Actively Recruiting
Predicting Outcomes in Intermediate and High-risk Non-muscle Invasive Bladder Cancer Using Automated Analysis of Digital Pathology Data
Led by University of Texas Southwestern Medical Center · Updated on 2025-08-17
600
Participants Needed
2
Research Sites
N/A
Total Duration
On this page
Sponsors
U
University of Texas Southwestern Medical Center
Lead Sponsor
V
Valar Labs
Collaborating Sponsor
AI-Summary
What this Trial Is About
Researchers are investigating an Artificial Intelligence (AI) tool designed to analyze bladder tumor tissue samples to predict how patients with intermediate and high-risk non-muscle invasive bladder cancer (NMIBC) will respond to intravesical Bacillus Calmette-Guérin (BCG) and intravesical chemotherapy treatments. This study aims to provide clinicians with a way to identify patients likely to benefit from these therapies or who may need alternative treatments, such as clinical trials or surgery. The study focuses on developing and validating this AI-based histologic analysis tool to improve treatment decisions for NMIBC patients. The study analyzes tissue specimens obtained from transurethral resection of bladder tumor (TURBT) before BCG induction and at recurrence after BCG treatment. Participants are grouped into high-risk and intermediate-risk NMIBC categories based on criteria like tumor grade, size, recurrence, and presence of carcinoma in situ. The AI tool will be developed and validated using these histologic samples to predict cancer recurrence following intravesical chemotherapy or BCG. This observational study includes patients who have received intravesical therapy such as BCG, mitomycin C, or Gemcitabine/Docetaxel within six months before enrollment. Participants will have their medical records and pathology samples reviewed to assess tumor characteristics and treatment responses. Researchers will monitor recurrence-free survival at 3, 6, 12, and 24 months after TURBT in both risk groups, as well as progression-free survival at 12 and 24 months. The study involves ongoing observation to evaluate the tool's ability to predict outcomes using digital pathology data. Participants will provide informed consent and are followed over time to collect data on their cancer status and treatment results.
CONDITIONS
Brief Title
Artificial Intelligence Prediction Tool in Non-muscle Invasive Bladder Cancer (NMIBC)
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Diagnosis of intermediate or high-risk non-muscle invasive bladder cancer as defined by AUA/SUO criteria
- Intravesical therapy within 6 months from enrollment including BCG, mitomycin C, or Gemcitabine/Docetaxel
- English or Spanish speakers
- 18 to 99 years of age
- Ability to understand and willingness to provide informed consent
You will not qualify if you...
- Inadequate tissue from TURBT
- Bladder cancer stage T2 or higher
- Receipt of systemic therapy
- Inability to read or write English or Spanish
- Unwillingness to sign written informed consent
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) for consent and eligibility confirmation
Duration - At time of enrollment and as needed at recurrence
Participants provide histologic specimens from recent Transurethral resection of bladder tumor (TURBT) and, if applicable, at time of recurrence after BCG induction for analysis.
Specimen collection occurs during routine clinical procedures; no additional study visits required
Duration - Up to 24 months following TURBT
Participants are monitored for recurrence and progression of non-muscle invasive bladder cancer following TURBT using surveillance cystoscopy and clinical follow-up.
Surveillance visits per routine care schedule, typically including cystoscopy visits at 3, 6, 12, and 24 months
Trial Site Locations
Total: 2 locations
1
University of Texas Southwestern Medical Center
Dallas, Texas, United States, 75390-9164
Actively Recruiting
2
University of Texas Health Science Center at San Antonio
San Antonio, Texas, United States, 78229
Actively Recruiting
Research Team
J
Jacob Taylor, MD
S
Sonobia Garrett
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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