{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:04:50Z","timestamp":1784199890450,"version":"3.55.0"},"reference-count":24,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,6,7]],"date-time":"2026-06-07T00:00:00Z","timestamp":1780790400000},"content-version":"vor","delay-in-days":6,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82474491"],"award-info":[{"award-number":["82474491"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>\n                      To investigate risk factors for refractory\n                      <jats:styled-content style=\"fixed-case\">\n                        <jats:italic>Helicobacter pylori<\/jats:italic>\n                      <\/jats:styled-content>\n                      infection (RHPI) complicated by chronic atrophic gastritis (CAG) and to develop a risk prediction model for early identification of high\u2010risk patients.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A retrospective cohort study enrolled 367 RHPI patients from January 2015 to December 2024. Demographic, inflammatory immune, tumor marker, and\n                      <jats:styled-content style=\"fixed-case\">\n                        <jats:italic>H. pylori<\/jats:italic>\n                      <\/jats:styled-content>\n                      antibody data were collected. Univariate and multivariate logistic regression identified risk factors, followed by LASSO regression for variable selection. A nomogram prediction model was constructed and evaluated using ROC curves, calibration curves, and decision curve analysis (DCA). In\u00a0vitro experiments validated key findings.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Multivariate analysis identified age (OR\u2009=\u20091.05, 95% CI: 1.02\u20131.08), smoking (OR\u2009=\u20092.37, 95% CI: 1.46\u20133.85), CA199 (OR\u2009=\u20091.12, 95% CI: 1.03\u20131.22), and lymphocyte ratio (LYMPH%) (OR\u2009=\u20091.08, 95% CI: 1.01\u20131.15) as independent risk factors (all\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05). The nomogram demonstrated excellent predictive performance with AUC 0.833 (95% CI: 0.791\u20130.876), sensitivity 94.50%, and specificity 78.40%. Calibration and decision curves confirmed good fit and clinical utility. In\u00a0vitro experiments showed refractory\n                      <jats:styled-content style=\"fixed-case\">\n                        <jats:italic>H. pylori<\/jats:italic>\n                      <\/jats:styled-content>\n                      strains promoted gastric mucosal damage through enhanced inflammatory immune responses (e.g., IL\u201010, TNF\u2010\u03b1;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study establishes the first disease\u2010specific prediction model for RHPI complicated by CAG using readily available clinical indicators. The model shows strong predictive performance and clinical utility for early screening and intervention. Further multicenter studies are needed to validate generalizability and explore associations with gastric precancerous progression.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cam4.72006","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T03:15:15Z","timestamp":1780888515000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring the High\u2010Risk Factors of Gastric \u201cInflammatory Cancer Transformation\u201d Based on Inflammatory Immune Response: Construction of\n                    <scp>RHPI<\/scp>\n                    Complicated With\n                    <scp>CAG<\/scp>\n                    Risk Prediction Model"],"prefix":"10.1002","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3566-5877","authenticated-orcid":false,"given":"Tian\u2010tong","family":"Jiang","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, 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