Machine Learning-Based Prediction of BCG Response in High-Risk Non-Muscle Invasive Bladder Cancer Patients

NCT ID: NCT05332353

Last Updated: 2022-04-18

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 100 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-04-01
• Study Completion Date: 2023-12-01

Brief Summary

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.

Detailed Description

Introduction:

In the era of BCG shortage and BCG-associated morbidity, the development of prognostic models remains a never-ending topic of research to predict Non Muscle Invasive Bladder Cancer (NMIBC) patients of high risk of BCG unresponsiveness; hence optimize their treatment, achieve survival benefit with minimal long-term morbidity, and prioritize patients with expected good response.

Aim of the study:

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.

Patients and Methods:

Patients with diagnosed bladder tumors seen through the outpatient clinic in the urology department (Urology and Nephrology Center, Mansoura University, Egypt) will be assessed for eligibility to the study and inclusion criteria (Ability to give informed consent, High-risk NMIBC, Good performance status and No prior history of BCG intravesical therapy) then asked to participate in this prospective study via an informed consent form.

All patients will be thoroughly evaluated by medical history and physical examination, routine laboratory investigations (including cytology and N/L ratio), mpMRI lower abdomen and pelvis and molecular markers evaluation (Urinary IL-10 levels by solid phase ELISA Immunoassay, Reverse Transcriptase-quantitative Polymerase Chain Reaction (RT qPCR) technology-based assessment of serum TNF-a and Chromosomal anomalies using FISH technique) . Then, all patients will be managed by cystoscopy and initial complete TURBTfollowed by re-staging TUR biopsy 2-6 weeks later on. All patients will be discharged after the re-staging TUR to receive adjuvant intravesical BCG therapy in the outpatient clinic and to be followed-up according to the predetermined protocol. If any patient has new tumour/positive cytology by outpatient cystoscopy after ICR, he will be readmitted to our center and subjected to cystoscopic-guided biopsy. If high grade or CIS proven pathology, BCG unresponsiveness will be considered. Univariate and multivariate analysis will be performed to identify independent prognostic factors associated with BCG unresponsiveness. After that, each of these factors will have a score according to its regression coefficient. Then, these independent factors with their scores will be summed into Artificial Neural Network-based prediction model for predicting BCG unresponsiveness.

Sample size and statistical analysis:

Sample size is calculated for the final analysis 6 months post initial TURBT with α = 0.05 (adjusted for the primary outcome which is BCG unresponsiveness) and a power of 80% (β = 0.20). A sample size of 45 patients per group should be available for final analysis. Since an overall dropout rate of about 10% is expected, 50 patients per group have to be recruited. All statistical analyses will be performed using ABM SPSS program version 20.

Ethical considerations:

A fully informed consent will be taken from all patients. The study will approved by the local ethical committee IRB (Institutional review board), faculty of medicine, Mansoura University. Patients will be managed according to Declaration of Helsinki.

Conditions

Non-Muscle Invasive Bladder Cancer

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

BCG responders

Non-muscle invasive bladder cancer patients who do not have T1/Ta HG recurrence within 6 months of adequate BCG therapy.

Bacillus Calmette-Guerin

Intervention Type: DRUG

Bacillus Calmette-Guerin (BCG) is immunotherapy to prevent recurrence and progression of non muscle invasive bladder cancer.

BCG non-responders

Non-muscle invasive bladder cancer patients who have T1/Ta HG recurrence within 6 months of adequate BCG therapy or CIS within 12 months of BCG therapy

Bacillus Calmette-Guerin

Intervention Type: DRUG

Bacillus Calmette-Guerin (BCG) is immunotherapy to prevent recurrence and progression of non muscle invasive bladder cancer.

Interventions

Bacillus Calmette-Guerin

Bacillus Calmette-Guerin (BCG) is immunotherapy to prevent recurrence and progression of non muscle invasive bladder cancer.

Intervention Type: DRUG

Other Intervention Names

BCG

Eligibility Criteria

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.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Mansoura University

OTHER

Sponsor Role: lead

Responsible Party

Osama Ezzat Mohammed Attia

principal investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Osama Ezzat, Ass. lect.

Role: PRINCIPAL_INVESTIGATOR

Urology and Nephrology Center , Mansoura university

Locations

Urology and Nephrology Center

Al Mansurah, Outside U.S./Canada, Egypt

Site Status: RECRUITING

Countries

Egypt

Central Contacts

Osama Ezzat, Ass. lect.

Role: CONTACT

osamaezzat1990@gmail.com

01023990432

Facility Contacts

Osama Ezzat, Ass. lect.

Role: primary

osamaezzat1990@gmail.com

01023990432

Other Identifiers

MD.22.03.622

Identifier Type: -

Identifier Source: org_study_id