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Clinical Study on Constructing a Machine Learning-Based Individualized Prediction Model Using Immune Response Patterns to Enhance Inhibitor Eradication Capability in Pediatric Hemophilia A

Clinical Study on Constructing a Machine Learning-Based Individualized Prediction Model Using Immune Response Patterns to Enhance Inhibitor Eradication Capability in Pediatric Hemophilia A

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ChiCTR
Registry ID
ChiCTR2600119260
Enrollment
Unknown
Registered
2026-02-25
Start date
2026-03-01
Completion date
Unknown
Last updated
2026-03-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hemophilia A

Interventions

Treatment regimen guided by the "Individualized Prediction Model”:"Individualized Prediction Model”

Sponsors

Beijing Childrens Hospital,Capital Medical University
Lead Sponsor

Eligibility

Sex/Gender
Male
Age
No minimum to 18 Years

Inclusion criteria

Inclusion criteria: 1.Diagnosis of moderate or severe hemophilia A; 2.Age = 0.6 Bethesda Units (BU), confirmed by at least two consecutive tests;

Exclusion criteria

Exclusion criteria: 1.Concomitant presence of other autoimmune diseases; 2.Requirement for immunoprophylaxis (vaccinations) or use of immunosuppressants for reasons unrelated to this study during the study period; 3.Requirement for major surgical intervention during the study period;

Design outcomes

Primary

MeasureTime frame
ITI success rate;—

Countries

China

Contacts

Public ContactWu Runhui

Beijing Childrens Hospital,Capital Medical University

runhuiwu@hotmail.com+86 10 5961 7138

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Mar 14, 2026