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Published on: September 22, 2020
Multiple biomarkers for mortality prediction in peripheral arterial disease
Stephen M Amrock1, Michael Weitzman2
1Department of Medicine, Oregon Health & Science University, Portland, OR, USA amrocks@ohsu.edu.
Abstract:
Few studies have assessed which biomarkers influence mortality risk among those with peripheral arterial disease (PAD). We analyzed data from 556 individuals identified to have PAD (i.e. ankle-brachial index ⩽ 0.9) with available measurements of C-reactive protein, the neutrophil-to-lymphocyte ratio (NLR), homocysteine, and the urinary albumin-to-creatinine ratio (UACR) in the 1999-2004 National Health and Nutrition Examination Survey. We investigated whether a combination of these biomarkers improved the prediction of all-cause and cardiovascular mortality beyond conventional risk factors. During follow-up (median, 8.1 years), 277 of 556 participants died; 63 deaths were attributed to cardiovascular disease. After adjusting for conventional risk factors, Cox proportional-hazards models showed the following to be most strongly associated with all-cause mortality (each is followed by the adjusted hazard ratio [HR] per 1 standard deviation increment in the log values): homocysteine (1.31), UACR (1.21), and NLR (1.20). UACR alone significantly predicted cardiovascular mortality (1.53). Persons in the highest quintile of multimarker scores derived from regression coefficients of significant biomarkers had elevated risks of all-cause mortality (adjusted HR, 2.45; 95% CI, 1.66-3.62; p for trend, <0.001) and cardiovascular mortality (adjusted HR, 2.20; 95% CI, 1.02-4.71; p for trend, 0.053) compared to those in the lowest two quintiles. The addition of continuous multimarker scores to conventional risk factors improved risk stratification of all-cause mortality (integrated discrimination improvement [IDI], 0.162; p<0.00001) and cardiovascular mortality (IDI, 0.058; p<0.00001). In conclusion, the addition of a continuous multimarker score to conventional risk factors improved mortality prediction among patients with PAD.
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