Evidence map›Paper›PMID 37837177›Full record

ArticleCancer2024

Promoting informed approaches in precision oncology and clinical trial participation for Black patients with cancer: Community-engaged development and pilot testing of a digital intervention.

Jinghua An, Jeanne M Ferrante, Myneka Macenat, Shridar Ganesan, Shawna V Hudson, Coral Omene, Harold Garcia, Anita Y Kinney

Abstract read
In one paragraph

Article in Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
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

8 authors.

Jinghua AnRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.ORCID https://orcid.org/0000-0002-1650-3855
Jeanne M FerranteRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.
Myneka MacenatRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.
Shridar GanesanRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.
Shawna V HudsonRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.
Coral OmeneRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.
Harold GarciaLawrence Herbert School of Communication, Hofstra University, Hempstead, New York, USA.
Anita Y KinneyRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA.

Funding

TRANSCRIPTIONAL PROFILINGP30CA072720 · NCI · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI Tracie Saunders · 1997 to 2026
$94.5M
NCI NIH HHS 3P30CA072720NCI NIH HHS P30 CA072720Pfizer Global Medical Grants
6 · The paper itself

Abstract

backgroundBlack patients with cancer are less likely to receive precision cancer treatments than White patients and are underrepresented in clinical trials. To address these disparities, the study aimed to develop and pilot-test a digital intervention to improve Black patients' knowledge about precision oncology and clinical trials, empower patients to increase relevant discussion, and promote informed decision-making.

methodsA community-engaged approach, including a Community Advisory Board and two rounds of key informant interviews with Black patients with cancer, their relatives, and providers (n = 48) was used to develop and refine the multimedia digital intervention. Thematic analysis was conducted for qualitative data. The intervention was then pilot-tested with 30 Black patients with cancer to assess feasibility, acceptability, appropriateness, knowledge, decision self-efficacy, and patient empowerment; Wilcoxon matched pairs signed-rank test was used to analyze quantitative data.

resultsThe digital tool was found to be feasible, acceptable, and culturally appropriate. Key informants shared their preferences and recommendations for the digital intervention and helped improve cultural appropriateness through user and usability testing. In the pilot test, appreciable improvement was found in participants' knowledge about precision oncology (z = -2.04, p = .052), knowledge about clinical trials (z = -3.14, p = .001), and decisional self-efficacy for targeted/immune therapy (z = -1.96, p = .0495).

conclusionsThe digital intervention could be a promising interactive decision-support tool for increasing Black patients' participation in clinical trials and receipt of precision treatments, including immunotherapy. Its use in clinical practice may reduce disparities in oncology care and research. PLAIN LANGUAGE SUMMARY: We developed a digital interactive decision support tool for Black patients with cancer by convening a Community Advisory Board and conducting interviews with Black patients with cancer, their relatives, and providers. We then pilot-tested the intervention with newly diagnosed Black patients with cancer and found appreciable improvement in participants' knowledge about precision oncology, knowledge about clinical trials, and confidence in making decisions for targeted/immune therapy. Our digital tool has great potential to be an affordable and scalable solution for empowering and educating Black patients with cancer to help them make informed decisions about precision oncology and clinical trials and ultimately reducing racial disparities.

Indexed as

Black or African AmericanClinical Trials as TopicNeoplasmsPatient ParticipationPrecision MedicineAdultAgedDecision MakingFemaleHealth Knowledge, Attitudes, PracticeHumansMaleMedical OncologyMiddle AgedPilot Projectschatbotclinical trial participationdecision‐makingdigital interventionimmunotherapyprecision medicinetargeted therapy

Identifiers

PMID37837177
PMCPMC11686548

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.