Disease Progression Modeling for an Ultra-Rare Disease: Lysosomal Acid Lipase Deficiency (LAL-D)
Author(s)
Mafalda Bourbon, Dr.1, Ali Canbay, Dr.2, Giuseppe Indolfi, Dr.3, Florence Lacaille, Dr.4, José Pastor, Dr.5, Jesús Quintero, Dr.6, Albina Tummolo, Dr.7, Natalia Male, MD8, SANDRA MERINO, PhD9, Josu Aguirre, PhD10, Marco Pinel, MD11.
1National Institute of Health Doutor Ricardo Jorge, Lisbon, Portugal, Lisbon, Portugal, 2University Hospital Knappschaftskrankenhaus Bochum, Bochum, Germany, Bochum, Germany, 3Meyer Children's University Hospital, Florence, Italy, Florence, Italy, 4Necker-Enfants Malades University Hospital, Paris, France, Paris, France, 5General University Hospital of Elche, Alicante, Spain, Alicante, Spain, 6Vall d'Hebron University Hospital, Barcelona, Spain, Barcelona, Spain, 7Giovanni XXIII Children's Hospital, Bari, Italy, Bari, Italy, 8Alexion, AstraZeneca Rare Disease, Barcelona, Spain, 9Alexion, AstraZeneca Rare Disease, BARCELONA, Spain, 10IQVIA, Barcelona, Spain, 11Consultant, IQVIA, Madrid, Spain.
1National Institute of Health Doutor Ricardo Jorge, Lisbon, Portugal, Lisbon, Portugal, 2University Hospital Knappschaftskrankenhaus Bochum, Bochum, Germany, Bochum, Germany, 3Meyer Children's University Hospital, Florence, Italy, Florence, Italy, 4Necker-Enfants Malades University Hospital, Paris, France, Paris, France, 5General University Hospital of Elche, Alicante, Spain, Alicante, Spain, 6Vall d'Hebron University Hospital, Barcelona, Spain, Barcelona, Spain, 7Giovanni XXIII Children's Hospital, Bari, Italy, Bari, Italy, 8Alexion, AstraZeneca Rare Disease, Barcelona, Spain, 9Alexion, AstraZeneca Rare Disease, BARCELONA, Spain, 10IQVIA, Barcelona, Spain, 11Consultant, IQVIA, Madrid, Spain.
OBJECTIVES: To develop a disease progression model for Lysosomal Acid Lipase Deficiency (LAL-D) in children and adults, accounting for hepatic and lipidic profiles (regardless symptomatology presence) and excluding early-onset (Wolman disease).
METHODS: For the hepatic profile, a six-health-state Markov model was developed to represent disease progression, from hepatic steatosis to fibrosis, advanced cirrhosis, and death. Death could occur at any health state from fibrosis onward. For the lipidic profile, a Low-Density Lipoprotein Cholesterol (LDL-C) buildup model was developed to represent LDL-C accumulation over time. Upon reaching a threshold, the risk of myocardial infarction (MI) increased exponentially, meaning that the more LDL-C accumulated over the years, the higher the risk of MI. Both profiles were assessed separately, and for each, three treatment scenarios were evaluated: untreated patients, early treatment with sebelipase alfa (SA), and delayed SA treatment post-diagnosis. SA efficacy was retrieved from clinical trials (LAL-CL02 and LAL-CL06), while all other data were sourced from the literature. Model cycles were 1 year long. The model accounted for more severe disease in early-onset cases, aligned with real-world data. A probabilistic sensitivity analysis was conducted to test the robustness of the model. Both, the model, assumptions and methodology were validated by a panel of key LAL-D opinion leaders.
RESULTS: Hepatic profile: 70 years after disease onset, early SA treatment resulted in a 28% reduction in the probability of death compared to untreated patients and an 18% reduction compared to delayed SA treatment. Lipidic profile: 70 years after disease onset, patients treated with SA upon diagnosis had a 1% cumulative risk of MI, compared to 10% with delayed treatment and 30% without treatment.
CONCLUSIONS: To the best of our knowledge, this is the first model to simulate LAL-D progression. The model supports early treatment of LAL-D patients to improve survival and manage cardiovascular events.
METHODS: For the hepatic profile, a six-health-state Markov model was developed to represent disease progression, from hepatic steatosis to fibrosis, advanced cirrhosis, and death. Death could occur at any health state from fibrosis onward. For the lipidic profile, a Low-Density Lipoprotein Cholesterol (LDL-C) buildup model was developed to represent LDL-C accumulation over time. Upon reaching a threshold, the risk of myocardial infarction (MI) increased exponentially, meaning that the more LDL-C accumulated over the years, the higher the risk of MI. Both profiles were assessed separately, and for each, three treatment scenarios were evaluated: untreated patients, early treatment with sebelipase alfa (SA), and delayed SA treatment post-diagnosis. SA efficacy was retrieved from clinical trials (LAL-CL02 and LAL-CL06), while all other data were sourced from the literature. Model cycles were 1 year long. The model accounted for more severe disease in early-onset cases, aligned with real-world data. A probabilistic sensitivity analysis was conducted to test the robustness of the model. Both, the model, assumptions and methodology were validated by a panel of key LAL-D opinion leaders.
RESULTS: Hepatic profile: 70 years after disease onset, early SA treatment resulted in a 28% reduction in the probability of death compared to untreated patients and an 18% reduction compared to delayed SA treatment. Lipidic profile: 70 years after disease onset, patients treated with SA upon diagnosis had a 1% cumulative risk of MI, compared to 10% with delayed treatment and 30% without treatment.
CONCLUSIONS: To the best of our knowledge, this is the first model to simulate LAL-D progression. The model supports early treatment of LAL-D patients to improve survival and manage cardiovascular events.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
CO75
Topic
Clinical Outcomes
Topic Subcategory
Clinical Outcomes Assessment
Disease
Rare & Orphan Diseases