Evidence map›Paper›PMID 29094086›Full record

ArticleJournal of global oncology2017

Breast Cancer Knowledge, Behaviors, and Preferences in Malawi: Implications for Early Detection Interventions From a Discrete Choice Experiment.

Racquel E Kohler, Satish Gopal, Clara N Lee, Bryan J Weiner, Bryce B Reeve, Stephanie B Wheeler

Open access · goldAbstract read
In one paragraph

Article in Journal of global oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
1.9field-weighted citation impact, top 13% 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.

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  15. Factors influencing breast cancer screening practices among women of reproductive age in South Kayonza District, Rwanda.Canadian oncology nursing journal = Revue canadienne de nursing oncologique · 2021
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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

6 authors at 1 institution in 1 country.

Racquel E Kohler, , , , , and , University of North Carolina at Chapel Hill, Chapel Hill, NC; and and , UNC Project Malawi, Lilongwe, Malawi.
Satish Gopal, , , , , and , University of North Carolina at Chapel Hill, Chapel Hill, NC; and and , UNC Project Malawi, Lilongwe, Malawi.
Clara N Lee, , , , , and , University of North Carolina at Chapel Hill, Chapel Hill, NC; and and , UNC Project Malawi, Lilongwe, Malawi.
Bryan J Weiner, , , , , and , University of North Carolina at Chapel Hill, Chapel Hill, NC; and and , UNC Project Malawi, Lilongwe, Malawi.
Bryce B Reeve, , , , , and , University of North Carolina at Chapel Hill, Chapel Hill, NC; and and , UNC Project Malawi, Lilongwe, Malawi.
Stephanie B Wheeler, , , , , and , University of North Carolina at Chapel Hill, Chapel Hill, NC; and and , UNC Project Malawi, Lilongwe, Malawi.
Kohler (New Zealand) · NZ

Funding

Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Deborah F. Tate · 1985 to 2026
$201.5M
Harvard Education Program in Cancer Prevention Control (R25T)R25CA057711 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI DAVISON, KIRSTEN · 1992 to 2018
$8.5M
Fogarty Global Health Fellows Coordinating CenterR25TW009340 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CHI, BENJAMIN H. · 2012 to 2016
$6.9M
Cancer Training GrantR25CA116339 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BASCH, ETHAN M., REEVE, BRYCE B · 2008 to 2017
$4.0M
Developing a clinical cohort of histopathologically characterized lymphomaK01TW009488 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GOPAL, SATISH · 2012 to 2016
$701k
FIC NIH HHS K01 TW009488FIC NIH HHS R25 TW009340NCI NIH HHS P30 CA016086NCI NIH HHS R25 CA057711NCI NIH HHS R25 CA116339
6 · The paper itself

Abstract

purposeBreast cancer is the most common female cancer in Africa and leading cause of death resulting from cancer; however, many countries lack early detection services. In Malawi, women are frequently diagnosed with large tumors after long symptomatic periods. Little is known about local cancer knowledge.

methodsWe administered a cross-sectional survey with a discrete choice experiment to a random sample in urban and rural areas of Lilongwe district. Bivariable and multivariable analyses determined factors associated with knowledge. Preference utilities for early detection interventions were estimated using a hierarchical Bayesian model in Sawtooth software.

resultsOf 213 women recruited, fewer than half were aware of breast cancer. In multivariable analysis, electricity at home and knowing someone with cancer increased the odds of awareness. Women were more knowledgeable about symptoms than treatment or risk factors; more than 60% erroneously believed local misconceptions. Seventeen percent were aware of breast self-examination, and 20% were aware of clinical breast examination (CBE); few reported either behavior. Common barriers included not knowing where to access CBE and transportation difficulties. Discrete choice experiment results indicated the detection strategy (breast health awareness, CBE, or both) was the most important attribute of an intervention, followed by the encounter setting and travel time.

conclusionAddressing misconceptions in health messages and engaging survivors to promote early detection may help improve breast cancer knowledge in Malawi. Program designs accounting for women's preferences should provide breast health education and CBEs in convenient settings to address transportation barriers, particularly for women with low socioeconomic position.

Identifiers

PMID29094086
PMCPMC5646878
OpenAlexW2606205493

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.