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Associated Trial(s):- NCT01715285 - A Randomized, Double-blind, Comparative Study of Abiraterone Acetate Plus Low-Dose Prednisone Plus Androgen Deprivation Therapy (ADT) Versus ADT Alone in Newly Diagnosed Subjects With High-Risk, Metastatic Hormone-naive Prostate Cancer (mHNPC)
- NCT02489318 - A Phase 3 Randomized, Placebo-controlled, Double-blind Study of Apalutamide Plus Androgen Deprivation Therapy (ADT) Versus ADT in Subjects With Metastatic Hormone-sensitive Prostate Cancer (mHSPC)
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Status: OngoingResearch Proposal
Project Title: Bellmunt Risk Score in mHSPC
Scientific Abstract:
Background and Objective
The Bellmunt Risk Score (BRS), a simple 3-factor model using ECOG performance status, hemoglobin, and liver metastases, is a validated prognostic tool for overall survival (OS) and radiographic progression-free survival (rPFS) in metastatic castration-resistant prostate cancer (mCRPC). This study aims to validate its prognostic utility in the earlier setting of metastatic hormone-sensitive prostate cancer (mHSPC).
Study Design and Participants
This will be a post-hoc analysis of pooled patient-level data from three Phase III mHSPC trials: ARASENS (NCT02799602), TITAN (NCT02489318), and LATITUDE (NCT01715285). All patients with available baseline data for the BRS components will be included.
Outcomes and Statistical Analysis
The primary outcome is OS, defined as time from randomization to death. The secondary outcome is PFS, time from randomization to progression, castration-resistance or death. The BRS (0-3 points) will be calculated for each patient. Kaplan-Meier method and log-rank tests will be used to compare survival by BRS group. To assess the score's independence as a predictor, a multivariable Cox proportional-hazards model will be fitted, adjusting for covariates like age, PSA, and treatment arm. A p-value <= 0.05 will be considered significant.
Brief Project Background and Statement of Project Significance:
The clinical course of metastatic prostate cancer is highly variable, making accurate prognosis a significant challenge. While complex prognostic models exist, there is a critical need for simple, accessible tools that can be used at the point of care to guide clinical decisions. The Bellmunt Risk Score (BRS) is a straightforward model based on three readily available clinical parameters: ECOG performance status (>=1), hemoglobin level (<10 g/dL), and the presence of liver metastases (1).
Our research group has previously validated the BRS in large, independent cohorts of patients with advanced, metastatic castration-resistant prostate cancer (mCRPC). In these studies, the BRS proved to be a robust and independent predictor of both overall survival (OS) and radiographic progression-free survival (rPFS) (2). We validated the prognostic utility recently in large-scale phase III trials (Publication under consideration, YODA #2024-0424).
However, the prognostic utility of this simple score in the earlier setting of metastatic hormone-sensitive prostate cancer (mHSPC) has not yet been established. This project aims to address that knowledge gap.
Statement of Project Significance
This research is significant because it seeks to validate a simple, no-cost, and globally applicable prognostic tool for a major patient population. If validated in mHSPC, the BRS will create immediately actionable, generalizable medical knowledge. The information gained will be used to materially enhance patient care in several ways:
Improved Clinical Decision-Making: It will provide clinicians with a tool to stratify patients into distinct risk groups at the time of diagnosis. This allows for more informed discussions about prognosis and can help guide the intensity of treatment, such as identifying high-risk patients who may benefit most from triplet therapies or enrollment in clinical trials.
Enhanced Patient Counseling: By providing a clearer prognostic outlook, the BRS will facilitate more transparent and realistic conversations between physicians, patients, and their families, strengthening the shared decision-making process.
Informing Future Research: The BRS can be incorporated into future clinical trial designs as a stratification factor, ensuring that treatment arms are balanced for risk and helping to identify which patient subgroups derive the most benefit from novel therapies.
Ultimately, this work will extend the utility of a proven prognostic score across the continuum of advanced prostate cancer, providing a valuable tool to personalize and improve care for men worldwide.
Specific Aims of the Project:
Aim 1: Validate the BRS for predicting Overall Survival (OS) in mHSPC.
Hypothesis: A higher baseline BRS (0-3) is associated with significantly shorter OS.
Aim 2: Evaluate the BRS for predicting Radiographic Progression-Free Survival (rPFS) in mHSPC.
Hypothesis: A higher baseline BRS is associated with a shorter time to radiographic disease progression or death.
Aim 3: Establish the BRS as an independent prognostic factor in mHSPC.
Hypothesis: The BRS will remain a robust and independent predictor of both OS and rPFS after adjusting for other established prognostic variables in multivariable models.
Study Design: Meta-analysis (analysis of multiple trials together)
What is the purpose of the analysis being proposed? Please select all that apply.: Confirm or validate previously conducted research on treatment effectiveness Participant-level data meta-analysis Meta-analysis using data from the YODA Project and other data sources
Software Used: R, RStudio
Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study:
This study will use Individual Patient Data (IPD) from three separate Phase III clinical trials.
Data Sources:
The data will be sourced from the following contributors and accessed through their respective platforms:
From the YODA Project (Johnson & Johnson):
TITAN trial (NCT02489318)
LATITUDE trial (NCT01715285)
From Bayer (via The Independent Review Panel):
ARASENS trial (NCT02799602)
Data Pooling and Analysis Platform:
We plan to pool the IPD from all three trials to create a large, combined cohort for this analysis. The entire IPD analysis will be conducted within the secure
Vivli research environment, which is equipped to handle and integrate data from multiple partners.
The study sample will be defined by applying the following criteria to the patient datasets from all three trials listed above:
Inclusion Criteria:
- Patients must have been successfully randomized in their respective parent trial (TITAN, LATITUDE, or ARASENS).
- Patients must have complete baseline data available for all three components required to calculate the Bellmunt Risk Score:
- ECOG Performance Status
- Hemoglobin level
- Liver metastasis status
Exclusion Criteria:
- Patients with missing baseline data for any one of the three Bellmunt Risk Score components will be excluded from the analysis, as the primary predictor variable cannot be calculated.
No other post-hoc demographic or clinical exclusion criteria will be applied.
Primary and Secondary Outcome Measure(s) and how they will be categorized/defined for your study:
Primary Outcome
Overall Survival (OS): This is the main outcome of the study. It is defined as the time elapsed from the date of patient randomization into their respective clinical trial until the date of death from any cause. This is a time-to-event outcome. Patients who have not died by the final data analysis cut-off will be censored at the date they were last confirmed to be alive.
Secondary Outcome
Progression-Free Survival: This is the key secondary outcome. It is defined as the time from the date of patient randomization until the first documented occurrence of either radiographic disease progression or castration-resistance or death from any cause, whichever comes first.
Main Predictor/Independent Variable and how it will be categorized/defined for your study:
The main predictor, or independent variable, for this research is the
Bellmunt Risk Score (BRS). It will be calculated for each patient at baseline and used as a categorical variable in all analyses.
Definition and Scoring
The BRS is an integer score ranging from 0 to 3, calculated by summing points assigned for the presence of three specific risk factors. One point is given for each of the following criteria met at baseline:
ECOG Performance Status >= 1: Patients with any level of functional impairment (not fully active).
Hemoglobin < 10 g/dL: Patients with anemia.
Presence of Liver Metastases: Patients whose cancer has spread to the liver.
Categorization
For the statistical analysis, the BRS will be treated as a categorical variable with four distinct levels, representing the total number of risk factors present for each patient:
BRS 0 (no risk factors)
BRS 1 (one risk factor)
BRS 2 (two risk factors)
BRS 3 (all three risk factors)
This categorization will allow for direct comparisons of survival outcomes between these distinct risk groups, for example, using Kaplan-Meier analysis.
Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study:
We'll include several well-established prognostic factors as covariates. This will allow us to assess the independent predictive value of the Bellmunt Risk Score (BRS) after accounting for these other important variables.
Age: This will be treated as a categorical variable. We will group patients into clinically relevant age brackets (e.g., 100 ng/mL. This approach was also used in our mCRPC validation study.
Disease Presentation: We will categorize patients based on when their metastatic disease was discovered. This will be a binary variable:
- De Novo: Metastases present at the initial diagnosis of prostate cancer.
- Metachronous: Metastases developed after prior treatment for localized disease.
Key Laboratory Values (ALP and LDH): Alkaline Phosphatase (ALP) and Lactate Dehydrogenase (LDH) are important biomarkers. They will be included as binary variables, categorized as normal versus elevated based on the upper limit of normal (ULN) for each respective laboratory test.
Treatment Arm: To control for the effect of the different therapies administered in the original trials, we will include the treatment arm as a categorical variable in our multivariable models. This will allow us to isolate the prognostic value of the BRS from the therapeutic effect of the study drug.
Statistical Analysis Plan:
This analysis involves 3 independent clinical trial datasets. To ensure transparency, we will first analyze these datasets separately before exploring any pooled analysis.
First, we'll summarize the baseline demographic and clinical characteristics of the patient cohort. Descriptive statistics for baseline demographics and clinical characteristics will be generated separately for each individual trial. Categorical variables (e.g., BRS group, ECOG PS, disease volume, presence of visceral metastases, treatment arm) will be presented as frequencies and proportions. Continuous variables (e.g., age, baseline PSA, ALP, LDH) will be summarized using medians and ranges. These characteristics will be described for the overall population and will also be stratified by the four Bellmunt Risk Score (BRS) groups (0, 1, 2, and 3). We will use the Chi-squared test for categorical variables and the Kruskal-Wallis test for continuous variables to compare patient characteristics across the BRS groups.
Bivariate and Survival Analysis
This part of the analysis will assess the direct relationship between the BRS and our primary and secondary time-to-event outcomes.
Kaplan-Meier Method: We will use the Kaplan-Meier method to estimate and generate survival curves for both Overall Survival (OS) and Radiographic Progression-Free Survival (rPFS). Separate curves will be plotted for each of the four BRS risk groups (0, 1, 2, and 3).
Log-Rank Test: The log-rank test will be used to statistically compare the survival distributions among the four BRS groups. This will directly test the hypothesis that the BRS effectively stratifies patients based on their survival outcomes.
Multivariable Analysis
To determine if the BRS is an independent prognostic factor, we will perform multivariable analyses. Cox Proportional-Hazards Model: A multivariable Cox regression model will be fitted for both OS and rPFS. This will allow us to assess the prognostic impact of the BRS while controlling for other important baseline variables. Model Covariates: The BRS will be included in the model as a categorical variable, with BRS=0 serving as the reference group. The model will be adjusted for other known prognostic factors, including:
- Age (categorical)
- Baseline PSA (categorical, e.g., >100 vs. <=100 ng/mL)
- Disease Volume (high vs. low)
- Disease Presentation (de novo vs. metachronous)
- Original treatment arm from the parent trial
The results will be presented as Hazard Ratios (HRs) with corresponding 95% Confidence Intervals (CIs) and p-values. We will also check the proportional hazards assumption for the models.
The primary analysis will use complete case analysis (listwise deletion).
As an exploratory step, we will conduct a two-stage meta-analysis. First, effect estimates (e.g., Hazard Ratios) will be calculated separately for each trial. Second, these estimates will be pooled using a random-effects model (DerSimonian and Laird method) to account for anticipated heterogeneity between the independent studies. We will assess statistical heterogeneity using the I^2 statistic and the chi^2 test for heterogeneity. Forest plots will be generated to visualize the study-specific and pooled estimates.
Narrative Summary:
The Bellmunt Risk Score (BRS) is a simple tool that predicts survival in men with advanced, hormone-resistant prostate cancer (mCRPC). It uses three common clinical factors: patient well-being (ECOG PS), concentration of the oxygen-carrying molecule within the blood (hemoglobin), and liver metastases. Our previous research has validated this score in mCRPC patients.
This new research aims to test if the BRS is also a valid prognostic tool for men at an earlier stage of disease: metastatic hormone-sensitive prostate cancer (mHSPC). We will analyze data from three large clinical trials (ARASENS, TITAN, LATITUDE) to see if this easy-to-use score can help predict outcomes in this different patient group. This could provide a valuable tool for doctors and patients to better understand prognosis and guide care.
Project Timeline:
Target Analysis Start Date: 01/25/2026
Estimated Analysis Completion Date: 01/25/2027
Estimated Manuscript Draft Date: 05/01/2027
Estimated Submission for Publication: 08/01/2027
Estimated Results Reported: 10/01/2027
Dissemination Plan: The primary method of dissemination will be through the publication of a manuscript in a high-impact, peer-reviewed medical journal. We will target leading international journals in the fields of oncology and urology, such as European Urology Oncology. We will adhere to open-access policies to ensure the findings are broadly accessible to researchers and clinicians globally.
Bibliography:
(1) Bellmunt J, Choueiri TK, Fougeray R, et al. Prognostic Factors in Patients With Advanced Transitional Cell Carcinoma of the Urothelial Tract Experiencing Treatment Failure With Platinum-Containing Regimens. J Clin Oncol. 2010;28(11):1850-5.
(2) Büttner T, Klümper N, Weiten R, et al. Bellmunt risk score as a survival predictor in patients with metastatic castration-resistant prostate cancer. The Prostate. 2024;84(12):1119-27.