Evidence mapPaperPMID 33825838Full record

ArticleJAMA network open2021

Comparison of Clinical Characteristics Between Clinical Trial Participants and Nonparticipants Using Electronic Health Record Data.

James R Rogers, Cong Liu, George Hripcsak, Ying Kuen Cheung, Chunhua Weng

Abstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 3 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

28 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

5 authors.

James R RogersDepartment of Biomedical Informatics, Columbia University, New York, New York.
Cong LiuDepartment of Biomedical Informatics, Columbia University, New York, New York.
George HripcsakDepartment of Biomedical Informatics, Columbia University, New York, New York.
Ying Kuen CheungDepartment of Biostatistics, Columbia University, New York, New York.
Chunhua WengDepartment of Biomedical Informatics, Columbia University, New York, New York.

Funding

NLM NIH HHS R01 LM009886
6 · The paper itself

Abstract

Importance: Assessing generalizability of clinical trials is important to ensure appropriate application of interventions, but most assessments provide minimal granularity on comparisons of clinical characteristics. Objective: To assess the extent of underlying clinical differences between clinical trial participants and nonparticipants by using a combination of electronic health record and trial enrollment data. Design, Setting, and Participants: This cross-sectional study used data obtained from a single academic medical center between September 1996 and January 2019 to identify 1645 clinical trial participants from a diverse set of 202 available trials conducted at the center. Using an aggregated resampling procedure, nonparticipants were matched to participants 1:1 based on trial conditions, number of recent visits to a health care professional, and calendar time. Exposures: Clinical trial enrollment vs no enrollment. Main Outcomes and Measures: The primary outcome was standardized differences in clinical characteristics between participants and nonparticipants in clinical trials stratified into the 4 most common disease domains. Results: This cross-sectional study included 1645 participants from 202 trials (929 [56.5%] male; mean [SD] age, 54.65 [21.38] years) and an aggregated set of 1645 nonparticipants (855 [52.0%] male; mean [SD] age, 57.24 [21.91] years). The most common disease domains for the selected trials were neoplastic disease (86 trials; 737 participants), disorders of the digestive system (31 trials; 321 participants), inflammatory disorders (28 trials; 276 participants), and disorders of the cardiovascular system (27 trials; 319 participants); trials could qualify for multiple disease domains. Among 31 conditions, the percentage of conditions for which the prevalence was lower among participants than among nonparticipants per standardized differences was 64.5% (20 conditions) for neoplastic disease trials, 61.3% (19) for digestive system trials, 58.1% (18) for inflammatory disorder trials, and 38.7% (12) for cardiovascular system trials. Among 17 medications, the percentage of medications for which use was less among participants than among nonparticipants per standardized differences was 64.7% (11) for neoplastic disease trials, 58.8% (10) for digestive system trials, 88.2% (15) for inflammatory disorder trials, and 52.9% (9) for cardiovascular system trials. Conclusions and Relevance: Using a combination of electronic health record and trial enrollment data, this study found that clinical trial participants had fewer comorbidities and less use of medication than nonparticipants across a variety of disease domains. Combining trial enrollment data with electronic health record data may be useful for better understanding of the generalizability of trial results.

Indexed as

AdolescentAdultAgedCase-Control StudiesClinical Trials as TopicCross-Sectional StudiesDatabases, FactualElectronic Health RecordsFemaleHumansMaleMiddle AgedPatient ParticipationYoung Adult

Identifiers

PMID33825838
PMCPMC8027910

What Socratic holds

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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 Socratic graph.