Clinical trial Recruiting at 2 sites Observational Ages 18 to 99

AI tool to predict treatment response in bladder cancer

Official title: Predicting Outcomes in Intermediate and High-risk Non-muscle Invasive Bladder Cancer Using Automated Analysis of Digital Pathology Data

Run by University of Texas Southwestern Medical Center · NCT05825950 · Data updated 2026-11-12

This study is testing a new AI tool that helps doctors predict how well bladder cancer patients will respond to certain treatments, so they can make better choices for those at risk of their cancer coming back.

Quick facts

Study typeObservational
Ages18 Years to 99 Years
SexAll
Enrollment600 (estimated)
SponsorUniversity of Texas Southwestern Medical Center
Academic / other
Drugs / interventionschemotherapy
Locations2 sites (Dallas, Texas and 1 other locations)
StatusRecruiting
StartedJanuary 25, 2024
Main results expectedSeptember 2026
Study endsSeptember 2026
Registry record updatedAugust 24, 2026
Trial IDNCT05825950 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Ideal candidates are adults aged 18 and older diagnosed with intermediate or high-risk non-muscle invasive bladder cancer.

Probably not a fit

Patients with inadequate tissue samples or those with muscle-invasive bladder cancer will not benefit from this study.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This multi-center observational study aims to develop and validate an AI-based histologic analysis tool that predicts responsiveness to intravesical Bacillus Calmette-Guérin (BCG) and chemotherapy in patients with intermediate and high-risk non-muscle invasive bladder cancer (NMIBC). The analysis will utilize histologic specimens obtained from patients prior to BCG induction and at recurrence after treatment. The tool is intended to assist clinicians in counseling patients and identifying those who may benefit from specific treatments or alternative strategies. This study addresses a critical gap in the management of NMIBC, particularly for patients who are at intermediate or high risk of recurrence.

Why it matters

Potential benefit: If successful, this tool could significantly improve treatment personalization and outcomes for patients with NMIBC.

How similar studies have gone: Other studies have shown promise in using AI for predictive analytics in cancer treatment, suggesting potential success for this approach.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Diagnosis of intermediate or high-risk non-muscle invasive bladder cancer as defined by AUA/SUO criteria (Intermediate-risk: recurrence within 1 year low grade Ta, solitary low grade Ta \>3 cm, multifocal low grade Ta, high grade Ta ≤3 cm, low grade T1; High risk: high grade T1, recurrent high grade Ta, high grade Ta \>3 cm, multifocal high grade Ta, any CIS, any BCG failure in high grade disease, any variant histology, any lymphovascular invasion) following pathologic evaluation of tissue specimens from TURBT.
* Intravesical therapy within 6 months from enrollment including patients treated with BCG, mitomycin C, or Gemcitabine/Docetaxel.
* English or Spanish speakers
* ≥ 18 years of age
* Ability to understand and the willingness to provide an informed consent

Exclusion Criteria:

* Inadequate tissue from TURBT
* ≥ T2 bladder cancer
* Systemic therapy
* Inability to read or write English or Spanish
* Unwilling to sign written informed consent

Where it's running

  • University of Texas Southwestern Medical Center
    Dallas, Texas, United States
    Recruiting
  • University of Texas Health Science Center at San Antonio
    San Antonio, Texas, United States
    Recruiting

Study contacts

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.