Real‐World Evaluation of AI‐Assisted Readout of Skin Prick Automated Test Results
(2026) Allergy — Vol. 81, n° 8, p. 3001-3003 (2026)
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Van Waterschoot, Julie 
- Abstract
- To the Editor, Allergy diagnostics has taken an innovative turn with the introduction of the skin prick automated test (SPAT) [1, 2]. For respiratory allergy, skin prick testing (SPT) and serum specific IgE (sIgE) measurement are the gold standard methods to detect IgE-mediated sensitisation [3]. Despite its high sensitivity, manual SPT is subject to operator-dependent variability and prone to human errors. SPAT addresses these issues by standardizing the entire procedure, applying a fixed amount of allergen and a controlled prick force, in combination with AI-assisted readout to improve efficiency [1]. Previous research has demonstrated that SPAT, compared to manual SPT, shows lower intra-subject variability [1], higher consistency, and reduced patient discomfort [4]. When applying the validated 4.5-mm cutoff , SPAT shows equivalent diagnostic accuracy in detecting birch pollen and house dust mite allergies [2]. More recently, AI has been integrated into SPAT to provide wheal measurement suggestions, further increasing standardization and efficiency. Seys et al. described how the AI algorithm was trained (n = 651), validated (n = 217), and independently tested (n = 95) [5]. A strong correlation was observed between the physician-measured and the AI-measured longest wheal diameter (Pearson r = 0.83; p < 0.0001), with 5.8% of AI measurements adjusted by physicians, resulting in a change in test interpretation in 0.5% of cases. To evaluate external validity in clinical practice, real-world SPAT data from 37 hospitals across 5 European countries were assessed. This cohort comprises test results from 10,756 patients (126,526 pricks) with respiratory (96.7%), food (3.3%), insect venom (0.06%) and drug (0.01%) allergens. AI-measured longest wheal diameters were compared with physician-verified AI measurements, confirming a strong correlation (Pearson r = 0.96, p < 0.0001; Figure 1). No wheal was detected by AI in 7.9% (10,031) of pricks, with only 0.3% (380) of pricks corresponding to a physician measurement of ≥ 4.5 mm. In total, 6.1% of the wheals were enlarged by the physician (median (IQR): +1.0 mm (+0.5; +1.6)), and 2.9% reduced (median (IQR): −0.8 mm (−1.8; −0.4)), resulting in a change in test interpretation-from negative to positive or vice versa-in 1.7% and 0.4% of the cases, respectively. An analysis of potential confounders is provided in the Supporting Information (Table S3-S5 and Figure S3). This large real-world analysis demonstrates that the AI model is broadly generalizable and shows acceptable clinical performance. The low rate of interpretation-affecting adjustments is reassuring. The observed high correlation between AI and physician-verified AI measurements suggests that the AI model performs consistently across different hospitals. This is particularly relevant in comparison to manual SPT, where inter-and intra-observer variability has historically been a major limitation [6]. We observed that the total number of physician adjusted wheals (9.0%) in the current study was lower than the inter-observer readout variability (median: 19.8%) reported previously This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
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Citations
Van Waterschoot, J., Seys, S., Baron, I., Clement, G., Craps, J., Dieudonné, T., De Greve, G., De Medts, J., Friese, N., Hagemann, J., Hannachi, F., Happaerts, S., Hill, E., Hox, V., Lantsoght, B., Lemmens, W., Levie, P., Libeer, C., Mentens, Y., et al. (2026). Real‐World Evaluation of AI‐Assisted Readout of Skin Prick Automated Test Results. Allergy, 81(8), 3001-3003. https://doi.org/10.1111/all.70431 (Original work published 2026)