Evidence map›Paper›PMID 32984386›Full record

ReviewFrontiers in medicine2020

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

Raja Atreya, Markus F Neurath, Britta Siegmund

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 2 pooled it
13.0field-weighted citation impact, top 1% of its field
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

64 citing papers in PubMed, 2 syntheses or guidelines pooled it, 118 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Patterns and predictors of biologic therapy switching in inflammatory bowel disease at a tertiary care center: A retrospective observational study.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association · 2026
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Drug Development in Inflammatory Bowel Diseases: What Is Next?Pharmaceuticals (Basel, Switzerland) · 2025
    Review
  17. Article
  18. IL-36/IL-36R signaling promotes CD4Frontiers in immunology · 2025
    Article
  19. Article
  20. Article

4 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

3 authors at 2 institutions in 1 country.

Raja AtreyaDepartment of Medicine, Medical Clinic 1, University Hospital Erlangen, University of Erlangen-Nürnberg Erlangen, Erlangen, Germany.
Markus F NeurathDepartment of Medicine, Medical Clinic 1, University Hospital Erlangen, University of Erlangen-Nürnberg Erlangen, Erlangen, Germany.
Britta SiegmundThe Transregio 241 IBDome Consortium, Berlin, Germany.
Universitätsklinikum Erlangen · DEFreie Universität Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of anti-TNF agents as the first approved targeted therapy in the treatment of inflammatory bowel disease (IBD) patients has made a major impact on our existing therapeutic algorithms. They have not only been approved for induction and maintenance treatment in IBD patients, but have also enabled us to define and achieve novel therapeutic outcomes, such as combination of clinical symptom control and endoscopic remission, as well as mucosal healing. Nevertheless, approximately one third of treated patients do not respond to initiated anti-TNF therapy and these treatments are associated with sometimes severe systemic side-effects. There is therefore the currently unmet clinical need do establish predictive markers of response to identify the subgroup of IBD patients, that have a heightened probability of response. There have so far been approaches from different fields of IBD research, to descry markers that would empower us to apply TNF-inhibitors in a more rational manner. These markers encompass findings from disease-related and clinical factors, pharmacokinetics, biochemical markers, blood and stool derived parameters, pharmacogenomics, microbial species, metabolic compounds, and mucosal factors. Furthermore, changes in the intestinal immune cell composition in response to therapeutic pressure of anti-TNF treatment have recently been implicated in the process of molecular resistance to these drugs. Insights into factors that determine resistance to anti-TNF therapy give reasonable hope, that a more targeted approach can then be utilized in these non-responders. Here, IL-23 could be identified as one of the key factors determining resistance to TNF-inhibitors. Growing insights into the molecular mechanism of action of TNF-inhibitors might also enable us to derive critical molecular markers that not only mediate the clinical effects of anti-TNF therapy, but which level of expression might also correlate with its therapeutic efficacy. In this narrative review, we present an overview of currently identified possible predictive markers for successful anti-TNF therapy and discuss identified molecular pathways that drive resistance to these substances. We will also point out the necessity and difficulty of developing and validating a diagnostic marker concerning clinically relevant outcome parameters, before they can finally enter daily clinical practice and enable a more personalized therapeutic approach.

Indexed as

anti-TNFinflammatory bowel diseasespersonalized medicinepredictionresponse

Identifiers

PMID32984386
PMCPMC7492550
OpenAlexW3081902840

What OpenQuestion 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 OpenQuestion graph.