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Titel:

Exploring the incremental utility of circulating biomarkers for robust risk prediction of incident atrial fibrillation in European cohorts using regressions and modern machine learning methods.

Dokumenttyp:
Article; Journal Article
Autor(en):
Toprak, Betül; Brandt, Stephanie; Brederecke, Jan; Gianfagna, Francesco; Vishram-Nielsen, Julie K K; Ojeda, Francisco M; Costanzo, Simona; Börschel, Christin S; Söderberg, Stefan; Katsoularis, Ioannis; Camen, Stephan; Vartiainen, Erkki; Donati, Maria Benedetta; Kontto, Jukka; Bobak, Martin; Mathiesen, Ellisiv B; Linneberg, Allan; Koenig, Wolfgang; Løchen, Maja-Lisa; Di Castelnuovo, Augusto; Blankenberg, Stefan; de Gaetano, Giovanni; Kuulasmaa, Kari; Salomaa, Veikko; Iacoviello, Licia; Niiranen,...     »
Abstract:
AIMS: To identify robust circulating predictors for incident atrial fibrillation (AF) using classical regressions and machine learning (ML) techniques within a broad spectrum of candidate variables. METHODS AND RESULTS: In pooled European community cohorts (n = 42 280 individuals), 14 routinely available biomarkers mirroring distinct pathophysiological pathways including lipids, inflammation, renal, and myocardium-specific markers (N-terminal pro B-type natriuretic peptide [NT-proBNP], high-sensitivity troponin I [hsTnI]) were examined in relation to incident AF using Cox regressions and distinct ML methods. Of 42 280 individuals (21 843 women [51.7%]; median [interquartile range, IQR] age, 52.2 [42.7, 62.0] years), 1496 (3.5%) developed AF during a median follow-up time of 5.7 years. In multivariable-adjusted Cox-regression analysis, NT-proBNP was the strongest circulating predictor of incident AF [hazard ratio (HR) per standard deviation (SD), 1.93 (95% CI, 1.82-2.04); P < 0.001]. Further, hsTnI [HR per SD, 1.18 (95% CI, 1.13-1.22); P < 0.001], cystatin C [HR per SD, 1.16 (95% CI, 1.10-1.23); P < 0.001], and C-reactive protein [HR per SD, 1.08 (95% CI, 1.02-1.14); P = 0.012] correlated positively with incident AF. Applying various ML techniques, a high inter-method consistency of selected candidate variables was observed. NT-proBNP was identified as the blood-based marker with the highest predictive value for incident AF. Relevant clinical predictors were age, the use of antihypertensive medication, and body mass index. CONCLUSION: Using different variable selection procedures including ML methods, NT-proBNP consistently remained the strongest blood-based predictor of incident AF and ranked before classical cardiovascular risk factors. The clinical benefit of these findings for identifying at-risk individuals for targeted AF screening needs to be elucidated and tested prospectively.
Zeitschriftentitel:
Europace
Jahr:
2023
Band / Volume:
25
Heft / Issue:
3
Seitenangaben Beitrag:
812-819
Volltext / DOI:
doi:10.1093/europace/euac260
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/36610061
Print-ISSN:
1099-5129
TUM Einrichtung:
273; Klinik für Herz- und Kreislauferkrankungen im Erwachsenenalter (DHM) (Prof. Schunkert)
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