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1630 A Patient-Centric Approach to Improve the Understanding of Sickle Cell Disease Using Real-World Data

Program: Oral and Poster Abstracts
Session: 904. Outcomes Research—Non-Malignant Conditions: Poster I
Hematology Disease Topics & Pathways:
sickle cell disease, Diseases, Hemoglobinopathies
Saturday, December 5, 2020, 7:00 AM-3:30 PM

E. Leila Jerome Clay, MD1, Miranda Bailey2*, Dan Drozd, MD, MSc3*, Jincy Paulose, M.D.2*, Nicholas Ramscar, MBBS4*, Kieran Mace, PhD3* and David Wormser, PhD, MSc, MPhil4*

1Johns Hopkins University, Johns Hopkins All Children’s Hospital, St Petersburg, FL
2US Oncology Medical, Novartis Pharmaceuticals Corporation, East Hanover, NJ
3PicnicHealth, San Francisco, CA
4Novartis Pharma AG, Basel, Switzerland

Background: Sickle cell disease (SCD) comprises a group of inherited blood disorders, and is a complex, multi-system, disease. SCD is associated with a variety of clinical complications that affect multiple organ systems. These complications are driven primarily by vaso-occlusion and hemolytic anemia, and can result in end-organ damage and early death. Painful vaso-occlusive crises (VOCs) are a characteristic feature of SCD and can require healthcare intervention. Despite recent advances in the screening, management and treatment of SCD, gaps remain in our understanding of the disease in the real-world setting. These include how best to transition from pediatric to adult care and how to manage specific complications.

Currently, most real-world evidence (RWE) is generated from information captured in payer databases, which is not as comprehensive as the information recorded in electronic medical records (EMRs). Despite being potentially valuable sources of real-world, clinical information, EMRs for individual patients in the USA are not centralized, often being held by multiple healthcare providers using different EMRs. This fragmented system prevents generation of clear, comprehensive RWE, both in general and for SCD specifically. Furthermore, there is a lack of harmonization between EMR companies/systems in the types of information included and how it’s recorded. A separate approach that collates all available data from EMRs into a single, comprehensive record prior to RWE analysis would therefore greatly improve the accessibility of the available information and the quality of subsequent data analysis.

Aims: In contrast to existing RWE, this study explores the value of collating EMRs for each patient into a single, consistently structured format, with the aim of developing richer RWE to complement existing data on SCD. It is hypothesized that the resulting longitudinal overview of each patient’s care will contribute to an improved understanding of SCD in the real-world setting: firstly, by better capturing how many VOCs patients with SCD experience, with an indication of the proportion of VOCs that are being home-managed; secondly, by gaining deeper insights into the prevalence and progression of end-organ damage and any association with VOCs; and finally, by highlighting the type and site of care of SCD in the real world (eg medications, treating healthcare professional [HCP] specialties and the type of clinic visited).

Study design: The study population will comprise 400 patients with SCD from the USA. Patient recruitment occurs directly via social media and indirectly through a variety of partnerships including HCPs and patient advocacy groups. To enroll, patients sign an informed consent form allowing their de-identified medical information to be shared with third-party organizations to advance SCD research. Enrolled patients gain access to their medical records via a dashboard. The key inclusion criteria are: a confirmed SCD diagnosis (irrespective of phenotype); aged ≥16 years at enrollment; and ≥1 inpatient admission for a VOC in the 12 months prior to enrollment. The key exclusion criterion is the absence of medical records. Components of EMRs collected include doctors’ notes, laboratory and test results, clinical imaging and treatment records. Human-curated natural language processing and machine learning is used to extract, structure and code data from the structured sections and unstructured narrative text of the EMR. All medical records, from all visits, will be collected where possible and are expected to comprise ≥7 years of retrospective data for each patient.

Results: Between 1 December 2019 and 24 June 2020, a total of 46 patients with a mean age of 36 years (SD 9.7) were enrolled. For each patient, a median of 6.8 years of data from a median of 32.5 providers were obtained.

Conclusions: The evidence derived from this study aims to advance the understanding of real-world practices in the management of SCD. It may also provide further learnings regarding the prevalence of complications and any association between VOCs and end-organ damage. Generating a single, structured overview of all EMRs for each patient allows for richer insight generation and a more comprehensive analysis of RWE, compared with existing approaches. The insights gained from this RWE may inform future studies and clinical trials in SCD, with the ultimate aim of improving the quality of life of patients.

Disclosures: Clay: Novartis: Consultancy; GBT: Consultancy. Bailey: Novartis Pharmaceuticals Corporation: Current Employment. Drozd: F. Hoffmann-La Roche Ltd: Other: All authors received support for third party writing assistance, furnished by Scott Battle, PhD, provided by F. Hoffmann-La Roche, Basel, Switzerland.; PicnicHealth: Current Employment, Current equity holder in private company. Paulose: Novartis Pharma AG: Current Employment. Ramscar: Novartis Pharma AG: Current Employment. Mace: Roche/Genentech: Ended employment in the past 24 months; PicnicHealth: Current Employment. Wormser: Novartis Pharma AG: Current Employment, Current equity holder in publicly-traded company.

*signifies non-member of ASH