Diagnostic accuracy, risk assessment, and cost-effectiveness of component-resolved diagnostics for food allergy : A systematic review

REVIEW ARTICLE Diagnostic accuracy, risk assessment, and cost-effectiveness of component-resolved diagnostics for food allergy: A systematic review J. Flores Kim 1 | N. McCleary 1,2 | B. I. Nwaru 1,3,4,5 | A. Stoddart 1,6 | A. Sheikh 1 1 Asthma UK Centre for Applied Research, Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK 2 Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada 3 Krefting Research Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden 4 School of Health Sciences, University of Tampere, Tampere, Finland 5 Wallenberg Centre for Molecular and Translational Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden 6 Edinburgh Clinical Trials Unit, Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK Correspondence Javier Flores Kim, Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK. Email: [email protected] Funding information This work was funded by the Chief Scientist Office, Scotland (HIPS/16/42). BN was supported by a fellowship from the University of Tampere, Finland, with additional support from the Farr Institute and Asthma UK Centre for Applied Research. The funder had no role in the design of the study, the collection, analysis and interpretation of data, the writing of the report, or in the decision to submit the article for publication., Grant/Award Number: HIPS/16/42 Abstract Background: Component-resolved diagnostics (CRD) are promising tools for diagnosing food allergy, offering the potential to determine specific phenotypes and to develop patient-tailored risk profiles. Nevertheless, the diagnostic accuracy of these tests varies across studies; thus, their clinical utility remains unclear. Therefore, we synthesized the evidence from studies investigating the diagnostic accuracy, risk assessment ability, and cost-effectiveness of CRD for food allergy. Methods: We systematically searched 10 electronic databases and four clinical trial registries for studies published from January 2000 to February 2017. The quality of included studies was assessed using QUADAS-2. Due to heterogeneity, we narratively synthesized the evidence. Results: Eleven studies met inclusion criteria, altogether recruiting 1098 participants. The food allergies investigated were cow’s milk, hen’s egg, peanut, hazelnut, and shrimp. The components with the highest diagnostic accuracy for each allergen, along with their sensitivity-specificity pairs, were as follows: Bos d 4 for cow’s milk (62.0% and 87.5%), Gal d 1 for hen’s egg (84.2% and 89.8% for heated egg, and 60.6% and 97.1% for raw egg), Ara h 6 for peanut (94.9% and 95.1%), Cor a 14 for hazelnut (100% and 93.8%), and Lit v 1 for shrimp (82.8% and 56.3%) allergy. Conclusion: Selected components of cow’s milk, hen’s egg, peanut, hazelnut, and shrimp allergen showed high specificity, but lower sensitivity. However, few studies exist for each component, and studies vary widely regarding the cutoff values used, making it challenging to synthesize findings across studies. Further research is needed to determine clinically appropriate cutoff values, risk assessment abilities, and cost-effectiveness of CRD approaches. KEYWORDS component-resolved diagnostics, cost-effectiveness, diagnostic test accuracy systematic review, food allergy, risk assessment Abbreviations: aa, amino acid; APT, atopy patch test; CRD, component-resolved diagnostics; DBPCFC, double-blind, placebo-controlled food challenge; DTA, diagnostic test accuracy; HSROC, hierarchical summary receiver operating characteristic; IgE, immunoglobulin E; NPV, negative predictive value; PPV, positive predictive value; QUADAS-2, quality assessment of diagnostic accuracy studies-2; ROB, risk of bias; ROC, receiver operating characteristic; sIgE, specific immunoglobulin E; SPT, skin prick test. --------------------------------------------------------------------------------------------------------------------------------------------------------- This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. ©2018 The Authors. Allergy Published by John Wiley & Sons Ltd. Accepted: 22 December 2017 DOI: 10.1111/all.13399 Allergy. 2018;73:1609–1621. wileyonlinelibrary.com/journal/all | 1609 1 | INTRODUCTION The high prevalence of food allergy is now an emerging global public health concern. 1 Estimates of the prevalence of food allergy vary, but overall lifetime prevalence has been estimated to be between 4% and 7% for children and between 3% and 6% for adults in economically developed countries. 2,3 The quality of life of patients with food allergy is often severely affected, resulting in considerable morbidity and healthcare utilization, including risk of accidental exposure leading to life-threatening anaphylactic reactions. 4 An accurate diagnosis of food allergy is essential to provide appropriate, potentially life-saving advice on how to prevent and manage allergic reactions and prevent unnecessary dietary restrictions. 1,4 The diagnosis of food allergy is dependent on a thorough clinical history as well as an objective marker of allergic sensitization and, in some cases, oral food challenge tests. 5 Current first-line tests to assess allergen sensitization are skin prick tests (SPT) and/or immunoassays of serum food-specific IgE (sIgE) levels. However, these approaches have a high rate of false-positive results and are poor predictors of the severity of allergic reactions. 4 Thus, diagnostic confirmation with (ideally) a double-blinded placebo-controlled food challenge (DBPCFC) is often required. 5 While DBPCFCs are considered the gold standard diagnostic tests, they are costly, technically challenging, time-consuming, labor-intensive, and are associated with important safety risks, as they can trigger anaphylactic reactions. 4 Given the limitations of conventional methods for diagnosing food allergy, new molecular-based diagnostic techniques—collectively referred to as component-resolved diagnostics (CRD)—have emerged as promising diagnostic tools. 6 While current approaches evaluate patients’reactivity to whole food extracts, CRD involves detecting sIgE levels to individual allergenic molecules or the epitopes of those allergens. 7 This approach may enhance determination of specific food allergy phenotypes, assist in the development of patient-tailored risk profiles for specific food allergens, and improve detection of possible cases of cross-reactivity between different allergenic molecules. 8 Over the last decade, researchers have compared CRD to conventional diagnostic approaches for food allergy. 9 Through this work, the major allergen components in different food allergies have been identified. However, the diagnostic accuracy of identified components varies across studies, and thus, the diagnostic value and clinical utility of CRD remains unclear. 9,10 CRD approaches are also expensive, which raises questions about their cost-effectiveness. 11 While the diagnostic accuracy of various tests for food allergy was evaluated in our previous systematic review, CRD was not included. 12 A health technology assessment was carried out to evaluate multiplex CRD assays, but clinical effectiveness (rather than diagnostic accuracy) was investigated. 13 To the best of our knowledge, only one CRD-specific diagnostic test accuracy (DTA) review has been conducted, but it focused solely on peanut allergy diagnosis. 14 This review concluded that Ara h 2 showed superior diagnostic accuracy than SPT and sIgE tests, and therefore has the potential to replace first-line tests for the diagnosis of peanut allergy. Given the increasing body of work, there is a need to undertake a more comprehensive evidence synthesis on the diagnostic accuracy of CRD. We therefore conducted a systematic review to: (i) determine the accuracy of CRD for the diagnosis of food allergy, focusing on the “big eight”food allergies (ie, cow’s milk, wheat, hen’s egg, peanut, soy, tree nuts, fish, and shellfish allergy); (ii) estimate the effectiveness and cost-effectiveness of CRD in comparison with conventional techniques for the diagnosis of these food allergies; and (iii) summarize the evidence on the ability of CRD to predict the severity of allergic reactions. We focused on these eight food allergies to align with the foods considered in our previous systematic reviews for the European Academy of Allergy and Clinical Immunology. 2,12 2 | METHODS The Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) checklist guided the reporting of this systematic review (see Table S1). 15 Our protocol was published 16 and preregistered (PROSPERO:CRD42016053512). 2.1 | Eligibility criteria We included prospective, retrospective, cross-sectional, and case-control studies that examined the accuracy of CRD in diagnosing cow’s milk, hen’s egg, wheat, soybean, peanut, tree nuts, fish, or shellfish allergy in children or adults. Studies were required to have sufficient data to calculate the following four relevant diagnostic measures: sensitivity, specificity, positive predicted value (PPV), and negative predictive value (NPV). Additionally, all studies were required to have a defined study population with either consecutive or random sampling of participants. Studies in which the recruitment technique used to select participants was not indicated were included, and the lack of information regarding their sampling methodology was noted during the quality assessment process. The reference standard was DBPCFC used in at least 50% of the participants. 2.2 | Search strategy Although CRD methods were originally described in the 1990s, 17 their application to food allergy diagnosis was not clinically implemented until the 2000s. 1 Hence, we chose the beginning of 2000 as the starting time for the literature search. We searched the following databases from January 2000 to February 2017: AMED (Ovid), CAB Abstracts (Ovid), the Cochrane Library, CINAHL (EBSCO), EMBASE (Ovid), Global Health (Ovid), PsycINFO (Ovid), Web of Science Core Collection (Thomson Reuters), WHO’s Global Health Library and the Health Economic Evaluations Database. Our full search strategy is included in the online supplement (Table S2). We also contacted international experts who have published in the field, screened the references cited in identified studies, and used the citation-tracking feature of Google Scholar to find any additional studies. The list of contacted experts can be found in the online supplement (Table S3). 1610 | FLORES KIM ET AL. Additionally, the International Standard Randomized Controlled Trial Number (ISRCTN) Registry, ClinicalTrials.gov, the Australian and New Zealand Clinical Trials Registry, and WHO’s International Clinical Trials Registry Platform (ICTRP) were searched to identify relevant ongoing studies. No language restrictions were applied. 2.3 | Study selection and data collection Two reviewers (JFK and NM) independently screened titles and abstracts and then reviewed full-texts to identify eligible studies. Authors of studies for which further details were required to determine inclusion or exclusion were contacted to obtain further information to enable a decision. For papers in languages other than English, speakers of the language in question were contacted to determine eligibility. Both reviewers independently extracted data from included studies using a form developed specifically for this systematic review. Study characteristics, DTA measures (ie, sensitivity, specificity, PPV and NPV), and 2 92 contingency tables (reflecting the number of true positives, true negatives, false positives, and false negatives) were extracted. DTA measures and 95% confidence intervals were calculated from 2 92 contingency tables when not provided by authors. 18-20 The two reviewers assessed the quality of the included studies using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. 21 Discrepancies were resolved by discussion and consensus, or when necessary, arbitrated by a third reviewer (BN). 2.4 | Data synthesis, analysis, and reporting Diagnostic accuracy measures (sensitivity, specificity, PPV, and NPV) of individual studies were summarized in tables and presented by allergy type and individual allergen component. We had planned to conduct meta-analyses of the evidence with respect to each allergen component by fitting a bivariate model (when included studies used a common threshold) or a hierarchical summary receiver operating characteristic (HSROC) model (when included studies used multiple thresholds). However, we were unable to do this, as the number of studies for each component was too small to permit quantitative syntheses. In a simulated analysis based on the Bayesian approach, it was recommended that a minimum of four studies were required to reasonably fit these models. 22 In a very few cases, we had a maximum of three studies per allergen component; the most common was two studies. The statistical programs we tried to use to fit the models (R and Stata) indicated that the models lacked convergence, as a result of containing too few studies. For these reasons, we narratively synthesized the evidence. 3 | RESULTS 3.1 | Study selection A total of 10 380 articles were identified through the literature search carried out on June 15, 2016. After excluding duplicate articles, 6853 titles and abstracts were screened against the inclusion and exclusion criteria; of these, 195 full-text papers were assessed. Thirteen articles reporting 11 studies met our criteria and were thus included. 23-35 Additionally, one potentially relevant ongoing clinical trial was found in ClinicalTrials.gov (details can be found in Table S4). The literature search was updated on February 9, 2017, to incorporate newly published papers. No additional relevant studies were identified in the updated search. The study screening and selection processes are summarized in Figure 1. A list of potentially relevant studies can be found in the Online supplement (Tables S5 and S6). The authors of these studies did not reply to a request for further information. 3.2 | Characteristics of included studies Table 1 summarizes the main characteristics of the 11 studies included. The studies altogether recruited a total of 1098 participants. Nine studies were carried out in Western Europe, 23-28,30,32,33 and two multicenter studies analyzed data from multiple countries. 31,34 Two studies used a case-control design, 32,34 while nine were crosssectional studies. 23-28,30,31,33 Two of the cross-sectional studies used consecutive sampling to recruit participants, 26,28 while the sampling strategy used in the remaining seven cross-sectional studies was unclear. 23-25,27,30,31,33 Taking all studies together, 87% of participants underwent DBPCFC to verify their food allergy status. The included studies analyzed the diagnostic accuracy of CRD for the following types of food allergy: cow’s milk (n =2), 23,33 hen’s egg (n =3), 24,25,33 peanut (n =3), 28,30,31 hazelnut (n =2), 27,32 and shrimp (n =2). 26,34 No studies investigated the other allergies of interest (i.e, wheat, soybean, and fish). All but one study analyzed a single type of allergy; this study analyzed the diagnostic accuracy of CRD for both cow’s milk and hen’s egg. 33 Five studies used the ImmunoCAP test to measure sIgE levels, 23,25-27,31,32 three studies used microarray techniques (ISAC CRD 51, ISAC 103, and ISAC 112), 24,28,33 one study used a combination of ImmunoCAP and a microarray technique (ISAC 112), 30 and one study used an immunoblotting technique for sIgE detection. 34 Two studies additionally analyzed the DTA of individual component epitopes using immunoblotting techniques. 26,34 3.3 | Quality assessment of included studies Table 1 includes a summary of the QUADAS-2 quality assessment for each study. Table S7 in the supplementary information provides the detailed QUADAS-2 assessments. 3.3.1 | Patient selection Two studies were rated as high risk of bias (ROB) in this domain because of the use of a case-control design. 32,34 Eight other studies were found to have an unclear ROB, mainly because they did not explicitly indicate their sampling methodology and/or did not avoid inappropriate exclusions. 23-25,27,28,30,31,33 The remaining study had a low ROB. 26 FLORES KIM ET AL. | 1611 3.3.2 | Index test Two studies had high ROB in this domain because they did not use prespecified thresholds for determining positive results. 27,33 Eight studies had unclear ROB because they did not report whether index test results were interpreted without knowledge of DBPCFC results. 23-26,28,31,32,34 Only one study had low ROB in this domain. 30 Two studies used immunoblotting assays to analyze sIgE reactivity against allergens; because these assays do not provide quantitative sIgE levels, these two studies were scored as unsure in terms of their applicability to this review’s research question. 26,34 3.3.3 | Reference standard One study did not specify the criteria used to classify DBPCFC results and was thus scored as having an unclear ROB in this domain. 26 Two FIGURE 1 PRISMA Diagram for the literature search 1612 | FLORES KIM ET AL. TABLE 1 Main characteristics of included studies First author, year Country of origin Reference no. Study design Food allergy studied Population Sample size Components tested Index test Number of patients that underwent DBPCFC QUADAS-2 risk of bias domains 1, 2, 3, 4 applicability domains 1, 2, 3 Alessandri 2012a Italy 23 Cross-sectional Cow Milk Children with suspected cow’s milk allergy 66 Bos d 4, 5, and 8 ImmunoCAP 66 (100%) Alessandri 2012b Italy 24 Cross-sectional Hen’s Egg Children with suspected hen’s egg allergy 68 Gal d 1,2, 3, and 5 ISAC 103 68 (100%) Ando 2008 Japan 25 Cross-sectional Hen’s Egg Children with suspected hen’s egg allergy 108 Gal d 1, and 2 ImmunoCAP 108 (100%) Ayuso 2012 Spain 26 Cross-sectional Shrimp Patients with reported immediate shrimp-allergic reactions 37 Pen a 1; and Lit v 1, 2, 3, and 4 ImmunoCAP and Immunoblot 31 (83.8%) Brandstrom 2015 Sweden 27 Cross-sectional Hazelnut Children referred for oral challenge for hazelnut allergy suspicion 40 Cor a 1, 8, 9, and 14; and Bet v 1 ImmunoCAP 40 (100%) Klemans 2014 (& Klemans 2013) The Netherlands 28,29 Cross-sectional Peanut Adults who underwent a DBPCFC for peanut allergy suspicion 107 Ara h 2 and 6 ISAC 112 107 (100%) (Continues) FLORES KIM ET AL. | 1613 TABLE 1 (Continued) First author, year Country of origin Reference no. Study design Food allergy studied Population Sample size Components tested Index test Number of patients that underwent DBPCFC QUADAS-2 risk of bias domains 1, 2, 3, 4 applicability domains 1, 2, 3 Kukkonen 2015 Finland 30 Cross-sectional Peanut Children with suspected peanut allergy 102 Ara h 1, 2, 3, 6, 8, and 9 ImmunoCap and ISAC112 102 (100%) Lieberman 2013 USA and Sweden 31 Cross-sectional Peanut Children referred to an allergy center for evaluation of peanut allergy 167 Ara h 1, 2, 3, and 8 ImmunoCAP 119 (71.3%) Masthoff 2013 (& Masthoff 2015) The Netherlands 32,35 Case-Control Hazelnut Patients sensitized to hazelnut extract 161 Cor a 1, 8, 9, and 14; and Bet v 1 ImmunoCAP 137 (85.1%) Ott 2008 Germany 33 Cross-sectional Hen’s Egg and Cow’s Milk Children with suspected hen’s egg or cow’s milk allergy 130 Gal d 1, 2 and 4; Bos d 4, and 5, and Caseins ISAC version CRD 51 103 (71%) Pascal 2015 Brazil, Spain, and USA 34 Case-control Shrimp Patients sensitized to shrimp 103 Lit v 1, Lit v 2, Lit v 3, and Lit v 4 Immunoblot 78 (76%) 1614 | FLORES KIM ET AL. studies were scored as unsure in terms of their applicability to this review’s research question. 30,32 The reason for this appraisal was that the purpose of this review was to assess the accuracy of CRD and its ability to predict allergy severity (both of which are assessed through objective symptoms in a DBPCFC), and the two aforementioned studies included patients with mild or subjective DBPCFC symptoms in the same group as patients with negative DBPCFC. 3.3.4 | Patient flow and timing Two studies had a high ROB in this domain because less than 100% of patients underwent DBPCFCs, and not all patient data were included in their data analysis. 26,34 Three studies specified the time interval between index and reference tests, compared all patients against the same reference standard, included all patients in data analysis, and were thus ranked as low ROB in this domain. 24,25,27 The remaining six studies failed to meet at least one of those criteria and were thus scored as having an unclear ROB. 23,28,30-33 3.4 | Diagnostic accuracy of CRD DTA measures for all the 11 studies are presented in Table 2. The information in this table includes data points for all sIgE cutoff values that the included studies used to define test positivity, as some studies used multiple values. In the following narrative synthesis, we present the results of the diagnostic accuracy of all components per food allergy type for only cutoff values with the highest diagnostic potential as defined in each study. 3.4.1 | Cow’s milk allergy Two studies evaluated CRD for cow’s milk allergy, 23,33 and the following components were assessed: Bos d 4 (a-lactalbumin), Bos d 5 (b-lactoglobulin), Bos d 8 (caseins), and the caseins (a-, b-, and j-) separately. The reported sensitivity-specificity for these components were as follows: for Bos d 4, 62.0% and 87.5% (with a cutoff value defining a positive test of >0.01 kUa/L), 23 and 50.0% and 93.0% (at >0.1 FI) 33 ; for Bos d 5, 82.0% and 62.5% (at >0.35 kUa/L), 23 and 23.8% and 95.3% (at >0.1 FI) 33 ; for Bos d 8, 88.0% and 56.3% (at >0.35 kUa/L) 23 ; and the casein with the highest DTA was j-casein with a sensitivity-specificity pair of 38.1% and 88.4% (at >0.1 FI). 33 3.4.2 | Hen’s egg allergy Three studies evaluated CRD for hen’s egg allergy, 24,25,33 and the following components were assessed: Gal d 1 (ovomucoid), Gal d 2 (ovalbumin), Gal d 3 (ovotransferrin), and Gal d 4 (lysozyme). Two studies investigated heated egg and raw egg allergy separately, 24,25 while the third study analyzed only raw egg allergy. 33 For heated egg allergy, the reported sensitivity-specificity for these components were as follows: for Gal d 1, 84.2% and 89.8% (at >0.01 kUa/L), 24 and 76.3% and 81.4% (at >4.4 kUa/L) 25 ; for Gal d 2, 52.6% and 83.7% (at >0.01 kUa/ L), 24 and 73.7% and 72.9% (at >6.33 kUa/L); 25 and for Gal d 3, 21.1% and 93.9% (at >0.01 kUa/L). 24 For raw egg allergy, the reported sensitivity-specificity for these components were as follow: for Gal d 1, 60.6% and 97.1% (at >0.01 kUa/L), 24 73.1% and 82.9% (at >2.26 kUa/ L), 25 and 57.8% and 86.7% (at >0 FI) 33 ; for Gal d 2, 42.4% and 88.6% (at >0.01 kUa/L), 24 and 76.1% and 82.9% (at >3.88 kUa/L), 25 and 57.8% and 80.0% (at >0 FI) 33 ; for Gal d 3, 18.2% and 97.1% (at >0.01 kUa/L) 24 ; and for Gal d 4, 17.8% and 100% (at >0 FI). 33 3.4.3 | Peanut allergy Three studies evaluated the diagnostic accuracy of CRD for peanut allergy, 28,30,31 and the following components were assessed: Ara h 1 (cupin, a 7S globulin), Ara h 2 (conglutin, a 2S albumin), Ara 3 (cupin, a 11S globulin), Ara h 6 (conglutin, a 2S albumin), Ara h 8 (Bet v 1 homologue), and Ara h 9 (LTP). The reported sensitivity-specificity for these components were as follows: for Ara h 1, 56.6% and 86.9% (at >0.35 kUa/L), 31 and 60.7% and 95.1% (at >0.8 kUa/L) 30 ; for Ara h 2, 69.2% and 90.5% (at >0.3 ISU/L), 28 80.2% and 91.8% (at >0.35 kUa/L), 31 and 80.3% and 95.1% (at >1.8 kUa/L) 30 ; for Ara h 3, 48.1% and 90.2% (at >0.35 kUa/L), 31 and 55.7% and 95.1% (at >0.8 kUa/L) 30 ; for Ara h 6, 61.5% and 95.2% (at >1.0 ISU/L) 28 , and 94.9% and 95.1% (at >0.8 ISU) 30 ; for Ara h 8, 34.9% and 42.6% (at >0.35 kUa/L), 31 and 78.7% and 14.6% (at >0.35 kUa/L) 30 ; and for Ara h 9, 14.8% and 85.4% (at >0.35 kUa/L). 30 3.4.4 | Hazelnut allergy Two studies evaluated the diagnostic accuracy of CRD for hazelnut allergy, 27,32 and the following components were assessed: Cor a 1 (PR-10 protein), Cor a 8 (LTP), Cor a 9 (11S seed storage globulin), and Cor a 14 (2S albumin). Additionally, one of the studies investigated whether sensitization to the allergens Bet v 1 (PR-10 protein) and Bet v 2 (profilin) (from the European White Birch) could also predict hazelnut allergy. 32 The reported sensitivity-specificity for these components were as follows: for Cor a 1, 79.7% and 7.3% (at >0.35 kUa/L 32 ; for Cor a 8, 6.3% and 96.3% (at >0.35 kUa/L) 32 ; for Cor a 9, 100% and 71.9% (at >0.65 kUa/L), 27 and 54.4% and 97.6% (at >1 kUa/L) 32 ; for Cor a 14, 100% and 93.8% (at >0.64 kUa/L), 27 and 54.4% and 85.4% (at >0.35 kUa/L) 32 ; for Bet v 1, 81.0% and 7.3% (at 0.35 kUa/L) 32 ; and for Bet v 2, 10.1% and 81.7% (at 0.35 kUa/L). 32 3.4.5 | Shrimp allergy Two studies reported data on CRD for shrimp allergy. 26,34 One study tested the component Pen a 1 (tropomyosin) using the ImmunoCAP test, 26 and the other study investigated the components Lit v 1 (tropomyosin) and Lit v 4 (sarcoplasmic calcium-binding protein) through an immunoblotting technique. 34 Additionally, both studies investigated the diagnostic value of several individual epitopes in shrimp through an immunoblotting technique. The components (and their epitopes) tested in this manner were as follows: Lit v 1, Lit v 2 (arginine kinase), Lit v 3 (myosin light chain), and Lit v 4. The reported FLORES KIM ET AL. | 1615 TABLE 2 Summary DTA measures of CRD components tested by allergy type Food allergy Component Study Year Reference no. Country Index test Cutoff value Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) Cow’s milk Bos d 4 Alessandri 2012a 23 Italy ISAC 103 >0 (kUa/L) 56.0 (41.3-70.0) 87.5 (61.7-98.5) 93.3 (78.9-98.1) 38.9 (38.9-47.8) Cow’s milk Bos d 4 Alessandri 2012a 23 Italy ISAC 103 >0.01 (kUa/L) 62.0 (47.2-75.4) 87.5 (61.7-98.5) 93.9 (80.6-98.3) 42.4 (33.1-52.4) Cow’s milk Bos d 4 Ott 2008 33 Germany ISAC CRD51 >0.1 (FI) 50.0 (34.2-65.8) 93.0 (80.9-98.5) 87.5 (69.3-95.6) 65.6 (58.2-72.3) Cow’s milk Bos d 4 Alessandri 2012a 23 Italy ImmunoCAP >0.35 (kUa/L) 80.0 (66.3-90.0) 50.0 (24.7-75.4) 83.3 (75.0-89.3) 44.4 (27.6-62.6) Cow’s milk Bos d 4 Alessandri 2012a 23 Italy ImmunoCAP >1.02 (kUa/L) 58.0 (43.2-71.8) 81.3 (54.4-96.0) 90.6 (77.2-96.5) 38.2 (29.3-48.1) Cow’s milk Bos d 5 Alessandri 2012a 23 Italy ImmunoCAP >0 (kUa/L) 90.0 (78.2-96.7) 50.0 (24.7-75.4) 84.9 (77.4-90.3) 61.5 (37.9-80.8) Cow’s milk Bos d 5 Alessandri 2012a 23 Italy ISAC 103 >0 (kUa/L) 40.0 (26.4-54.8) 93.8 (69.8-99.8) 95.2 (74.4-99.3) 33.3 (27.8-39.3) Cow’s milk Bos d 5 Alessandri 2012a 23 Italy ISAC 103 >0.01 (kUa/L) 44.0 (30.0-58.8) 93.8 (69.8-99.8) 95.7 (76.3-99.3) 34.9 (28.9-41.4) Cow’s milk Bos d 5 Ott 2008 33 Germany ISAC CRD 51 >0.1 (FI) 23.8 (12.1-39.5) 95.3 (84.2-99.4) 83.3 (53.8-95.6) 56.2 (51.7-60.6) Cow’s milk Bos d 5 Alessandri 2012a 23 Italy ImmunoCAP >0.35 (kUa/L) 82.0 (68.6-91.4) 62.5 (35.4-84.8) 87.2 (78.2-92.9) 52.6 (35.5-69.2) Cow’s milk Bos d 8 Alessandri 2012a 23 Italy ISAC 103 >0 (kUa/L) 54.0 (39.3-68.2) 81.3 (54.4-96.0) 90.0 (75.9-96.3) 36.1 (27.9-45.3) Cow’s milk Bos d 8 Alessandri 2012a 23 Italy ISAC 103 >0.01 (kUa/L) 56.0 (41.3-70.0) 81.3 (54.4-96.0) 90.3 (76.6-96.4) 37.1 (28.6-46.6) Cow’s milk Bos d 8 Alessandri 2012a 23 Italy ImmunoCAP >0.35 (kUa/L) 88.0 (75.7-95.5) 56.3 (29.9-80.3) 86.3 (78.1-91.7) 60.0 (38.7-78.1) Cow’s milk Bos d 8 Alessandri 2012a 23 Italy ImmunoCAP >0.44 (kUa/L) 82.0 (68.6-91.4) 62.5 (35.4-84.8) 87.2 (78.2-92.9) 52.6 (35.5-69.2) Cow’s milk a-casein Ott 2008 33 Germany ISAC CRD 51 >0.1 (FI) 26.2 (13.9-42.0) 97.7 (87.7-99.9) 91.7 (59.8-98.8) 57.5 (52.9-62.0) Cow’s milk b-casein Ott 2008 33 Germany ISAC CRD 51 >0.1 (FI) 26.2 (13.9-42.0) 93.0 (80.9-98.5) 78.6 (52.4-92.4) 56.3 (51.4-61.1) Cow’s milk j-casein Ott 2008 33 Germany ISAC CRD 51 >0.1 (FI) 38.1 (23.6-54.4) 88.4 (74.9-96.1) 76.2 (56.3-88.8) 59.4 (53.0-65.5) Heated Hen’s Egg Gal d 1 Alessandri 2012b 24 Italy ISAC 103 >0.01 (kUa/L) 84.2 (60.4-96.6) 89.8 (77.8-96.6) 76.2 (57.7-88.3) 93.6 (83.8-97.7) Heated Hen’s Egg Gal d 1 Ando 2008 25 Japan ImmunoCAP >0.37 (kUa/L) 97.4 (86.2-99.9) 35.7 (24.6-48.1) 45.1 (40.7-49.7) 96.2 (77.9-99.4) Heated Hen’s Egg Gal d 1 Ando 2008 25 Japan ImmunoCAP >4.4 (kUa/L) 76.3 (59.8-88.6) 81.4 (70.3-89.8) 69.0 (57.0-79.0) 86.4 (78.0-91.9) Heated Hen’s Egg Gal d 2 Alessandri 2012b 24 Italy ISAC 103 >0.01 (kUa/L) 52.6 (28.9-75.6) 83.7 (70.3-92.7) 55.6 (36.8-72.9) 82.0 (73.6-88.1) Heated Hen’s Egg Gal d 2 Ando 2008 25 Japan ImmunoCAP >0.37 (kUa/L) 100.0 (90.8-100) 21.4 (12.5-32.9) 40.9 (37.9-43.9) 100.0 (NA) Heated Hen’s Egg Gal d 2 Ando 2008 25 Japan ImmunoCAP >6.33 (kUa/L) 73.7 (56.9-86.6) 72.9 (60.9-82.8) 59.6 (49.0-69.3) 83.6 (76.6-89.9) Heated Hen’s Egg Gal d 3 Alessandri 2012b 24 Italy ISAC 103 >0.01 (kUa/L) 21.1 (6.1-45.6) 93.9 (83.1-98.7) 57.1 (24.7-84.4) 75.4 (70.6-79.6) Raw Hen’s Egg Gal d 1 Ott 2008 33 Germany ISAC CRD 51 >0 (FI) 57.8 (42.2-72.3) 86.7 (59.5-98.3) 92.9 (77.7-98.0) 40.6 (31.6-50.4) Raw Hen’s Egg Gal d 1 Alessandri 2012b 24 Italy ISAC 103 >0.01 (kUa/L) 60.6 (42.1-77.1) 97.1 (85.1-99.9) 95.2 (74.0-99.3) 72.3 (63.1-80.0) Raw Hen’s Egg Gal d 1 Ando 2008 25 Japan ImmunoCAP >0.37 (kUa/L) 86.6 (76.0-93.7) 41.5 (26.3-57.9) 70.7 (64.8-76.1) 65.4 (48.2-79.3) Raw Hen’s Egg Gal d 1 Ando 2008 25 Japan ImmunoCAP >2.26 (kUa/L) 73.1 (60.9-83.2) 82.9 (67.9-92.9) 87.5 (77.8-93.3) 65.4 (55.4-74.2) Raw Hen’s Egg Gal d 2 Ott 2008 33 Germany ISAC CRD 51 >0 (FI) 57.8 (42.2-72.3) 80.0 (51.9-95.7) 89.7 (75.3-96.1) 38.7 (29.2-49.1) Raw Hen’s Egg Gal d 2 Alessandri 2012b 24 Italy ISAC 103 >0.01 (kUa/L) 42.4 (25.5-60.8) 88.6 (73.3-96.8) 77.8 (56.2-90.5) 62.0 (54.3-69.1) Raw Hen’s Egg Gal d 2 Ando 2008 25 Japan ImmunoCAP >0.37 (kUa/L) 97.0 (89.6-99.6) 31.7 (18.1-48.1) 69.9 (65.2-74.2) 86.7 (60.7-96.5) Raw Hen’s Egg Gal d 2 Ando 2008 25 Japan ImmunoCAP >3.88 (kUa/L) 76.1 (64.1-85.7) 82.9 (67.9-92.9) 87.9 (78.6-93.6) 68.0 (57.6-76.9) (Continues) 1616 | FLORES KIM ET AL. TABLE 2 (Continued) Food allergy Component Study Year Reference no. Country Index test Cutoff value Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) Raw Hen’s Egg Gal d 3 Alessandri 2012b 24 Italy ISAC 103 >0.01 (kUa/L) 18.2 (7.0-35.5) 97.1 (85.1-99.9) 85.7 (43.3-97.9) 55.7 (51.5-59.9) Raw Hen’s Egg Gal d 4 Ott 2008 33 Germany ISAC CRD 51 >0 (FI) 17.8 (8.0-32.1) 100.0 (78.2-100) 100.0 (NA) 28.8 (26.1-31.7) Peanut Ara h 1 Kukkonen 2015 30 Finland ImmunoCAP >0.35 kUa/L 63.9 (50.6-75.8) 87.8 (73.8-95.9) 88.6 (77.1-94.8) 62.1 (53.5-70.0) Peanut Ara h 1 Lieberman 2013 31 USA and Sweden ImmunoCAP >0.35 kUa/L 56.6 (46.6-66.2) 86.9 (75.8-94.2) 88.2 (79.4-93.6) 53.5 (47.6-59.4) Peanut Ara h 1 Kukkonen 2015 30 Finland ImmunoCAP >0.8 kUa/L 60.7 (47.3-72.9) 95.1 (83.5-99.4) 94.9 (82.5-98.6) 61.9 (54.2-69.1) Peanut Ara h 2 Klemans 2014 28 The Netherlands ISAC 112 >0.3 ISU/L 69.2 (56.6-80.1) 90.5 (77.4-97.3) 91.8 (81.4-96.7) 65.5 (56.6-73.5) Peanut Ara h 2 Kukkonen 2015 30 Finland ImmunoCAP >0.35 kUa/L 95.1 (86.3-99.0) 73.2 (57.1-85.8) 84.1 (76.0-89.8) 90.9 (76.6-96.8) Peanut Ara h 2 Lieberman 2013 31 USA and Sweden ImmunoCAP >0.35 kUa/L 80.2 (71.3-87.3) 91.8 (81.9-97.3) 94.4 (88.0-97.5) 72.7 (64.4-79.8) Peanut Ara h 2 Klemans 2014 28 The Netherlands ISAC 112 >1.0 ISU/L 58.5 (45.6-70.6) 95.2 (83.8-99.4) 95.0 (82.9-98.7) 59.7 (52.4-66.6) Peanut Ara h 2 Kukkonen 2015 30 Finland ImmunoCAP >1.8 kUa/L 80.3 (68.2-89.4) 95.1 (83.5-99.4) 96.1 (86.3-99.0) 76.5 (66.1-84.4) Peanut Ara h 3 Kukkonen 2015 30 Finland ImmunoCAP >0.35 kUa/L 57.4 (46.1-70.0) 90.2 (76.9-97.3) 89.7 (77.1-95.8) 58.7 (51.1-66.0) Peanut Ara h 3 Lieberman 2013 31 USA and Sweden ImmunoCAP >0.35 kUa/L 48.1 (38.3-58.1) 90.2 (79.8-96.3) 89.5 (79.5-94.9) 50.0 (45.0-55.0) Peanut Ara h 3 Kukkonen 2015 30 Finland ImmunoCAP >0.8 kUa/L 55.7 (42.5-68.5) 95.1 (83.5-99.4) 94.4 (81.2-98.5) 59.1 (51.9-65.9) Peanut Ara h 6 Kukkonen 2015 30 Finland ISAC 112 >0.3 ISU 98.3 (90.9-100) 90.2 (76.9-97.3) 93.5 (85.1-97.4) 97.4 (84.1-99.6) Peanut Ara h 6 Klemans 2014 28 The Netherlands ISAC 112 >0.3 ISU/L 70.8 (58.2-81.4) 85.7 (71.5-94.6) 88.5 (78.2-94.2) 65.5 (56.0-73.8) Peanut Ara h 6 Kukkonen 2015 30 Finland ISAC 112 >0.8 ISU/L 94.9 (85.9-98.9) 95.1 (83.5-99.4) 96.6 (87.9-99.1) 92.9 (81.2-97.5) Peanut Ara h 6 Klemans 2014 28 The Netherlands ISAC 112 >1.0 ISU/L 61.5 (48.6-73.4) 95.2 (83.8-99.4) 95.2 (83.6-98.7) 61.5 (53.9-68.7) Peanut Ara h 8 Kukkonen 2015 30 Finland ImmunoCAP >0.35 kUa/L 78.7 (66.3-88.1) 14.6 (5.6-29.2) 57.8 (53.3-62.2) 31.6 (16.0-52.7) Peanut Ara h 8 Lieberman 2013 31 USA and Sweden ImmunoCAP >0.35 kUa/L 34.9 (25.9-44.8) 42.6 (30.0-55.9) 51.4 (43.0-59.7) 27.4 (21.4-34.2) Peanut Ara h 9 Kukkonen 2015 30 Finland ImmunoCAP >0.35 kUa/L 14.8 (7.0-26.2) 85.4 (70.8-94.4) 60.0 (36.6-79.6) 40.2 (36.4-44.2) Hazelnut Cor a 1 Masthoff 2012 32 The Netherlands ImmunoCAP >0.35 kUa/L 79.7 (69.2-88.0) 7.3 (2.7-15.3) 45.3 (42.2-48.5) 27.3 (13.4-47.6) Hazelnut Cor a 8 Masthoff 2013 32 The Netherlands ImmunoCAP >0.35 kUa/L 6.3 (2.1-14.2) 96.3 (89.7-99.2) 62.5 (29.2-87.1) 51.6 (49.9-53.4) Hazelnut Cor a 9 Masthoff 2013 32 The Netherlands ImmunoCAP >0.35 kUa/L 59.5 (47.9-70.4) 87.8 (78.7-94.0) 82.5 (71.9-89.6) 69.2 (63.0-74.8) Hazelnut Cor a 9 Bransdstrom 2015 27 Sweden ImmunoCAP >0.65 kUa/L 100.0 (63.1-100) 71.9 (53.3-86.3) 47.1 (33.8-60.7) 100.0 (NA) Hazelnut Cor a 9 Masthoff 2013 32 The Netherlands ImmunoCAP >1 kUa/L 54.4 (42.8-65.7) 97.6 (91.7-99.7) 95.6 (84.4-98.9) 69.0 (63.5-73.9) Hazelnut Cor a 9 Masthoff 2013 32 The Netherlands ImmunoCAP >5 kUa/L 30.4 (20.5-41.8) 98.8 (93.4-100) 96.0 (76.9-99.4) 59.6 (56.0-63.1) Hazelnut Cor a 14 Masthoff 2013 32 The Netherlands ImmunoCAP >0.35 kUa/L 54.4 (42.8-65.7) 85.4 (75.8-92.2) 78.2 (67.2-86.3) 66.0 (60.1-71.6) Hazelnut Cor a 14 Bransdstrom 2015 27 Sweden ImmunoCAP >0.64 kUa/L 100.0 (63.1-100) 93.8 (79.2-99.2) 80.0 (51.1-93.9) 100.0 (NA) Hazelnut Cor a 14 Masthoff 2013 32 The Netherlands ImmunoCAP >1 kUa/L 50.6 (39.1-62.1) 86.6 (77.3-93.1) 78.4 (66.8-86.8) 64.5 (58.9-69.8) Hazelnut Cor a 14 Masthoff 2013 32 The Netherlands ImmunoCAP >5 kUa/L 39.2 (28.4-50.9) 98.8 (93.4-100) 96.9 (81.3-100) 62.8 (58.5-66.9) (Continues) FLORES KIM ET AL. | 1617