{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["14(23)"],"submitter":["Harada GK"],"pubmed_abstract":["<h4>Background</h4>The relative benefit of neoadjuvant therapies remains controversial for patients with (borderline) resectable pancreatic ductal adenocarcinoma (PDAC). The purpose of this study was to create a model to predict response to multiagent neoadjuvant chemotherapy (NAC) followed by radiotherapy with elective nodal irradiation (ENI).<h4>Methods</h4>Using the National Cancer Database (NCDB), we identified patients with cT1-4N0M0 PDAC diagnosed between 2006 and 2020 treated with multiagent NAC, radiation with ENI, followed by curative resection with nodal dissection. A LASSO logistic regression model was used to predict ypN0 status, with generation of a nomogram and assessment of outcomes in training and testing cohorts. Secondary endpoints of negative-margin resection and overall"],"journal":["Cancer medicine"],"pagination":["e71447"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12679486"],"repository":["biostudies-literature"],"pubmed_title":["Predicting Benefit of Neoadjuvant Chemotherapy and Elective Nodal Irradiation in Pancreatic Adenocarcinoma: A Supervised Machine Learning Approach."],"pmcid":["PMC12679486"],"pubmed_authors":["Seyedin SN","Dayyani F","Harada GK","Park J","Imagawa D","Jutric Z","Peterson N","Hong DS","Munjal A","Valerin J"],"additional_accession":[]},"is_claimable":false,"name":"Predicting Benefit of Neoadjuvant Chemotherapy and Elective Nodal Irradiation in Pancreatic Adenocarcinoma: A Supervised Machine Learning Approach.","description":"<h4>Background</h4>The relative benefit of neoadjuvant therapies remains controversial for patients with (borderline) resectable pancreatic ductal adenocarcinoma (PDAC). The purpose of this study was to create a model to predict response to multiagent neoadjuvant chemotherapy (NAC) followed by radiotherapy with elective nodal irradiation (ENI).<h4>Methods</h4>Using the National Cancer Database (NCDB), we identified patients with cT1-4N0M0 PDAC diagnosed between 2006 and 2020 treated with multiagent NAC, radiation with ENI, followed by curative resection with nodal dissection. A LASSO logistic regression model was used to predict ypN0 status, with generation of a nomogram and assessment of outcomes in training and testing cohorts. Secondary endpoints of negative-margin resection and overall","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Dec","modification":"2026-06-05T22:36:11.184Z","creation":"2026-05-23T03:10:14.295Z"},"accession":"S-EPMC12679486","cross_references":{"pubmed":["41347669"],"doi":["10.1002/cam4.71447"]}}