作者: Nathaniel Weygant , Jiannan Yao , Dongfeng Qu , Parthasarathy Chandrakesan , Guangyu An
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摘要: Background: Accurately predicting recurrence in early stage cancer patients may be used to avoid unnecessary therapies with significant side effects or deliver early interventions that can improve outcomes. Both early stage lung (LAc) and pancreatic adenocarcinoma (PDAc) are high-recurrence cancers for which biomarkers that can quantify this risk could benefit patients. In stage I LAc only a small percentage of stage IB patients receive chemotherapy, while more patients may derive additional benefit if identified. In PDAc, patients with the most aggressive stage I-II disease could derive benefit from early aggressive combination chemotherapy if identified.Methods: Training and test sets (n=10) were selected by random sampling RNA-seq expression data into groups of 65% and 35% respectively. Cox proportional hazards and Kaplan-Meier analysis were used to predict RFS and OS. Maximally selected rank …