Evidence map›Paper›PMID 35786002›Full record

ArticleClinical trials (London, England)2022

An adaptive clinical trial design to identify the target dose of tenecteplase for treatment of acute pulmonary embolism.

Sharon D Yeatts, Lydia D Foster, William G Barsan, Nicholas S Berry, Clifton W Callaway, Roger J Lewis, Benjamin R Saville, Robert Silbergleit, Jeffrey A Kline

Open access · greenAbstract readClinical Trial Protocol
In one paragraph

Article in Clinical trials (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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 at 7 institutions in 1 country.

Sharon D YeattsDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.ORCID 0000-0001-9235-0670
Lydia D FosterDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
William G BarsanDepartment of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA.
Nicholas S BerryBerry Consultants, LLC, Austin, TX, USA.ORCID 0000-0001-8701-3258
Clifton W CallawayDepartment of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Roger J LewisBerry Consultants, LLC, Austin, TX, USA.
Benjamin R SavilleBerry Consultants, LLC, Austin, TX, USA.
Robert SilbergleitDepartment of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-4101-2430
Jeffrey A KlineDepartment of Emergency Medicine, Wayne State University, Detroit, MI, USA.
Medical University of South Carolina · USUniversity of Michigan · USBerry & Associates (United States) · USUCLA Medical Center · USUniversity of Pittsburgh · USVanderbilt University · USWayne State University · US

Funding

Strategies to Innovate EmeRgENcy Care Clinical Trials Network (SIREN) - Clinical Coordinating Center (CCC)U24NS100659 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WILLIAM G BARSAN, Clifton W. Callaway · 2017 to 2026
$6.4M
Strategies to Innovate EmeRgENcy Care Clinical Trials Network (SIREN) - Data Coordinating CenterU24NS100655 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI VALERIE L DURKALSKI, Sharon Dziuba Yeatts · 2017 to 2026
$4.4M
Design and planning of a multicenter adaptive dose selection trial of fibrinolytics for acute submassive pulmonary embolismU34HL144374 · NHLBI · INDIANA UNIVERSITY INDIANAPOLIS · PI KLINE, JEFFREY A, YEATTS, SHARON DZIUBA · 2019 to 2019
$206k
NHLBI NIH HHS U34 HL144374NINDS NIH HHS U24 NS100655NINDS NIH HHS U24 NS100659
6 · The paper itself

Abstract

BACKGROUND/

aimsFibrinolytic therapy with tenecteplase has been proposed for patients with pulmonary embolism but the optimal dose is unknown. Higher-than-necessary dosing is likely to cause excess bleeding. We designed an adaptive clinical trial to identify the minimum and assumed safest dose of tenecteplase that maintains efficacy.

methodsWe propose a Bayesian adaptive, placebo-controlled, group-sequential dose-finding trial using response-adaptive randomization to preferentially allocate subjects to the most promising doses, dual analyses strategies (continuous and dichotomized) using a gatekeeping approach to maximize clinical impact, and interim stopping rules to efficiently address competing trial objectives. The operating characteristics of the proposed design were evaluated using Monte Carlo simulation across multiple hypothetical efficacy scenarios.

resultsSimulation demonstrated response-adaptive randomization can preferentially allocate subjects to doses which appear to be performing well based on interim data. Interim decision-making, including the interim evaluation of both analysis strategies with gatekeeping, allows the trial to continue enrollment when success with the dichotomized analysis strategy appears sufficiently likely and to stop enrollment and declare superiority based on the continuous analysis strategy when there is little chance of ultimately declaring superiority with the dichotomized analysis.

conclusionThe proposed design allows evaluation of a greater number of dose levels than would be possible with a non-adaptive design and avoids the need to choose either the continuous or the dichotomized analysis strategy for the primary endpoint.

Indexed as

Pulmonary EmbolismResearch DesignAcute DiseaseAdaptive Clinical Trials as TopicBayes TheoremDose-Response Relationship, DrugHumansRandomized Controlled Trials as TopicTenecteplaseTenecteplaseadaptive clinical trialBayes theoremdose selectionPulmonary embolismstatistical methodsthrombolysis

Identifiers

PMID35786002
PMCPMC9691514
OpenAlexW4283785451

What OpenQuestion holds

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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.