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NCT06162884: IS-PPF

Single Time Point Prediction as Earlier Diagnosis of Progressive Pulmonary Fibrosis

Recruiting now Last updated 15 June 2025
What this trial tests

trial in Pulmonary Fibrosis in 200 participants. Currently enrolling.

Timeline
6 November 2024
Primary endpoint
22 November 2027
19 August 2028

Quick facts

Lead sponsorUniversity of California, Los Angeles
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment200
Start date6 November 2024
Primary completion22 November 2027
Estimated completion19 August 2028
Sites1 location across United States

Conditions studied

Sponsor

University of California, Los Angeles

Who can join

18 and older, any sex, with Pulmonary Fibrosis. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This study is a prospective observational study for subjects with idiopathic pulmonary fibrosis (IPF) or non-IPF interstitial lung diseases (ILD). The purpose of this study is to compare whether imaging patterns from high-resolution computed tomography (HRCT) at baseline can predict worsening. Single Time point Prediction (STP) is a score derived from an artificial intelligenc/ machine learning (AI/ML) using the radiomic features from a HRCT scan that quantifies the imaging patterns of short-term predictive worsening.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Pulmonary Fibrosis

Currently open trials in the same condition.

Other University of California, Los Angeles trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06162884.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing