Non-Muscle Invasive Bladder Cancer Clinical Trial
Official title:
Machine Learning-Based Prediction of BCG Response in High-Risk Non-Muscle Invasive Bladder Cancer Patients
This prospective study aims at using Artificial intelligence to create a helpful unbiased machine learning-based model that predicts BCG unresponsiveness in high risk BCG-naïve NMIBC patients incorporating all potential clinico-pathological, radiological and/or molecular prognostic factors.
Status | Recruiting |
Enrollment | 100 |
Est. completion date | December 1, 2023 |
Est. primary completion date | December 1, 2022 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: 1. Ability to give informed consent. 2. High-risk NMIBC (any patient with high grade Ta or high grade T1 or CIS or recurrent multiple large tumors with low grade Ta/T1) 3. Good performance status (Defined as: performance status 0 or 1 at the time of TURBT according to Eastern Cooperative Oncology Group-ECOG-). 4. No prior history of BCG intravesical therapy. Exclusion Criteria: 1. History of previous radiotherapy or systemic chemotherapy. 2. Post TURBT histopathology report showing any of the following; 1. Benign histopathology. 2. Muscle invasive urothelial carcinoma. 3. Non urothelial carcinoma of the bladder. |
Country | Name | City | State |
---|---|---|---|
Egypt | Urology and Nephrology Center | Mansoura | Outside U.S./Canada |
Lead Sponsor | Collaborator |
---|---|
Mansoura University |
Egypt,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | BCG unresponsiveness | T1/Ta HG recurrence within 6 months of adequate BCG therapy | 6 months |
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