Investigation of predictive factors for therapeutic efficacy of immunosuppressive therapy for inflammatory bowel disease using machine learning

Investigation of predictive factors for therapeutic efficacy of immunosuppressive therapy for inflammatory bowel disease using machine learning - Investigation of predictive factors for therapeutic efficacy of immunosuppressive therapy for inflammatory bowel disease using machine learning

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000046284

Enrollment

300

Registered

2021-12-20

Start date

2021-11-25

Completion date

Unknown

Last updated

2026-06-29

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

Conditions

Inflammatory bowel disease

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: This study includes patients with inflammatory bowel diseases who started immunosuppressive therapy at the Department of Gastroenterology and Hepatology, Kyorin University Hospital. The diagnosis of ulcerative colitis and Crohn's disease is made following the guideline by the Japanese Inflammatory Bowel Disease Research Group affiliated with the Japan Ministry of Heath, Labour and Welfare.

Exclusion criteria

Exclusion criteria: Patients who don't consent to this study.

Design outcomes

Primary

Measure	Time frame
This observational study investigates biomarkers that are useful for predicting the therapeutic efficacy of immunosuppressive therapy for inflammatory bowel disease.	—

Countries

Japan

Contacts

Public ContactJun Miyoshi

Kyorin University School of Medicine Department of Gastroenterology and Hepatology

jmiyoshi@ks.kyorin-u.ac.jp0422-47-5511

Outcome results