Evidence map›Paper›PMID 37261631›Full record

ArticleMetabolic brain disease2023

Beijing Children's Hospital guidelines on the design and conduction of the first standardized database for medulloblastoma.

Wei Yang, Wenping Ma, Jiansong Huang, Yingjie Cai, Xiaojiao Peng, Fengmao Zhao, Di Zhang, Zhewei Zou, Hailang Sun, Xiang Qi and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Metabolic brain disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

11 authors at 2 institutions in 1 country.

Wei Yang *Department of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.ORCID 0000-0003-3157-6662
Wenping Ma *Department of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.ORCID 0000-0002-1564-4584
Jiansong Huang *Department of Neurosurgery, Peking University International Hospital, Peking University Health Science Center, Peking University, Beijing, 102200, China.ORCID 0000-0001-7794-3443
Yingjie CaiDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.ORCID 0000-0001-9421-2001
Xiaojiao PengDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.ORCID 0009-0004-6264-6031
Fengmao ZhaoDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.ORCID 0009-0000-3672-3671
Di ZhangDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.ORCID 0009-0000-5802-4150
Zhewei ZouDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.ORCID 0009-0002-8049-185X
Hailang SunDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China. et2007yy@126.com.ORCID 0009-0005-9256-9564
Xiang QiDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China. qxxillim@163.com.ORCID 0009-0002-1280-6733
Ming GeDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China. ming_ge@126.com.ORCID 0000-0002-4476-4331
Capital Medical University · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medulloblastoma (MB) is one of the most common malignant childhood brain tumors (WHO grade IV). Its high degree of malignancy leads to an unsatisfactory prognosis, requiring more precise and personalized treatment in the near future. Multi-omics and artificial intelligence have been playing a significant role in precise medical research, but their implementation needs a large amount of clinical information and biomaterials. For these reasons, it is urgent for current MB researchers to establish a large sample-size database of MB that contains complete clinical data and sufficient biomaterials such as blood, cerebrospinal fluid (CSF), cancer tissue, and urine. Unfortunately, there are few biobanks of pediatric central nervous system (CNS) tumors throughout the world for limited specimens, scarce funds, different standards collecting methods and et cl. Even though, China falls behind western countries in this area. The present research set up a standard workflow to construct the Beijing Children's Hospital Medulloblastoma (BCH-MB) biobank. Clinical data from children with MB and for collecting and storing biomaterials, along with regular follow-up has been collected and recorded in this database. In the future, the BCH-MB biobank could make it possible to validate the promising biomarkers already identified, discover unrevealed MB biomarkers, develop novel therapies, and establish personalized prognostic models for children with MB upon the support of its sufficient data and biomaterials, laying the foundation for individualized therapies of children with MB.

Indexed as

Brain NeoplasmsCerebellar NeoplasmsMedulloblastomaArtificial IntelligenceChildHospitalsHumansPrognosisBio-bankChildrenChinaMedulloblastomaProtocol

Identifiers

PMID37261631
OpenAlexW4378952351

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.