Evidence map›Paper›PMID 38608567›Full record

ArticleDiabetes & metabolic syndrome2024

Incorporating polygenic risk into the Leicester Risk Assessment score for 10-year risk prediction of type 2 diabetes.

Xiaonan Liu, Thomas J Littlejohns, Jelena Bešević, Fiona Bragg, Lei Clifton, Jennifer A Collister, Eirini Trichia, Laura J Gray, Kamlesh Khunti, David J Hunter

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetes & metabolic syndrome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

10 authors at 3 institutions in 2 countries.

Xiaonan LiuNuffield Department of Population Health, University of Oxford, Oxford, UK.
Thomas J LittlejohnsNuffield Department of Population Health, University of Oxford, Oxford, UK. Electronic address: thomas.littlejohns@ndph.ox.ac.uk.
Jelena BeševićNuffield Department of Population Health, University of Oxford, Oxford, UK.
Fiona BraggNuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Lei CliftonNuffield Department of Population Health, University of Oxford, Oxford, UK.
Jennifer A CollisterNuffield Department of Population Health, University of Oxford, Oxford, UK.
Eirini TrichiaNuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Laura J GrayDepartment of Population Health Sciences, University of Leicester, UK.
Kamlesh KhuntiDiabetes Research Centre, University of Leicester, Leicester, UK.
David J HunterNuffield Department of Population Health, University of Oxford, Oxford, UK; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA.
University of Oxford · GBUniversity of Leicester · GBHarvard University · US

Funding

Medical Research Council MC_PC_20029Medical Research Council MC_PC_20058
6 · The paper itself

Abstract

aimsWe evaluated whether incorporating information on ethnic background and polygenic risk enhanced the Leicester Risk Assessment (LRA) score for predicting 10-year risk of type 2 diabetes.

methodsThe sample included 202,529 UK Biobank participants aged 40-69 years. We computed the LRA score, and developed two new risk scores using training data (80% sample): LRArev, which incorporated additional information on ethnic background, and LRAprs, which incorporated polygenic risk for type 2 diabetes. We assessed discriminative and reclassification performance in a test set (20% sample). Type 2 diabetes was ascertained using primary care, hospital inpatient and death registry records.

resultsOver 10 years, 7,476 participants developed type 2 diabetes. The Harrell's C indexes were 0.796 (95% Confidence Interval [CI] 0.785, 0.806), 0.802 (95% CI 0.792, 0.813), and 0.829 (95% CI 0.820, 0.839) for the LRA, LRArev and LRAprs scores, respectively. The LRAprs score significantly improved the overall reclassification compared to the LRA (net reclassification index [NRI] = 0.033, 95% CI 0.015, 0.049) and LRArev (NRI = 0.040, 95% CI 0.024, 0.055) scores.

conclusionsPolygenic risk moderately improved the performance of the existing LRA score for 10-year risk prediction of type 2 diabetes.

Indexed as

Diabetes Mellitus, Type 2AdultAgedFemaleFollow-Up StudiesGenetic Predisposition to DiseaseHumansMaleMiddle AgedMultifactorial InheritancePrognosisRisk AssessmentRisk FactorsLeicester Risk AssessmentPolygenic risk scoreRisk predictionType 2 diabetesUK Biobank

Identifiers

PMID38608567
PMCPMC11913737
OpenAlexW4393321427

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.