Evidence map›Paper›PMID 40134221›Full record

ReviewDiabetes, obesity & metabolism2025

Type 1 diabetes risk factors, risk prediction and presymptomatic detection: Evidence and guidance for screening.

Ezio Bonifacio, Anette-Gabriele Ziegler

Abstract readReview
In one paragraph

Review in Diabetes, obesity & metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed, 1 synthesis or guideline 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

2 authors.

Ezio BonifacioCenter for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany.
Anette-Gabriele ZieglerGerman Center for Environmental Health, Institute of Diabetes Research, Helmholtz Munich, Munich, Germany.ORCID 0000-0002-6290-5548

Funding

Bayerische Staatsministerium für Wirtschaft, Landesentwicklung und Energie, Prevention of Autoimmune Diabetes-Digital LabBreakthrough T1D 1-SRA-2014-310-M-RBundesministerium für Bildung und Forschung DZKJ 01GL2406CBundesministerium für Bildung und Forschung FZK 01KX1818Deutscher Diabetiker Bund e.VGerman Center for Diabetes Research (DVD e.V.)Innovative Health Initiative 101132379Novo Nordisk Foundation NNF22SA0081044
6 · The paper itself

Abstract

Type 1 diabetes is recognized as a chronic disease with a presymptomatic phase that does not require insulin therapy and a clinical phase where insulin treatment becomes necessary. The presymptomatic phase is characterized by the presence of autoantibodies targeting pancreatic islet beta cell antigens (islet autoantibodies). This phase is further classified into three stages: Stage 1, defined by normoglycaemia; Stage 2, characterized by dysglycaemia; and Stage 3, marked by hyperglycaemia, which typically presents clinically and necessitates insulin therapy. The prospect of therapies to delay the onset of clinical disease and insulin treatment has been a driver of research into the presymptomatic phase since the discovery of islet autoantibodies. With the recent approval of teplizumab as a therapy to delay disease progression, attention has increasingly focused on diagnosing individuals with Stage 1 and Stage 2 type 1 diabetes. However, diagnosing an asymptomatic condition that affects fewer than 1 in 200 individuals poses significant challenges. As we enter this new era of diagnosis, it is crucial to refine diagnostic approaches to ensure accuracy and effectiveness. This review summarizes current evidence and guidance while emphasizing the need for continued research alongside broader application of screening. PLAIN LANGUAGE SUMMARY: Type 1 diabetes is an autoimmune disease that affects approximately 0.5% of individuals. In this publication, the authors provide a comprehensive overview of strategies for identifying individuals in the pre-symptomatic, early stages of the disease. Early-stage type 1 diabetes can be detected by the presence of autoantibodies against specific proteins in the blood, signaling an ongoing disease process before clinical symptoms appear. Genetic factors also contribute to the development of these autoantibodies and the disease itself. The paper explores how these markers are used for early identification, emphasizing optimal screening ages and the role of confirmation tests in preventing misdiagnosis. A key consideration in early diagnosis is that disease progression varies-some individuals develop clinical diabetes rapidly, while others may take many years. The authors discuss additional tests that can help predict how soon a diagnosed individual may require insulin treatment. Finally, the paper highlights ongoing challenges in optimizing screening for wider application and the complexities of integrating research-based screening into routine clinical practice.

Indexed as

Diabetes Mellitus, Type 1Mass ScreeningAutoantibodiesDisease ProgressionEarly DiagnosisHumansPractice Guidelines as TopicRisk FactorsAutoantibodiescohort studycost‐effectivenesspopulation studyprimary caretype 1 diabetes

Identifiers

PMID40134221
PMCPMC12312825

What Socratic holds

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LicenceCC BY
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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.