The NAples Pediatric Food Allergy (NAPFA) SCORE: a multivariable model for the prediction of food allergy in children

Background: Food allergy (FA) is one of the most common chronic conditions in children. Diagnostic delays and errors in FA are relevant problems in clinical practice.Non-invasive and accessible tools for FA diagnosis are highly required. We aimed todevelop an easy-to-use clinical score to facilitate the diagnostic approach for pediatricFA (i.e. the NAPFA score).Methods: Subjects with suspected FA aged 0–14 years were prospectively evaluatedat a tertiary center for pediatric allergy, gastroenterology, and nutrition.Upon completing the diagnostic workup, the subjects were diagnosed with FA basedon the oral food challenge result, or with other conditions. Bootstrapped multivaria-ble logistic regression was employed to construct two models that estimate the prob-ability of having FA, one (M1) without the results of the allergy screening tests, whilethe other (M2) including them.Results: Six hundred and twenty-seven pediatric subjects were included in the study.The median (interquartile interval) age at symptom onset was 8 (3;27) months. M1employed the following predictors: sex, age at symptoms onset, cesarean delivery,occurrence of atopic dermatitis before FA onset, first degree family members with al-lergy, symptoms occurrence after ingestion of specific food, and skin, gastrointestinal,respiratory, and systemic symptoms. M2 replaced the occurrence of symptoms afteringestion of specific food with the results of allergy tests. The c-statistic was 0.915(95% bootstrapped CI: 0.895–0.937) for M1 and 0.977 (95% CI: 0.969–0.992) for M2.Both models demonstrated good internal calibration and a favorable decision analysiscurve.