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WFRF:(De Koning Tom J.)
 

Sökning: WFRF:(De Koning Tom J.) > Development and Val...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00004096naa a2200385 4500
001oai:lup.lub.lu.se:0f746758-e7f3-4a27-949b-7564be025626
003SwePub
008220103s2021 | |||||||||||000 ||eng|
0247 a https://lup.lub.lu.se/record/0f746758-e7f3-4a27-949b-7564be0256262 URI
0247 a https://doi.org/10.3390/jpm111213222 DOI
040 a (SwePub)lu
041 a engb eng
042 9 SwePub
072 7a art2 swepub-publicationtype
072 7a ref2 swepub-contenttype
1001 a Castela Forte, Joséu University of Groningen,Ancora Health B.V.4 aut
2451 0a Development and Validation of Decision Rules Models to Stratify Coronary Artery Disease, Diabetes, and Hypertension Risk in Preventive Care : Cohort Study of Returning UK Biobank Participants
264 c 2021-12-07
264 1b MDPI AG,c 2021
520 a Many predictive models exist that predict risk of common cardiometabolic conditions. However, a vast majority of these models do not include genetic risk scores and do not distinguish between clinical risk requiring medical or pharmacological interventions and pre-clinical risk, where lifestyle interventions could be first-choice therapy. In this study, we developed, validated, and compared the performance of three decision rule algorithms including biomarkers, physical measurements, and genetic risk scores for incident coronary artery disease (CAD), diabetes (T2D), and hypertension against commonly used clinical risk scores in 60,782 UK Biobank participants. The rules models were tested for an association with incident CAD, T2D, and hypertension, and hazard ratios (with 95% confidence interval) were calculated from survival models. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), and Net Reclassification Index (NRI). The higher risk group in the decision rules model had a 40-, 40.9-, and 21.6-fold increased risk of CAD, T2D, and hypertension, respectively (p < 0.001 for all). Risk increased significantly between the three strata for all three conditions (p < 0.05). Based on genetic risk alone, we identified not only a high-risk group, but also a group at elevated risk for all health conditions. These decision rule models comprising blood biomarkers, physical measurements, and polygenic risk scores moderately improve commonly used clinical risk scores at identifying individuals likely to benefit from lifestyle intervention for three of the most common lifestyle-related chronic health conditions. Their utility as part of digital data or digital therapeutics platforms to support the implementation of lifestyle interventions in preventive and primary care should be further validated.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Endokrinologi och diabetes0 (SwePub)302052 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Endocrinology and Diabetes0 (SwePub)302052 hsv//eng
7001 a Folkertsma, Pytriku Ancora Health B.V.,University of Groningen4 aut
7001 a Gannamani, Rahulu University of Groningen,Ancora Health B.V.4 aut
7001 a Kumaraswamy, Sridharu Ancora Health B.V.4 aut
7001 a Mount, Sarahu Ancora Health B.V.4 aut
7001 a de Koning, Tom Ju Lund University,Lunds universitet,Pediatrik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Paediatrics (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,University of Groningen4 aut0 (Swepub:lu)to2856jd
7001 a van Dam, Sipkou Ancora Health B.V.,University of Groningen4 aut
7001 a Wolffenbuttel, Bruce H Ru University of Groningen4 aut
7102 a University of Groningenb Ancora Health B.V.4 org
7730 t Journal of Personalized Medicined : MDPI AGg 11:12q 11:12x 2075-4426
8564 u http://dx.doi.org/10.3390/jpm11121322x freey FULLTEXT
8564 u https://pure.rug.nl/ws/files/200131338/jpm_11_01322_v2.pdf
8564 8u https://lup.lub.lu.se/record/0f746758-e7f3-4a27-949b-7564be025626
8564 8u https://doi.org/10.3390/jpm11121322

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