Belgian lung function tracking for adults with chronic respiratory disease
Official title: Belgian Lung Function Study: Personalised Longitudinal Lung Function Analysis as a Marker of Disease Progression
Run by KU Leuven · NCT07419555 · Data updated 2026-11-12
This project will test whether a machine-learning model can use past and routine lung tests to predict future lung function patterns for adults with chronic respiratory diseases.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 5000 (estimated) |
| Sponsor | KU Leuven Academic / other |
| Locations | 5 sites (Edegem and 4 other locations) |
| Status | Recruiting |
| Started | March 25, 2026 |
| Main results expected | March 1, 2029 |
| Study ends | March 1, 2029 |
| Registry record updated | October 20, 2026 |
| Trial ID | NCT07419555 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (18+) with a diagnosed chronic respiratory disease who are followed at one of the four participating Belgian hospitals and have a baseline full lung function test plus at least three historical spirometry measurements over a two-year window.
✕Probably not a fit
Patients without adequate historical spirometry (fewer than three measurements or less than two years of data), those who have had a lung transplant, those unable to consent, or patients not cared for at the participating centres are unlikely to benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a multicentre observational study to prospectively validate a machine-learning model that predicts individual and population lung function trajectories using historical and routine lung function data. Investigators will collect baseline complete pulmonary function tests, prior spirometry history (minimum three measurements over at least two years), and follow participants for clinical outcomes including mortality, hospitalisations, emergency visits, and patient-reported outcomes. Predicted trajectories will be compared to observed trajectories to identify unexpected declines or improvements and to relate those deviations to step-up in care and health outcomes. Approximately 4,000 patients are expected from four Belgian hospitals to provide sufficient data for model validation and outcome analyses.
Why it matters
Potential benefit: If successful, the model could enable earlier detection of unexpected lung function decline or improvement and help target interventions to reduce hospitalisations and mortality.
How similar studies have gone: Related machine-learning approaches have produced promising retrospective predictions of lung function, but prospective validation linking predictions to clinical outcomes is limited and remains novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * 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 * Have at least 3 historical spirometry measurements over a minimal time window of 2 years prior to inclusion * Planned routine follow-up within standard clinical care in one of the participating hospitals Exclusion Criteria: * Patients who have had a lung transplantation * Patients not being able to give consent to participate
Where it's running
-
UZ Antwerpen
Edegem, Belgium Recruiting -
Ziekenhuis Oost-Limburg
Genk, Belgium Recruiting -
UZ Gent
Ghent, Belgium Recruiting -
UZ Leuven
Leuven, Belgium Recruiting -
AZ Delta
Roeselare, Belgium Recruiting
Study contacts
- Principal investigator: Wim Janssens — UZ/KU Leuven
- Study coordinator: Marieke Wuyts
- Email: marieke.wuyts@kuleuven.be
- Phone: 016 34 31 59
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.