Temporal trends and short term prediction of relative survival in ependymoma using model based period analysis

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Population-based evidence on temporal changes in survival remains limited, and up-to-date estimates are particularly needed 4,5 . We therefore used model-based period analysis to evaluate temporal trends in relative survival and to generate short-term forecasts in patients with ependymoma 6,7 . Methods Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) database 8 (Incidence – SEER Research Data, 17 Registries, Nov 2024 Sub). Patients diagnosed during 2000–2019 with ICD-O-3 histology/behavior codes 9391/3, 9392/3, 9393/3, and 9394/3 and primary sites restricted to C71.* and C72.0–C72.1 were included. Five-year relative survival (RS) was estimated using period analysis 9,10 ; expected survival was derived using the Ederer II method 11 , and standard errors were calculated using Greenwood’s formula. Diagnosis periods were grouped as 2000–2004, 2005–2009, 2010–2014, and 2015–2019. Temporal trends were assessed across diagnosis-period mid-years on the absolute survival scale. Given that only four observed diagnosis periods were available, Joinpoint analysis was used only to assess whether an overall linear trend was present, rather than to identify multiple slope changes. Short-term forecasts for 2020–2024 were generated using inverse-variance-weighted models based on the observed period estimates. Results The baseline descriptive cohort included 4,070 patients, and the RS analytic cohort included 3,770 patients. Overall 5-year RS increased from 81.7% in 2000–2004 to 89.5% in 2015–2019. Period-specific estimates supported a significant upward linear trend over time. Non-anaplastic ependymoma showed consistently high 5-year RS, increasing from 86.1% to 94.4%, whereas anaplastic ependymoma showed lower but improving RS, increasing from 55.1% to 74.1%. Temporal improvement was more pronounced in anaplastic disease than in non-anaplastic disease. Model-based short-term forecasts suggested that overall 5-year RS may continue to improve in 2020–2024. Spinal/cauda equina tumors showed persistently favorable survival, whereas infratentorial and other intracranial tumors had lower RS with gradual improvement. In supplementary stage analyses, localized disease consistently showed better RS than non-localized disease. Conclusions Model-based period analysis showed a steady improvement in 5-year relative survival for ependymoma from 2000–2004 to 2015–2019. Short-term forecasts suggested that this favorable pattern may extend into 2020–2024, although prognostic heterogeneity remained evident across major clinicopathological subgroups. Ependymoma relative survival period analysis SEER population-based study short-term prediction Figures Figure 1 Figure 2 Figure 3 Introduction Ependymoma is a rare tumor of the central nervous system that arises throughout the neuraxis and affects both children and adults 3 , 12 – 14 . Its clinical behavior is highly heterogeneous, reflecting variation in anatomical site, histological subtype, age at diagnosis, and disease extent. Although gross total resection remains a cornerstone of management, prognosis differs substantially across patient subgroups, and long-term survival patterns at the population level remain incompletely characterized 3 , 4 , 12 . Many previous population-based studies of ependymoma have focused on overall survival or cause-specific survival using conventional cohort-based methods 15 – 19 . However, these approaches may be less suitable for describing the most current survival experience in a setting where diagnosis, classification, and treatment continue to evolve. In contrast, relative survival provides a useful population-level measure that does not depend on the accuracy of cause-of-death classification, and period analysis can generate more up-to-date survival estimates than traditional cohort approaches. In addition, model-based period analysis has been used to facilitate formal assessment of temporal trends and short-term forecasting of survival 6 . Therefore, using the SEER database, the present study aimed to: (1) estimate period-specific 5-year relative survival for patients with ependymoma diagnosed during 2000–2019; (2) evaluate temporal trends in relative survival using model-based period analysis, with supplementary trend assessment based on diagnosis-period mid-years; and (3) assess whether temporal survival patterns differed according to histology, primary site group, and stage. By doing so, we sought to provide a contemporary population-based description of temporal survival trends in ependymoma and a cautious short-term forecast based on observed period estimates. Methods Data source and study population Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program using the Incidence – SEER Research Data, 17 Registries, Nov 2024 Sub (2000–2022). Ependymoma was identified using ICD-O-3 histology/behavior codes 9391/3, 9392/3, 9393/3, and 9394/3. The primary site was restricted to C71.* (brain) and C72.0–C72.1 (spinal cord/cauda equina). Although the selected SEER submission provides follow-up through 2022, the main analyses were restricted to patients diagnosed during 2000–2019 to maintain comparability across four predefined, non-overlapping 5-year diagnosis periods (2000–2004, 2005–2009, 2010–2014, and 2015–2019). Cases diagnosed in 2020–2022 were not included in the main trend figures because they do not constitute a diagnosis period directly comparable to the four complete 5-year intervals used in the present model-based period analysis. Period analysis and estimation of relative survival Period analysis was used to estimate 5-year relative survival (RS). Relative survival was defined as the ratio of observed survival in the patient cohort to expected survival in the general population. Expected survival was derived from SEER life tables using the Ederer II method, and standard errors were calculated using Greenwood’s formula. Period-specific 5-year RS estimates with 95% confidence intervals (CI) were reported for each diagnosis period. This approach was chosen to provide more up-to-date survival estimates than traditional cohort-based survival analyses. Stratification variables Histology was stratified into anaplastic ependymoma (ICD-O-3 9392/3) and non-anaplastic ependymoma (ICD-O-3 9391/3, 9393/3, and 9394/3). Primary site was categorized into three clinically interpretable groups: Spinal/Cauda equina (C72.0–C72.1), Infratentorial (C71.6–C71.7), and Other intracranial (C71.0–C71.5, C71.8–C71.9). The non-anaplastic category was used as a pragmatic analytic grouping to provide stable population-level estimates across histological subtypes with similar expected prognosis. Stage-stratified analyses were conducted as supplementary analyses using the Combined Summary Stage with Expanded Regional Codes (2004+) variable. To align with 5-year diagnosis periods, stage analyses were restricted to 2005–2019 and summarized as Localized only versus Non-localized (Regional + Distant combined). Unknown/unstaged cases were excluded from stage-stratified survival analyses. Assessment of temporal trends Temporal trends in period estimates of 5-year RS were evaluated using diagnosis-period mid-years (2002, 2007, 2012, and 2017) as the time variable. Because only four observed diagnosis periods were available, the primary objective was to assess whether an overall linear temporal trend was present rather than to identify multiple changes in slope. Joinpoint regression on the linear scale was therefore used as a supplementary trend-assessment procedure. For the overall and histology-stratified analyses, the final selected models contained 0 joinpoints, supporting interpretation of a single approximately linear trend over time. The slope represents the absolute change in 5-year RS (percentage points) per calendar year, and statistical significance was assessed at α = 0.05. Prediction of 5-year relative survival for 2020–2024 To generate short-term forecasts for the subsequent diagnosis period (2020–2024), inverse-variance-weighted models were fitted to the observed period-specific 5-year RS estimates from 2000–2004, 2005–2009, 2010–2014, and 2015–2019, using diagnosis-period mid-year (2002, 2007, 2012, and 2017) as the time variable. Predictions were then obtained for the mid-year 2022, corresponding to the diagnosis period 2020–2024. Because these forecasts were based on a small number of observed periods, they were interpreted as short-term extrapolations rather than validated future observations. Predicted values were restricted to the plausible range of 0% to 100%, and detailed uncertainty estimates are reported in Supplementary Table S4. Statistical considerations Baseline descriptive characteristics were summarized for the baseline descriptive cohort, whereas RS estimates were derived from the RS analytic cohort generated by the SEER*Stat relative survival session. Accordingly, differences in sample size between descriptive and analytic tables reflect differences in eligibility for relative survival estimation rather than inconsistencies in disease definition. These two cohorts served different analytic purposes and should therefore not be expected to have identical denominators. Results Study cohort The baseline descriptive cohort included 4,070 patients diagnosed during 2000–2019 who met the site and histology criteria. Baseline characteristics across diagnosis periods are summarized in Table 1 . Table 1 Baseline characteristics of patients with ependymoma by diagnosis period in the baseline descriptive cohort. Characteristic 2000–2004 (n = 955) 2005–2009 (n = 1036) 2010–2014 (n = 1046) 2015–2019 (n = 1033) Sex Male 491 (51.41%) 533 (51.45%) 542 (51.82%) 528 (51.11%) Female 464 (48.59%) 503 (48.55%) 504 (48.18%) 505 (48.89%) Race White 815 (85.34%) 867 (83.69%) 862 (82.41%) 823 (79.67%) Black 81 (8.48%) 87 (8.40%) 94 (8.99%) 99 (9.58%) Other 52 (5.45%) 72 (6.95%) 79 (7.55%) 90 (8.71%) Unknown 7 (0.73%) 10 (0.97%) 11 (1.05%) 21 (2.03%) Age at diagnosis (years) 0–17 243 (25.45%) 248 (23.94%) 263 (25.14%) 251 (24.30%) 18–39 234 (24.50%) 258 (24.90%) 254 (24.28%) 256 (24.78%) 40–59 340 (35.60%) 349 (33.69%) 314 (30.02%) 323 (31.27%) ≥ 60 138 (14.45%) 181 (17.47%) 215 (20.55%) 203 (19.65%) Histology Anaplastic (9392/3) 130 (13.61%) 177 (17.08%) 221 (21.13%) 233 (22.56%) Non-anaplastic (9391/3, 9393/3, 9394/3) 825 (86.39%) 859 (82.92%) 825 (78.87%) 800 (77.44%) Stage (summary stage, expanded regional codes; 2004+) Localized only — 843 (81.37%) 880 (84.13%) 878 (85.00%) Non-localized — 136 (13.13%) 130 (12.43%) 104 (10.07%) Unknown/unstaged — 57 (5.50%) 36 (3.44%) 51 (4.94%) Primary site group Spinal/Cauda equina 432 (45.24%) 471 (45.46%) 486 (46.46%) 502 (48.60%) Infratentorial 200 (20.94%) 249 (24.03%) 211 (20.17%) 223 (21.59%) Other intracranial 323 (33.82%) 316 (30.50%) 349 (33.37%) 308 (29.82%) Stage distribution in Table 1 is based on the baseline descriptive cohort. Stage-stratified relative survival analyses were performed in the RS analytic cohort and are reported in Supplementary Tables S2–S3. Cases diagnosed in 2000–2004 are shown with stage unavailable in the main table because the expanded stage variable was used for supplementary analyses restricted to 2005–2019. For period estimation of 5-year RS, the RS analytic cohort included 3,770 patients, with period-specific sample sizes of 896 in 2000–2004, 961 in 2005–2009, 966 in 2010–2014, and 947 in 2015–2019. Baseline characteristics The distribution of baseline characteristics across diagnosis periods is shown in Table 1 . Across periods, the sex distribution remained relatively stable, with a slight male predominance. The proportion of older patients gradually increased over time, whereas the proportion of pediatric patients slightly decreased in the most recent period. Non-anaplastic histology remained the predominant subtype across all diagnosis periods, although the proportion of anaplastic tumors increased from 13.3% in 2000–2004 to 22.1% in 2015–2019. Spinal/cauda equina tumors accounted for the largest site-based subgroup throughout the study period. Overall period estimates and trend Overall 5-year RS estimated by period analysis increased steadily across diagnosis periods, from 81.7% in 2000–2004 to 89.5% in 2015–2019 ( Fig. 2 A; Table 2 ). Analysis across diagnosis-period mid-years supported a significant increasing trend in overall 5-year RS. Supplementary Joinpoint analysis selected 0 joinpoints, consistent with an approximately linear improvement over 2002–2017. Table 2 Observed period-specific and model-based predicted 5-year relative survival in the overall cohort and histology groups. Section Group Period N RS (95% CI) SE Histology Anaplastic (ICD-O-3 9392/3) 2000–2004 123 55.1 (46.3–63.9) 4.5 Histology Anaplastic (ICD-O-3 9392/3) 2005–2009 169 63.5 (56.1–70.9) 3.8 Histology Anaplastic (ICD-O-3 9392/3) 2010–2014 212 68.1 (61.6–74.6) 3.3 Histology Anaplastic (ICD-O-3 9392/3) 2015–2019 228 74.1 (68.0–80.2) 3.1 Histology Anaplastic (ICD-O-3 9392/3) 2020–2024 80.3 Histology Non-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3) 2000–2004 773 86.1 (83.4–88.8) 1.4 Histology Non-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3) 2005–2009 792 90.8 (88.4–93.2) 1.2 Histology Non-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3) 2010–2014 754 93.2 (91.0–95.4) 1.1 Histology Non-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3) 2015–2019 719 94.4 (92.0–96.8) 1.2 Histology Non-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3) 2020–2024 97.9 Overall Overall 2000–2004 896 81.7 (79.0–84.4) 1.4 Overall Overall 2005–2009 961 86.0 (83.6–88.4) 1.2 Overall Overall 2010–2014 966 87.8 (85.4–90.2) 1.2 Overall Overall 2015–2019 947 89.5 (87.1–91.9) 1.2 Overall Overall 2020–2024 92.4 Observed values are presented as RS (95% CI) . The 2020–2024 column shows the model-based predicted 5-year RS. Detailed prediction uncertainty intervals and subgroup-specific trend parameters are provided in Supplementary Table S4 . Histology-stratified period estimates and trends When stratified by histology, non-anaplastic ependymoma consistently showed high 5-year RS with a gradual increase over time (86.1% in 2000–2004 to 94.4% in 2015–2019). In contrast, anaplastic ependymoma had substantially lower 5-year RS but demonstrated improvement across periods (55.1% in 2000–2004 to 74.1% in 2015–2019) ( Fig. 2 B; Table 2 ). Both histological subgroups showed increasing period-specific 5-year RS over time. Supplementary Joinpoint analysis selected 0 joinpoints for both subgroup models, indicating that the observed improvement was compatible with a single linear increasing trend across the study periods. The increasing trend was more pronounced for anaplastic ependymoma (1.206 percentage points/year; slope = 1.206420, SE = 0.099618, P = 0.006749), whereas non-anaplastic ependymoma also increased significantly (0.530 percentage points/year; slope = 0.530024, SE = 0.115440, P = 0.044308) (Supplementary Table S1). Despite these improvements, anaplastic ependymoma consistently exhibited lower 5-year RS and wider uncertainty due to smaller sample sizes. Prediction of 5-year relative survival for 2020–2024 Model-based short-term extrapolation suggested that the favorable trend in 5-year RS may extend into 2020–2024. The forecasted 5-year RS for the overall cohort was higher than that observed in 2015–2019, and similar upward patterns were seen in the histology-stratified analyses ( Table 2 ; Supplementary Table S4). These forecasted values should be interpreted cautiously because they were derived from a limited number of observed diagnosis periods. In supplementary subgroup forecasts, the predicted 5-year RS for primary site groups in 2020–2024 was 96.1% for spinal/cauda equina tumors, 87.8% for infratentorial tumors, and 87.9% for other intracranial tumors. In stage-stratified forecasts, the predicted 5-year RS was 92.6% for localized disease and 74.8% for non-localized disease. These supplementary predictions should be interpreted cautiously, particularly for stage-specific analyses, because they were based on fewer observed diagnosis periods and, in some subgroups, smaller sample sizes ( Fig. 3 , Supplementary Figure S1, and Supplementary Table S4). Supplementary analyses Primary site group Period estimates of 5-year RS differed by primary site group ( Fig. 3 ). Spinal/cauda equina tumors exhibited consistently high 5-year RS across periods (approximately 95–96%), while infratentorial and other intracranial tumors showed lower RS with temporal improvement. These subgroup-specific forecasts were descriptive and exploratory, particularly for site groups with relatively stable or near-ceiling survival estimates. Stage Stage-stratified analyses were performed as supplementary analyses for cases diagnosed in 2005–2019. Unknown/unstaged cases were excluded from stage-stratified analyses (2005–2009: 26/961, 2.7%; 2010–2014: 18/966, 1.9%; 2015–2019: 28/947, 3.0%; Supplementary Table S2). Overall, localized disease exhibited consistently higher 5-year RS than non-localized disease across diagnosis periods (Supplementary Figure S1; Supplementary Table S3). In stage-stratified forecasts, the predicted 5-year RS for 2020–2024 was 92.6% for localized disease and 74.8% for non-localized disease (Supplementary Table S4). Stage-specific forecasts, particularly for non-localized disease, should be interpreted cautiously because they were based on only three observed diagnosis periods and relatively small subgroup sizes. Discussion In this population-based study using SEER data, we found that 5-year relative survival for ependymoma improved steadily from 2000–2004 to 2015–2019. Analysis across diagnosis-period mid-years supported an approximately linear increase over time, and short-term extrapolation suggested that this favorable pattern may extend into 2020–2024. Although anaplastic ependymoma consistently showed worse survival than non-anaplastic disease 12 , its survival improved more rapidly over time in our analysis, which may reflect advances in diagnosis, risk stratification, and multidisciplinary treatment during the study period. Several factors may underlie the temporal improvement in relative survival observed in this study. Advances in neuroimaging and neuropathological classification may have improved diagnostic precision and case ascertainment over time 20 . Refinements in microsurgical techniques, perioperative management, radiotherapy delivery, and multidisciplinary care may also have increased the likelihood of effective resection and optimized postoperative treatment 13 . At the population level, these developments may together have contributed to the progressive survival improvement observed across successive diagnosis periods. Our subgroup analyses further demonstrated marked heterogeneity in survival patterns. Non-anaplastic tumors maintained consistently high 5-year relative survival across diagnosis periods, whereas anaplastic tumors showed lower but progressively improving survival. This pattern is clinically plausible and is consistent with established biological and prognostic differences across ependymoma subtypes12. Similarly, tumors arising in the spinal cord or cauda equina showed the highest relative survival, whereas infratentorial and other intracranial tumors had lower survival with gradual improvement over time3. These differences may reflect variation in tumor biology, anatomical accessibility, extent of resection, and postoperative functional risk. In supplementary stage analyses, localized disease consistently showed better relative survival than non-localized disease, further supporting the prognostic importance of disease extent. Overall, these findings suggest that improvements in population-level survival are not necessarily accompanied by uniform prognostic gains across all clinicopathological subgroups. Model-based short-term extrapolation suggested that the favorable pattern observed through 2015–2019 may extend into the subsequent diagnosis period. However, these estimates should be interpreted as model-based short-term projections rather than verified future observations, especially in subgroup analyses based on a limited number of diagnosis periods or small sample sizes. Stage-specific projections likewise warrant caution, because estimates in more finely stratified groups are more vulnerable to modeling assumptions and random variation 6 . The present study illustrates the utility of combining relative survival with period analysis to monitor contemporary survival patterns in a rare central nervous system tumor. Relative survival offers an important advantage in registry-based studies because it does not rely on the accuracy of cause-of-death attribution, whereas period analysis provides more up-to-date survival estimates than traditional cohort-based approaches. The additional forecasting component may be useful for descriptive short-term planning, but such projections should be interpreted cautiously when only a limited number of observed diagnosis periods are available 21 . Several limitations should be acknowledged. First, this was a retrospective registry-based analysis and is therefore subject to the inherent constraints of observational data. Second, although SEER provides broad population coverage, the database lacks several potentially important clinical variables, including extent of resection, radiotherapy dose and field, systemic treatment details, recurrence patterns, molecular subgroup information, and central pathology review. Third, baseline descriptive analyses and relative survival analyses were derived from related but not identical cohorts, because eligibility for relative survival estimation depends on the SEER*Stat relative survival framework and follow-up information. Fourth, an additional methodological limitation is that only four observed diagnosis periods were available for the main analyses, and only three periods were available for stage-stratified analyses. Accordingly, Joinpoint outputs should be interpreted as support for an overall linear temporal trend rather than evidence for discrete slope changes, and subgroup-specific forecasts should be regarded as exploratory. Finally, although the SEER submission used in this study included follow-up through 2022, the main analyses were restricted to 2000–2019 to preserve comparability across four non-overlapping 5-year diagnosis periods. More recent years may be incorporated in future work using updated rolling-period or extended-period frameworks. Conclusion In summary, 5-year relative survival for ependymoma improved steadily across diagnosis periods from 2000–2004 to 2015–2019 in this SEER-based model-based period analysis. Short-term model-based extrapolation suggested that this favorable pattern may continue into 2020–2024, although substantial heterogeneity remained across histology, primary site group, and stage. These findings provide an updated population-based description of survival trends in ependymoma and support cautious use of period-based forecasting for short-term monitoring. Declarations Consent to publish Not applicable. Data availability statement The datasets analyzed during the current study were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. SEER data are available through the official SEER Program and SEER*Stat platform. Direct links are as follows: https://seer.cancer.gov/ ; https://seer.cancer.gov/data/ ; https://seer.cancer.gov/seerstat/. Ethics approval This study used de-identified, publicly available SEER data; therefore, institutional review board approval and informed consent were not required. Author Contributions All authors contributed to the study conception and design. The study was conceptualized and supervised by Xiangyu Wang and Jun Lyu. Material preparation, data collection, and statistical analysis were performed by Zhiling Tan, Wengang Li, Youzhong Ye, Zhuqing Xie and Changju Hui. The first draft of the manuscript was written by Zhiling Tan, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding No funding was received for this study. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Jeong D, et al. Multidimensional profiling of heterogeneity in supratentorial ependymomas. Nature. 2026. https://doi.org/10.1038/s41586-026-10214-2 . Obrecht-Sturm D, et al. Distinct relapse pattern across molecular ependymoma types. Neuro-Oncol. 2025;27:267–76. Ghasemi DR et al. A brief history of ependymoma. Neuro-Oncol. noag016 (2026) 10.1093/neuonc/noag016 Hoogendijk R, et al. Long-term survival and cure fraction estimates for paediatric central nervous system tumours in 31 european countries (EUROCARE-6): A population-based study. Lancet Oncol. 2025;26:1091–9. Price M, et al. 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Supplementary Files SupplementaryTables.docx SupplementaryFigureS1.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 05 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers agreed at journal 01 May, 2026 Reviewers invited by journal 02 Apr, 2026 Editor invited by journal 24 Mar, 2026 Editor assigned by journal 21 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 18 Mar, 2026 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-9122854","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":617835977,"identity":"a1b5c8b1-92e5-4d98-844c-ddeb01da2444","order_by":0,"name":"Zhiling Tan","email":"","orcid":"","institution":"First Affiliated Hospital of Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Zhiling","middleName":"","lastName":"Tan","suffix":""},{"id":617835978,"identity":"51e7cb5d-e0f9-4e6b-b6b2-347c1ba2d126","order_by":1,"name":"Wengang Li","email":"","orcid":"","institution":"The First People's Hospital of Chenzhou","correspondingAuthor":false,"prefix":"","firstName":"Wengang","middleName":"","lastName":"Li","suffix":""},{"id":617835979,"identity":"70874db1-84d6-4beb-bf6a-7544953a5dcf","order_by":2,"name":"Youzhong Ye","email":"","orcid":"","institution":"The First People's Hospital of Chenzhou","correspondingAuthor":false,"prefix":"","firstName":"Youzhong","middleName":"","lastName":"Ye","suffix":""},{"id":617835980,"identity":"1a90f811-4471-48f4-870b-fa57bf1119b7","order_by":3,"name":"Zhuqing Xie","email":"","orcid":"","institution":"The First People's Hospital of Chenzhou","correspondingAuthor":false,"prefix":"","firstName":"Zhuqing","middleName":"","lastName":"Xie","suffix":""},{"id":617835981,"identity":"7e8937d2-7bf5-4a7a-bfa1-d2b583eb526a","order_by":4,"name":"Changju Hui","email":"","orcid":"","institution":"Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Changju","middleName":"","lastName":"Hui","suffix":""},{"id":617835982,"identity":"04786856-9111-4b41-bfd9-9c7c81d158a7","order_by":5,"name":"Xiangyu Wang","email":"","orcid":"","institution":"First Affiliated Hospital of Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Xiangyu","middleName":"","lastName":"Wang","suffix":""},{"id":617835983,"identity":"a8bdefd5-4a83-4bd7-8d63-07ae7dada702","order_by":6,"name":"Jun Lyu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIie3NPQrCMBTA8SeBuqTVMVKoV4hkFbxKguBUoSK4qgjxCu3gHZzEseLgEpw76tJNEHoATf0Cl8bRIX8IeTz48QBstj/M048CdHEDoZQ+VqmBOE8yCFpLyX8nuj2jSj2FmZCQjt0tErMsvI5HEgIv47UiMhDmKkfM4+GaJRJYK+PIj41EYrEgmrgSxDrjDsJmQoQk4akk018JZRgrKAmnRoLzqLOSPCD10h1JJ1HnhV9FGvX+hl7kDff2KGd40m17h/6uqCLQ5A59X9QD0X9tVgX0mRSdXuNnsNlsNttXd42+Q+IQYglTAAAAAElFTkSuQmCC","orcid":"","institution":"First Affiliated Hospital of Jinan University","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Lyu","suffix":""}],"badges":[],"createdAt":"2026-03-14 13:24:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9122854/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9122854/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106382598,"identity":"d166aff6-e39c-448f-9aca-3f55f66dfa72","added_by":"auto","created_at":"2026-04-08 05:28:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":163615,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of cohort selection for the baseline descriptive cohort, RS analytic cohort, and supplementary stage-stratified cohort. The stage-stratified supplementary analysis was restricted to cases diagnosed in 2005–2019.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9122854/v1/40ad6003f00a09a928409029.png"},{"id":106404655,"identity":"ae606621-cadb-4a93-bdff-551655b08dc9","added_by":"auto","created_at":"2026-04-08 09:16:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":104938,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends in observed and predicted 5-year relative survival (RS) for the overall cohort and histology groups in ependymoma. Panel A shows the overall cohort, and Panel B shows the histology-stratified subgroups. Solid lines indicate observed period estimates for 2000–2004, 2005–2009, 2010–2014, and 2015–2019, and dashed lines indicate model-based predictions for 2020–2024. Anaplastic ependymoma was defined by ICD-O-3 code 9392/3, whereas non-anaplastic ependymoma included ICD-O-3 codes 9391/3, 9393/3, and 9394/3. Error bars indicate 95% confidence intervals for observed estimates and model-based uncertainty intervals for predicted values.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9122854/v1/29ebe17521185e337ecee431.png"},{"id":106382601,"identity":"106c4282-f25c-4578-9cb0-19604d79212d","added_by":"auto","created_at":"2026-04-08 05:28:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":113566,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends in observed and predicted 5-year relative survival (RS) by primary site group in ependymoma. Primary site groups were categorized as Spinal/Cauda equina, Infratentorial, and Other intracranial. Solid lines indicate observed period estimates for 2000–2004, 2005–2009, 2010–2014, and 2015–2019, and dashed lines indicate model-based predictions for 2020–2024. Error bars indicate 95% confidence intervals for observed estimates and model-based uncertainty intervals for predicted values.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9122854/v1/4a34c519f1a279f96c358b99.png"},{"id":106415132,"identity":"798fb69d-8d21-4575-ac3a-6c099e14ed62","added_by":"auto","created_at":"2026-04-08 10:33:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7840555,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9122854/v1/758861af-b25e-4f2a-bbf8-b56dcef7b775.pdf"},{"id":106382599,"identity":"2b942e09-439f-4f16-8438-b74a7014994b","added_by":"auto","created_at":"2026-04-08 05:28:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19439,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9122854/v1/5b6b7789c49b5bd5c92cefbd.docx"},{"id":106404555,"identity":"021491e1-58ea-49a3-a7b0-f5dc1f8635cf","added_by":"auto","created_at":"2026-04-08 09:16:13","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":94834,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9122854/v1/b782cd936117bd494268f00e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eTemporal trends and short term prediction of relative survival in ependymoma using model based period analysis \u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cb\u003eEpendymoma is a rare tumor of the central nervous system that arises throughout the neuraxis and affects both children and adults\u003c/b\u003e \u003csup\u003e \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. \u003cb\u003eIts clinical behavior is highly heterogeneous, reflecting variation in anatomical site, histological subtype, age at diagnosis, and disease extent. Although gross total resection remains a cornerstone of management, prognosis differs substantially across patient subgroups, and long-term survival patterns at the population level remain incompletely characterized\u003c/b\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMany previous population-based studies of ependymoma have focused on overall survival or cause-specific survival using conventional cohort-based methods\u003c/b\u003e \u003csup\u003e \u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. \u003cb\u003eHowever, these approaches may be less suitable for describing the most current survival experience in a setting where diagnosis, classification, and treatment continue to evolve. In contrast, relative survival provides a useful population-level measure that does not depend on the accuracy of cause-of-death classification, and period analysis can generate more up-to-date survival estimates than traditional cohort approaches. In addition, model-based period analysis has been used to facilitate formal assessment of temporal trends and short-term forecasting of survival\u003c/b\u003e\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTherefore, using the SEER database, the present study aimed to: (1) estimate period-specific 5-year relative survival for patients with ependymoma diagnosed during 2000\u0026ndash;2019; (2) evaluate temporal trends in relative survival using model-based period analysis, with supplementary trend assessment based on diagnosis-period mid-years; and (3) assess whether temporal survival patterns differed according to histology, primary site group, and stage. By doing so, we sought to provide a contemporary population-based description of temporal survival trends in ependymoma and a cautious short-term forecast based on observed period estimates.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source and study population\u003c/h2\u003e \u003cp\u003e \u003cb\u003eData were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program using the Incidence \u0026ndash; SEER Research Data, 17 Registries, Nov 2024 Sub (2000\u0026ndash;2022). Ependymoma was identified using ICD-O-3 histology/behavior codes 9391/3, 9392/3, 9393/3, and 9394/3. The primary site was restricted to C71.* (brain) and C72.0\u0026ndash;C72.1 (spinal cord/cauda equina).\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAlthough the selected SEER submission provides follow-up through 2022, the main analyses were restricted to patients diagnosed during 2000\u0026ndash;2019 to maintain comparability across four predefined, non-overlapping 5-year diagnosis periods (2000\u0026ndash;2004, 2005\u0026ndash;2009, 2010\u0026ndash;2014, and 2015\u0026ndash;2019). Cases diagnosed in 2020\u0026ndash;2022 were not included in the main trend figures because they do not constitute a diagnosis period directly comparable to the four complete 5-year intervals used in the present model-based period analysis.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePeriod analysis and estimation of relative survival\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003ePeriod analysis was used to estimate 5-year relative survival (RS). Relative survival was defined as the ratio of observed survival in the patient cohort to expected survival in the general population. Expected survival was derived from SEER life tables using the Ederer II method, and standard errors were calculated using Greenwood\u0026rsquo;s formula. Period-specific 5-year RS estimates with 95% confidence intervals (CI) were reported for each diagnosis period. This approach was chosen to provide more up-to-date survival estimates than traditional cohort-based survival analyses.\u003c/b\u003e \u003c/p\u003e\n\u003ch3\u003eStratification variables\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eHistology was stratified into anaplastic ependymoma (ICD-O-3 9392/3) and non-anaplastic ependymoma (ICD-O-3 9391/3, 9393/3, and 9394/3). Primary site was categorized into three clinically interpretable groups: Spinal/Cauda equina (C72.0\u0026ndash;C72.1), Infratentorial (C71.6\u0026ndash;C71.7), and Other intracranial (C71.0\u0026ndash;C71.5, C71.8\u0026ndash;C71.9). The non-anaplastic category was used as a pragmatic analytic grouping to provide stable population-level estimates across histological subtypes with similar expected prognosis.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eStage-stratified analyses were conducted as supplementary analyses using the Combined Summary Stage with Expanded Regional Codes (2004+) variable. To align with 5-year diagnosis periods, stage analyses were restricted to 2005\u0026ndash;2019 and summarized as Localized only versus Non-localized (Regional\u0026thinsp;+\u0026thinsp;Distant combined). Unknown/unstaged cases were excluded from stage-stratified survival analyses.\u003c/b\u003e \u003c/p\u003e\n\u003ch3\u003eAssessment of temporal trends\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eTemporal trends in period estimates of 5-year RS were evaluated using diagnosis-period mid-years (2002, 2007, 2012, and 2017) as the time variable. Because only four observed diagnosis periods were available, the primary objective was to assess whether an overall linear temporal trend was present rather than to identify multiple changes in slope. Joinpoint regression on the linear scale was therefore used as a supplementary trend-assessment procedure. For the overall and histology-stratified analyses, the final selected models contained 0 joinpoints, supporting interpretation of a single approximately linear trend over time. The slope represents the absolute change in 5-year RS (percentage points) per calendar year, and statistical significance was assessed at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/b\u003e \u003c/p\u003e\n\u003ch3\u003ePrediction of 5-year relative survival for 2020–2024\u003c/h3\u003e\n\u003cp\u003e\u003cb\u003eTo generate short-term forecasts for the subsequent diagnosis period (2020\u0026ndash;2024), inverse-variance-weighted models were fitted to the observed period-specific 5-year RS estimates from 2000\u0026ndash;2004, 2005\u0026ndash;2009, 2010\u0026ndash;2014, and 2015\u0026ndash;2019, using diagnosis-period mid-year (2002, 2007, 2012, and 2017) as the time variable. Predictions were then obtained for the mid-year 2022, corresponding to the diagnosis period 2020\u0026ndash;2024. Because these forecasts were based on a small number of observed periods, they were interpreted as short-term extrapolations rather than validated future observations. Predicted values were restricted to the plausible range of 0% to 100%, and detailed uncertainty estimates are reported in Supplementary Table S4.\u003c/b\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical considerations\u003c/h2\u003e \u003cp\u003e \u003cb\u003eBaseline descriptive characteristics were summarized for the baseline descriptive cohort, whereas RS estimates were derived from the RS analytic cohort generated by the SEER*Stat relative survival session. Accordingly, differences in sample size between descriptive and analytic tables reflect differences in eligibility for relative survival estimation rather than inconsistencies in disease definition. These two cohorts served different analytic purposes and should therefore not be expected to have identical denominators.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy cohort\u003c/h2\u003e \u003cp\u003e \u003cb\u003eThe baseline descriptive cohort included 4,070 patients diagnosed during 2000\u0026ndash;2019 who met the site and histology criteria. Baseline characteristics across diagnosis periods are summarized in\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of patients with ependymoma by diagnosis period in the baseline descriptive cohort.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2000\u0026ndash;2004\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;955)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2005\u0026ndash;2009\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1036)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1046)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1033)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e491 (51.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e533 (51.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e542 (51.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e528 (51.11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e464 (48.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e503 (48.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e504 (48.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e505 (48.89%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e815 (85.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e867 (83.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e862 (82.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e823 (79.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (8.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (8.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (8.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99 (9.58%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (5.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (6.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 (7.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90 (8.71%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (0.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (0.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (1.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (2.03%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at diagnosis (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e243 (25.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e248 (23.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e263 (25.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e251 (24.30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e234 (24.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258 (24.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e254 (24.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e256 (24.78%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e340 (35.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349 (33.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e314 (30.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e323 (31.27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138 (14.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181 (17.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e215 (20.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e203 (19.65%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnaplastic (9392/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (13.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e177 (17.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e221 (21.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e233 (22.56%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-anaplastic (9391/3, 9393/3, 9394/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e825 (86.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e859 (82.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e825 (78.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e800 (77.44%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage (summary stage, expanded regional codes; 2004+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocalized only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e843 (81.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e880 (84.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e878 (85.00%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-localized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136 (13.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130 (12.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104 (10.07%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown/unstaged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (5.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (3.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51 (4.94%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary site group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpinal/Cauda equina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e432 (45.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e471 (45.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e486 (46.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e502 (48.60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfratentorial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200 (20.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e249 (24.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e211 (20.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e223 (21.59%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther intracranial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e323 (33.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e316 (30.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e349 (33.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e308 (29.82%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eStage distribution in\u003c/em\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cem\u003eis based on the baseline descriptive cohort. Stage-stratified relative survival analyses were performed in the RS analytic cohort and are reported in Supplementary Tables S2\u0026ndash;S3. Cases diagnosed in 2000\u0026ndash;2004 are shown with stage unavailable in the main table because the expanded stage variable was used for supplementary analyses restricted to 2005\u0026ndash;2019.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFor period estimation of 5-year RS, the RS analytic cohort included 3,770 patients, with period-specific sample sizes of 896 in 2000\u0026ndash;2004, 961 in 2005\u0026ndash;2009, 966 in 2010\u0026ndash;2014, and 947 in 2015\u0026ndash;2019.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003e \u003cb\u003eThe distribution of baseline characteristics across diagnosis periods is shown in\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eAcross periods, the sex distribution remained relatively stable, with a slight male predominance. The proportion of older patients gradually increased over time, whereas the proportion of pediatric patients slightly decreased in the most recent period. Non-anaplastic histology remained the predominant subtype across all diagnosis periods, although the proportion of anaplastic tumors increased from 13.3% in 2000\u0026ndash;2004 to 22.1% in 2015\u0026ndash;2019. Spinal/cauda equina tumors accounted for the largest site-based subgroup throughout the study period.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOverall period estimates and trend\u003c/h2\u003e \u003cp\u003e \u003cb\u003eOverall 5-year RS estimated by period analysis increased steadily across diagnosis periods, from 81.7% in 2000\u0026ndash;2004 to 89.5% in 2015\u0026ndash;2019 (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e). Analysis across diagnosis-period mid-years supported a significant increasing trend in overall 5-year RS. Supplementary Joinpoint analysis selected 0 joinpoints, consistent with an approximately linear improvement over 2002\u0026ndash;2017.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eObserved period-specific and model-based predicted 5-year relative survival in the overall cohort and histology groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRS (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic (ICD-O-3 9392/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000\u0026ndash;2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.1 (46.3\u0026ndash;63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic (ICD-O-3 9392/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2005\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.5 (56.1\u0026ndash;70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic (ICD-O-3 9392/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68.1 (61.6\u0026ndash;74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic (ICD-O-3 9392/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.1 (68.0\u0026ndash;80.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic (ICD-O-3 9392/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2020\u0026ndash;2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000\u0026ndash;2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86.1 (83.4\u0026ndash;88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2005\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.8 (88.4\u0026ndash;93.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.2 (91.0\u0026ndash;95.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.4 (92.0\u0026ndash;96.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-anaplastic (ICD-O-3 9391/3, 9393/3, 9394/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2020\u0026ndash;2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000\u0026ndash;2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81.7 (79.0\u0026ndash;84.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2005\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86.0 (83.6\u0026ndash;88.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87.8 (85.4\u0026ndash;90.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.5 (87.1\u0026ndash;91.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2020\u0026ndash;2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eObserved values are presented as \u003cb\u003eRS (95% CI)\u003c/b\u003e. The \u003cb\u003e2020\u0026ndash;2024\u003c/b\u003e column shows the model-based predicted 5-year RS. Detailed prediction uncertainty intervals and subgroup-specific trend parameters are provided in \u003cb\u003eSupplementary Table S4\u003c/b\u003e.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eHistology-stratified period estimates and trends\u003c/h2\u003e \u003cp\u003e \u003cb\u003eWhen stratified by histology, non-anaplastic ependymoma consistently showed high 5-year RS with a gradual increase over time (86.1% in 2000\u0026ndash;2004 to 94.4% in 2015\u0026ndash;2019). In contrast, anaplastic ependymoma had substantially lower 5-year RS but demonstrated improvement across periods (55.1% in 2000\u0026ndash;2004 to 74.1% in 2015\u0026ndash;2019) (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eBoth histological subgroups showed increasing period-specific 5-year RS over time. Supplementary Joinpoint analysis selected 0 joinpoints for both subgroup models, indicating that the observed improvement was compatible with a single linear increasing trend across the study periods. The increasing trend was more pronounced for anaplastic ependymoma (1.206 percentage points/year; slope\u0026thinsp;=\u0026thinsp;1.206420, SE\u0026thinsp;=\u0026thinsp;0.099618, P\u0026thinsp;=\u0026thinsp;0.006749), whereas non-anaplastic ependymoma also increased significantly (0.530 percentage points/year; slope\u0026thinsp;=\u0026thinsp;0.530024, SE\u0026thinsp;=\u0026thinsp;0.115440, P\u0026thinsp;=\u0026thinsp;0.044308) (Supplementary Table S1). Despite these improvements, anaplastic ependymoma consistently exhibited lower 5-year RS and wider uncertainty due to smaller sample sizes.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePrediction of 5-year relative survival for 2020\u0026ndash;2024\u003c/h2\u003e \u003cp\u003e \u003cb\u003eModel-based short-term extrapolation suggested that the favorable trend in 5-year RS may extend into 2020\u0026ndash;2024. The forecasted 5-year RS for the overall cohort was higher than that observed in 2015\u0026ndash;2019, and similar upward patterns were seen in the histology-stratified analyses (\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; \u003cb\u003eSupplementary Table S4). These forecasted values should be interpreted cautiously because they were derived from a limited number of observed diagnosis periods.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eIn supplementary subgroup forecasts, the predicted 5-year RS for primary site groups in 2020\u0026ndash;2024 was 96.1% for spinal/cauda equina tumors, 87.8% for infratentorial tumors, and 87.9% for other intracranial tumors. In stage-stratified forecasts, the predicted 5-year RS was 92.6% for localized disease and 74.8% for non-localized disease. These supplementary predictions should be interpreted cautiously, particularly for stage-specific analyses, because they were based on fewer observed diagnosis periods and, in some subgroups, smaller sample sizes (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cb\u003eSupplementary Figure S1, and Supplementary Table S4).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSupplementary analyses\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003ePrimary site group\u003c/h2\u003e \u003cp\u003e \u003cb\u003ePeriod estimates of 5-year RS differed by primary site group (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e). Spinal/cauda equina tumors exhibited consistently high 5-year RS across periods (approximately 95\u0026ndash;96%), while infratentorial and other intracranial tumors showed lower RS with temporal improvement. These subgroup-specific forecasts were descriptive and exploratory, particularly for site groups with relatively stable or near-ceiling survival estimates.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStage\u003c/h2\u003e \u003cp\u003e \u003cb\u003eStage-stratified analyses were performed as supplementary analyses for cases diagnosed in 2005\u0026ndash;2019. Unknown/unstaged cases were excluded from stage-stratified analyses (2005\u0026ndash;2009: 26/961, 2.7%; 2010\u0026ndash;2014: 18/966, 1.9%; 2015\u0026ndash;2019: 28/947, 3.0%; Supplementary Table S2). Overall, localized disease exhibited consistently higher 5-year RS than non-localized disease across diagnosis periods (Supplementary Figure S1; Supplementary Table S3). In stage-stratified forecasts, the predicted 5-year RS for 2020\u0026ndash;2024 was 92.6% for localized disease and 74.8% for non-localized disease (Supplementary Table S4). Stage-specific forecasts, particularly for non-localized disease, should be interpreted cautiously because they were based on only three observed diagnosis periods and relatively small subgroup sizes.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eIn this population-based study using SEER data, we found that 5-year relative survival for ependymoma improved steadily from 2000\u0026ndash;2004 to 2015\u0026ndash;2019. Analysis across diagnosis-period mid-years supported an approximately linear increase over time, and short-term extrapolation suggested that this favorable pattern may extend into 2020\u0026ndash;2024. Although anaplastic ependymoma consistently showed worse survival than non-anaplastic disease\u003c/b\u003e \u003csup\u003e \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e \u003c/sup\u003e, \u003cb\u003eits survival improved more rapidly over time in our analysis, which may reflect advances in diagnosis, risk stratification, and multidisciplinary treatment during the study period.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSeveral factors may underlie the temporal improvement in relative survival observed in this study. Advances in neuroimaging and neuropathological classification may have improved diagnostic precision and case ascertainment over time\u003c/b\u003e \u003csup\u003e \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e \u003c/sup\u003e. \u003cb\u003eRefinements in microsurgical techniques, perioperative management, radiotherapy delivery, and multidisciplinary care may also have increased the likelihood of effective resection and optimized postoperative treatment\u003c/b\u003e\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. \u003cb\u003eAt the population level, these developments may together have contributed to the progressive survival improvement observed across successive diagnosis periods.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eOur subgroup analyses further demonstrated marked heterogeneity in survival patterns. Non-anaplastic tumors maintained consistently high 5-year relative survival across diagnosis periods, whereas anaplastic tumors showed lower but progressively improving survival. This pattern is clinically plausible and is consistent with established biological and prognostic differences across ependymoma subtypes12. Similarly, tumors arising in the spinal cord or cauda equina showed the highest relative survival, whereas infratentorial and other intracranial tumors had lower survival with gradual improvement over time3. These differences may reflect variation in tumor biology, anatomical accessibility, extent of resection, and postoperative functional risk. In supplementary stage analyses, localized disease consistently showed better relative survival than non-localized disease, further supporting the prognostic importance of disease extent. Overall, these findings suggest that improvements in population-level survival are not necessarily accompanied by uniform prognostic gains across all clinicopathological subgroups.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eModel-based short-term extrapolation suggested that the favorable pattern observed through 2015\u0026ndash;2019 may extend into the subsequent diagnosis period. However, these estimates should be interpreted as model-based short-term projections rather than verified future observations, especially in subgroup analyses based on a limited number of diagnosis periods or small sample sizes. Stage-specific projections likewise warrant caution, because estimates in more finely stratified groups are more vulnerable to modeling assumptions and random variation\u003c/b\u003e \u003csup\u003e \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e \u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe present study illustrates the utility of combining relative survival with period analysis to monitor contemporary survival patterns in a rare central nervous system tumor. Relative survival offers an important advantage in registry-based studies because it does not rely on the accuracy of cause-of-death attribution, whereas period analysis provides more up-to-date survival estimates than traditional cohort-based approaches. The additional forecasting component may be useful for descriptive short-term planning, but such projections should be interpreted cautiously when only a limited number of observed diagnosis periods are available\u003c/b\u003e \u003csup\u003e \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e \u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSeveral limitations should be acknowledged. First, this was a retrospective registry-based analysis and is therefore subject to the inherent constraints of observational data. Second, although SEER provides broad population coverage, the database lacks several potentially important clinical variables, including extent of resection, radiotherapy dose and field, systemic treatment details, recurrence patterns, molecular subgroup information, and central pathology review. Third, baseline descriptive analyses and relative survival analyses were derived from related but not identical cohorts, because eligibility for relative survival estimation depends on the SEER*Stat relative survival framework and follow-up information. Fourth, an additional methodological limitation is that only four observed diagnosis periods were available for the main analyses, and only three periods were available for stage-stratified analyses. Accordingly, Joinpoint outputs should be interpreted as support for an overall linear temporal trend rather than evidence for discrete slope changes, and subgroup-specific forecasts should be regarded as exploratory. Finally, although the SEER submission used in this study included follow-up through 2022, the main analyses were restricted to 2000\u0026ndash;2019 to preserve comparability across four non-overlapping 5-year diagnosis periods. More recent years may be incorporated in future work using updated rolling-period or extended-period frameworks.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003e \u003cb\u003eIn summary, 5-year relative survival for ependymoma improved steadily across diagnosis periods from 2000\u0026ndash;2004 to 2015\u0026ndash;2019 in this SEER-based model-based period analysis. Short-term model-based extrapolation suggested that this favorable pattern may continue into 2020\u0026ndash;2024, although substantial heterogeneity remained across histology, primary site group, and stage. These findings provide an updated population-based description of survival trends in ependymoma and support cautious use of period-based forecasting for short-term monitoring.\u003c/b\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. SEER data are available through the official SEER Program and SEER*Stat platform. Direct links are as follows: https://seer.cancer.gov/ ; https://seer.cancer.gov/data/ ; https://seer.cancer.gov/seerstat/.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used de-identified, publicly available SEER data; therefore, institutional review board approval and informed consent were not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. The study was conceptualized and supervised by Xiangyu Wang and Jun Lyu. Material preparation, data collection, and statistical analysis were performed by Zhiling Tan, Wengang Li, Youzhong Ye, Zhuqing Xie and Changju Hui. The first draft of the manuscript was written by Zhiling Tan, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJeong D, et al. Multidimensional profiling of heterogeneity in supratentorial ependymomas. Nature. 2026. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41586-026-10214-2\u003c/span\u003e\u003cspan address=\"10.1038/s41586-026-10214-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eObrecht-Sturm D, et al. Distinct relapse pattern across molecular ependymoma types. Neuro-Oncol. 2025;27:267\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhasemi DR et al. A brief history of ependymoma. \u003cem\u003eNeuro-Oncol.\u003c/em\u003e noag016 (2026) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/neuonc/noag016\u003c/span\u003e\u003cspan address=\"10.1093/neuonc/noag016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoogendijk R, et al. Long-term survival and cure fraction estimates for paediatric central nervous system tumours in 31 european countries (EUROCARE-6): A population-based study. Lancet Oncol. 2025;26:1091\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrice M, et al. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2018\u0026ndash;2022. Neuro-Oncol. 2025;27:iv1\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBing X, et al. Using period analysis for timely assessment and prediction of 5-year relative survival for childhood cancer patients from TaiZhou, eastern China. Int J Cancer. 2026;158:1555\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFan X, et al. Evaluation and prediction analysis of 3- and 5-year relative survival rates of patients with cervical cancer: a model-based period analysis. Cancer Control J Moffitt Cancer Cent. 2024;31:10732748241232324.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePenberthy L, Friedman S. The SEER program\u0026rsquo;s evolution: supporting clinically meaningful population-level research. \u003cem\u003eJ. Natl. Cancer Inst. Monogr.\u003c/em\u003e 2024, 110\u0026ndash;117 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrenner H, Gefeller O. An alternative approach to monitoring cancer patient survival. Cancer. 1996;78:2004\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrenner H, Hakulinen T. Up-to-date and precise estimates of cancer patient survival: model-based period analysis. Am J Epidemiol. 2006;164:689\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHakulinen T, Sepp\u0026auml; K, Lambert PC. Choosing the relative survival method for cancer survival estimation. Eur J Cancer. 2011;47:2202\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaleh AH, et al. The biology of ependymomas and emerging novel therapies. Nat Rev Cancer. 2022;22:208\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRud\u0026agrave; R, Bruno F, Pellerino A, Soffietti R, Ependymoma. Evaluation and management updates. Curr Oncol Rep. 2022;24:985\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLombardi G, et al. An overview of intracranial ependymomas in adults. Cancers. 2021;13:6128.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElgenidy A, et al. Survival patterns and mortality causes in patients with invasive ependymoma: A retrospective cohort analysis from 2000 to 2019. Med Sci. 2025;13:139.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang C et al. Outcomes and pattern of care for spinal myxopapillary ependymoma in the modern era-a population-based observational study. \u003cem\u003eCancers\u003c/em\u003e 16, 2013 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAchey RL, et al. Ependymoma, NOS and anaplastic ependymoma incidence and survival in the united states varies widely by patient and clinical characteristics, 2000\u0026ndash;2016. Neuro-Oncol Pract. 2020;7:549\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDibas M, et al. Novel nomograms predicting overall and cancer-specific survival of malignant ependymoma patients: A population-based study. J Neurosurg Sci. 2023;67:93\u0026ndash;102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhutada AS, et al. Development and validation of a predictive nomogram for patients with myxopapillary ependymoma: a surveillance, epidemiology, and end results (SEER) retrospective cohort analysis. Glob Spine J. 2025;15:1905\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePohl LC, et al. Molecular characteristics and improved survival prediction in a cohort of 2023 ependymomas. Acta Neuropathol (Berl). 2024;147:24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMariotto AB et al. Cancer survival: An overview of measures, uses, and interpretation. \u003cem\u003eJ. Natl. Cancer Inst. Monogr.\u003c/em\u003e 2014, 145\u0026ndash;186 (2014).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Ependymoma, relative survival, period analysis, SEER, population-based study, short-term prediction","lastPublishedDoi":"10.21203/rs.3.rs-9122854/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9122854/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEpendymoma is a rare central nervous system tumor with substantial heterogeneity in anatomical site, histology, and clinical outcome\u003csup\u003e1–3\u003c/sup\u003e. Population-based evidence on temporal changes in survival remains limited, and up-to-date estimates are particularly needed\u003csup\u003e4,5\u003c/sup\u003e. We therefore used model-based period analysis to evaluate temporal trends in relative survival and to generate short-term forecasts in patients with ependymoma\u003csup\u003e6,7\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were obtained from the Surveillance, Epidemiology, and End Results (SEER) database\u003csup\u003e8\u003c/sup\u003e (Incidence – SEER Research Data, 17 Registries, Nov 2024 Sub). Patients diagnosed during 2000–2019 with ICD-O-3 histology/behavior codes 9391/3, 9392/3, 9393/3, and 9394/3 and primary sites restricted to C71.* and C72.0–C72.1 were included. Five-year relative survival (RS) was estimated using period analysis\u003csup\u003e9,10\u003c/sup\u003e; expected survival was derived using the Ederer II method\u003csup\u003e11\u003c/sup\u003e, and standard errors were calculated using Greenwood’s formula. Diagnosis periods were grouped as 2000–2004, 2005–2009, 2010–2014, and 2015–2019. Temporal trends were assessed across diagnosis-period mid-years on the absolute survival scale. Given that only four observed diagnosis periods were available, Joinpoint analysis was used only to assess whether an overall linear trend was present, rather than to identify multiple slope changes. Short-term forecasts for 2020–2024 were generated using inverse-variance-weighted models based on the observed period estimates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline descriptive cohort included 4,070 patients, and the RS analytic cohort included 3,770 patients. Overall 5-year RS increased from 81.7% in 2000–2004 to 89.5% in 2015–2019. Period-specific estimates supported a significant upward linear trend over time. Non-anaplastic ependymoma showed consistently high 5-year RS, increasing from 86.1% to 94.4%, whereas anaplastic ependymoma showed lower but improving RS, increasing from 55.1% to 74.1%. Temporal improvement was more pronounced in anaplastic disease than in non-anaplastic disease. Model-based short-term forecasts suggested that overall 5-year RS may continue to improve in 2020–2024. Spinal/cauda equina tumors showed persistently favorable survival, whereas infratentorial and other intracranial tumors had lower RS with gradual improvement. In supplementary stage analyses, localized disease consistently showed better RS than non-localized disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eModel-based period analysis showed a steady improvement in 5-year relative survival for ependymoma from 2000–2004 to 2015–2019. Short-term forecasts suggested that this favorable pattern may extend into 2020–2024, although prognostic heterogeneity remained evident across major clinicopathological subgroups.\u003c/p\u003e","manuscriptTitle":"Temporal trends and short term prediction of relative survival in ependymoma using model based period analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-08 05:28:44","doi":"10.21203/rs.3.rs-9122854/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-06T01:04:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4124297153581180758733761964938426329","date":"2026-05-04T09:47:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"312348370899313879885384989631496773710","date":"2026-05-01T12:00:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T04:25:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-24T12:14:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-21T08:27:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-19T04:28:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2026-03-19T02:20:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8ee8540c-54ca-4a55-9f5c-d17451d06214","owner":[],"postedDate":"April 8th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-06T01:04:05+00:00","index":74,"fulltext":""},{"type":"reviewerAgreed","content":"4124297153581180758733761964938426329","date":"2026-05-04T09:47:11+00:00","index":73,"fulltext":""},{"type":"reviewerAgreed","content":"312348370899313879885384989631496773710","date":"2026-05-01T12:00:00+00:00","index":60,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T05:28:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-08 05:28:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9122854","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9122854","identity":"rs-9122854","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}