Evidence map›Paper›PMID 33705303›Full record

ArticlePreventing chronic disease2021

Quantification of Potential Inequities in Breast Cancer Incidence in New Mexico Through Bayesian Disease Mapping.

David Zahrieh, Michael A Golafshar, Samir H Patel, Todd A DeWees

Open access · diamondAbstract read
In one paragraph

Article in Preventing chronic disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 43% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. 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 at 2 institutions in 1 country.

David ZahriehDepartment of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.
Michael A GolafsharDepartment of Health Sciences Research, Mayo Clinic, Scottsdale, Arizona.
Samir H PatelDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona.
Todd A DeWeesDepartment of Health Sciences Research, Mayo Clinic, Scottsdale, Arizona.
Mayo Clinic in Arizona · USMayo Clinic in Florida · US

Funding

Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI Felicity Enders · 1985 to 2026
$151.3M
Statistics CoreU10CA180882 · NCI · MAYO CLINIC ROCHESTER · PI Sumithra Jay Mandrekar · 2014 to 2026
$115.0M
NCI NIH HHS P30 CA015083NCI NIH HHS U10 CA180882
6 · The paper itself

Abstract

introductionThe incidence of breast cancer among non-Hispanic American Indian and Alaska Native (AI/AN) women varies across the United States. We applied county-level Bayesian disease mapping to quantify potential inequities in 10-year breast cancer incidence in New Mexico to better inform health equity initiatives among its non-Hispanic at-risk AI/AN population.

methodsWe used data from the Surveillance, Epidemiology, and End Results (SEER) program from 2005 through 2014 to identify new cases of breast cancer in New Mexico's 33 counties. To account for spatial variation, a county-level Area Deprivation Index, and the small area estimation problem inherent in these data, we borrowed strength globally and locally by applying Bayesian disease mapping to the counts of age-adjusted county-level breast cancer incidence. We quantified the disparity effect, as measured by the age-adjusted rate ratio, comparing the incidence of breast cancer between at-risk non-Hispanic AI/AN and non-Hispanic White women and assessed whether the ratio differed among counties.

resultsAccounting for over-dispersion and spatial correlation among the 33 counties and a county-level Area Deprivation Index, the posterior mean of the overall age-adjusted rate ratio was 0.384 (95% credible interval, 0.253--0.546). The age-adjusted rate of breast cancer in non-Hispanic AI/AN women was 0.38 times the corresponding age-adjusted rate for non-Hispanic White women; however, a significant reduction in breast cancer incidence was observed in 16 of the 33 counties.

conclusionThe application of Bayesian disease mapping to these data provided substantial evidence of an overall disparity in breast cancer incidence between at-risk non-Hispanic AI/AN and non-Hispanic White women in New Mexico, which was more marked than previously reported and limited to certain counties. Targeted statewide and county-level health-equity initiatives may lead to a reduction in these disparities.

Indexed as

Breast NeoplasmsIndians, North AmericanWhiteBayes TheoremFemaleHumansIncidenceNew MexicoUnited States

Identifiers

PMID33705303
PMCPMC7986972
OpenAlexW3133566048

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.