Integration of Systemic Inflammation Response Index (SIRI) and Clinicopathological Factors Enhances Survival Prediction in Colorectal Cancer: A Retrospective Cohort Study

Integration of Systemic Inflammation Response Index (SIRI) and Clinicopathological Factors Enhances Survival Prediction in Colorectal Cancer: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integration of Systemic Inflammation Response Index (SIRI) and Clinicopathological Factors Enhances Survival Prediction in Colorectal Cancer: A Retrospective Cohort Study Jinquan Li, Xiaosheng Hu, Shanzhong Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6931060/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. The current TNM staging systems exhibit limited prognostic accuracy because they do not account for host inflammatory responses. This study aimed to develop and validate a novel prognostic nomogram integrating clinicopathological features with systemic inflammatory biomarkers to improve survival prediction in patients with CRC after radical resection. Methods In this retrospective cohort study, clinical data from‌ 324 patients with CRC who underwent surgery between January 2010 and March 2020 were analyzed. Preoperative hematological indices‌ (including NLR, PLR, LMR, FAR, ‌dNLR‌, MCVL, SIRI, SII, PNI, IIC, PINI, HALP) ‌and clinicopathological variables were assessed., Variable selection ‌was conducted‌ using univariate Cox analysis, LASSO regression (Lambda.1se) and multivariate Cox analysis. The final model was constructed ‌ as a nomogram and validated for 1-, 3-, and 5-year overall survival (OS) predictions using ROC analysis, calibration curves, and decision curve analysis (DCA). Results Multivariate analysis identified four independent prognostic factors: N stage (N1: HR = 2.72, 95% CI 1.51–4.89, p < 0.001; N2: HR = 5.26, 95% CI 2.60–10.67, p < 0.001), vascular invasion (HR = 6.02, 95% CI 3.79–9.58, p < 0.001), perineural invasion (HR = 2.02, 95% CI 1.29–3.16, p = 0.002), and SIRI ≥ 2.39 (HR = 2.03, 95% CI 1.33–3.09, p < 0.001). The nomogram demonstrated ‌significantly‌ superior prognostic accuracy compared with conventional ‌TNM staging‌, with excellent calibration in both the training and validation cohorts. DCA confirmed ‌ the significant net clinical benefits of the nomogram‌. Risk stratification revealed ‌significantly divergent‌ survival rates between the high- and low-risk groups (p < 0.001). Conclusions Our inflammatory-clinicopathological nomogram ‌provides superior prognostic accuracy‌ to conventional TNM staging, ‌enabling‌ personalized risk assessment and treatment optimization for patients with CRC. ‌SIRI integration, as a key biomarker, underscores the critical role of systemic inflammation‌. Colorectal cancer Prognostic model Systemic inflammation Nomogram SIRI Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6931060","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486135166,"identity":"7955c36e-6fa9-47ef-8813-30c30242e99a","order_by":0,"name":"Jinquan Li","email":"","orcid":"","institution":"The First People’s Hospital of Jingdezhen","correspondingAuthor":false,"prefix":"","firstName":"Jinquan","middleName":"","lastName":"Li","suffix":""},{"id":486135167,"identity":"2ad994c5-5da0-4e59-9e98-b2120b830085","order_by":1,"name":"Xiaosheng Hu","email":"","orcid":"","institution":"The First People’s Hospital of Jingdezhen","correspondingAuthor":false,"prefix":"","firstName":"Xiaosheng","middleName":"","lastName":"Hu","suffix":""},{"id":486135168,"identity":"e0d4b44a-0186-4748-8b6f-5fa7effad35b","order_by":2,"name":"Shanzhong Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACxvbGxgcfKmx4GNsbiNTC3HP4sOGMM2kyzD0HiNTCPiMtTZq37bAN+4wEIrXwzsgxk5zBlsbDO/PxxhsMNTbRBLVI9rwxtvjAY8MjOTut2ILhWFpuAyEthu05hjdnSKTxGM7OMZNgbDhMWIv9gRwDaR6Dwzz2N88QqYWxIy1JmifhMA/jDB5itYAD+UAaD2MP0C8JxPgFHJUf/9nYM7Yf3njjQ40NYS3IwEAigRTlEC2k6hgFo2AUjIKRAQAOBkOwFbG4mQAAAABJRU5ErkJggg==","orcid":"","institution":"The First People’s Hospital of Jingdezhen","correspondingAuthor":true,"prefix":"","firstName":"Shanzhong","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-06-19 12:08:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6931060/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6931060/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89491386,"identity":"90990c75-9c6c-4073-a285-07521cc91552","added_by":"auto","created_at":"2025-08-20 13:54:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":840207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6931060/v1_covered_37e54fd1-b9ed-42f0-a2a0-bc9db1e148cd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integration of Systemic Inflammation Response Index (SIRI) and Clinicopathological Factors Enhances Survival Prediction in Colorectal Cancer: A Retrospective Cohort Study","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Colorectal cancer, Prognostic model, Systemic inflammation, Nomogram, SIRI","lastPublishedDoi":"10.21203/rs.3.rs-6931060/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6931060/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eColorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. The current TNM staging systems exhibit limited prognostic accuracy because they do not account for host inflammatory responses. This study aimed to develop and validate a novel prognostic nomogram integrating clinicopathological features with systemic inflammatory biomarkers to improve survival prediction in patients with CRC after radical resection.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eIn this retrospective cohort study, clinical data from\u0026zwnj; 324 patients with CRC who underwent surgery between January 2010 and March 2020 were analyzed. Preoperative hematological indices\u0026zwnj; (including NLR, PLR, LMR, FAR, \u0026zwnj;dNLR\u0026zwnj;, MCVL, SIRI, SII, PNI, IIC, PINI, HALP) \u0026zwnj;and clinicopathological variables were assessed., Variable selection \u0026zwnj;was conducted\u0026zwnj; using univariate Cox analysis, LASSO regression (Lambda.1se) and multivariate Cox analysis. The final model was constructed \u0026zwnj; as a nomogram and validated for 1-, 3-, and 5-year overall survival (OS) predictions using ROC analysis, calibration curves, and decision curve analysis (DCA).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMultivariate analysis identified four independent prognostic factors: N stage (N1: HR\u0026thinsp;=\u0026thinsp;2.72, 95% CI 1.51\u0026ndash;4.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; N2: HR\u0026thinsp;=\u0026thinsp;5.26, 95% CI 2.60\u0026ndash;10.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), vascular invasion (HR\u0026thinsp;=\u0026thinsp;6.02, 95% CI 3.79\u0026ndash;9.58, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), perineural invasion (HR\u0026thinsp;=\u0026thinsp;2.02, 95% CI 1.29\u0026ndash;3.16, p\u0026thinsp;=\u0026thinsp;0.002), and SIRI\u0026thinsp;\u0026ge;\u0026thinsp;2.39 (HR\u0026thinsp;=\u0026thinsp;2.03, 95% CI 1.33\u0026ndash;3.09, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The nomogram demonstrated \u0026zwnj;significantly\u0026zwnj; superior prognostic accuracy compared with conventional \u0026zwnj;TNM staging\u0026zwnj;, with excellent calibration in both the training and validation cohorts. DCA confirmed \u0026zwnj; the significant net clinical benefits of the nomogram\u0026zwnj;. Risk stratification revealed \u0026zwnj;significantly divergent\u0026zwnj; survival rates between the high- and low-risk groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur inflammatory-clinicopathological nomogram \u0026zwnj;provides superior prognostic accuracy\u0026zwnj; to conventional TNM staging, \u0026zwnj;enabling\u0026zwnj; personalized risk assessment and treatment optimization for patients with CRC. \u0026zwnj;SIRI integration, as a key biomarker, underscores the critical role of systemic inflammation\u0026zwnj;.\u003c/p\u003e","manuscriptTitle":"Integration of Systemic Inflammation Response Index (SIRI) and Clinicopathological Factors Enhances Survival Prediction in Colorectal Cancer: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-17 20:07:28","doi":"10.21203/rs.3.rs-6931060/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"14625b69-7244-484a-9a32-7ab74e73690f","owner":[],"postedDate":"July 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-20T13:53:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-17 20:07:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6931060","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6931060","identity":"rs-6931060","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}