Evidence map›Paper›PMID 22215562›Full record

ArticleEuropean journal of epidemiology2012

External validation of the KORA S4/F4 prediction models for the risk of developing type 2 diabetes in older adults: the PREVEND study.

Ali Abbasi, Eva Corpeleijn, Linda M Peelen, Ron T Gansevoort, Paul E de Jong, Rijk O B Gans, Wolfgang Rathmann, Bernd Kowall, Christine Meisinger, Hans L Hillege and 4 more

Abstract readValidation Study
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In one paragraph

Article in European journal of epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
  7. The Generation R Study: Biobank update 2015.European journal of epidemiology · 2014
    Article
  8. Review
  9. The Rotterdam Study: 2014 objectives and design update.European journal of epidemiology · 2013
    Article
  10. Article
  11. Article
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

14 authors.

Ali AbbasiDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. a.abbasi@epi.umcg.nl
Eva Corpeleijn
Linda M Peelen
Ron T Gansevoort
Paul E de Jong
Rijk O B Gans
Wolfgang Rathmann
Bernd Kowall
Christine Meisinger
Hans L Hillege
Ronald P Stolk
Gerjan Navis
Joline W J Beulens
Stephan J L Bakker

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, prediction models for type 2 diabetes mellitus (T2DM) in older adults (aged ≥55 year) were developed in the KORA S4/F4 study, Augsburg, Germany. We aimed to externally validate the KORA models in a Dutch population. We used data on both older adults (n = 2,050; aged ≥55 year) and total non-diabetic population (n = 6,317; aged 28-75 year) for this validation. We assessed performance of base model (model 1: age, sex, BMI, smoking, parental diabetes and hypertension) and two clinical models: model 1 plus fasting glucose (model 2); and model 2 plus uric acid (model 3). For 7-year risk of T2DM, we calculated C-statistic, Hosmer-Lemeshow χ(2)-statistic, and integrated discrimination improvement (IDI) as measures of discrimination, calibration and reclassification, respectively. After a median follow-up of 7.7 years, 199 (9.7%) and 374 (5.9%) incident cases of T2DM were ascertained in the older and total population, respectively. In the older adults, C-statistic was 0.66 for model 1. This was improved for model 2 and model 3 (C-statistic = 0.81) with significant IDI. In the total population, these respective C-statistics were 0.77, 0.85 and 0.85. All models showed poor calibration (P < 0.001). After adjustment for the intercept and slope of each model, we observed good calibration for most models in both older and total populations. We validated the KORA clinical models for prediction of T2DM in an older Dutch population, with discrimination similar to the development cohort. However, the models need to be corrected for intercept and slope to acquire good calibration for application in a different setting.

Indexed as

Decision Support TechniquesModels, BiologicalAdultAgedAge FactorsBiomarkersBlood GlucoseBody Mass IndexDiabetes Mellitus, Type 2FemaleFollow-Up StudiesHumansHypertensionIncidenceLogistic ModelsMaleBiomarkersBlood GlucoseUric Acid

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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.