Evidence map›Paper›PMID 34588593›Full record

ArticleScientific reports2021

Nomograms for predicting the overall survival of patients with cerebellar glioma: an analysis of the surveillance epidemiology and end results (SEER) database.

Jie Li, Wobin Huang, Jiajing Chen, Zhuhui Li, Bocong Liu, Peng Wang, Jun Zhang

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jie LiNeurosurgery, Dalang Hospital, Dongguan, 523770, Guangdong, China. 1548337395@qq.com.
Wobin HuangNeurosurgery, Dalang Hospital, Dongguan, 523770, Guangdong, China.
Jiajing ChenNeurosurgery, Dalang Hospital, Dongguan, 523770, Guangdong, China.
Zhuhui LiNeurosurgery, Dalang Hospital, Dongguan, 523770, Guangdong, China.
Bocong LiuNeurosurgery, Dalang Hospital, Dongguan, 523770, Guangdong, China.
Peng WangNeurosurgery, Dalang Hospital, Dongguan, 523770, Guangdong, China.
Jun ZhangNeurosurgery, Dalang Hospital, Dongguan, 523770, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At present, our understanding of cerebellar glioma is still insufficient. This study collected information on patients in the SEER database to identify the predictive factors for patients with cerebellar glioma. Data from patients with cerebellar glioma diagnosed from 1975 to 2018 were retrieved from the Surveillance Epidemiology and End Results Database. We randomly divided the patients into a training group and a validation group, established a nomogram based on the training group, and used the validation group data to verify the clinical value of the model. A total of 508 patients were included in this study. Multivariate analysis was performed based on the data before randomization, and the results showed that the patient's age, WHO grade, histological type, and extent were significantly correlated with the survival rate. The C-index of the OS nomograms of the training cohort was 0.909 (95% CI, (0.880-0.938)) and 0.932 (95% CI, (0.889-0.975)) in the validation group. The calibration curve of OS for 3 and 5 years showed that there was good consistency between the actual survival probability and the predicted survival probability. For patients with cerebellar glioma, the age at diagnosis, WHO grade of the glioma, histological type, and extension are the four factors that most strongly affect the overall survival outcomes. Furthermore, our model may be a useful tool for predicting OS in these patients.

Indexed as

AdultAge FactorsCerebellar NeoplasmsFemaleGliomaHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasm GradingNomogramsRetrospective StudiesRisk AssessmentRisk FactorsSEER ProgramSurvival Rate

Identifiers

PMID34588593
PMCPMC8481460

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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 OpenQuestion graph.