{"paper_id":"0eb35f72-10cd-4f14-bfb9-8b721a6f9b14","body_text":"Clinical Characteristics and Risk Factors for Recurrence or Progression of Pediatric Intracranial Pilocytic Astrocytoma: A Single-center Retrospective 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 Clinical Characteristics and Risk Factors for Recurrence or Progression of Pediatric Intracranial Pilocytic Astrocytoma: A Single-center Retrospective Study Qingtian Liang, Sihan Zhu, Yizhu Du, Zuqing Wu, Zhuqing Cheng, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8290546/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 Objective To identify risk factors for recurrence or progression in pediatric intracranial pilocytic astrocytoma (PA) and develop a prognostic model for 5-year progression-free survival (PFS). Methods This retrospective study included patients under 18 diagnosed with PA (2010–2024). Variables with P < 0.1 in univariate analysis were entered into multivariate Cox modeling, with the final model selected by bidirectional stepwise selection using the lowest Akaike information criterion (AIC). Model performance was assessed by concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, time-dependent area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Internal validation was performed by bootstrapping, and a nomogram was constructed for risk stratification. Kaplan-Meier (K-M) and log-rank tests were used to compare survival outcomes. Results Seventy-two patients were included. Age ≤ 3 years (HR = 0.13, P = 0.02), supratentorial tumor location (HR = 7.69, P = 0.02), and Ki-67 ≥ 5% (HR = 16.42, P < 0.001) were independent predictors of recurrence/progression. The model showed excellent discrimination (C-index = 0.92; bootstrap-corrected = 0.89) and good calibration. Time-dependent AUCs at 1, 3, and 5 years were 0.906, 0.911, and 0.911, respectively. The nomogram showed that Ki-67 contributed the greatest prognostic weight, followed by age and tumor location. Patients with higher total scores (> 158.76) had significantly shorter 5-year PFS. Conclusions This nomogram may assist clinicians in estimating postoperative prognosis in children and adolescents with PA. It provides a foundation for future studies incorporating larger cohorts and molecular markers, and may help identify high-risk patients even after gross total resection (GTR). pilocytic astrocytoma pediatric brain tumor low-grade glioma risk factors prognosis prognostic model 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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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\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research 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Variables with P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.1 in univariate analysis were entered into multivariate Cox modeling, with the final model selected by bidirectional stepwise selection using the lowest Akaike information criterion (AIC). Model performance was assessed by concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, time-dependent area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Internal validation was performed by bootstrapping, and a nomogram was constructed for risk stratification. Kaplan-Meier (K-M) and log-rank tests were used to compare survival outcomes.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eSeventy-two patients were included. Age\\u0026thinsp;\\u0026le;\\u0026thinsp;3 years (HR\\u0026thinsp;=\\u0026thinsp;0.13, P\\u0026thinsp;=\\u0026thinsp;0.02), supratentorial tumor location (HR\\u0026thinsp;=\\u0026thinsp;7.69, P\\u0026thinsp;=\\u0026thinsp;0.02), and Ki-67\\u0026thinsp;\\u0026ge;\\u0026thinsp;5% (HR\\u0026thinsp;=\\u0026thinsp;16.42, P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) were independent predictors of recurrence/progression. The model showed excellent discrimination (C-index\\u0026thinsp;=\\u0026thinsp;0.92; bootstrap-corrected\\u0026thinsp;=\\u0026thinsp;0.89) and good calibration. Time-dependent AUCs at 1, 3, and 5 years were 0.906, 0.911, and 0.911, respectively. The nomogram showed that Ki-67 contributed the greatest prognostic weight, followed by age and tumor location. Patients with higher total scores (\\u0026gt;\\u0026thinsp;158.76) had significantly shorter 5-year PFS.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eThis nomogram may assist clinicians in estimating postoperative prognosis in children and adolescents with PA. 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