(EOCRC,即在50岁之前诊断的)的幸存者在完成治疗后可能会复发。在这项国际、多中心、I-II-III期EDRN生物标志物研究中,我们确定了一组肿瘤来源的EOCRC复发生物标志物。然后,我们训练并独立验证了机器学习模型(XGBoost),以预测I-III期EOCRC患者的5年无复发和总生存期(RFS和OS)。在培训队列中,“低风险”EOCRC患者的2年、5年和10年RFS发生率在统计学上均较高(51.0 vs 92.4%;34.4% vs. 92.4%;25.8% vs. 92.4%;p
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).
期刊介绍:
Online-only and open access, npj Precision Oncology is an international, peer-reviewed journal dedicated to showcasing cutting-edge scientific research in all facets of precision oncology, spanning from fundamental science to translational applications and clinical medicine.