Evidence map›Paper›PMID 34594567›Full record

ReviewNeuro-oncology practice2021

Cancer predisposition in pediatric neuro-oncology-practical approaches and ethical considerations.

Steffen Hirsch, Nicola Dikow, Stefan M Pfister, Kristian W Pajtler

Abstract readReview
In one paragraph

Review in Neuro-oncology practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Article
  2. Immunotherapy for pediatric low-grade gliomas.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2024
    Review
  3. Review
  4. 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

4 authors.

Steffen HirschHopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.ORCID https://orcid.org/0000-0002-4920-0930
Nicola DikowInstitute of Human Genetics, Heidelberg University Hospital, Heidelberg, Germany.
Stefan M PfisterHopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
Kristian W PajtlerHopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A genetic predisposition to tumor development can be identified in up to 10% of pediatric patients with central nervous system (CNS) tumors. For some entities, the rate of an underlying predisposition is even considerably higher. In recent years, population-based approaches have helped to further delineate the role of cancer predisposition in pediatric oncology. Investigations for cancer predisposition syndrome (CPS) can be guided by clinical signs and family history leading to directed testing of specific genes. The increasingly adopted molecular analysis of tumor and often parallel blood samples with multi-gene panel, whole-exome, or whole-genome sequencing identifies additional patients with or without clinical signs. Diagnosis of a genetic predisposition may put an additional burden on affected families. However, information on a given cancer predisposition may be critical for the patient as potentially influences treatment decisions and may offer the patient and healthy carriers the chance to take part in intensified surveillance programs aiming at early tumor detection. In this review, we discuss some of the practical and ethical challenges resulting from the widespread use of new diagnostic techniques and the most important CPS that may manifest with brain tumors in childhood.

Indexed as

cancergeneticspediatricspredisposition

Identifiers

PMID34594567
PMCPMC8475219

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.