Multi-Omics Data-Derived Inflammatory Phenotype for ABPA Recurrence Risk Prediction: A Multicenter Study
Status: Recruiting
Location: See location...
Study Type: Observational
SUMMARY
To develop and externally validate a machine learning model for predicting the 1-year risk of relapse in patients with stable ABPA, and to further evaluate its value in risk stratification and clinical decision-making.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Maximum Age: 80
Healthy Volunteers: f
View:
• Female and Male patients aged 18-80 years
• diagnosis of Allergic Bronchopulmonary Aspergillosis ABPA accroding to the 2024 ISHAM Working Group Diagnostic Criteria
Locations
Other Locations
China
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
RECRUITING
Jinan
Contact Information
Primary
Qian Qi
qiqianqlh@163.com
+86 13706380314
Time Frame
Start Date: 2021-01-01
Estimated Completion Date: 2028-12-31
Participants
Target number of participants: 300
Treatments
ABPA recurrence group and No ABPA recurrence group
Patients with stable ABPA who visited multicenter hospitals between January 2021 and January 2025 were enrolled and followed up for one year. Based on the definition of ABPA relapse, they were categorized into a relapse group and a non-relapse group. Key features from medical records, inflammatory markers, fungal omics, radiomics, and pulmonary function tests were selected for model development.
Related Therapeutic Areas
Sponsors
Leads: Qianfoshan Hospital