Evidence map›Paper›PMID 41145623›Full record

ArticleScientific reports2025

Development and validation of a prognostic nomogram for overall survival in individuals with malignant meningiomas: a population-based study.

Hongliang Ge, Yajun Jing, Jinye Su, Qiu He, Dengliang Wang, Jiawei Cai, Zanyi Wu, Dezhi Kang

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Hongliang Ge *Department of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 20 Cha Zhong Lu, Taijiang District, Fuzhou, 350004, Fujian, China.
Yajun Jing *Department of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 20 Cha Zhong Lu, Taijiang District, Fuzhou, 350004, Fujian, China.
Jinye Su *Department of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 20 Cha Zhong Lu, Taijiang District, Fuzhou, 350004, Fujian, China.
Qiu HeDepartment of Immunology, Northwestern University, Suite 120, 2122 Sheridan Road, Evanston, IL, 60208, USA.
Dengliang WangDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 20 Cha Zhong Lu, Taijiang District, Fuzhou, 350004, Fujian, China.
Jiawei CaiDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 20 Cha Zhong Lu, Taijiang District, Fuzhou, 350004, Fujian, China. joychua3127@163.com.
Zanyi WuDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 20 Cha Zhong Lu, Taijiang District, Fuzhou, 350004, Fujian, China. kirby98@126.com.
Dezhi KangDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 20 Cha Zhong Lu, Taijiang District, Fuzhou, 350004, Fujian, China. kdz99988@vip.sina.com.

Funding

Natural Science Foundation of Fujian Province 2023J01602
6 · The paper itself

Abstract

Malignant meningiomas are a rare type of central nervous system tumor. Therefore, little is known about the best methods for treating malignant meningiomas and their prognostic factors. The aim of this study was to identify risk factors and develop a prognostic model for patients with malignant meningiomas. First, 2360 cases of malignant meningiomas from the Surveillance, Epidemiology, and End Results database were randomly divided into the primary and validation cohorts. Next, multivariate Cox regression identified several independent predictors of survival in malignant meningioma patients. These included patient demographics (age, gender, race), tumor features (laterality, size, stage), treatment timing (months from diagnosis to treatment), treatment modality, and tumor history (counts of both in situ/malignant and benign/borderline tumors), as well as year of diagnosis. Third, a nomogram was used to represent the prediction model, which was built based on independent predictors and optimized using the Akaike information criterion. Finally, we evaluated the predictive performance using the concordance index and receiver operating characteristic curve and clinical value using decision curve analysis. Notably, the strong discrimination ability of the model was demonstrated by the concordance index of the nomogram and the area under the receiver operating characteristic curve, both of which were between 0.7 and 0.8. The calibration plots in both cohorts showed high agreement between actual observation and nomogram prediction, and decision curve analysis demonstrated the significant clinical value of the nomogram. In conclusion, the nomogram is a practical and useful tool for assessing prognosis and determining effective treatment approaches.

Indexed as

Meningeal NeoplasmsMeningiomaNomogramsAdultAgedFemaleHumansMaleMiddle AgedPrognosisRisk FactorsROC CurveSEER ProgramCox regression analysisMalignant meningiomaNomogramPrognosisRisk factor

Identifiers

PMID41145623
PMCPMC12559311

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