Evidence map›Paper›PMID 37589143›Full record

ArticleClinical trials (London, England)2023

Assessing the use of observational methods and real-world data to emulate ongoing randomized controlled trials.

Joshua D Wallach, Yihong Deng, Eric C Polley, Sanket S Dhruva, Jeph Herrin, Kenneth Quinto, Charu Gandotra, William Crown, Peter Noseworthy, Xiaoxi Yao and 4 more

Abstract readComparative Study
In one paragraph

Article in Clinical trials (London, England), 2023. 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. Article
  3. Review
  4. Article
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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

14 authors.

Joshua D WallachDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.ORCID 0000-0002-2816-6905
Yihong DengRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
Eric C PolleyDepartment of Public Health Sciences, University of Chicago, Chicago, IL, USA.
Sanket S DhruvaSection of Cardiology, Department of Medicine, San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.
Jeph HerrinSection of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA.
Kenneth QuintoOffice of Medical Policy, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Springs, MD, USA.
Charu GandotraOffice of New Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Springs, MD, USA.
William CrownFlorence Heller Graduate School, Brandeis University, Waltham, MA, USA.
Peter NoseworthyRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
Xiaoxi YaoRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
Molly Moore JefferyDivision of Health Care Delivery Research and Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA.
Timothy D LyonDepartment of Urology, Mayo Clinic, Jacksonville, FL, USA.
Joseph S RossCenter for Outcomes Research and Evaluation, Yale New Haven Health, New Haven, CT, USA.ORCID 0000-0002-9218-3320
Rozalina G McCoyRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale-Mayo FDA Center for Excellence in Regulatory Science and InnovationU01FD005938 · FDA · YALE UNIVERSITY · PI Joseph Solomon Ross · 2016 to 2026
$25.4M
Comparative Effectiveness and Safety of Osteoporosis Drug TherapiesR01AG079113 · NIA · MAYO CLINIC ROCHESTER · PI Juan P Brito Campana, Rozalina Grubina McCoy · 2022 to 2026
$3.3M
Shared decision making for stroke prevention in atrial fibrillation (SDM4Afib)R01HL131535 · NHLBI · MAYO CLINIC ROCHESTER · PI MONTORI, VICTOR MANUEL · 2016 to 2020
$3.2M
Minnesota Learning Health System Mentored Career Development Program (MN-LHS)K12HS026379 · AHRQ · UNIVERSITY OF MINNESOTA · PI BEEBE, TIMOTHY, LINZER, MARK · 2018 to 2022
$2.9M
Understanding hospital value: provider, hospital and community effectsR01HS022882 · AHRQ · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HORWITZ, LEORA · 2014 to 2023
$2.9M
Implementing Shared Decision Making (SDM) for Individualized CV Prevention (SDM4IP)R01HL151662 · NHLBI · MAYO CLINIC ROCHESTER · PI MONTORI, VICTOR MANUEL, RIDGEWAY, JENNIFER L · 2020 to 2023
$2.7M
Leveraging Physician Networks to Improve Care and Outcomes for Low-Income PopulationsR01HL144644 · NHLBI · YALE UNIVERSITY · PI NDUMELE, CHIMA · 2019 to 2021
$1.6M
Gastrointestinal Safety of Antithrombotic Drug RegimensR01HS025402 · AHRQ · MAYO CLINIC ARIZONA · PI ABRAHAM, NEENA S · 2017 to 2020
$1.6M
Medical reversals: De-implementing ineffective and unsafe treatmentsR01HS025164 · AHRQ · UNIVERSITY OF MINNESOTA · PI KARACA-MANDIC, PINAR · 2017 to 2020
$1.4M
Identifying Patient Subgroups That Are Most Likely To Benefit From Medications Used To Treat Alcohol Use DisorderK01AA028258 · NIAAA · YALE UNIVERSITY · PI WALLACH, JOSHUA DAVID · 2021 to 2025
$892k
Predicting the Risk of Severe Hypoglycemic and Hyperglycemic Events in Adults with DiabetesK23DK114497 · NIDDK · MAYO CLINIC ROCHESTER · PI MCCOY, ROZALINA GRUBINA · 2017 to 2021
$846k
AHRQ HHS K12 HS026379AHRQ HHS R01 HS022882AHRQ HHS R01 HS025164AHRQ HHS R01 HS025402AHRQ HHS R03 HS025517FDA HHS U01 FD005938NCATS NIH HHS UL1 TR001863NHLBI NIH HHS R01 HL131535NHLBI NIH HHS R01 HL144644NHLBI NIH HHS R01 HL151662NHLBI NIH HHS R56 HL130496NIAAA NIH HHS K01 AA028258NIA NIH HHS R01 AG079113NIDDK NIH HHS K23 DK114497NIDDK NIH HHS R03 DK127010
6 · The paper itself

Abstract

BACKGROUND/

aimsThere has been growing interest in better understanding the potential of observational research methods in medical product evaluation and regulatory decision-making. Previously, we used linked claims and electronic health record data to emulate two ongoing randomized controlled trials, characterizing the populations and results of each randomized controlled trial prior to publication of its results. Here, our objective was to compare the populations and results from the emulated trials with those of the now-published randomized controlled trials.

methodsThis study compared participants' demographic and clinical characteristics and study results between the emulated trials, which used structured data from OptumLabs Data Warehouse, and the published PRONOUNCE and GRADE trials. First, we examined the feasibility of implementing the baseline participant characteristics included in the published PRONOUNCE and GRADE trials' using real-world data and classified each variable as ascertainable, partially ascertainable, or not ascertainable. Second, we compared the emulated trials and published randomized controlled trials for baseline patient characteristics (concordance determined using standardized mean differences <0.20) and results of the primary and secondary endpoints (concordance determined by direction of effect estimates and statistical significance).

resultsThe PRONOUNCE trial enrolled 544 participants, and the emulated trial included 2226 propensity score-matched participants. In the PRONOUNCE trial publication, one of the 32 baseline participant characteristics was listed as an exclusion criterion on ClinicalTrials.gov but was ultimately not used. Among the remaining 31 characteristics, 9 (29.0%) were ascertainable, 11 (35.5%) were partially ascertainable, and 10 (32.2%) were not ascertainable using structured data from OptumLabs. For one additional variable, the PRONOUNCE trial did not provide sufficient detail to allow its ascertainment. Of the nine variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 6 (66.7%). The primary endpoint of time from randomization to the first major adverse cardiovascular event and secondary endpoints of nonfatal myocardial infarction and stroke were concordant between the emulated trial and published randomized controlled trial. The GRADE trial enrolled 5047 participants, and the emulated trial included 7540 participants. In the GRADE trial publication, 8 of 34 (23.5%) baseline participant characteristics were ascertainable, 14 (41.2%) were partially ascertainable, and 11 (32.4%) were not ascertainable using structured data from OptumLabs. For one variable, the GRADE trial did not provide sufficient detail to allow for ascertainment. Of the eight variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 4 (50.0%). The primary endpoint of time to hemoglobin A1c ≥7.0% was mostly concordant between the emulated trial and the published randomized controlled trial.

conclusionDespite challenges, observational methods and real-world data can be leveraged in certain important situations for a more timely evaluation of drug effectiveness and safety in more diverse and representative patient populations.

Indexed as

Myocardial InfarctionResearch DesignHumansLongitudinal StudiesPandemicsRandomized Controlled Trials as Topicobservational methodsreal-world dataTarget trial emulation

Identifiers

PMID37589143
PMCPMC10843567

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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.