FIRST INSIGHTS FROM GERMAN HEALTH DATA LAB: REAL-WORLD EPIDEMIOLOGY AND OUTCOMES OF TRANSTHYRETIN AMYLOID CARDIOMYOPATHY (ATTR-CM) IN GERMANY
Author(s)
Leonie Kunk, MSc1, Teresa Trenkwalder, Prof. Dr. med.2, Katharina Knoll, Dr. med.2, Stefka Stoyanova, State Examination in Medicine1, Anna Filonenko, MSc, DrPH1, Lili Jiang, PhD3, Nils Kossack, Dipl.-Math.4, Evelyn Reinhard, PhD5, Eva Hradetzky, PhD1, Agnes Kisser, PhD1, Sebastian Spethmann, Prof. Dr. med, MHBA6.
1Pfizer Pharma GmbH, Berlin, Germany, 2Department of Cardiovascular Diseases; School of Medicine and Health, German Heart Center Munich; Technical University of Munich University Hospital, Technical University of Munich, Munich, Germany, 3Pfizer Inc., USA, New York, NY, USA, 4WIG2 Institute, Leipzig, Germany, 5WIG2 GmbH, Leipzig, Germany, 6Department of Cardiology, Angiology and Intensive Care Medicine, German Heart Center at Charité – University Medical Center Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
1Pfizer Pharma GmbH, Berlin, Germany, 2Department of Cardiovascular Diseases; School of Medicine and Health, German Heart Center Munich; Technical University of Munich University Hospital, Technical University of Munich, Munich, Germany, 3Pfizer Inc., USA, New York, NY, USA, 4WIG2 Institute, Leipzig, Germany, 5WIG2 GmbH, Leipzig, Germany, 6Department of Cardiology, Angiology and Intensive Care Medicine, German Heart Center at Charité – University Medical Center Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
OBJECTIVES: Advances in imaging modalities and availability of disease-modifying therapies have increased disease awareness, facilitated earlier diagnosis, and improved survival among patients with ATTR-CM. Nationwide real-world evidence in Germany remains limited. This study aims to describe incidence, characteristics and health outcomes of patients with ATTR-CM in Germany, using data from the newly established German Health Data Lab (HDL).
METHODS: We conducted a retrospective observational study using data from HDL covering all statutory health insurance (SHI)-insured individuals in Germany (~ 73 million, ~90% of the German population) across both inpatient (IP) and outpatient (OP) care sectors from 2019 to 2023. As there is no specific ICD-10 code for ATTR-CM, we adopted previously developed claims-based algorithms to define the study population requiring a combination of diagnostic codes of amyloidosis and cardiac involvement in temporal association with the amyloidosis diagnosis and excluding other types of amyloidosis. Adults (≥18 years) with incident ATTR-CM diagnosis between 2020 and 2022 were identified and followed-up. Outcomes included overall survival and cardiovascular hospitalizations. A prior feasibility analysis using the WIG2 benchmark database (~3 million SHI insured individuals) was conducted to test the selection algorithm and estimate the size of the study population.
RESULTS: Based on feasibility analysis, the HDL database is expected to yield approximately 5,400 incident ATTR-CM patients between 2020-2022. Full analyses are ongoing. Preliminary results confirmed the feasibility of identifying the target population and relevant outcomes. This project highlights the importance of allocating sufficient time for iterative validation, algorithm refinement, and technical implementation when working within the HDL environment.
CONCLUSIONS: This study is designed to provide first nationwide insights into ATTR-CM in Germany using the HDL. The HDL represents a highly promising data source; however, initial experiences indicate that projects require additional time for implementation and analysis. Prior feasibility analysis using the WIG2 database enabled script development and plausibility checks.
METHODS: We conducted a retrospective observational study using data from HDL covering all statutory health insurance (SHI)-insured individuals in Germany (~ 73 million, ~90% of the German population) across both inpatient (IP) and outpatient (OP) care sectors from 2019 to 2023. As there is no specific ICD-10 code for ATTR-CM, we adopted previously developed claims-based algorithms to define the study population requiring a combination of diagnostic codes of amyloidosis and cardiac involvement in temporal association with the amyloidosis diagnosis and excluding other types of amyloidosis. Adults (≥18 years) with incident ATTR-CM diagnosis between 2020 and 2022 were identified and followed-up. Outcomes included overall survival and cardiovascular hospitalizations. A prior feasibility analysis using the WIG2 benchmark database (~3 million SHI insured individuals) was conducted to test the selection algorithm and estimate the size of the study population.
RESULTS: Based on feasibility analysis, the HDL database is expected to yield approximately 5,400 incident ATTR-CM patients between 2020-2022. Full analyses are ongoing. Preliminary results confirmed the feasibility of identifying the target population and relevant outcomes. This project highlights the importance of allocating sufficient time for iterative validation, algorithm refinement, and technical implementation when working within the HDL environment.
CONCLUSIONS: This study is designed to provide first nationwide insights into ATTR-CM in Germany using the HDL. The HDL represents a highly promising data source; however, initial experiences indicate that projects require additional time for implementation and analysis. Prior feasibility analysis using the WIG2 database enabled script development and plausibility checks.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EPH189
Topic
Clinical Outcomes, Epidemiology & Public Health, Real World Data & Information Systems
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory), Rare & Orphan Diseases