Establishment of a framework for assessing mortality in persons with congenital hemophilia A and its application to an adverse event reporting database. (16th December 2020)

• Record Type: Journal Article
• Authors: Pipe, Steven W.; Kruse‐Jarres, Rebecca; Mahlangu, Johnny N.; Pierce, Glenn F.; Peyvandi, Flora; Kuebler, Peter; De Ford, Christian; Sanabria, Fabián; Ko, Richard H.; Chang, Tiffany; Hay, Charles R. M.
• Is Part Of: Journal of thrombosis and haemostasis. Volume 19(2021)Supplement 1
• Page Start: 21
• Page End: 31
• Publication Date: 2020-12-16
• Subjects: algorithms -- cause of death -- data analysis -- hemophilia A -- mortality; Thrombosis -- Periodicals; Hemostasis -- Periodicals; Blood coagulation disorders -- Periodicals; 616.1
• DOI: 10.1111/jth.15186
• Languages: English
• ISSNs: 1538-7933

Abstract

Abstract: Background: Despite recent therapeutic advances, life expectancy in persons with congenital hemophilia A (PwcHA) remains below that of the non‐HA population. As new therapies are introduced, a uniform approach to the assessment of mortality is required for comprehensive evaluation of risk–benefit profiles, timely identification of emerging safety signals, and comparisons between treatments. Objectives: Develop and test a framework for consistent reporting and analysis of mortality across past, current, and future therapies. Patients/Methods: We identified known causes of mortality in PwcHA through literature review, analysis of the US Food and Drug Administration Adverse Event Reporting System (FAERS) database, and expert insights. Leading causes of death in general populations are those recognized by the Centers for Disease Control and Prevention and the World Health Organization. We developed an algorithm for assessing fatalities in PwcHA and used this to categorize FAERS data as a proof of concept. Results: PwcHA share mortality causes with the non‐HA population including cardiovascular disease, malignancy, infections, pulmonary disease, dementias, and trauma/suicide. Causes associated with HA include hemorrhage, thrombosis, human immunodeficiency virus, hepatitis C virus, and liver dysfunction. We propose an algorithm employing these classes to categorize fatalities and use it to classify FAERS fatality data between 01/01/2000 and 03/31/2020; the most common causes were hemorrhage (22.2%) and thrombosis (10.4%). Conclusions: A conceptual framework for examining mortality in PwcHA receiving any hemophilia therapy is proposed to analyze and interpret fatalities, enabling consistent and objective assessment. Application of the framework using FAERS data suggests a generally consistent pattern of reported mortality across HA treatments, supporting the utility of this unified approach.