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This study developed an integrated preoperative prediction model that merges preoperatively available clinicopathological characteristics with spectral CT parameters to distinguish Lauren subtypes and predict disease-free survival (DFS).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This single-centre, retrospective diagnostic-accuracy study included 224 chemotherapy-treated gastric cancer patients with histopathologically confirmed intestinal or diffuse-type Lauren classification and two-year disease-free survival outcomes. Portal-venous phase spectral computed tomography (CT) parameters (CT\u2087\u2080\u2096\u2091\n                      <jats:sub>v<\/jats:sub>\n                      , iodine concentration, and normalized iodine concentration) and clinicopathological variables (tumor differentiation and Borrmann type) were assessed. Independent predictors were identified using multivariate logistic regression, and three models were constructed: clinicopathological, spectral CT, and combined. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, calibration curves, decision curve analysis, and 1000-bootstrap internal validation. Disease-free survival was further analysed using Kaplan\u2013Meier curves, the log-rank test, and Cox proportional hazards regression.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Multivariate analysis identified poor differentiation (OR\u2009=\u20099.80, P\u2009&lt;\u2009&lt;\u20090.001) and Borrmann type III\/IV (OR\u2009=\u20092.65,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.004) as clinicopathological predictors, while portal-venous phase CT at 70\u00a0keV (OR\u2009=\u20091.34, P\u2009&lt;\u2009&lt;\u20090.001), iodine concentration (OR\u2009=\u20092.08,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.001), and normalized iodine concentration (OR\u2009=\u20092.09, P\u2009&lt;\u2009&lt;\u20090.001) were significant spectral CT predictors of diffuse-type histology. The combined model demonstrated an area under the curve (AUC) of 0.901 (95% CI: 0.859\u20130.944) for Lauren classification, outperforming both the pathological model (AUC\u2009=\u20090.810) and the spectral CT model (AUC\u2009=\u20090.861). The optimism-corrected AUC was 0.901 (95% CI: 0.857\u20130.943) based on 1000-bootstrap validation. For disease-free survival (DFS) prediction, the model achieved an AUC of 0.896 (95% CI: 0.851\u20130.941) at a cut-off value of 0.646, with an optimism-corrected AUC of 0.895 (95% CI: 0.850\u20130.939). Calibration curves and decision curve analysis indicated satisfactory agreement and a superior net benefit. Kaplan-Meier analysis revealed significant separation between high-risk and low-risk groups (2-year DFS rates: 7.2% versus 84.4%; log-rank chi2\u2009=\u2009158.88, P\u2009&lt;\u2009&lt;\u20090.001), and Cox regression analysis confirmed a substantially increased recurrence risk in the high-risk group (HR\u2009=\u200910.97, 95% CI: 6.68\u201317.99, P\u2009&lt;\u2009&lt;\u20090.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The integrated model provides accurate preoperative Lauren classification and robust DFS prediction, serving as a multimodal tool for gastric cancer risk stratification and treatment planning.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s40644-026-01064-2","type":"journal-article","created":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T10:56:16Z","timestamp":1780484176000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Lauren classification-based combined model integrating clinicopathological and spectral CT features for disease-free survival prediction in gastric cancer"],"prefix":"10.1186","volume":"26","author":[{"given":"Haibo","family":"You","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiezhu","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianqian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Long","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenyang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,3]]},"reference":[{"issue":"3","key":"1064_CR1","first-page":"209","volume":"71","author":"H Sung","year":"2021","unstructured":"Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. 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