Actively Recruiting
Multi-Omics Data-Derived Inflammatory Phenotype for ABPA Recurrence Risk Prediction: A Multicenter Study
Led by Qianfoshan Hospital · Updated on 2026-06-01
300
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
AI-Summary
What this Trial Is About
This research aims to develop and validate a machine learning model to predict the one-year risk of relapse in patients with stable allergic bronchopulmonary aspergillosis (ABPA). By identifying inflammatory phenotypes through advanced data analysis, the study seeks to improve how patients are managed based on their risk levels. The project combines multiple types of data including imaging, fungal profiles, inflammatory markers, lung function tests, and clinical records to better understand ABPA recurrence. The study collects detailed medical information from patients with stable ABPA who visited multiple hospitals between January 2021 and January 2025. These patients are grouped into relapse and non-relapse categories based on their one-year follow-up. Machine learning techniques are used to select key features from the collected data to build a prediction model. Patients identified as low risk will receive routine monitoring, while those at high risk will receive more intensive care and management. Participants will undergo evaluations including pulmonary function tests, inflammatory marker assessments, fungal omics, and radiological imaging. Researchers will monitor for disease recurrence during the remission period over one year. The study measures how well the model can predict relapse to help guide personalized treatment decisions. Data collection and analysis aim to enhance clinical outcomes by tailoring follow-up and interventions based on individual risk levels.
CONDITIONS
Brief Title
Multi-Omics Inflammatory Phenotype for ABPA Recurrence Risk Prediction
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Female and Male patients aged 18-80 years
- Diagnosis of Allergic Bronchopulmonary Aspergillosis (ABPA) according to the 2024 ISHAM Working Group Diagnostic Criteria
You will not qualify if you...
- Patients with malignant tumors or severe organ dysfunction such as cardiac, cerebral, or renal problems
- Patients with severe comorbidities including active pulmonary tuberculosis, lung cancer, chronic heart failure (NYHA class III), chronic kidney disease stage 5, or decompensated cirrhosis
- Patients with immunosuppressive status, including HIV infection or long-term use of oral corticosteroids or immunosuppressive agents
- Pregnant or lactating women
- Patients with missing key data or incomplete medical records
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - 1 year
Participants with stable ABPA are observed with data collected from medical records, inflammatory markers, fungal omics, radiomics, and pulmonary function tests to develop a risk prediction model.
Regular assessments based on routine clinical visits
Trial Site Locations
Total: 1 location
1
Department of Respiratory, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, #16766, Jingshi Road, Jinan City, Shandong Province, China, Jinan, Shandong 250014
Jinan, Shandong, China, 250014
Actively Recruiting
Research Team
Q
Qian Qi
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
1
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