<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>14(23)</volume><submitter>Harada GK</submitter><pubmed_abstract>&lt;h4>Background&lt;/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).&lt;h4>Methods&lt;/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</pubmed_abstract><journal>Cancer medicine</journal><pagination>e71447</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12679486</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Predicting Benefit of Neoadjuvant Chemotherapy and Elective Nodal Irradiation in Pancreatic Adenocarcinoma: A Supervised Machine Learning Approach.</pubmed_title><pmcid>PMC12679486</pmcid><pubmed_authors>Seyedin SN</pubmed_authors><pubmed_authors>Dayyani F</pubmed_authors><pubmed_authors>Harada GK</pubmed_authors><pubmed_authors>Park J</pubmed_authors><pubmed_authors>Imagawa D</pubmed_authors><pubmed_authors>Jutric Z</pubmed_authors><pubmed_authors>Peterson N</pubmed_authors><pubmed_authors>Hong DS</pubmed_authors><pubmed_authors>Munjal A</pubmed_authors><pubmed_authors>Valerin J</pubmed_authors></additional><is_claimable>false</is_claimable><name>Predicting Benefit of Neoadjuvant Chemotherapy and Elective Nodal Irradiation in Pancreatic Adenocarcinoma: A Supervised Machine Learning Approach.</name><description>&lt;h4>Background&lt;/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).&lt;h4>Methods&lt;/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</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Dec</publication><modification>2026-06-05T22:36:11.184Z</modification><creation>2026-05-23T03:10:14.295Z</creation></dates><accession>S-EPMC12679486</accession><cross_references><pubmed>41347669</pubmed><doi>10.1002/cam4.71447</doi></cross_references></HashMap>