Evidence map›Paper›PMID 31872154›Full record

ArticleContemporary clinical trials communications2019

How current reporting practices may mask differences: A call for examining cancer-specific demographic enrollment patterns in cancer treatment clinical trials.

Hala T Borno, Eric J Small, Li Zhang, Mindy C DeRouen, Ann Griffin, Joseph McGuire, Charles J Ryan, Robert A Hiatt, Celia P Kaplan

Abstract read
In one paragraph

Article in Contemporary clinical trials communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Review
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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

9 authors.

Hala T BornoUniversity of California at San Francisco, Division of Hematology/Oncology, United States.
Eric J SmallUniversity of California at San Francisco, Division of Hematology/Oncology, United States.
Li ZhangDepartment of Epidemiology and Biostatistics, University of California San Francisco, United States.
Mindy C DeRouenHelen Diller Family Comprehensive Cancer Center, United States.
Ann GriffinHelen Diller Family Comprehensive Cancer Center, United States.
Joseph McGuireHelen Diller Family Comprehensive Cancer Center, United States.
Charles J RyanUniversity of Minnesota, Division of Hematology/Oncology, United States.
Robert A HiattDepartment of Epidemiology and Biostatistics, University of California San Francisco, United States.
Celia P KaplanUniversity of California at San Francisco, Division of General Internal Medicine, United States.

Funding

Women's CancerP30CA077598 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Douglas Yee · 1998 to 2026
$100.4M
NCI NIH HHS P30 CA077598
6 · The paper itself

Abstract

backgroundA lack of diversity among clinical trial (CT) participants remains a critical problem. Few studies have examined recruitment variability in cancer treatment CTs by cancer type. Given the increasing organ-specific specialization of oncologic care, an understanding of this variability may affect institutional recruitment practices.

methodsThis study examines three data sources from 2010 through 2014. The analyzed sample includes 3,580 CT participants identified in the institutional Clinical Trials Management System (CTMS) database and 20,305 incident cases of invasive cancer within a Comprehensive Cancer Center (CCC) institutional catchment area. A total of 341,114 incident cases of primary invasive cancer were identified through the California Cancer Registry (CCR). The primary study measurements were sociodemographic characteristics of the three populations (age, sex, race/ethnicity, and health insurance).

resultsRacial/ethnic disparities were observed, with more incident cases of Whites seen in cancer center (68%) and enrolled in CTs (72%) compared to incident cases in catchment area (67%) (p < 0.001) overall. More older adults (65) were enrolled in prostate cancer CTs (58%) than seen in cancer center (45%) (p < 0.001). Alternatively, fewer older adults were enrolled in breast and colorectal CTs than seen in cancer center (p < 0.001). Among colon (p < 0.001), breast (p < 0.001), and prostate (p<0.001) cancer types, insurance type significantly varied between incident cases in catchment area, cancer center, and among CT participants. For colorectal cancer, no difference in sex distribution was observed overall. A significant difference in insurance type within each cancer type was observed (p < 0.001).

conclusionsThese findings suggest that reporting overall recruitment frequencies may mask differences by cancer type.

Indexed as

Cancer disparitiesPrecision medicineRecruitment scienceRepresentativeness in clinical trials

Identifiers

PMID31872154
PMCPMC6915794

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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.