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Prognostic factors and clinical nomogram predicting survival in high-grade glioma
Thara Tunthanathip1, Sanguansin Ratanalert2, Sakchai Sae-Heng1, Thakul Oearsakul1, Ittichai Sakarunchai1, Anukoon Kaewborisutsakul1, Thirachit Chotsampancharoen3, Utcharee Intusoma4, Amnat Kitkhuandee5, Tanat Vaniyapong6
1 Department of Surgery, Division of Neurosurgery, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
2 School of Medicine, Mae Fah Luang University, Chiang Rai, Thailand
3 Department of Pediatrics, Division of Hematology/Oncology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
4 Department of Pediatrics, Division of Pediatric Neurology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
5 Department of Surgery, Division of Neurosurgery, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
6 Department of Surgery, Division of Neurosurgery, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
Correspondence Address:
Thara Tunthanathip,
Department of Surgery, Division of Neurosurgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110
Thailand
 Source of Support: None, Conflict of Interest: None DOI: 10.4103/jcrt.JCRT_233_19
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Background: Genomic-based tools have been used to predict poor prognosis high-grade glioma (HGG). As genetic technologies are not generally available in countries with limited resources, clinical parameters may be still necessary to use in predicting the prognosis of the disease. This study aimed to identify prognostic factors associated with survival of patients with HGG. We also proposed a validated nomogram using clinical parameters to predict the survival of patients with HGG.
Methods: A multicenter retrospective study was conducted in patients who were diagnosed with anaplastic astrocytoma (WHO III) or glioblastoma (WHO IV). Collected data included clinical characteristics, neuroimaging findings, treatment, and outcomes. Prognostic factor analysis was conducted using Cox proportional hazard regression analysis. Then, we used the significant prognostic factors to develop a nomogram. A split validation of nomogram was performed. Twenty percent of the dataset was used to test the performance of the developed nomogram.
Results: Data from 171 patients with HGG were analyzed. Overall median survival was 12 months (interquartile range: 5). Significant independent predictors included frontal HGG (hazard ratio [HR]: 0.62; 95% confidence interval [CI]: 0.40–0.60), cerebellar HGG (HR: 4.67; 95% CI: 0.93–23.5), (HR: 1.55; 95% CI: 1.03–2.32; reference = total resection), and postoperative radiotherapy (HR: 0.18; 95% CI: 0.10–0.32). The proposed nomogram was validated using nomogram's predicted 1-year mortality rate. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the curve of our nomogram were 1.0, 0.50, 0.45, 1.0, 0.64, and 0.75, respectively.
Conclusion: We developed a nomogram for individually predicting the prognosis of HGG. This nomogram had acceptable performances with high sensitivity for predicting 1-year mortality.
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