Evidence map›Paper›PMID 35471562›Full record

ArticleTherapeutic innovation & regulatory science2022

False Negative ECG Device Results May Increase the Risk of Adverse Events in Clinical Oncology Trials.

Luc Dekie, Robert B Kleiman

Open access · hybridAbstract read
In one paragraph

Article in Therapeutic innovation & regulatory science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Luc DekieClario, 1818 Market Street, Suite 2600, Philadelphia, PA, 19103, USA. luc.dekie@clario.com.ORCID 0000-0001-5706-8813
Robert B KleimanClario, 1818 Market Street, Suite 2600, Philadelphia, PA, 19103, USA.
Clarion University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSites participating in clinical trials may not have the expertise and infrastructure to accurately measure cardiac intervals on 12-lead ECGs and rely heavily on the automated ECG device generated results for clinical decision-making.

methodsUsing a dataset of over 260,000 ECGs collected in clinical oncology studies, we investigated the mean difference and the rate of false negative results between the digital ECG machine QTc and QRS measurements compared to those obtained by a centralized ECG core lab.

resultsThe mean differences between the core lab and the automated algorithm QTcF and QRS measurements were + 1.8 ± 16.0 ms and - 1.0 ± 8.8 ms, respectively. Among the ECGs with a centralized QTcF value > 450 or > 470 ms, 39.5% and 47.8% respectively had a device reported QTcF value ≤ 450 ms or ≤ 470 ms. Among the ECGs with a centrally measured QTcF > 500 ms, 55.8% had a device reported value ≤ 500 ms. Automated QTcF measurements failed to detect a QTcF increase > 60 ms for 53.9% of the ECGs identified by the core lab. Automated measurements also failed to detect QRS prolongation, though to a lesser extent than failures to detect QTc prolongation. Among the ECGs with a centrally measured QRS > 110 or 120 ms, 7.9% and 7.3% respectively had a device reported QRS value ≤ 110 ms or ≤ 120 ms.

conclusionRelying on automated measurements from ECG devices for patient inclusion and treatment (dis)continuation decisions poses a potential risk to patients participating in oncology studies.

Indexed as

Long QT SyndromeNeoplasmsAlgorithmsElectrocardiographyHumansMedical OncologyCore labECG algorithmFalse negativeOncology trialsQRSQTcF

Identifiers

PMID35471562
PMCPMC9135776
OpenAlexW4224879639

What OpenQuestion holds

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LicenceCC BY
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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.