Abstract
Dried blood spot (DBS) methodology offers significant advantages over venipuncture in studies of vulnerable populations or large-scale studies, including reduced participant burden and higher response rates. Uncertainty about the validity of cardiovascular disease (CVD) risk biomarkers remains a barrier to wide-scale use. We determined the validity of DBS-derived biomarkers of CVD risk versus gold-standard assessments, and study-specific, serum-equivalency values for clinical relevance of DBS-derived values. Concurrent venipuncture serum and DBS samples (n = 150 adults) were assayed in Clinical Laboratory Improvement Amendments-certified and DBS laboratories, respectively. Time controls of DBS standard samples were assayed single-blind along with test samples. Linear regression analyses evaluated DBS-to-serum equivalency values; agreement and bias were assessed via Bland-Altman plots. Linear regressions of venipuncture values on DBS-to-serum equivalencies provided R2 values for total cholesterol, high-density lipoprotein cholesterol (HDL-C), and C-reactive protein (CRP) of 0.484, 0.118, and 0.666, respectively. Bland-Altman plots revealed minimal systematic bias between DBS-to-serum and venipuncture values; precision worsened at higher mean values of CRP. Time controls revealed little degradation or change in analyte values for HDL-C and CRP over 30 weeks. We concluded that DBS-assessed biomarkers represent a valid alternative to venipuncture assessments. Large studies using DBS should include study-specific serum-equivalency determinations to optimize individual-level sensitivity, the viability of detecting intervention effects, and generalizability in community-level primary prevention interventions.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 285-297 |
| Number of pages | 13 |
| Journal | Biodemography and Social Biology |
| Volume | 61 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jan 1 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Demography
- Ecology, Evolution, Behavior and Systematics
- Anthropology
- Genetics
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