Prediction model to identify patients with hypereosinophilic syndrome using real-world data.
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| Title: | Prediction model to identify patients with hypereosinophilic syndrome using real-world data. |
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| Authors: | Khoury P; National Institute of Allergy and Infectious Diseases, Bethesda, Md., Chung Y; AstraZeneca Pharmaceuticals, Wilmington, Del., Carstens D; AstraZeneca Pharmaceuticals, Wilmington, Del., Cook EE; Analysis Group Inc, Boston, Mass., Mu F; Analysis Group Inc, Boston, Mass., Cheng M; Analysis Group Inc, Boston, Mass., Judson E; AstraZeneca Pharmaceuticals, Wilmington, Del., Chen J; Analysis Group Inc, Boston, Mass., Wang T; Analysis Group Inc, Boston, Mass., Chen Z; Analysis Group Inc, Boston, Mass., Ogbogu PU; University Hospitals Rainbow Babies and Children's Hospital, Cleveland, Ohio.; Case Western Reserve University School of Medicine, Cleveland, Ohio. |
| Source: | The journal of allergy and clinical immunology. Global [J Allergy Clin Immunol Glob] 2025 Oct 24; Vol. 5 (1), pp. 100588. Date of Electronic Publication: 2025 Oct 24 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier Inc Country of Publication: United States NLM ID: 9918453488706676 Publication Model: eCollection Cited Medium: Internet ISSN: 2772-8293 (Electronic) Linking ISSN: 27728293 NLM ISO Abbreviation: J Allergy Clin Immunol Glob Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2772-8293 |
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| DOI: | 10.1016/j.jacig.2025.100588 |
