Evidence map›Paper›PMID 33014882›Full record

ArticleFrontiers in oncology2020

Incidence, Prognostic Factors and Survival for Hemangioblastoma of the Central Nervous System: Analysis Based on the Surveillance, Epidemiology, and End Results Database.

Xiangdong Yin, Hongzhou Duan, Zhiqiang Yi, Chunwei Li, Runchun Lu, Liang Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

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.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 43 citations in OpenAlex.

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  10. Machine learning-driven national analysis for predicting adverse outcomes in intramedullary spinal cord tumor surgery.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025
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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

6 authors at 2 institutions in 1 country.

Xiangdong YinDepartment of Neurosurgery, Peking University First Hospital, Beijing, China.
Hongzhou DuanDepartment of Neurosurgery, Peking University First Hospital, Beijing, China.
Zhiqiang YiDepartment of Neurosurgery, Peking University First Hospital, Beijing, China.
Chunwei LiDepartment of Neurosurgery, Peking University First Hospital, Beijing, China.
Runchun LuDepartment of Neurosurgery, Peking University First Hospital, Beijing, China.
Liang LiDepartment of Neurosurgery, Peking University First Hospital, Beijing, China.
Peking University · CNPeking University First Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHemangioblastomas are uncommon, benign neoplasms of the central nervous system (CNS). This study aims to evaluate the incidence, demographics, clinical characteristics, and prognosis of CNS hemangioblastomas using the data from the Surveillance, Epidemiology, and End Results (SEER) Program.

methodsUnivariate and multivariate analyses using the Cox proportional hazards model were employed to identify prognostic factors of overall survival. The Kaplan-Meier method was utilized to evaluate overall survival distribution by treatment modality. A nomogram was further built to predict survival at 3 and 5 years.

resultsThe overall incidence rate of CNS hemangioblastomas was 0.141 per 100,000 person-years. Through univariate analysis and multivariate analyses, age between 60 and 79 years (HR = 3.697,

conclusionIn conclusion, age, race, tumor location, number of tumors, and prior surgery are prognostic factors for survival. Surgery was the most common modality and was suggested as an effective and optimal treatment. The proposed nomogram can predict the prognosis of patients with CNS hemangioblastomas and help clinicians in making decisions.

Indexed as

hemangioblastomaincidencenomogramprognosisSEERsurvivaltreatment

Identifiers

PMID33014882
PMCPMC7509109
OpenAlexW3084057256

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.