Objectives: SHARE, a pan-European panel study in 27 European countries and Israel, has collected dried blood spot (DBS) samples from approximately 27 000 respondents in 13 countries. We aim to obtain factors to convert analyte values between DBS and venous blood samples (VBS) taking account of adverse fieldwork conditions such as small spot size, high temperature and humidity, short drying time and long shipment times.Methods: We obtained VBS and DBS from a set of 20 donors in a laboratory setting, and treated the DBS in a systematic and controlled fashion simulating SHARE fieldwork conditions. We used the 3420 outcomes to estimate from DBS analyte values the values that we would have obtained had it been feasible to collect and analyze the donors' venous blood samples.Results: The influence of field conditions and sample quality on DBS analyte values is significant and differs among assays. Varying spot size is the main challenge and affects all markers except HbA1c. Smaller spots lead to overly high measured levels. A missing desiccant is detrimental for all markers except CRP and tHb. The temperature to which the samples are exposed plays a significant role for HDL and CysC, while too brief a drying time affects CRP and CysC. Lab-based adjustment formulae only accounting for the differences between re-liquefied DBS and venous blood do not address these fieldwork conditions.Conclusions: By simulating adverse fieldwork conditions in the lab, we were able to validate DBS collected under such conditions and established conversion formulae with high prediction accuracy.
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.
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