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Machine Learning Analysis of Individual Tumor Lesions in Four Metastatic Colorectal Cancer Clinical Studies: Linking Tumor Heterogeneity to Overall Survival.

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第一作者： Diego,Vera-Yunca

第一单位： Pharmacometrics & Systems Pharmacology, Department of Pharmaceutical Technology and Chemistry, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.

作者： Diego,Vera-Yunca ^[1] ; Pascal,Girard ^[2] ; Zinnia P,Parra-Guillen ^[3] ; Alain,Munafo ^[2] ; Iñaki F,Trocóniz ^[3] ; Nadia,Terranova ^[4]

作者单位： Pharmacometrics & Systems Pharmacology, Department of Pharmaceutical Technology and Chemistry, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain. ^[1] Merck Institute for Pharmacometrics, Merck Serono S.A., Switzerland, a Subsidiary of Merck KGaA, Darmstadt, Germany. ^[2] Pharmacometrics & Systems Pharmacology, Department of Pharmaceutical Technology and Chemistry, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.;IdiSNA, Navarra Institute for Health Research, Pamplona, Spain. ^[3] Merck Institute for Pharmacometrics, Merck Serono S.A., Switzerland, a Subsidiary of Merck KGaA, Darmstadt, Germany. nadia.terranova@merckgroup.com. ^[4]

关键词 cetuximab individual tumor lesion dynamics machine-learning metastatic colorectal cancer survival analysis tumor size modeling

主题词抗肿瘤药(Antineoplastic Agents);癌(Carcinoma);结直肠肿瘤(Colorectal Neoplasms);人类(Humans);肿瘤转移(Neoplasm Metastasis);比例危险度模型(Proportional Hazards Models)

DOI 10.1208/s12248-020-0434-7

PMID 32185612

发布时间 2021-01-19

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