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NCT05825950 | RECRUITING | Non-muscle-invasive Bladder Cancer

Artificial Intelligence Prediction Tool in Non-muscle Invasive Bladder Cancer (NMIBC)
Sponsor:

University of Texas Southwestern Medical Center

Information provided by (Responsible Party):

Solomon Woldu

Brief Summary:

This is a multi-center study and the aim is to develop and validate an Artificial Intelligence (AI) -based histologic analysis tool to predict responsiveness to intravesical Bacillus Calmette-Guérin (BCG) and intravesical chemotherapy in intermediate and high-risk non-muscle invasive bladder cancer patients.

Condition or disease

Non-muscle-invasive Bladder Cancer

Detailed Description:

Analysis will be performed on the most recent Transurethral resection of bladder tumor (TURBT) histologic specimen obtained prior to BCG induction and on histologic specimens at time of recurrence after BCG induction. This stratification is of potential utility to clinicians for patient counseling purposes, for the identification of patients likely to benefit from induction or re-induction with BCG, and for consideration of alternative treatment strategies including clinical trials, chemotherapy, or cystectomy. Additionally, there is currently no reliable tool for identifying which NMIBC patients are most likely to benefit from adjuvant BCG versus intravesical chemotherapy. This is of current relevance in the management of Intermediate-risk (IR) NMIBC since both BCG and chemotherapy are first-line treatment options and will likely become of increasing relevance in High-risk (HR) NMIBC as efficacious first-line alternatives to intravesical BCG are introduced into clinical practice. In the proposed prospective study, the study team also aims to develop and then validate an AI-based histologic analysis tool for clinicians that is intended to predict recurrence following intravesical chemotherapy in IR and HR NMIBC patients.

Study Type : OBSERVATIONAL
Estimated Enrollment : 600 participants
Official Title : Predicting Outcomes in Intermediate and High-risk Non-muscle Invasive Bladder Cancer Using Automated Analysis of Digital Pathology Data
Actual Study Start Date : 2024-01-25
Estimated Primary Completion Date : 2026-09
Estimated Study Completion Date : 2026-09

Information not available for Arms and Intervention/treatment

Ages Eligible for Study: 18 Years to 99 Years
Sexes Eligible for Study: ALL
Accepts Healthy Volunteers:
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
Artificial Intelligence Prediction Tool in Non-muscle Invasive Bladder Cancer (NMIBC)

Location Details

NCT05825950

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Locations

RECRUITING

United States, Texas

University of Texas Southwestern Medical Center

Dallas, Texas, United States, 75390-9164