Belgian Lung Function Study
AIRCAST
2 other identifiers
observational
4,000
1 country
4
Brief Summary
Currently, it remains unclear how to manage serial lung function measurements in a clinical setting. The investigators aimed to tackle this problem by developing a machine learning (ML) model that can accurately predict population and individual lung function trajectories. These predictions would enable the investigators to identify positive or negative deviations, thereby revealing unexpected disease patterns. A prospective validation is needed that includes data on mortality, hospitalisations, emergency-room visits and patient-reported outcomes. Within this study, the goal is to validate the ML model with the data collected from this observational study.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Mar 2026
Typical duration for all trials
4 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 12, 2026
CompletedFirst Posted
Study publicly available on registry
February 19, 2026
CompletedStudy Start
First participant enrolled
March 25, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 1, 2029
ExpectedStudy Completion
Last participant's last visit for all outcomes
March 1, 2029
March 30, 2026
March 1, 2026
2.9 years
February 12, 2026
March 25, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Accuracy of lung function predictions (FEV1)
Proportion of correct and incorrect FEV1 predictions compared to the observed measure
at 1 and 2-year follow-up
Secondary Outcomes (6)
Differences in clinical outcomes between correct and incorrect lung function predictions (FEV1)
at 1 and 2-year follow-up
Accuracy of lung function predictions
at 1 and 2-year follow-up
Differences in clinical outcomes between correct and incorrect lung function predictions
at 1 and 2-year follow-up
Identifying the minimal needed to make predictions
after 2 years
Performance of ML-based predictions compared to linear regression analysis
at 1 and 2-year follow-up
- +1 more secondary outcomes
Eligibility Criteria
Chronic respiratory diseases
You may qualify if:
- Above 18 years old
- Diagnosed with a chronic respiratory disease and followed up in one of the participating Belgian hospitals
- Performed a complete lung function test (spirometry, body plethysmography and diffusion capacity) at baseline
- Planned routine follow-up within standard clinical care in one of the participating hospitals
You may not qualify if:
- Patients who have had a lung transplantation
- Patients not being able to give consent to participate
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- KU Leuvenlead
- AZ Deltacollaborator
- University Hospital, Antwerpcollaborator
- Ziekenhuis Oost-Limburgcollaborator
Study Sites (4)
UZ Antwerpen
Edegem, 2650, Belgium
Ziekenhuis Oost-Limburg
Genk, 3600, Belgium
UZ Leuven
Leuven, 3000, Belgium
AZ Delta
Roeselare, 8800, Belgium
Study Officials
- PRINCIPAL INVESTIGATOR
Wim Janssens
UZ/KU Leuven
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Principal Investigator
Study Record Dates
First Submitted
February 12, 2026
First Posted
February 19, 2026
Study Start
March 25, 2026
Primary Completion (Estimated)
March 1, 2029
Study Completion (Estimated)
March 1, 2029
Last Updated
March 30, 2026
Record last verified: 2026-03