Evidence map›Paper›PMID 36759347›Full record

ArticleDiabetologia2023

Islet Autoantibody Standardization Program: interlaboratory comparison of insulin autoantibody assay performance in 2018 and 2020 workshops.

Ilaria Marzinotto, David L Pittman, Alistair J K Williams, Anna E Long, Peter Achenbach, Michael Schlosser, Beena Akolkar, William E Winter, Vito Lampasona, participating laboratories

Open access · hybridFull text read
In one paragraph

Article in Diabetologia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 2 pooled it
15.3field-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

41 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.

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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

10 authors at 7 institutions in 4 countries.

Ilaria MarzinottoSan Raffaele Diabetes Research Institute, San Raffaele Scientific Institute, Milan, Italy.ORCID https://orcid.org/0000-0002-4765-4509
David L PittmanDepartment of Pathology, University of Florida, Gainesville, FL, USA.
Alistair J K WilliamsDiabetes and Metabolism, Translational Health Sciences, University of Bristol, Bristol, UK.
Anna E LongDiabetes and Metabolism, Translational Health Sciences, University of Bristol, Bristol, UK.ORCID https://orcid.org/0000-0002-6847-2771
Peter AchenbachInstitute of Diabetes Research, Helmholtz Munich, German Research Center for Environmental Health, Neuherberg, Germany. peter.achenbach@helmholtz-muenchen.de.ORCID https://orcid.org/0000-0001-6720-2684
Michael SchlosserDepartment of General Surgery, Visceral, Thoracic and Vascular Surgery, University Medical Center Greifswald, Greifswald, Germany.
Beena AkolkarDivision of Diabetes, Endocrinology, and Metabolic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA.ORCID https://orcid.org/0000-0002-2351-5942
William E WinterDepartment of Pathology, University of Florida, Gainesville, FL, USA.
Vito LampasonaSan Raffaele Diabetes Research Institute, San Raffaele Scientific Institute, Milan, Italy. lampasona.vito@hsr.it.ORCID http://orcid.org/0000-0001-5162-8445
participating laboratories
University of Bristol · GBUniversity of Florida · USHelmholtz Zentrum München · DENational Institute of Diabetes and Digestive and Kidney Diseases · USSan Raffaele University of Rome · ITUniversitätsmedizin Greifswald · DEVita-Salute San Raffaele University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisThe Islet Autoantibody Standardization Program (IASP) aims to improve the performance of immunoassays measuring autoantibodies in type 1 diabetes and the concordance of results across laboratories. IASP organises international workshops distributing anonymised serum samples to participating laboratories and centralises the collection and analysis of results. In this report, we describe the results of assays measuring IAA submitted to the IASP 2018 and 2020 workshops.

methodsThe IASP distributed uniquely coded sera from individuals with new-onset type 1 diabetes, multiple islet autoantibody-positive individuals, and diabetes-free blood donors in both 2018 and 2020. Serial dilutions of the anti-insulin mouse monoclonal antibody HUI-018 were also included. Sensitivity, specificity, area under the receiver operating characteristic curve (ROC-AUC), partial ROC-AUC at 95% specificity (pAUC95) and concordance of qualitative/quantitative results were compared across assays.

resultsResults from 45 IAA assays of seven different formats and from 37 IAA assays of six different formats were submitted to the IASP in 2018 and 2020, respectively. The median ROC-AUC was 0.736 (IQR 0.617-0.803) and 0.790 (IQR 0.730-0.836), while the median pAUC95 was 0.016 (IQR 0.004-0.021) and 0.023 (IQR 0.014-0.026) in the 2018 and 2020 workshops, respectively. Assays largely differed in AUC (IASP 2018 range 0.232-0.874; IASP 2020 range 0.379-0.924) and pAUC95 (IASP 2018 and IASP 2020 range 0-0.032). CONCLUSIONS/

interpretationAssay formats submitted to this study showed heterogeneous performance. Despite the high variability across laboratories, the in-house radiobinding assay (RBA) remains the gold standard for IAA measurement. However, novel non-radioactive IAA immunoassays showed a good performance and, if further improved, might be considered valid alternatives to RBAs.

Indexed as

AutoantibodiesDiabetes Mellitus, Type 1AnimalsGlutamate DecarboxylaseInsulin AntibodiesMiceReference StandardsROC CurveSensitivity and SpecificityAutoantibodiesGlutamate DecarboxylaseInsulin AntibodiesAutoantibodiesIAAIASP interlaboratory comparison studySensitivitySpecificityType 1 diabetes

Identifiers

PMID36759347
PMCPMC10036445
OpenAlexW4319812499

What OpenQuestion holds

Textfull text, public
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 OpenQuestion graph.