Discussion
As few studies have established nomogram for predicting the survival of patients with brainstem glioma patients, the sample size involved was small, and the prognostic factors have been limited13. Thus, we developed a clinical nomogram to predict the survival based on SEER database. The SEER registry is the largest population-based database of cancer patients in the United States, covering approximately 26% of patients diagnosed with cancer in the nation. We reviewed patients’ data from the latest version of the SEER as released in 2015 (covering 18 registries, 1973-2015), by using SEER*Stat version 8.3.5, and we also set a strict inclusion and exclusion criteria.
In this study, patient survival was predicted using a clinical nomogram that was based on SEER database. This was necessitated because the traditional staging classification, which is commonly used for survival predicting and clinical strategies selecting for patients with cancers cannot accurately and consistently distinguish the difference in survival among various stages. The nomogram is a comprehensive, accurate, and useful prognostic model, which has been previously used for many kinds of malignances. However, in those studies, the limitations were small sample sizes and analysis of few prognostic factors. Five independent prognostic factors: age, race, tumor size, grade and radiotherapy, identified through univariable and multivariable Cox-Regression analyses were incorporated in the clinical nomogram. Tumor histology grade category contributed significantly to prognosis, according to the nomogram, which is consistent, but not identical, with previous studies on survival risk factors for glioma patients, where poorly differentiated and undifferentiated status were highly associated with poor prognosis in children stem glioma patients. Most people with low-grade gliomas are treated with surgery and may receive radiotherapy thereafter. However, in this study, we found that pediatric brainstem gliomas patients had no survival benefits from radiotherapy. We also found that chemotherapy, was not an effective measure to improve outcome in cases retrieved from the SEER database14,15. There was a relatively significant effect of race on patient survival with longer median survival times in white people compared to black people.
For validation of the nomogram to guarantee that the model could be generally applied and to avoid overfitting, it was necessary to evaluate discrimination using the C-index and calibration, which was assessed by comparing the agreement between predicted and actual survival of patients16,17. Our nomogram discriminated and predicted survival more efficiently than the traditional staging system. Further, the decision curves analysis showed that our model had a better clinical net benefit across all threshold probabilities18,19. Moreover, the risk stratification system applied to two risk groups of patients could discriminate CSS in children stem glioma.
The strength of our analysis of the risk stratification system is that the nomogram was an accurate and reliable prognostic model that could aid clinicians identify high-risk patients for targeted adjuvant treatment, particularly for our highly selective cohort20. There were some certain limitations in our study. First, although we performed multivariable analysis to minimize confounder effect associated with the heterogeneities, this was a retrospective analysis, which was further compromised by the small sample size and must be accounted for when interpreting the results21. Second, the retrospective analysis may have introduced the possibility of selection bias in the study design22. Third, the SEER database lacks information on modern gene-array technology and molecular biomarkers, such as status IDH1/TERT expression23-26, which have proven to be associated with CSS in children stem glioma patients. Therefore, future prospective analysis is warranted to predict survival of pediatric cases of gliomas.