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Updated: Oct 21, 2026
Dried Blood Spots - Preparing and Processing for Use in Immunoassays and in Molecular Techniques
Published on: March 13, 2015
Impact of dried blood spot diameter and transit time on analyte concentrations and cut-off classification in routine
Nick Flynn1, Sarah Hogg1, Stuart J Moat2,3
1Biochemical Genetics Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Objectives:
To assess the effect of dried blood spot (DBS) diameter and specimen transit time on newborn screening (NBS) analyte concentrations and classification against cut-off values (CoV) using routine NBS data.
Methods:
DBS size and quality were assessed using a validated computer vision algorithm. Ordinary least squares analysis assessed associations between differences in DBS diameter and differences in within-batch duplicate thyroid stimulating hormone (TSH, n=1,101) and immunoreactive trypsinogen (IRT, n=2,581) results, and between specimen transit time and initial TSH (n=175,774), IRT (n=225,602), amino acids and acylcarnitine (n=227,032) results. The impact of pre-analytical factors on classification against CoVs was modelled using routine NBS data (n=256,554).
Results:
Differences in DBS diameter were positively associated with percentage concentration differences for both TSH (3.03 % per mm, 95 % CI: 1.87-4.19) and IRT (3.05 % per mm, 95 % CI: 1.96-4.15). Methionine and TSH decreased by 3.79 % (95 % CI: 3.67-3.91) and 2.53 % (95 % CI: 2.24-2.82) respectively, per additional day in transit. Methionine instability showed seasonal variation, with greater declines during wetter months. DBS diameter and transit time were estimated to influence classification against CoVs in 636 (95 % CI: 507-843) UK results annually. Reclassification risk increased for DBS specimens outside the recommended diameter range (8-14 mm; IRT risk ratio: 3.7, 95 % CI: 1.8-7.5) and for transit times ≥7 days (methionine risk ratio 48.6, 95 % CI: 16.9-139.8).
Conclusions:
DBS size and transit time affect analyte concentrations and classification against screening CoVs. Pre-analytical quality should be optimised to reduce its impact on NBS result classification.
