Evidence map›Paper›PMID 40931922›Full record

ArticleCancer2025

Determinants of geographic variation in the incidence of adult nonmalignant meningioma in the United States, 2010-2019.

Diana R Withrow, Joseph Boyle, Martha S Linet, Christine A Pittman Ballard, Gino Cioffi, Carol Kruchko, Donald L Miller, Valentina I Petkov, Mackenzie Price, Kristin Waite and 2 more

Erratum issuedAbstract read
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In one paragraph

Article in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Diana R WithrowDepartment of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.ORCID https://orcid.org/0000-0002-9757-040X
Joseph BoyleMassey Comprehensive Cancer Center, Virginia Commonwealth University, Richmond, Virginia, USA.
Martha S LinetDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Christine A Pittman BallardDepartment of Neurosurgery, Duke University School of Medicine, Durham, North Carolina, USA.
Gino CioffiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Carol KruchkoCentral Brain Tumor Registry of the United States, Hinsdale, Illinois, USA.
Donald L MillerCenter for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland, USA.
Valentina I PetkovDivision of Cancer Control and Population Sciences, Surveillance Research Program, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Mackenzie PriceCentral Brain Tumor Registry of the United States, Hinsdale, Illinois, USA.ORCID https://orcid.org/0000-0001-6369-0609
Kristin WaiteDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Quinn T OstromDepartment of Neurosurgery, Duke University School of Medicine, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0003-3469-7558
Jill S Barnholtz-SloanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUS incidence rates of nonmalignant brain tumors are 3-fold higher in highest versus lowest incidence states. A county-level analysis was conducted to assess whether geographic variation in nonmalignant meningioma (NMM) incidence is related to demographics, cancer registry, health care, and other factors.

methodsAge-adjusted incidence rates of NMM in US counties during 2010-2019 were modeled with data from the Central Brain Tumor Registry of the United States. Demographic, geographic, cancer registry, environmental, health care, health, lifestyle, and socioeconomic factors at the county level were drawn from numerous data sources. Bayesian index regression models were fit containing spatial random effects.

resultsThree domains were significantly associated with rates of NMM at the county level: cancer registry practices (funding source and % radiographically confirmed), socioeconomic status index (higher levels with percent working in white-collar occupations as an important contributor), and demographics (% Black and % female). No associations were observed for general health or environmental factors. In the fully adjusted model, the number of counties with significantly elevated and lowered spatial random effects decreased by 33% and 28%, respectively, compared to a no-covariate model.

conclusionsAlthough general health and environmental factors cannot be ruled out in explaining the geographic variation in NMM incidence rates, results suggest that socioeconomic factors, certain demographic characteristics, and cancer diagnosis and registry practices may all play a significant role in driving such variation. These results may have implications for other tumor types diagnosed primarily radiographically or outside hospital settings, where variation in detection and reporting may affect incidence rates.

Indexed as

Meningeal NeoplasmsMeningiomaAdultAgedBayes TheoremFemaleHumansIncidenceMaleMiddle AgedRegistriesSocioeconomic FactorsUnited Statesbrain tumordetectiondiagnosisgeographyincidencemeningioma

Identifiers

PMID40931922
PMCPMC12424014

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Registered trials

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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.