Evidence map›Paper›PMID 33658187›Full record

SynthesisBMJ (Clinical research ed.)2021

Treatment effects in randomised trials using routinely collected data for outcome assessment versus traditional trials: meta-research study.

Kimberly A Mc Cord, Hannah Ewald, Arnav Agarwal, Dominik Glinz, Soheila Aghlmandi, John P A Ioannidis, Lars G Hemkens

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMJ (Clinical research ed.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 3 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

25 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

7 authors.

Kimberly A Mc CordBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel, University of Basel, 4031 Basel, Switzerland.
Hannah EwaldBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel, University of Basel, 4031 Basel, Switzerland.
Arnav AgarwalDepartment of Medicine, University of Toronto, Toronto, ON, Canada.
Dominik GlinzBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel, University of Basel, 4031 Basel, Switzerland.
Soheila AghlmandiBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel, University of Basel, 4031 Basel, Switzerland.
John P A IoannidisStanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Lars G HemkensBasel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel, University of Basel, 4031 Basel, Switzerland lars.hemkens@usb.ch.ORCID 0000-0002-3444-1432

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare effect estimates of randomised clinical trials that use routinely collected data (RCD-RCT) for outcome ascertainment with traditional trials not using routinely collected data.

designMeta-research study. DATA SOURCE: Studies included in the same meta-analysis in a Cochrane review. ELIGIBILITY CRITERIA FOR STUDY SELECTION: Randomised clinical trials using any type of routinely collected data for outcome ascertainment, including from registries, electronic health records, and administrative databases, that were included in a meta-analysis of a Cochrane review on any clinical question and any health outcome together with traditional trials not using routinely collected data for outcome measurement. REVIEW

methodsEffect estimates from trials using or not using routinely collected data were summarised in random effects meta-analyses. Agreement of (summary) treatment effect estimates from trials using routinely collected data and those not using such data was expressed as the ratio of odds ratios. Subgroup analyses explored effects in trials based on different types of routinely collected data. Two investigators independently assessed the quality of each data source.

results84 RCD-RCTs and 463 traditional trials on 22 clinical questions were included. Trials using routinely collected data for outcome ascertainment showed 20% less favourable treatment effect estimates than traditional trials (ratio of odds ratios 0.80, 95% confidence interval 0.70 to 0.91, I

conclusionsRandomised clinical trials using routinely collected data for outcome ascertainment show smaller treatment benefits than traditional trials not using routinely collected data. These differences could have implications for healthcare decision making and the application of real world evidence.

Indexed as

Outcome Assessment, Health CareRandomized Controlled Trials as TopicRoutinely Collected Health DataHumans

Identifiers

PMID33658187
PMCPMC7926294

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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 Socratic graph.