Effects of spot size on biomarker levels of field-collected dried blood spots: A new algorithm for exact dried blood spot size measurement

Abstract

Objectives: The quality of blood values analyzed from survey-collected dried blood spot (DBS) samples is affected by fieldwork conditions, particularly spot size. We offer an image-based algorithm that accurately measures the area of field-collected DBS and we investigate the impact of spot size on the analyzed blood marker values. Methods: SHARE, a pan-European study, collected 24 000 DBS samples in 12 countries in its sixth wave. Our new algorithm uses photographs of the DBS samples to calculate the number of pixels of the blood-covered area to measure the spot sizes accurately. We ran regression models to examine the association of spot size and seven DBS analytes. We then compared the application of our new spot-size measures to common spot-size estimation. Results: Using automated spot-size measurement, we found that spot size has a significant effect on all markers. Smaller spots are associated with lower measured levels, except for HbA1c, for which we observe a negative effect. Our precisely measured spot sizes explain substantially more variance of DBS analytes compared to commonly used spot-size estimation. Conclusion: The new algorithm accurately measures the size of field-collected DBS in an automated way. This methodology can be applied to surveys even with very large numbers of observations. The measured spot sizes improve the accuracy of conversion formulae that translate blood marker values derived from DBS into venous blood values. The significance of the spot-size effects on biomarkers in DBS should also incentivize the improvement of fieldwork training and monitoring.