Evidence map›Paper›PMID 23045539›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2012

Boston Patient Navigation Research Program: the impact of navigation on time to diagnostic resolution after abnormal cancer screening.

Tracy A Battaglia, Sharon M Bak, Timothy Heeren, Clara A Chen, Richard Kalish, Stephen Tringale, James O Taylor, Barbara Lottero, A Patrick Egan, Nisha Thakrar and 1 more

Abstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed, 8 pooled it
7.1field-weighted citation impact, top 2% 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

92 citing papers in PubMed, 8 syntheses or guidelines pooled it, 125 citations in OpenAlex.

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  4. Adherence in the Cancer Care Setting: a Systematic Review of Patient Navigation to Traverse Barriers.Journal of cancer education : the official journal of the American Association for Cancer Education · 2018
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  13. Neighborhood factors associated with time to resolution following an abnormal breast or cervical cancer screening test.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2014
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  14. Can patient navigation improve receipt of recommended breast cancer care? Evidence from the National Patient Navigation Research Program.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2014
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32 more citing papers are in PubMed but not listed here.

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

11 authors at 6 institutions in 1 country.

Tracy A BattagliaWomen's Health Unit, Section of General Internal Medicine, Evans Department of Medicine, Boston Medical Center, Boston University School of Medicine, Boston, MA 02118, USA. Tracy.Battaglia@bmc.org
Sharon M Bak
Timothy Heeren
Clara A Chen
Richard Kalish
Stephen Tringale
James O Taylor
Barbara Lottero
A Patrick Egan
Nisha Thakrar
Karen M Freund
Boston Medical Center · USBoston University · USCommunity Health Center · USNeighborhood Health · USHealth Net · USTufts Medical Center · US

Funding

"Patient Navigation in the SafetyNet: CONNECTeDD"U01CA116892 · NCI · BOSTON MEDICAL CENTER · PI FREUND, KAREN · 2005 to 2010
$4.3M
NCI NIH HHS U01 CA116892NCI NIH HHS U01 CA116892-01
6 · The paper itself

Abstract

backgroundThere is a need for controlled studies to assess the impact of patient navigation in vulnerable cancer populations.

methodsBoston Patient Navigation Research Program conducted a quasi-experimental patient navigation intervention across six federally qualified inner-city community health centers, three assigned to a breast cancer navigation intervention and three assigned to a cervical cancer navigation intervention; each group then served as the control for the other. Eligible women had an abnormal breast or cervical cancer screening test conducted at one of the participating health centers during a baseline (2004-2005) or intervention period (2007-2008). Kaplan-Meier survival curves and proportional hazards regression examined the effect of patient navigation on time to definitive diagnosis, adjusting for covariates, clustering by clinic and differences between the baseline and intervention period.

resultsWe enrolled 997 subjects in the baseline period and 3,041 subjects during the intervention period, of whom 1,497 were in the navigated arm, and 1,544 in the control arm. There was a significant decrease in time to diagnosis for subjects in the navigated group compared with controls among those with a cervical screening abnormality [aHR 1.46; 95% confidence interval (CI), 1.1-1.9]; and among those with a breast cancer screening abnormality that resolved after 60 days (aHR 1.40; 95% CI, 1.1-1.9), with no differences before 60 days.

conclusionsThis study documents a benefit of patient navigation on time to diagnosis among a racially/ethnically diverse inner city population. IMPACT: Patient navigation may address cancer health disparities by reducing time to diagnosis following an abnormal cancer-screening event.

Indexed as

Early Detection of CancerPatient NavigationAdolescentAdultAgedBreast NeoplasmsFemaleHumansInsurance, HealthKaplan-Meier EstimateMiddle AgedProportional Hazards ModelsTime FactorsUterine Cervical Neoplasms

Identifiers

PMID23045539
PMCPMC3472624
OpenAlexW2149562646

What OpenQuestion holds

Textmetadata
LicenceTDM
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.