Abstract
BackgroundDried blood spot (DBS) microsampling has gained interest in different clinical fields, owing to its many advantages compared to conventional blood sampling. However, whilst being applied for decades for screening purposes, some challenges, such as the hematocrit (Hct) effect, hinder further widespread use of DBS for quantitative purposes in clinical practice. Amongst the approaches that were developed to cope with this issue, is the Hct prediction of DBS using near-infrared (NIR) spectroscopy. MethodsUsing left-over EDTA-anticoagulated patient samples, the accuracy and precision, stability, and robustness were assessed. Furthermore, applicability of the method on capillary DBS was evaluated via finger prick samples. ResultsA maximal bias, respectively CV, of 0.012 L/L and 4.5% were obtained. The method was robust towards several aspects, including storage (except for storage at 60°C), measurement location, type of filter paper and spotted volume. Furthermore, the potential to predict the Hct of capillary DBS was demonstrated. ConclusionA commercially available NIR set-up was extensively and successfully validated, allowing non-contact Hct prediction of DBS with excellent accuracy and precision. This allows to correct for the Hct-based bias observed in partial-punch DBS analysis and the set-up of blood-plasma conversion factors, increasing the application potential of patient-centric sampling.
Highlights
IntroductionIn particular in therapeutic drug monitoring (TDM), the interest in dried blood sampling keeps growing
In different clinical fields, and in particular in therapeutic drug monitoring (TDM), the interest in dried blood sampling keeps growing
For the former, the most important consequence is the differential area over which a drop of blood of the same volume spreads depending on the Hct, thereby possibly affecting analytical results when sub-punches of the DBS are Abbreviations: CV, Coefficient of variation; DBS, Dried blood spot(s); FT, Freeze-thaw; Hct, Hematocrit; HIL-index, Hemolytic/icteric/lipemic index; ISR, Incurred sample reanalysis; limits of agreement (LoA), Limit(s) of agreement; NIR, Near-infrared spectroscopy; PC, Principal component; partial least squares (PLS), Partial least squares; room temperature (RT), Room temperature; TDM, Therapeutic drug monitoring; ultraviolet–visible spectroscopy (UV/Vis), Ultraviolet–visible
Summary
In particular in therapeutic drug monitoring (TDM), the interest in dried blood sampling keeps growing. Amongst the main challenges associated with DBS sampling for quan titative purposes is the so-called hematocrit (Hct) effect [3], which has an analytical and a physiological aspect [4] For the former, the most important consequence is the differential area over which a drop of blood of the same volume spreads depending on the Hct, thereby possibly affecting analytical results when sub-punches of the DBS are Abbreviations: CV, Coefficient of variation; DBS, Dried blood spot(s); FT, Freeze-thaw; Hct, Hematocrit; HIL-index, Hemolytic/icteric/lipemic index; ISR, Incurred sample reanalysis; LoA, Limit(s) of agreement; NIR, Near-infrared spectroscopy; PC, Principal component; PLS, Partial least squares; RT, Room temperature; TDM, Therapeutic drug monitoring; UV/Vis, Ultraviolet–visible. Conclusion: A commercially available NIR set-up was extensively and successfully validated, allowing noncontact Hct prediction of DBS with excellent accuracy and precision This allows to correct for the Hct-based bias observed in partial-punch DBS analysis and the set-up of blood-plasma conversion factors, increasing the application potential of patient-centric sampling
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