Food allergy diagnosis remains challenging due to the difficulty of distinguishing true clinical allergy from asymptomatic sensitization. Inaccurate diagnosis may result in unnecessary dietary restrictions, reduced quality of life, or, conversely, failure to identify individuals at risk of severe allergic reactions. This review critically analyzes the efficacy, limitations, and clinical utility of currently available diagnostic tests for food allergy, with particular emphasis on their ability to predict true clinical reactivity. A comprehensive literature review was conducted to evaluate the sensitivity, specificity, and predictive values of both traditional and emerging diagnostic modalities. English-language guidelines, systematic reviews, and key clinical studies published primarily within the past 15 years (up to 2025) were identified through PubMed and Google Scholar. Classic diagnostic tools, including skin prick testing (SPT) and serum-specific IgE (sIgE), were assessed alongside novel approaches such as component-resolved diagnostics (CRD), basophil activation test (BAT), mast cell activation test (MAT), atopy patch testing (APT), cytokine profiling, and omics-based diagnostics. Particular attention was given to how these tests compare with the oral food challenge (OFC), which remains the diagnostic gold standard. The findings demonstrate that while conventional tests offer high sensitivity and are valuable for initial risk assessment, their limited specificity often leads to overdiagnosis. Emerging molecular and cellular assays show improved specificity and functional relevance, especially in complex cases involving polysensitization or unclear clinical histories and may reduce reliance on OFCs in the future. However, accessibility, cost, and lack of standardization currently limit their widespread clinical application. Advances in artificial intelligence and data integration hold promise for improving diagnostic accuracy through enhanced interpretation of complex immunological data. Based on the synthesized evidence, this review proposes an evidence-based, stepwise, and individualized diagnostic algorithm for food allergy. Integrating clinical history, targeted testing, and selective use of OFCs can improve diagnostic certainty, enhance food safety, minimize unnecessary dietary avoidance, and optimize patient outcomes. The review underscores the need for continued research, standardization, and validation of novel diagnostic tools to support personalized and precise food allergy management.
Napiorkowska-Baran et al. (Tue,) studied this question.