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Risk factors for childhood and adult primary brain tumors
Open accessAbstract
Primary brain tumors account for ~1% of new cancer cases and ~2% of cancer deaths in the United States; however, they are the most commonly occurring solid tumors in children. These tumors are very heterogeneous and can be broadly classified into malignant and benign (or non-malignant), and specific histologies vary in frequency by age, sex, and race/ethnicity. Epidemiological studies have explored numerous potential risk factors, and thus far the only validated associations for brain tumors are ionizing radiation (which increases risk in both adults and children) and history of allergies (which decreases risk in adults). Studies of genetic risk factors have identified 32 germline variants associated with increased risk for these tumors in adults (25 in glioma, 2 in meningioma, 3 in pituitary adenoma, and 2 in primary CNS lymphoma), and further studies are currently under way for other histologic subtypes, as well as for various childhood brain tumors. While identifying risk factors for these tumors is difficult due to their rarity, many existing datasets can be leveraged for future discoveries in multi-institutional collaborations. Many institutions are continuing to develop large clinical databases including pre-diagnostic risk factor data, and developments in molecular characterization of tumor subtypes continue to allow for investigation of more refined phenotypes. Key Point 1. Brain tumors are a heterogeneous group of tumors that vary significantly in incidence by age, sex, and race/ethnicity.2. The only well-validated risk factors for brain tumors are ionizing radiation (which increases risk in adults and children) and history of allergies (which decreases risk).3. Genome-wide association studies have identified 32 histology-specific inherited genetic variants associated with increased risk of these tumors.
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“The other types include pituitary tumors, pineal gland tumors, ependymomas, craniopharyngiomas, lymphomas, germ cell tumors, and schwannomas [87].”
From A Comprehensive Analysis of Recent Deep and Federated-Learning-Based Methodologies for Brain Tumor Diagnosis (2022) · cites this paper as [87]
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Metadata
- Authors
- Ostrom, Q. T., Fahmideh, M. A., Cote, D. J., Muskens, I. S., Schraw, J. M., Scheurer, M. E., & Bondy, M. L.
- Affiliations
- Baylor College of Medicine (US)
- Karolinska University Hospital (SE)
- Channing Division of Network Medicine, Harvard Medical School, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- University of Southern California (US)
- Corresponding author
- Ostrom, Quinn T
- ORCID
- Venue
- Neuro-Oncology
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-07-12
- Volume
- 21
- Issue
- 11
- Pages
- 1357-1375
- ISSN
- 1522-8517 (ISSN-L)
- 1523-5866
- PMC
- PMC6827837
- OpenAlex
- W2961422708
- Cited by
- 314
- References
- 165
- Citations by year
- 2026: 29 · 2025: 54 · 2024: 68 · 2023: 64 · 2022: 49 · 2021: 35 · 2020: 13 · 2019: 2
- FWCI
- 3.01
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neuro-Oncology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Cancer Prevention and Research Institute of Texas (RP160097T)
- National Institutes of Health (T32 CA 009001, R01CA194189)
- Takeda Pharmaceutical Company Limited (115766)
- Topics
- Health Sciences › Medicine › Oncology › Glioma Diagnosis and Treatment
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Health Sciences › Medicine › Oncology › Brain Metastases and Treatment
- Keywords
- primary brain tumors, pediatric brain tumors, adult brain tumors, risk factors, ionizing radiation exposure, allergy history, germline genetic variants, glioma, meningioma, pituitary adenoma, primary central nervous system lymphoma, tumor histology, genome-wide association study
- MeSH terms
- Adult, Brain Neoplasms, Child, Humans, Risk Factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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