Evidence map›Paper›PMID 27394678›Full record

ArticleCancer epidemiology2016

Racial and socio-economic disparities in breast cancer hospitalization outcomes by insurance status.

Tomi Akinyemiju, Swati Sakhuja, Neomi Vin-Raviv

Open access · greenAbstract read
In one paragraph

Article in Cancer epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
16.3field-weighted citation impact, top 1% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

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  11. Race, Age, Gender, and Insurance Status: A Comparative Analysis of Access to and Quality of Gastrointestinal Cancer Care.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Tomi AkinyemijuDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham Alabama, USA; Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham Alabama, USA. Electronic address: tomiakin@uab.edu.
Swati SakhujaDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham Alabama, USA.
Neomi Vin-RavivRocky Mountain Cancer Rehabilitation Institute, School of Sport and Exercise Science, University of Northern Colorado, Greeley, CO, USA; School of Social Work, College of Health and Human Sciences, Colorado State University, Fort Collins, CO, USA.
University of Alabama at Birmingham · USColorado State University · US

Funding

TRAINING AND CAREER DEVELOPMENTU54CA118948 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Timiya S Nolan · 2005 to 2026
$26.6M
University of Alabama at Birmingham's Diabetes Research CenterP30DK079626 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Kirk Michael Habegger · 2013 to 2026
$19.5M
NCI NIH HHS U54 CA118948NIDDK NIH HHS P30 DK079626
6 · The paper itself

Abstract

backgroundBreast cancer remains a major cause of morbidity and mortality among women in the US, and despite numerous studies documenting racial disparities in outcomes, the survival difference between Black and White women diagnosed with breast cancer continues to widen. Few studies have assessed whether observed racial disparities in outcomes vary by insurance type e.g. Medicare/Medicaid versus private insurance. Differences in coverage, availability of networked physicians, or cost-sharing policies may influence choice of treatment and treatment outcomes, even after patients have been hospitalized, effects of which may be differential by race. PURPOSE: The aim of this analysis was to examine hospitalization outcomes among patients with a primary diagnosis of breast cancer and assess whether differences in outcome exist by insurance status after adjusting for age, race/ethnicity and socio-economic status.

methodsWe obtained data on over 67,000 breast cancer patients with a primary diagnosis of breast cancer for this cross-sectional study from the 2007-2011 Healthcare Cost and Utilization project Nationwide Inpatient Sample (HCUP-NIS), and examined breast cancer surgery type (mastectomy vs. breast conserving surgery or BCS), post-surgical complications and in-hospital mortality. Multivariable regression models were used to compute estimates, odds ratios and 95% confidence intervals.

resultsBlack patients were less likely to receive mastectomies compared with White women (OR: 0.80, 95% CI: 0.71-0.90), regardless of whether they had Medicare/Medicaid or Private insurance. Black patients were also more likely to experience post-surgical complications (OR: 1.41, 95% CI: 1.12-1.78) and higher in-hospital mortality (OR: 1.57, 95%: 1.21-2.03) compared with White patients, associations that were strongest among women with Private insurance. Women residing outside of large metropolitan areas were significantly more likely to receive mastectomies (OR: 1.89, 95% CI: 1.54-2.31) and experience higher in-hospital mortality (OR: 1.74, 95% CI: 1.40-2.16) compared with those in metropolitan areas, regardless of insurance type.

conclusionAmong hospitalized patients with breast cancer, racial differences in hospitalization outcomes existed and worse outcomes were observed among Black women with private insurance. Future studies are needed to determine factors associated with poor outcomes in this group of women, as well as to examine contributors to low BCS adoption in non-metropolitan areas.

Indexed as

AdultAgedBreast NeoplasmsCross-Sectional StudiesFemaleHealthcare DisparitiesHospitalizationHumansInsurance CoverageMiddle AgedRacial GroupsSocial ClassUnited StatesInsurance typeMortalityPost-surgical complicationsRace/EthnicitySocio-economic status

Identifiers

PMID27394678
PMCPMC5321053
OpenAlexW2474165062

What OpenQuestion holds

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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.