Interstitial Lung Disease Trial, Recruiting
Who may be able to join
AI generated eligibility summary. Written by an AI model from the official source data and checked on a sample basis. It can contain mistakes, so confirm anything important against the original source. How we use AI
Who might be able to join this trial:
- People who are 40 years of age or older
- People who have been diagnosed with IPF (idiopathic pulmonary fibrosis) according to established 2018 international guidelines, as confirmed by the doctor running the trial
- People who have signed a consent form agreeing to take part
Who may not be able to join:
- People who are pregnant or planning to become pregnant during the study
- Women who are able to become pregnant and are not willing to either abstain from heterosexual intercourse or use two reliable methods of contraception (at least one of which must have a failure rate of less than 1% per year, such as hormonal contraceptives, an intrauterine device, or surgical sterilisation) for the duration of the study
- People with a significant medical, surgical, or mental health condition that the trial doctor believes could affect their safety or their ability to complete the study (confirm with trial site)
Important: Always verify eligibility with the trial site directly before applying.
Based on publicly available eligibility criteria from ClinicalTrials.gov. Verify directly with the trial site before acting. This is not medical advice.
Contact this trial
Principal Investigator: Noth Imre, MD, Division of Pulmonary and Critical Care
Phone: 4342436074
Contact details sourced from ClinicalTrials.gov. Verify directly with the trial site before attending.
GP referral letter
Print a one-page summary to share with your doctor.
Trial details
Where this trial is recruiting
Primary endpoints
Derivation of DTA in IPF only cases from the PFF-PR and its associations with disease severity and outcomes.; Determine whether known IPF-risk genetic variants are associated with DTA score.; Identify novel genetic variants that associate with DTA score progression.; Determine if DTA or any constituent radiomic features correlate with select plasma proteins.; Determine if DTA or any of constituent radiomic features correlate with transcriptomic; Determine the best combination of markers (DTA, proteins and transcriptome) for machine learning algorithms for AUC evaluation of ROCs on all 3 cohort...
Can't join this trial?
Data last synced from ClinicalTrials.gov: 28 July 2026. Trial status can change. Always verify current status directly with the trial site before making any decision.