Trial reportSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2022
[Development and Evaluation of Prognostic Nomogram Model for Adult Ventricle Glioma Patients].
Trial report in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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
1 citing paper in PubMed, 1 citations in OpenAlex.
- Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To explore the prognostic factors of adult ventricle glioma (AVG) and to construct and evaluate a survival-related prognostic nomogram model, which could provide further reference for the clinical management of AVG patients. Methods: The patients covered in the study were selected from the Surveillance Epidemiology and End Results (SEER) database (1973-2016). They all had definite histological diagnosis of AVG. They were assigned randomly to the training cohort and the validation cohort by random number table at a 2/1 ratio. Survival analysis was performed by Kaplan-Meier analysis. Cox regression analysis was employed to determine the independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS). Then, integrating the basic characteristics of patients, the survival-related nomogram predictive model for OS and CSS in the training cohort was constructed, respectively. After that, internal cross validation and external validation of the model were carried out with the training cohort and the validation cohort in succession. The authenticity and reliability of the nomogram model were evaluated by calculating the concordance index (C-index). Calibration plots were constructed to assess the agreement between the predicted values and the observed values in the training cohort and the validation cohort. Results: A total of 369 AVG patients, including 218 males and 151 females, were included. The median age of the patients was 53. According to the WHO classification of gliomas, 66 (17.9%) patients had grade Ⅱ gliomas, 73 (19.8%) had grade Ⅲ gliomas, and 230 (62.3%) had grade Ⅳ gliomas. Regarding the extent of resection (EOR), 59 (16.0%) had gross total resection (GTR) and 145 (39.3%) had subtotal resection (STR) or partial resection (PR). Of all the patients, 167 (45.3%) received postoperative radiotherapy and 143 (38.8%) received postoperative chemotherapy. Patients were randomized into the training cohort ( Conclusion: This nomogram predictive model of OS and CSS showed moderately reliable predictive performance, providing helpful reference information for clinicians to make quick and simple assessment of the survival probability of AVG patients.
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