ArticleDiscover oncology2025
Vestibular schwannoma clinical prognostic factors and nomogram construction using SEER database.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
objectiveThis study aimed to delineate the long-term overall survival (OS) landscape and identify factors associated with OS in a large, population-based cohort of patients diagnosed with vestibular schwannoma (VS). MATERIALS AND
methodsClinical, demographic, and treatment data for VS patients from the SEER database (2000-2019) were extracted and randomly divided into training and validation cohorts. Cohort comparability was assessed using Chi-square, Fisher's exact, and Mann-Whitney U tests. Univariate and multivariate Cox proportional hazards models were used to identify factors associated with OS. Nomograms for predicting 3-, 5-, and 10-year OS were constructed. Model performance was evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
resultsFrom the initial pool of 28,693 VS patients in the SEER database, 20,235 were included in the analysis. Among these, 14,167 patients (70.01%) were allocated to the training cohort, and 6,068 patients (29.99%) to the validation cohort. Multivariate Cox regression identified age (hazard ratio [HR] = 12.895; 95% confidence interval [CI] 8.347-19.809; p < 0.001), sex (HR = 0.761; 95% CI 0.683-0.849; p < 0.001), race (HR = 0.214; 95% CI 0.089-0.515; p < 0.001), tumor size (HR = 3.024; 95% CI 2.464-3.712; p < 0.001), primary site surgery (HR = 0.409; 95% CI 0.300-0.557; p < 0.001), and radiation therapy (HR = 0.812; 95% CI 0.710-0.929; p = 0.002) as independent prognostic factors. Nomograms based on these variables demonstrated robust predictive capability, with a C-index of 0.737 ± 0.065 for the training cohort and an AUC of 0.759, 0.766, and 0.790 for predicting 3-, 5-, and 10-year OS, respectively. In the validation cohort, the model yielded a C-index of 0.763 ± 0.053 and AUCs of 0.757, 0.765, and 0.760 for the corresponding timeframes. Other factors, such as year of diagnosis, reporting source, surgical-radiation sequence, laterality, and chemotherapy, did not exhibit significant associations with OS.
conclusionThis analysis of over 20,000 VS patients provides a comprehensive overview of long-term survival in this patient population. We identified age, sex, race, tumor size, and treatment modality (surgery and radiotherapy) as factors associated with OS. The developed nomograms offer a tool for visualizing the combined impact of these demographic and clinical factors on long-term survival, which may contribute to comprehensive patient assessment and counseling at the time of diagnosis.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.