Evidence map›Paper›PMID 37502999›Full record

ArticlemedRxiv : the preprint server for health sciences2023

DESIGN DIFFERENCES EXPLAIN VARIATION IN RESULTS BETWEEN RANDOMIZED TRIALS AND THEIR NON-RANDOMIZED EMULATIONS.

Rachel Heyard, Leonhard Held, Sebastian Schneeweiss, Shirley V Wang

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Rachel HeyardCenter for Reproducible Science, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland.ORCID 0000-0002-7531-4333
Leonhard HeldCenter for Reproducible Science, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland.ORCID 0000-0002-8686-5325
Sebastian SchneeweissDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremon St, Boston MA 02120.ORCID 0000-0003-2575-467X
Shirley V WangDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremon St, Boston MA 02120.ORCID 0000-0001-7761-7090

Funding

Randomized Cardiovascular Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology (RCT DUPLICATE)R01HL141505 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SCHNEEWEISS, SEBASTIAN G., WANG, SHIRLEY · 2019 to 2023
$3.6M
New approaches to safety monitoring of novel systemic treatments for atopic dermatitis in clinical practice and underrepresented populationsR01AR080194 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Sebastian G. Schneeweiss · 2022 to 2026
$3.3M
Understanding effectiveness of new drugs in older adults shortly after market entryR01AG053302 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI WANG, SHIRLEY · 2018 to 2021
$2.0M
NHLBI NIH HHS R01 HL141505NIAMS NIH HHS R01 AR080194NIA NIH HHS R01 AG053302
6 · The paper itself

Abstract

Objectives: While randomized controlled trials (RCTs) are considered a standard for evidence on the efficacy of medical treatments, non-randomized real-world evidence (RWE) studies using data from health insurance claims or electronic health records can provide important complementary evidence. The use of RWE to inform decision-making has been questioned because of concerns regarding confounding in non-randomized studies and the use of secondary data. RCT-DUPLICATE was a demonstration project that emulated the design of 32 RCTs with non-randomized RWE studies. We sought to explore how emulation differences relate to variation in results between the RCT-RWE study pairs. Methods: We include all RCT-RWE study pairs from RCT-DUPLICATE where the measure of effect was a hazard ratio and use exploratory meta-regression methods to explain differences and variation in the effect sizes between the results from the RCT and the RWE study. The considered explanatory variables are related to design and population differences. Results: Most of the observed variation in effect estimates between RCT-RWE study pairs in this sample could be explained by three emulation differences in the meta-regression model: (i) in-hospital start of treatment (not observed in claims data), (ii) discontinuation of certain baseline therapies at randomization (not part of clinical practice), (iii) delayed onset of drug effects (missed by short medication persistence in clinical practice). Conclusions: This analysis suggests that a substantial proportion of the observed variation between results from RCTs and RWE studies can be attributed to design emulation differences. (238 words).

Indexed as

designemulation differencesheterogeneitymeta-regressionrandomized controlled trialReal-world evidence

Identifiers

PMID37502999
PMCPMC10370236

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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.