Evidence map›Paper›PMID 26177009›Full record

ArticleAmerican journal of respiratory and critical care medicine2015

Implications of Heterogeneity of Treatment Effect for Reporting and Analysis of Randomized Trials in Critical Care.

Theodore J Iwashyna, James F Burke, Jeremy B Sussman, Hallie C Prescott, Rodney A Hayward, Derek C Angus

Abstract read
In one paragraph

Article in American journal of respiratory and critical care medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 153 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
153citing papers in PubMed, 7 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

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

  1. Pooled it
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  3. Between-trial heterogeneity in ARDS research.Intensive care medicine · 2021
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  17. A Detoxification Intervention for Gulf War Illness: A Pilot Randomized Controlled Trial.International journal of environmental research and public health · 2019
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  20. Balanced Crystalloids versus Saline in the Intensive Care Unit. The SALT Randomized Trial.American journal of respiratory and critical care medicine · 2017
    Trial

93 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Theodore J Iwashyna1 Department of Internal Medicine and.ORCID http://orcid.org/0000-0002-4226-9310
James F Burke4 Department of Neurology, University of Michigan, Ann Arbor, Michigan.
Jeremy B Sussman1 Department of Internal Medicine and.
Hallie C Prescott1 Department of Internal Medicine and.
Rodney A Hayward1 Department of Internal Medicine and.
Derek C Angus5 Clinical Research, Investigation, and Systems Modeling of Acute Illness Laboratory, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.

Funding

Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
PULMONARY CELLULAR AND MOLECULAR BIOLOGY TRAININGT32HL007749 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Robert Pickett Dickson · 1993 to 2026
$19.9M
Protocolized Care for Early Septic Shock (ProCESS)P50GM076659 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ANGUS, DEREK C · 2006 to 2012
$11.2M
Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Procalcitonin Antibiotic Consensus Trial (ProACT)R01GM101197 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HUANG, DAVID TOM · 2013 to 2017
$5.0M
Reducing Racial Disparities in Post-Stroke Disability in the ElderlyR01MD008879 · NIMHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BURKE, JAMES FRANCIS, SKOLARUS, LESLI ELIZABETH · 2014 to 2018
$1.9M
Using Outcomes Analyses to Inform Implementation of NINDS Clinical TrialsK08NS082597 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BURKE, JAMES FRANCIS · 2013 to 2017
$948k
Longterm Impact of Natural Disasters on Disability and Health in Older AmericansR21AG044752 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI IWASHYNA, THEODORE J · 2013 to 2014
$428k
Implementation research of benefit-based treatment for cardiovascular diseaseIK2HX001368 · VA · VETERANS HEALTH ADMINISTRATION · PI SUSSMAN, JEREMY BRODER · 2015 to 2019
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HSRD VA I01 HX002014HSRD VA IK2 HX001368NHLBI NIH HHS T32 HL007749NIA NIH HHS R21 AG044752NIDDK NIH HHS P30 DK020572NIDDK NIH HHS P30DK020572NIDDK NIH HHS P30 DK092926NIGMS NIH HHS P50 GM076659NIGMS NIH HHS R01 GM101197NIMHD NIH HHS R01 MD008879NINDS NIH HHS K08 NS082597
6 · The paper itself

Abstract

Randomized clinical trials (RCTs) are conducted to guide clinicians' selection of therapies for individual patients. Currently, RCTs in critical care often report an overall mean effect and selected individual subgroups. Yet work in other fields suggests that such reporting practices can be improved. Specifically, this Critical Care Perspective reviews recent work on so-called "heterogeneity of treatment effect" (HTE) by baseline risk and extends that work to examine its applicability to trials of acute respiratory failure and severe sepsis. Because patients in RCTs in critical care medicine-and patients in intensive care units-have wide variability in their risk of death, these patients will have wide variability in the absolute benefit that they can derive from a given therapy. If the side effects of the therapy are not perfectly collinear with the treatment benefits, this will result in HTE, where different patients experience quite different expected benefits of a therapy. We use simulations of RCTs to demonstrate that such HTE could result in apparent paradoxes, including: (1) positive trials of therapies that are beneficial overall but consistently harm or have little benefit to low-risk patients who met enrollment criteria, and (2) overall negative trials of therapies that still consistently benefit high-risk patients. We further show that these results persist even in the presence of causes of death unmodified by the treatment under study. These results have implications for reporting and analyzing RCT data, both to better understand how our therapies work and to improve the bedside applicability of RCTs. We suggest a plan for measurement in future RCTs in the critically ill.

Indexed as

AgedCritical CareFemaleHumansMaleRandomized Controlled Trials as TopicRespiratory InsufficiencySepsisacute respiratory failureheterogeneity of treatment effectprecision medicinerandomized clinical trialssepsis

Identifiers

PMID26177009
PMCPMC4642199

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.