Evidence map›Paper›PMID 39312685›Full record

ArticleJNCI cancer spectrum2024

Socioeconomic and urban-rural disparities in genome-matched treatment receipt and survival after genomic tumor testing.

Jessica F DiBiase, Elizabeth Scharnetzki, Emily Edelman, E Kate Reed, Petra Helbig, Jens Rueter, Susan Miesfeldt, Cara L Frankenfeld, Paul K J Han, Elizabeth A Jacobs and 2 more

Abstract read
In one paragraph

Article in JNCI cancer spectrum, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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

12 authors.

Jessica F DiBiaseCenter for Interdisciplinary Population and Health Research, MaineHealth Institute for Research, Westbrook, ME, USA.ORCID 0000-0003-3834-8873
Elizabeth ScharnetzkiCenter for Interdisciplinary Population and Health Research, MaineHealth Institute for Research, Westbrook, ME, USA.ORCID 0000-0002-5727-0189
Emily EdelmanThe Jackson Laboratory, Augusta, ME, USA.
E Kate ReedThe Jackson Laboratory, Augusta, ME, USA.ORCID 0000-0003-3307-8093
Petra HelbigThe Jackson Laboratory, Augusta, ME, USA.ORCID 0009-0009-0069-0447
Jens RueterThe Jackson Laboratory, Augusta, ME, USA.ORCID 0000-0002-9021-025X
Susan MiesfeldtCancer Risk and Prevention Program, Maine Medical Center Cancer Institute and MaineHealth Cancer Care Network, Scarborough, ME, USA.ORCID 0000-0001-8227-3165
Cara L FrankenfeldCenter for Interdisciplinary Population and Health Research, MaineHealth Institute for Research, Westbrook, ME, USA.ORCID 0000-0002-2318-0791
Paul K J HanCenter for Interdisciplinary Population and Health Research, MaineHealth Institute for Research, Westbrook, ME, USA.ORCID 0000-0003-0165-1940
Elizabeth A JacobsTufts University School of Medicine, Boston, MA, USA.ORCID 0000-0002-5549-7718
Eric C AndersonCenter for Interdisciplinary Population and Health Research, MaineHealth Institute for Research, Westbrook, ME, USA.ORCID 0000-0002-4215-6308
Maine Cancer Genomics Initiative Working Group

Funding

CTSA Institutional Mentored Career Development Program (KL2)KL2TR002545 · NCATS · TUFTS UNIVERSITY BOSTON · PI FREUND, KAREN · 2018 to 2022
$5.0M
Harold Alfond FoundationJackson LaboratoryNCATS NIH HHS KL2 TR002545NIH HHS KL2TR002545
6 · The paper itself

Abstract

backgroundEmerging cancer treatments are often most available to socially advantaged individuals. This study examines the relationship of patient educational attainment, income level, and rurality to the receipt of genome-matched treatment and overall survival.

methodsSurvey and clinical data were collected from patients with cancer (n = 1258) enrolled in the Maine Cancer Genomics Initiative. Logistic regression models examined whether receipt of genome-matched treatment differed by patient education, income, and rurality. Kaplan-Meier curves and Cox regression were conducted to evaluate 12-month mortality. We completed additional exploratory analyses using Kaplan-Meier curves and Cox models stratified by receipt of genome-matched treatment. Logistic and Cox regression models were adjusted for age and gender.

resultsEducational attainment, income level, and rurality were not associated with genome-matched treatment receipt. Of 1258 patients, 462 (36.7%) died within 365 days of consent. Mortality risk was associated with lower educational attainment (hazard ratio [HR] = 1.30, 95% confidence interval [CI] = 1.06 to 1.59; P = .013). No statistically significant differences in mortality risk were observed for income level or rurality. Exploratory models suggest that patients who did not receive genome-matched treatment with lower educational attainment had higher mortality risk (HR = 1.36, 95% CI = 1.09 to 1.69; P = .006). For patients who did receive genome-matched treatment, there was no difference in mortality risk between the education groups (HR = 1.01, 95% CI = 0.56 to 1.81; P > .9).

conclusionAlthough there were no disparities in who received genome-matched treatment, we found a disparity in mortality associated with education level, which was more pronounced for patients who did not receive genome-matched treatment. Future research is warranted to investigate the intersectionality of social disadvantage with clinical outcomes to address survival disparities.

Indexed as

Educational StatusHealthcare DisparitiesNeoplasmsProportional Hazards ModelsRural PopulationSocioeconomic FactorsAdultAgedFemaleGenetic TestingGenomicsHumansIncomeKaplan-Meier EstimateLogistic ModelsMaine

Identifiers

PMID39312685
PMCPMC11483106

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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.