Estimating the Risk of Severe Peanut Allergy Using Clinical Background and IgE Sensitization Profiles

  1. Datema, Mareen R.
  2. Lyons, Sarah A.
  3. Fernández-Rivas, Montserrat
  4. Ballmer-Weber, Barbara
  5. Knulst, André C.
  6. Asero, Riccardo
  7. Barreales, Laura
  8. Belohlavkova, Simona
  9. Blay, Frédéric de
  10. Clausen, Michael
  11. Dubakiene, Ruta
  12. Fernández-Perez, Cristina
  13. Fritsche, Philipp
  14. Gislason, David
  15. Hoffmann-Sommergruber, Karin
  16. Jedrzejczak-Czechowicz, Monika
  17. Jongejan, Laurian
  18. Kowalski, Marek L.
  19. Kralimarkova, Tanya Z.
  20. Lidholm, Jonas
  21. Papadopoulos, Nikolaos G.
  22. Popov, Todor A.
  23. Del Prado, Nayade
  24. Purohit, Ashok
  25. Reig, Isabel
  26. Seneviratne, Suranjith L.
  27. Sinaniotis, Athanassios
  28. Vassilopoulou, Emilia
  29. Versteeg, Serge A.
  30. Vieths, Stefan
  31. Welsing, Paco M. J.
  32. Mills, E. N. Clare
  33. Le, Thuy-My
  34. Zwinderman, Aeilko H.
  35. van Ree, Ronald

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1000 Titel
  • Estimating the Risk of Severe Peanut Allergy Using Clinical Background and IgE Sensitization Profiles
1000 Autor/in
  1. Datema, Mareen R. |
  2. Lyons, Sarah A. |
  3. Fernández-Rivas, Montserrat |
  4. Ballmer-Weber, Barbara |
  5. Knulst, André C. |
  6. Asero, Riccardo |
  7. Barreales, Laura |
  8. Belohlavkova, Simona |
  9. Blay, Frédéric de |
  10. Clausen, Michael |
  11. Dubakiene, Ruta |
  12. Fernández-Perez, Cristina |
  13. Fritsche, Philipp |
  14. Gislason, David |
  15. Hoffmann-Sommergruber, Karin |
  16. Jedrzejczak-Czechowicz, Monika |
  17. Jongejan, Laurian |
  18. Kowalski, Marek L. |
  19. Kralimarkova, Tanya Z. |
  20. Lidholm, Jonas |
  21. Papadopoulos, Nikolaos G. |
  22. Popov, Todor A. |
  23. Del Prado, Nayade |
  24. Purohit, Ashok |
  25. Reig, Isabel |
  26. Seneviratne, Suranjith L. |
  27. Sinaniotis, Athanassios |
  28. Vassilopoulou, Emilia |
  29. Versteeg, Serge A. |
  30. Vieths, Stefan |
  31. Welsing, Paco M. J. |
  32. Mills, E. N. Clare |
  33. Le, Thuy-My |
  34. Zwinderman, Aeilko H. |
  35. van Ree, Ronald |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-06-07
1000 Erschienen in
1000 Quellenangabe
  • 2:670789
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.3389/falgy.2021.670789 |
1000 Ergänzendes Material
  • https://www.frontiersin.org/articles/10.3389/falgy.2021.670789/full#h12 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUND: It is not well-understood why symptom severity varies between patients with peanut allergy (PA). OBJECTIVE: To gain insight into the clinical profile of subjects with mild-to-moderate and severe PA, and investigate individual and collective predictive accuracy of clinical background and IgE to peanut extract and components for PA severity. METHODS: Data on demographics, patient history and sensitization at extract and component level of 393 patients with probable PA (symptoms ≤ 2 h + IgE sensitization) from 12 EuroPrevall centers were analyzed. Univariable and penalized multivariable regression analyses were used to evaluate risk factors and biomarkers for severity. RESULTS: Female sex, age at onset of PA, symptoms elicited by skin contact with peanut, family atopy, atopic dermatitis, house dust mite and latex allergy were independently associated with severe PA; birch pollen allergy with mild-to-moderate PA. The cross-validated AUC of all clinical background determinants combined (0.74) was significantly larger than the AUC of tests for sensitization to extract (0.63) or peanut components (0.54–0.64). Although larger skin prick test wheal size, and higher IgE to peanut extract, Ara h 1 and Ara h 2/6, were associated with severe PA, and higher IgE to Ara h 8 with mild-to-moderate PA, addition of these measurements of sensitization to the clinical background model did not significantly improve the AUC. CONCLUSIONS: Models combining clinical characteristics and IgE sensitization patterns can help establish the risk of severe reactions for peanut allergic patients, but clinical background determinants are most valuable for predicting severity of probable PA in an individual patient.
1000 Sacherschließung
lokal IgE
lokal EuroPrevall
lokal prediction
lokal peanut allergy
lokal component-resolved diagnostics
gnd 4034871-4 Lebensmittelallergie
lokal clinical background
lokal iFAAM
lokal severity
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
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1000 Label
1000 Förderer
  1. Sixth Framework Programme |
  2. Seventh Framework Programme |
1000 Fördernummer
  1. FP6- FOOD-CT-2005-514000
  2. 312147
1000 Förderprogramm
  1. EuroPrevall
  2. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Sixth Framework Programme |
    1000 Förderprogramm EuroPrevall
    1000 Fördernummer FP6- FOOD-CT-2005-514000
  2. 1000 joinedFunding-child
    1000 Förderer Seventh Framework Programme |
    1000 Förderprogramm -
    1000 Fördernummer 312147
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6431802.rdf
1000 Erstellt am 2022-02-28T09:43:38.766+0100
1000 Erstellt von 323
1000 beschreibt frl:6431802
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet 2022-03-08T08:34:05.744+0100
1000 Objekt bearb. Tue Mar 08 08:33:44 CET 2022
1000 Vgl. frl:6431802
1000 Oai Id
  1. oai:frl.publisso.de:frl:6431802 |
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