Evidence mapPaperPMID 40129946Full record

ReviewFrontiers in pharmacology2025

A comprehensive review of methodologies and application to use the real-world data and analytics platform TriNetX.

Ralf J Ludwig, Matthew Anson, Henner Zirpel, Diamant Thaci, Henning Olbrich, Katja Bieber, Khalaf Kridin, Astrid Dempfle, Philip Curman, Sizheng S Zhao and 1 more

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
108citing papers in PubMed, 1 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

108 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Mechanical Thrombectomy Versus Anticoagulation in Intermediate-Risk Pulmonary Embolism: A Risk-Stratified, Propensity Score-Matched Analysis.Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions · 2026
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48 more citing papers are in PubMed but not listed here.

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

11 authors.

Ralf J LudwigLübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany.
Matthew AnsonDepartment of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom.
Henner ZirpelInstitute and Comprehensive Centre for Inflammation Medicine, University-Hospital Schleswig-Holstein, Lübeck, Germany.
Diamant ThaciInstitute and Comprehensive Centre for Inflammation Medicine, University-Hospital Schleswig-Holstein, Lübeck, Germany.
Henning OlbrichDepartment of Dermatology, University Hospital Schleswig-Holstein Lübeck, Lübeck, Germany.
Katja BieberLübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany.
Khalaf KridinLübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany.
Astrid DempfleInstitute of Medical Informatics and Statistics, Kiel University, Kiel, Germany.
Philip CurmanLübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany.
Sizheng S ZhaoCentre for Musculoskeletal Research at University of Manchester, Manchester, United Kingdom.
Uazman AlamDepartment of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Randomized controlled trials (RCTs) are the gold standard for evaluating the efficacy and safety of both pharmacological and non-pharmacological interventions. However, while they are designed to control confounders and ensure internal validity, their usually stringent inclusion and exclusion criteria often limit the generalizability of findings to broader patient populations. Moreover, RCTs are resource-intensive, frequently underpowered to detect rare adverse events, and sometimes narrowly focused due to their highly controlled environments. In contrast, real-world data (RWD), typically derived from electronic health records (EHRs) and claims databases, offers a valuable counterpart for answering research questions that may be impractical to address through RCTs. Recognizing this, the US Food and Drug Administration (FDA) has increasingly relied on real-world evidence (RWE) from RWD to support regulatory decisions and post-market surveillance. Platforms like TriNetX, that leverage large-scale RWD, facilitate collaborations between academia, industry, and healthcare organizations, and constitute an in-depth tool for retrieval and analysis of RWD. TriNetX's federated network architecture allows real-time, privacy-compliant data access, significantly enhancing the ability to conduct retrospective studies and refine clinical trial designs. With access to currently over 150 million EHRs, TriNetX has proven particularly effective in filling gaps left by RCTs, especially in the context of rare diseases, rare endpoints, and diverse patient populations. As the role of RWD in healthcare continues to expand, TriNetX stands out as a critical tool that complements traditional clinical trials, bridging the gap between controlled research environments and real-world practice. This review provides a comprehensive analysis of the methodologies and applications of the TriNetX platform, highlighting its potential contribution to advance patient care and outcomes.

Indexed as

cohort studydrug discoveryKaplan–Meier estimatorreal-world dataTriNetX

Identifiers

PMID40129946
PMCPMC11931024

What Socratic holds

Textmetadata
LicenceCC BY
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.