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ASH Research Collaborative Presents First Data at the ASH Annual Meeting

January 15, 2025

January 2025

In December, the first three studies to use data from the Sickle Cell Disease (SCD) Program within the American Society of Hematology Research Collaborative (ASH RC) Data Hub were presented as poster and online abstracts at the 66th ASH Annual Meeting and Exposition in San Diego. The studies were conducted by investigators at participating sites within the Data Hub’s SCD Program and span various topics, such as trends for use of disease-modifying therapy, ASH RC data quality, and population overview.

“ASH has assembled one of the largest databases of people with SCD,” said Charles Abrams, MD, chair of the ASH RC SCD Program Leadership Team and vice chair for research and chief scientific officer at the University of Pennsylvania. “This will allow us to generate high-quality, real-world evidence to help improve our care of patients.”

Established in 2017, the ASH RC is a nonprofit organization that works to improve the lives of people affected by blood diseases by fostering collaborative partnerships to accelerate research and improve outcomes for individuals with hematologic diseases by advancing treatment developments and generating evidence to support clinical decisions and care. Read on to learn more about how researchers are working to do just that in some of the first studies to come out of the ASH RC Data Hub.

Underuse of Disease-Modifying Therapies in SCD

Underuse of disease-modifying therapies (DMTs) continues to be a challenge among individuals with SCD, and data on DMT use often come from insurance databases, focus primarily on hydroxyurea, or are limited by geographic region or institution. Using the ASH RC Data Hub, which offers a diverse set of patients with SCD and is unrestricted by payer type, researchers at the Cincinnati Children’s Hospital Medical Center, led by Omar Niss, MD, were able to get a more comprehensive, real-word perspective on rates of DMT use.1

A total of 22,793 patients with SCD (55.8% female) were pulled from the ASH Data Hub between 2015 and 2023. DMT use was defined as reported treatment with hydroxyurea, voxelotor, or L-glutamine for at least 90 days within a year. DMT use did grow slightly between 2015 and 2023 but generally remained low. DMT use increased from 7.2% in 2015 to 19.8% in 2023 and was primarily driven by hydroxyurea, the use of which increased from 5.5% to 16.6%. The adoption of other DMTs was much lower and did not change much: 0.7% in 2020 to 1.6% in 2023 with voxelotor, and 1.3% in 2018 to 1.2% in 2023 with L-glutamine. In addition, even among patients with verified HbSS genotype, only 35% were prescribed DMTs.

Further validations are underway to verify the accuracy and reliability of these findings, but overall, this real-world analysis “underscores the persistent and alarming underutilization of DMTs in SCD,” the researchers noted, particularly with newer therapies.

Additionally, Dr. Abrams said, such a study highlights how “the Data Hub, through its ability of analyzing real-world data, can offer insights into how drugs are actually used in clinical practice.”

Concordance in SCD Diagnosis Type

An analysis of the SCD Data Hub conducted by Alexis Thompson, MD, MPH, and colleagues found that there is a high level of concordance between investigator-verified and manually abstracted SCD diagnosis types.2

Sites within the SCD Data Hub extract and transfer electronic health record (EHR) data at least quarterly using the Observational Medical Outcomes Partnership (OMOP) common data model. The SCD Data Hub is also supplemented with a site principal investigator attestation of an SCD diagnosis based on existing data sources, and such diagnoses are designated as “investigator verified.”

At the time of the study, the SCD Data Hub contained more than 10,000 patients across 12 sites with investigator-verified SCD diagnosis types. SCD types were reported as HbSS (67.2%), HbSC (22.2%), HbSβ0 thalassemia (2.1%), HbSβ+ thalassemia (6.1%), and HbS/other (2.4%). In the study, called the Data Validation Pilot Project, SCD type was manually abstracted in a random sample of 243 patients across 10 sites. Of the 243 patient cases, 233 had concordant SCD diagnosis types, resulting in an overall concordance rate of 96%.

In accordance with Dr. Abrams’ sentiments, the researchers concluded, “The ASH RC DH [Data Hub] is one of the largest SCD data resources in the United States. Investigator-verified diagnosis had high concordance with a manual chart abstraction in a random sample of patients across 10 sites. This concordance increases confidence in the validity of both existing and future SCD DH data.”

Phenotyping Using EHR Data

With limited population-based data on complications and outcomes in people with SCD in the U.S., researchers, led by John J. Strouse, MD, PhD, of Duke University, identified a need for automated methods to determine subtypes of SCD using real-world data from EHRs, an aim that would also better support learning between health care systems.3

To evaluate the feasibility of computable phenotyping using clinical features to classify individuals by genotype, the team used participant data from the Outcome Modifying Genes in SCD Study (OMG-SCD) with confirmed genotype. They hoped to use real-world EHR data from the ASH RC to develop a multivariable logistic regression model in order to classify participants into two groups: those with sickle cell anemia (HbSS/HbSβ0) and those with other genotypes (HbSC, HbSβ+). The ASH RC data, spanning from 2008 to 2023, included more than 8,000 children and adults with longitudinal data, an investigator-confirmed diagnosis of SCD, and no prior history of hematopoietic cell transplantation.

Looking at 674 adult participants from OMG-SCD, researchers identified 559 (83%) with HbSS, 24 (3.6%) with HbSβ0, 67 (9.9%) with HbSC, and 24 (3.4%) with HbSβ+. Several laboratory values, including hemoglobin concentration, mean corpuscular volume, and reticulocyte percentage, were successful in classifying participants into these two groups, with areas under the curve of 0.908, 0.801, and 0.912, respectively. Other variables, such as white blood cell and platelet counts and past hydroxyurea treatment, had a more modest discriminatory ability.

The study is ongoing, and the researchers noted that they plan to validate their results using additional 2022-2023 EHR data submitted to the ASH RC.

For more information on the ASH RC, visit ashresearchcollaborative.org.

References

  1. Niss O, Fenchel M, Kingsley E, et al. Underutilization of disease-modifying therapies in sickle cell disease: a real-world analysis from the ASH Research Collaborative Data Hub. Abstract 2312. Presented at the 66th American Society of Hematology Annual Meeting and Exposition; December 7, 2024; San Diego, California.
  2. Thompson A, Singh A, Neuberg DS, et al. High concordance between investigator-verified diagnosis and manual data abstraction for sickle cell diagnosis type: an ASH Research Collaborative Data Hub validation study. Abstract 2313. Presented at the 66th American Society of Hematology Annual Meeting and Exposition; December 7, 2024; San Diego, California.
  3. Strouse JJ, Kayle M, Oyedeji CI, et al. Electronic heath record phenotypes to classify sickle cell anemia versus other subtypes of sickle cell disease. Blood. 2024;144(Suppl 1):7652.

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