Evidence map›Paper›PMID 23648893›Full record

ReviewIslets

Antigen-based vs. systemic immunomodulation in type 1 diabetes: the pros and cons.

Sofie Robert, Hannelie Korf, Conny Gysemans, Chantal Mathieu

Open access · bronzeAbstract readComparative StudyReview
In one paragraph

Review in Islets. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Review
  7. Latent autoimmune diabetes of the adult: current knowledge and uncertainty.Diabetic medicine : a journal of the British Diabetic Association · 2015
    Review
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

4 authors at 2 institutions in 2 countries.

Sofie RobertClinical and Experimental Endocrinology, Katholieke Universiteit Leuven, Campus Gasthuisberg, Leuven, Belgium.
Hannelie Korf
Conny Gysemans
Chantal Mathieu
Institute of Experimental Endocrinology of the Slovak Academy of Sciences · SKKU Leuven · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In type 1 diabetic patients insulin-producing pancreatic β-cells are destroyed by an orchestrated immune process involving self-reactive auto-antigen-specific CD4⁺ and CD8⁺ T cells. Efforts to reverse or prevent this destructive immunological cascade have led to promising results in animal models, however, the transition to the clinic has yet been unsuccessful. In addition, current clinical studies lack reliable biomarkers to circumscribe end-point parameters and define therapeutic success. Here, we give a current overview of both antigen-specific and non-specific systemic immunomodulatory approaches with a focus on the therapies verified or under evaluation in a clinical setting. While both approaches have their advantages and disadvantages, rationally designed combination therapies may yield the highest therapeutic efficacy. In order for future strategies to be effective, new well-defined biomarkers need to be developed and the extrapolation process of dose, timing and frequency from in vivo models to patients needs to be carefully reconsidered.

Indexed as

AutoimmunityImmunomodulationAnimalsAutoantigensDiabetes Mellitus, Type 1HumansImmunosuppression TherapyImmunotherapy, ActiveTranslational Research, BiomedicalAutoantigensAg-specificclinical trialcombination therapypatientsystemictherapytype 1 diabetes

Identifiers

PMID23648893
PMCPMC4204023
OpenAlexW2320489147

What OpenQuestion holds

Textmetadata
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.