Machine learning to distinguish EGPA from HES
The Use of Machine Learning Techniques for the Differential Diagnosis Between Eosinophilic Granulomatosis With Polyangiitis and Hypereosinophilic Syndrome
This project will test whether machine learning applied to clinical, lab, and instrument data can help tell EGPA apart from HES and predict how patients respond to treatment.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 60 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Fondazione IRCCS Policlinico San Matteo di Pavia Academic / other |
| Locations | 1 site (Pavia) |
| Trial ID | NCT07275190 on ClinicalTrials.gov |
What this trial studies
Researchers will collect clinical history, laboratory results, instrumental data, and blood samples from adults diagnosed with EGPA or HES at a single center in Pavia, Italy. The collected data will be processed and analyzed with machine learning algorithms to identify patterns and features that differentiate the two conditions and to develop models predicting treatment response. Participation involves informed consent and blood draws for laboratory assessment; no investigational drugs or therapeutic interventions are given. The ultimate aim is to produce an algorithmic tool that could support clinicians in making more accurate and timely diagnoses.
Who should consider this trial
Good fit: Adults aged 18 or older with a confirmed diagnosis of EGPA or HES who can provide informed consent (or have an authorized representative) are eligible.
Not a fit: People without a confirmed EGPA or HES diagnosis, those with other known causes of eosinophilia, and individuals expecting direct therapeutic benefit are unlikely to gain personal medical benefit from participation.
Why it matters
Potential benefit: If successful, this approach could speed up and improve diagnostic accuracy between EGPA and HES, helping clinicians choose more appropriate treatments sooner.
How similar studies have performed: Machine learning has shown promise in differentiating related inflammatory and hematologic disorders, but applying it specifically to distinguish EGPA from HES is relatively novel and not yet widely validated.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. 18 years of age or over 2. A diagnosis of EGPA or HES 3. Willing and able to give informed written consent, or willing to give permission for a nominated friend or relative to provide written informed assent if they are unable to do so because of physical disabilities Exclusion Criteria: 1. Lack of a confirmed diagnosis of EGPA or HES. 2. Other causes of eosinophilia
Where this trial is running
Pavia
- Fondazione IRCCS Policlinico San Matteo, SC Reumatologia — Pavia, Italy (Recruiting)
Study contacts
- Study coordinator: Carlomaurizio Montecucco
- Email: carlomaurizio.montecucco@unipv.it
- Phone: 390382502948
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.