Cotinine as a marker for risk prediction in the Ludwigshafen Risk and Cardiovascular Health Study
Background: Cotinine is one of the major metabolites of nicotine. The aim our study was to investigate cotinine as a marker for individual risk prediction in the Ludwigshafen Risk and Cardiovascular Health study. Methods: 840 samples had detectable cotinine measured using a radioimmunoassay (RIA nic...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article (Journal) |
| Language: | English |
| Published: |
April 2015
|
| In: |
Respiratory physiology & neurobiology
Year: 2015, Volume: 209, Pages: 17-22 |
| ISSN: | 1878-1519 |
| DOI: | 10.1016/j.resp.2014.10.008 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1016/j.resp.2014.10.008 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S1569904814002808 
|
| Author Notes: | Graciela Delgado, Rüdiger Siekmeier, Bernhard K. Krämer, Winfried März, Marcus E. Kleber |
| Summary: | Background: Cotinine is one of the major metabolites of nicotine. The aim our study was to investigate cotinine as a marker for individual risk prediction in the Ludwigshafen Risk and Cardiovascular Health study. Methods: 840 samples had detectable cotinine measured using a radioimmunoassay (RIA nicotine metabolite, DPC Biermann GmbH). The distribution of risk factors across quartiles of cotinine or pack-years was analyzed by ANOVA and the association of cotinine and pack-years with mortality by Cox regression. Results: Cotinine and pack-years both showed significant association with mortality in adjusted models with HRs (95% CI) of 1.30 (1.17-1.44) and 1.26 (1.13-1.42) comparing the third to the first tertile for cotinine and pack-years, respectively. Either cotinine or pack-years or self-reported smoking increased the area-under-the-curve significantly as compared to a basic model including other risk factors. Discussion: Cotinine is a strong predictor of mortality in non-smokers as well as in smokers. As objectively measurable parameter cotinine would be preferable for risk prediction. |
|---|---|
| Item Description: | Gesehen am 25.01.2018 |
| Physical Description: | Online Resource |
| ISSN: | 1878-1519 |
| DOI: | 10.1016/j.resp.2014.10.008 |