Development and Internal Validation of a Clinical Cox Model for Predicting Overall Survival in Patients with Lung Cancer: Real-World Evidence from Seven Hospitals in China

Development and Internal Validation of a Clinical Cox Model for Predicting Overall Survival in Patients with Lung Cancer: Real-World Evidence from Seven Hospitals in China | 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 Development and Internal Validation of a Clinical Cox Model for Predicting Overall Survival in Patients with Lung Cancer: Real-World Evidence from Seven Hospitals in China LiHui Liu, Pan Zuo, Chunlan Yu, Xinhai Shen, Yong Zhou, Baoping Luo, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7743556/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 In routine practice, complete TNM staging is often unavailable, limiting the prognostic utility of staging alone. We investigated whether a pragmatic clinical-variable–only Cox model based on routinely collected data could provide robust short- to mid-term risk stratification for overall survival (OS) compared with a simple stage-only model using an ordinal three-level system (early/mid/late). Methods We undertook a multicentre retrospective cohort study across seven hospitals in China. Consecutive adults with pathologically confirmed lung cancer diagnosed between 2011 and 2023 were screened; after prespecified exclusions, 865 patients were included and split into training (n=584) and internal validation (n=281) cohorts. Median follow-up was 8 months (range, 1–114). Prespecified predictors were smoking status, white blood cell count (WBC), lymphocyte count (LYM), prothrombin activity (PTA), D-dimer level, receipt of chemotherapy in the initial treatment window, and age. The comparator was a staging-only Cox model (three-level staging). The primary outcome was OS (diagnosis to death; censored at last contact). Performance was evaluated using time-dependent AUCs at 6/12/18 months and the C-index; calibration intercept/slope and plots; decision-curve analysis (DCA); and categorical and continuous net reclassification improvement (NRI). Risk-stratified Kaplan–Meier curves assessed separation. Results Multivariable Cox regression showed independent associations with OS for smoking (HR 1.57, 95% CI 1.26–1.96), WBC (HR 1.015, 95% CI 1.000–1.030), LYM (HR 0.98, 95% CI 0.966–0.993), PTA (HR 0.986, 95% CI 0.981–0.992), D-dimer (HR 1.036, 95% CI 1.019–1.053), chemotherapy (HR 0.434, 95% CI 0.273–0.688), and age (HR 1.038, 95% CI 1.027–1.048). Discrimination at 6/12/18 months was acceptable to good (training AUCs 0.729/0.761/0.761; validation AUCs 0.804/0.789/0.803), with overall good calibration (close alignment with the ideal line in the 0.30–0.80 range). Versus the staging-only model, validation AUCs for the comparator were ~0.512/0.516/0.525, and the clinical model achieved greater net benefit across DCA thresholds ~0.10–0.80; time-dependent discrimination substantially favored the clinical model (ΔC, fit2−fit1 = −0.253; 95% CI −0.292 to −0.204; p=6.56×10⁻³⁰). Reclassification improved at each horizon (categorical NRI 0.839/0.473/0.473; continuous NRI 0.879/0.884/0.884). Kaplan–Meier curves showed clear, monotonic separation of low-, intermediate-, and high-risk groups. Conclusions In this seven-centre real-world cohort, a clinical variable–only Cox model built from routinely available data outperformed a staging-only approach for predicting 6–18-month OS, showing superior discrimination, acceptable calibration, greater net benefit, and substantial reclassification gains. These findings support the use of readily obtainable clinical data for short- to mid-term risk stratification and shared decision-making when detailed TNM information is scarce. Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7743556","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":522364861,"identity":"ddda8b01-3fde-444e-81a5-d8484256a004","order_by":0,"name":"LiHui 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We investigated whether a pragmatic clinical-variable–only Cox model based on routinely collected data could provide robust short- to mid-term risk stratification for overall survival (OS) compared with a simple stage-only model using an ordinal three-level system (early/mid/late).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe undertook a multicentre retrospective cohort study across seven hospitals in China. Consecutive adults with pathologically confirmed lung cancer diagnosed between 2011 and 2023 were screened; after prespecified exclusions, 865 patients were included and split into training (n=584) and internal validation (n=281) cohorts. Median follow-up was 8 months (range, 1–114). Prespecified predictors were smoking status, white blood cell count (WBC), lymphocyte count (LYM), prothrombin activity (PTA), D-dimer level, receipt of chemotherapy in the initial treatment window, and age. The comparator was a staging-only Cox model (three-level staging). The primary outcome was OS (diagnosis to death; censored at last contact). Performance was evaluated using time-dependent AUCs at 6/12/18 months and the C-index; calibration intercept/slope and plots; decision-curve analysis (DCA); and categorical and continuous net reclassification improvement (NRI). Risk-stratified Kaplan–Meier curves assessed separation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariable Cox regression showed independent associations with OS for smoking (HR 1.57, 95% CI 1.26–1.96), WBC (HR 1.015, 95% CI 1.000–1.030), LYM (HR 0.98, 95% CI 0.966–0.993), PTA (HR 0.986, 95% CI 0.981–0.992), D-dimer (HR 1.036, 95% CI 1.019–1.053), chemotherapy (HR 0.434, 95% CI 0.273–0.688), and age (HR 1.038, 95% CI 1.027–1.048). Discrimination at 6/12/18 months was acceptable to good (training AUCs 0.729/0.761/0.761; validation AUCs 0.804/0.789/0.803), with overall good calibration (close alignment with the ideal line in the 0.30–0.80 range). Versus the staging-only model, validation AUCs for the comparator were ~0.512/0.516/0.525, and the clinical model achieved greater net benefit across DCA thresholds ~0.10–0.80; time-dependent discrimination substantially favored the clinical model (ΔC, fit2−fit1 = −0.253; 95% CI −0.292 to −0.204; p=6.56×10⁻³⁰). Reclassification improved at each horizon (categorical NRI 0.839/0.473/0.473; continuous NRI 0.879/0.884/0.884). Kaplan–Meier curves showed clear, monotonic separation of low-, intermediate-, and high-risk groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this seven-centre real-world cohort, a clinical variable–only Cox model built from routinely available data outperformed a staging-only approach for predicting 6–18-month OS, showing superior discrimination, acceptable calibration, greater net benefit, and substantial reclassification gains. These findings support the use of readily obtainable clinical data for short- to mid-term risk stratification and shared decision-making when detailed TNM information is scarce.\u003c/p\u003e","manuscriptTitle":"Development and Internal Validation of a Clinical Cox Model for Predicting Overall Survival in Patients with Lung Cancer: Real-World Evidence from Seven Hospitals in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 08:22:44","doi":"10.21203/rs.3.rs-7743556/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":"6d77061b-ffa2-42c3-b89b-2d9c117a9f5a","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-03T20:23:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 08:22:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7743556","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7743556","identity":"rs-7743556","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}