{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T20:48:49Z","timestamp":1789591729853,"version":"build-2803163510"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T00:00:00Z","timestamp":1778112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82270590"],"award-info":[{"award-number":["82270590"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Inflammatory and coagulation abnormalities are closely linked to disease progression in Crohn\u2019s disease (CD). However, whether integrating these biomarkers can improve long-term surgical risk stratification and inform treatment decision-making remains unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 1,060 patients with CD were enrolled. Candidate predictors, including inflammatory and coagulation biomarkers, were selected using LASSO-Cox regression and the Boruta algorithm. Surgery-free survival was assessed using Kaplan-Meier analysis. Eight machine learning models were developed and evaluated using five-fold cross-validation. Shapley additive explanations (SHAP) were used to interpret the best-performing model. Inverse probability weighting was applied to reduce confounding and selection bias and to assess the benefit of biologic therapy across risk strata.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Inflammatory and coagulation biomarkers, together with disease-related features, were major determinants of long-term surgical risk in CD. Among the eight models tested, the gradient boosting machine (GBM) achieved the best performance, with a C-index of 0.816 (95% confidence interval [CI], 0.789-0.843), significantly outperforming the Cox model (0.680, 95% CI, 0.643-0.717;\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.001). The model showed robust time-dependent discrimination, with 1-, 3-, 5-AUC values up to 0.836, 0.851, 0.832, and an integrated Brier score of 0.103. SHAP analysis indicated that inflammatory and coagulation markers together contributed approximately 70% of GBM model explainability. Consistent with these findings, dual-mediator analysis showed that fibrinogen accounted for 44.5% of the inflammation-associated increase in surgical risk, whereas D-dimer mediated 6% of the excess risk. Compared with the Cox model, the GBM improved 5-year risk reclassification, with a net reclassification improvement of 0.425 and an integrated discrimination improvement of 0.181. After inverse probability weighting, biologic therapy was associated with significant benefit in the intermediate- (pooled hazard ratio (HR) = 0.44, 95% CI: 0.26-0.75, pooled\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.003) and high-risk groups (pooled HR\u00a0=\u00a00.51, 95% CI: 0.30-0.88, pooled\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.016), but not in the low-risk group (pooled HR\u00a0=\u00a00.87, 95% CI: 0.47-1.61, pooled\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.657). An online platform was developed to support individualized risk stratification and treatment assessment.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Integrating inflammatory and coagulation biomarkers improves surgical risk stratification in Crohn\u2019s disease and may help identify patients most likely to benefit from biologic therapy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1657279","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T04:56:55Z","timestamp":1778129815000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating inflammatory and coagulation biomarkers for surgical risk stratification and treatment benefit assessment in Crohn\u2019s 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China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yawei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of General Surgery, The Second Xiangya Hospital, Central South University","place":["Changsha, Hunan, China"]},{"name":"Department of Geriatric Surgery, The Second Xiangya Hospital, Central South University","place":["Changsha Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hengchang","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of General Surgery, The Second Xiangya Hospital, Central South University","place":["Changsha, Hunan, China"]},{"name":"Department of Geriatric Surgery, The Second Xiangya Hospital, Central South University","place":["Changsha Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of General Surgery, The Second Xiangya Hospital, Central South 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