Document Type

Article

Publication Date

4-28-2026

Comments

This article is the author’s final published version in Blood Advances, Volume 10, Issue 8, 2026, Pages 2608-2615.

The published version is available at https://doi.org/10.1182/bloodadvances.2025017562. Copyright © 2026 American Society of Hematology.

 

Abstract

Sickle cell disease (SCD) is the most common inherited blood disorder in the United States. The American Society of Hematology Research Collaborative (ASH RC) has built an SCD Data Hub (DH) to facilitate research and quality improvement using real-world data. To our knowledge, we report here the first analyses from the DH, focusing on cohort demographics and accurate identification of SCD diagnosis type. DH sites have data use agreements with ASH RC to extract and transfer electronic health record (EHR) data at least quarterly. Principal investigators (PI) provided additional attestation of SCD diagnosis based on existing local data sources deemed sufficient by the PI. A random sample of 25 patients (per site) with a physician-attested diagnosis and at least 1 encounter in 2022 had SCD type and other variables manually abstracted by site personnel. Concordance was calculated as the percentage of cases with the same SCD type determined by the physician-attested and abstracted methods. Twenty DH sites have submitted data for 23 970 unique individuals with SCD. The median patient age was 23 years (range, birth to 75 years); 55.4% were female. Physician-attested SCD diagnosis types on 9484 patients from 13 sites were reported as HbSS (67.2%), HbSC (22.2%), HbSß0thalassemia (2.1%), HbSβ+thalassemia (6.1%), and HbS/other (2.4%). Physician-attested SCD type had 94% (233/248) concordance with manual chart abstraction. High concordance increases confidence in the validity of SCD DH data. Well-curated and transformed data on a large cohort of individuals with SCD will be leveraged to conduct observational studies and inform the design and feasibility of prospective interventional studies.

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Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Language

English

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