ArticleFrontiers in oncology2022
A Nomogram to Predict Recurrence-Free Survival Following Surgery for Vestibular Schwannoma.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Pooled it
- A morphological features-based nomogram for predicting facial nerve function in the immediate postoperative period after vestibular schwannoma surgery.Journal of neuro-oncology · 2025Article
- Development of a Predictive Model for Persistent Dizziness Following Vestibular Schwannoma Surgery.The Laryngoscope · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Vestibular schwannoma (VS) is the most common benign tumor of the posterior fossa. The recurrence of VS has always received widespread attention. This study aimed to develop a nomogram to predict Recurrence-free survival (RFS) following resection of VS. Methods: A total of 425 patients with VS who underwent resection at the Department of Neurosurgery in Chinese PLA General Hospital between January 2014 and December 2020 were enrolled in this retrospective study. The medical records and follow-up data were collected. Cox regression analysis was used to screen prognostic factors and construct the nomogram. The predictive accuracy and clinical benefits of the nomogram were validated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results: The Cox regression analysis revealed that age (HR = 0.96; 95% CI 0.94 - 0.99; p < 0.01), EOR (HR = 4.65; 95% CI 2.22 - 9.74; p < 0.001), and Ki-67 (HR = 1.16; 95% CI 1.09 - 1.23; p < 0.001) were all significantly correlated with recurrence, and they were finally included in the nomogram model. The concordance index of the nomogram was 0.86. The areas under the curve (AUCs) of the nomogram model of 3-, 4- and 5-year were 0.912, 0.865, and 0.809, respectively. A well-fitted calibration curve was also generated for the nomogram model. The DCA curves also indicated that the nomogram model had satisfactory clinical utility compared to the single indicators. Conclusions: We developed a nomogram that has high accuracy in predicting RFS in patients after resection of VS. All of the included prognostic factors are easy to obtain. The nomogram can improve the postoperative management of patients and assist clinicians in individualized clinical treatment. Furthermore, we generated a web-based calculator to facilitate clinical application: https://abc123-123.shinyapps.io/VS-RFS/.
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