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@ARTICLE{Xie:300252,
author = {R. Xie$^*$ and T. Vlaski$^*$ and K. Trares$^*$ and C.
Herder and B. Holleczek and H. Brenner$^*$ and B.
Schöttker$^*$},
title = {{L}arge-{S}cale {P}roteomics {I}mprove {R}isk {P}rediction
for {T}ype 2 {D}iabetes.},
journal = {Diabetes care},
volume = {48},
number = {6},
issn = {0149-5992},
address = {Alexandria, Va.},
publisher = {Assoc.},
reportid = {DKFZ-2025-00713},
pages = {922-926},
year = {2025},
note = {#EA:C070#LA:C070# / 2025 Jun 1;48(6):922-926},
abstract = {This study evaluated the incremental predictive value of
proteomic biomarkers in assessing 10-year type 2 diabetes
risk when added to the clinical Cambridge Diabetes Risk
Score (CDRS).Data from 21,898 UK Biobank participants were
used for model derivation and internal validation, and 4,454
Epidemiologische Studie zu Chancen der Verhütung,
Früherkennung und optimierten Therapie chronischer
Erkrankungen in der älteren Bevölkerung (ESTHER) cohort
(Germany) participants were used for external validation.
Proteomic profiling included the Olink Explore (2,085
proteins) and Olink Target 96 Inflammation panel (73
proteins).Adding 15 proteins from Olink Explore or 6
proteins from the Olink Inflammation panel improved the
C-index of the CDRS by 0.029 or 0.016 in internal validation
with net reclassification of $23.0\%$ and $29.0\%,$
respectively. External validation was only conducted for the
six-protein-extended model, and the C-index improved by
0.014.The Olink Explore-based 15-protein model enhanced the
CDRS model performance most, and this promising prediction
model should be externally validated. Our successful
external validation of the Olink Inflammation panel-based
six-protein model shows that this is a promising endeavor.},
cin = {C070},
ddc = {610},
cid = {I:(DE-He78)C070-20160331},
pnm = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
pid = {G:(DE-HGF)POF4-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:40178901},
doi = {10.2337/dc24-2478},
url = {https://inrepo02.dkfz.de/record/300252},
}