Evidence map›Paper›PMID 20693189›Full record

ArticleClinical trials (London, England)2010

Measurement of islet cell antibodies in the Type 1 Diabetes Genetics Consortium: efforts to harmonize procedures among the laboratories.

Polly J Bingley, Alistair J K Williams, Peter G Colman, Shane A Gellert, George Eisenbarth, Liping Yu, Letitia H Perdue, June J Pierce, Joan E Hilner, Concepcion Nierras and 3 more

Abstract readComparative Study
In one paragraph

Article in Clinical trials (London, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

  1. Established and emerging biomarkers for the prediction of type 1 diabetes: a systematic review.Translational research : the journal of laboratory and clinical medicine · 2014
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Alternate Ways to Quantify Antibodies.Diabetes technology & therapeutics · 2015
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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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

13 authors.

Polly J BingleyDepartment of Clinical Science at North Bristol, University of Bristol, Bristol, UK.
Alistair J K Williams
Peter G Colman
Shane A Gellert
George Eisenbarth
Liping Yu
Letitia H Perdue
June J Pierce
Joan E Hilner
Concepcion Nierras
Beena Akolkar
Michael W Steffes
T1DGC

Funding

Type 1 Diabetes Genetics ConsortiumU01DK062418 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI RICH, STEPHEN S. · 2002 to 2007
$59.8M
NIDDK NIH HHS U01 DK062418
6 · The paper itself

Abstract

backgroundand PURPOSE: Three network laboratories measured antibodies to islet autoantigens. Antibodies to glutamic acid decarboxylase (GAD65 [GADA]) and the intracellular portion of protein tyrosine phosphatase (IA-2(ic) [IA-2A]) were measured by similar, but not identical, methods in samples from participants in the Type 1 Diabetes Genetics Consortium (T1DGC).

methodsAll laboratories used radiobinding assays to detect antibodies to in vitro transcribed and translated antigen, but with different local standards, calibrated against the World Health Organization (WHO) reference reagent. Using a common method to calculate WHO units/mL, we compared results reported on samples included in the Diabetes Autoantibody Standardization Program (DASP), and developed standard methods for reporting in WHO units/mL. We evaluated intra-assay and inter-assay coefficient of variation (CV) in blind duplicate samples and assay comparability in four DASP workshops.

resultsValues were linearly related in the three laboratories for both GADA and IA-2A, and intra-assay technical errors for values within the standard curve were below 13% for GADA and below 8.5% for IA-2A. Correlations in samples tested 1-2 years apart were >97%. Over the course of the study, internal CVs were 10-20% with one exception, and the laboratories concordantly called samples GADA or IA-2A positive or negative in 96.7% and 99.6% of duplicates within the standard curve. Despite acceptable CVs and general concordance in ranking samples, the laboratories differed markedly in absolute values for GADA and IA-2A reported in WHO units/mL in DASP over a large range of values. LIMITATIONS: With three laboratories using different assay methods (including calibrators), consistent values among them could not be attained.

conclusionsModifications in the assays are needed to improve comparability of results expressed as WHO units/mL across laboratories. It will be essential to retain high intra- and inter-assay precision, sensitivity and specificity and to confirm the accuracy of harmonized methods.

Indexed as

AntibodiesAutoantigensClinical Laboratory TechniquesData CollectionDiabetes Mellitus, Type 1EducationGlobal HealthHumansInternationalityIslets of LangerhansQuality ControlROC CurveStatistics as TopicAntibodiesAutoantigens

Identifiers

PMID20693189
PMCPMC2917851

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Registered trials

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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.