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Associated Trial(s):- 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)
- NCT01946204 - A Multicenter, Randomized, Double-Blind, Placebo-Controlled, Phase III Study of ARN-509 in Men With Non-Metastatic (M0) Castration-Resistant Prostate Cancer
- NCT00638690 - A Phase 3, Randomized, Double-Blind, Placebo-Controlled Study of Abiraterone Acetate (CB7630) Plus Prednisone in Patients With Metastatic Castration-Resistant Prostate Cancer Who Have Failed Docetaxel-Based Chemotherapy
- 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)
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Status: OngoingResearch Proposal
Project Title: Impact of Body Mass Index on Survival Outcomes in Patients With castration sensitive prostate cancer and castration resistant prostate cancer
Scientific Abstract:
Background
The prognostic role of body mass index (BMI) in advanced prostate cancer remains unclear, with conflicting evidence reported across disease states. While an "obesity paradox" has been suggested in some settings, its consistency and clinical relevance remain uncertain.
Objective
To evaluate the prognostic and potential predictive impact of baseline BMI across different stages of advanced prostate cancer using individual patient data from multiple phase III trials.
Study Design
This is a retrospective, post hoc analysis of four randomized phase III trials: TITAN trial, LATITUDE trial, SPARTAN trial, and COU-AA-301 trial. Analyses will be conducted separately within each trial.
Participants
Patients enrolled in the respective trials with available baseline BMI data were included. BMI was categorized according to standard definitions as underweight, normal weight, overweight, and obese.
Primary and Secondary Outcome Measure(s)
The primary outcome is overall survival (OS). Secondary outcomes include radiographic progression-free survival (rPFS) and metastasis-free survival (MFS; assessed in SPARTAN).
Statistical Analysis
Cox proportional hazards models will be used to evaluate the association between BMI categories and clinical outcomes. Multivariable analyses will be performed to adjust for relevant baseline covariates. Interaction analyses will be conducted to assess whether BMI modified treatment effects. All analyses will be performed within each individual trial.
Brief Project Background and Statement of Project Significance:
Obesity has been increasingly recognized as an important factor influencing cancer biology and clinical outcomes. In prostate cancer, however, the role of body mass index (BMI) remains controversial. While some studies suggest that higher BMI is associated with worse oncologic outcomes due to adverse metabolic and hormonal effects, others have reported a paradoxical association between overweight or obesity and improved survival, particularly in patients with advanced disease. These inconsistent findings may reflect differences in disease state, treatment exposure, and study design.
To date, most investigations of BMI in prostate cancer have been limited to single-cohort analyses or retrospective datasets, often lacking standardized treatment and comprehensive clinical annotation. As a result, the prognostic and predictive value of BMI across the continuum of advanced prostate cancer--from metastatic castration-sensitive to castration-resistant disease--remains unclear.
The availability of individual patient data from multiple large randomized phase III trials, including TITAN trial, LATITUDE trial, SPARTAN trial, and COU-AA-301 trial, provides a unique opportunity to address this knowledge gap. These trials represent diverse disease states and treatment settings, enabling a comprehensive evaluation of BMI in a controlled and well-annotated context.
The significance of this study lies in its ability to clarify whether BMI serves as a consistent prognostic factor or a modifier of treatment effect across different stages of advanced prostate cancer. Understanding the role of BMI may improve risk stratification, inform treatment decision-making, and generate insights into the biological mechanisms underlying obesity-related differences in cancer outcomes. Moreover, this study has the potential to establish BMI as a readily available and clinically applicable biomarker in the management of advanced prostate cancer.
Specific Aims of the Project:
The overall objective of this study is to evaluate the prognostic and predictive role of baseline body mass index (BMI) across the continuum of advanced prostate cancer using individual patient data from randomized phase III trials.
Aim 1: To determine the prognostic impact of baseline BMI on clinical outcomes.
We will evaluate the association between baseline BMI and survival outcomes, including overall survival (OS), radiographic progression-free survival (rPFS), and metastasis-free survival (MFS), within each trial. Multivariable Cox proportional hazards models will be used to assess whether BMI is an independent prognostic factor after adjusting for established clinical covariates.
Aim 2: To assess whether BMI modifies the treatment effect of systemic therapies.
We will investigate the interaction between BMI and treatment allocation in each trial to determine whether BMI influences the efficacy of androgen receptor--targeted therapies. Interaction terms will be incorporated into multivariable models to evaluate BMI as a predictive biomarker.
Aim 3: To evaluate the consistency of BMI effects across different disease states.
We will compare the association between BMI and clinical outcomes across metastatic castration-sensitive, non-metastatic castration-resistant, and metastatic castration-resistant prostate cancer settings. Trial-specific results will be synthesized to assess whether the impact of BMI is consistent or context-dependent across disease stages.
Study Design: Individual trial analysis
What is the purpose of the analysis being proposed? Please select all that apply.: Research on clinical prediction or risk prediction
Software Used: R
Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study:
Data Source
This study will use individual patient-level data from four randomized phase III clinical trials in advanced prostate cancer: TITAN trial, LATITUDE trial, SPARTAN trial, and COU-AA-301 trial. These trials represent distinct disease states, including metastatic castration-sensitive prostate cancer (mCSPC), non-metastatic castration-resistant prostate cancer (nmCRPC), and metastatic castration-resistant prostate cancer (mCRPC), and provide well-annotated clinical data with standardized outcome definitions.
Inclusion Criteria
Patients will be included if they meet the following criteria:
Enrollment in one of the four specified phase III trials
Availability of baseline body mass index (BMI), calculated from recorded height and weight at study entry
Availability of key baseline clinical variables required for multivariable adjustment (e.g., age, ECOG performance status, baseline PSA)
Availability of follow-up data for at least one relevant clinical outcome (e.g., OS, rPFS, or MFS, depending on the trial)
Exclusion Criteria
Patients will be excluded based on the following criteria:
Missing baseline BMI data or implausible BMI values (e.g., extreme outliers)
Missing essential outcome data (e.g., no survival follow-up)
Missing key covariates required for adjusted analyses, if not amenable to imputation
Withdrawal of consent or exclusion from the original trial analysis population
Duplicate or inconsistent records
Additional Considerations
Analyses will be conducted separately within each trial to account for differences in disease state and study design. No pooling of raw data across trials will be performed without appropriate statistical adjustment. Sensitivity analyses may be conducted to evaluate the impact of missing data and alternative BMI categorizations.
Primary and Secondary Outcome Measure(s) and how they will be categorized/defined for your study:
Primary Outcome
Overall Survival (OS):
Overall survival will be defined as the time from randomization to death from any cause. Patients who are alive at the time of data cutoff will be censored at the date of last known follow-up. OS will be analyzed as a time-to-event outcome using Cox proportional hazards models.
Secondary Outcomes
1. Radiographic Progression-Free Survival (rPFS):
rPFS will be defined as the time from randomization to radiographic disease progression or death from any cause, whichever occurs first, according to the protocol-specific criteria of each trial. Patients without an event will be censored at the last adequate radiographic assessment.
2. Metastasis-Free Survival (MFS):
In the non-metastatic castration-resistant prostate cancer setting (SPARTAN trial), MFS will be defined as the time from randomization to the development of distant metastasis or death from any cause, consistent with the original trial definition.
3. Time to Castration-Resistant Prostate Cancer (CRPC):
In metastatic castration-sensitive prostate cancer trials (TITAN trial and LATITUDE trial), time to CRPC will be defined according to protocol-specific criteria, including biochemical and/or radiographic progression under continuous androgen deprivation therapy.
4. PSA-Based Outcomes (Exploratory, if available):
Time to PSA progression
PSA response (e.g., >=50% decline from baseline)
Definitions will follow the original trial protocols where applicable.
Outcome Categorization and Analysis
All primary and secondary outcomes will be analyzed as time-to-event variables. Hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) will be estimated using Cox proportional hazards models. Analyses will be conducted separately within each trial to account for differences in disease state and endpoint definitions.
Main Predictor/Independent Variable and how it will be categorized/defined for your study:
The primary independent variable in this study is baseline body mass index (BMI).
Definition of BMI
BMI will be calculated using baseline measurements of body weight and height recorded at trial enrollment, according to the standard formula: weight (kg) divided by height squared (m^2). Baseline BMI will be treated as a pre-treatment variable.
Categorization of BMI (Primary Approach)
BMI will be categorized according to the World Health Organization (WHO) classification as follows:
<18.5 kg/m^2: Underweight
18.5--24.9 kg/m^2: Normal weight (reference group)
25.0--29.9 kg/m^2: Overweight
>=30.0 kg/m^2: Obese
If necessary due to sample size distribution, categories may be combined (e.g., <25 vs >=25 kg/m^2).
Alternative Modeling Approaches (Secondary Analyses)
To comprehensively assess the relationship between BMI and clinical outcomes, additional analyses will include:
BMI as a continuous variable (per 5 kg/m^2 increase)
Non-linear modeling using restricted cubic splines (if supported by sample size)
Handling of Missing or Implausible Values
Patients with missing baseline BMI data will be excluded from the primary analysis. Implausible BMI values (extreme outliers) will be assessed and excluded or winsorized as appropriate. Sensitivity analyses may be performed to evaluate the impact of missing data.
Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study:
Other Variables of Interest
In addition to baseline BMI, clinically relevant covariates will be included for multivariable adjustment.
Demographic Variable
Age:
Analyzed as a continuous variable and, if appropriate, categorized by median or clinically relevant cutoffs.
Clinical Variables
ECOG Performance Status:
Categorized as 0 vs 1.
Gleason Score:
Categorized as <=7 vs >=8 (or according to available categories).
Disease Burden / Extent:
For mCSPC trials, defined as high vs low volume (CHAARTED criteria) or high-risk features per protocol.
For mCRPC, presence of visceral metastases (yes vs no).
PSA Doubling Time:
Included for nmCRPC as continuous or categorized, depending on availability.
Prior Docetaxel Use:
Categorized as yes vs no, where applicable.
Laboratory Variables
Baseline PSA:
Analyzed as continuous (log-transformed if appropriate) and optionally categorized.
Alkaline Phosphatase (ALP):
Continuous and/or categorized by upper limit of normal.
Hemoglobin:
Continuous; anemia may be defined using standard thresholds.
Lactate Dehydrogenase (LDH):
Included where available, particularly in mCRPC.
Treatment-Related Variables
Treatment Allocation:
Categorized by randomized treatment group.
Additional Consideration
Variable definitions will follow each trial protocol. Covariate selection will be based on clinical relevance and data availability, and analyses will be conducted separately within each trial.
Statistical Analysis Plan:
All analyses will be conducted using individual patient data from TITAN trial, LATITUDE trial, SPARTAN trial, and COU-AA-301 trial. Analyses will be performed separately within each trial to account for differences in disease state and study design.
Descriptive Analysis
Baseline characteristics will be summarized by BMI categories using appropriate descriptive statistics. Continuous variables will be presented as median (interquartile range) or mean (standard deviation), and categorical variables as frequencies and percentages. Group comparisons will be performed using chi-square tests or ANOVA, as appropriate.
Primary Analysis
The association between BMI and overall survival (OS) will be evaluated using Cox proportional hazards models. Hazard ratios (HRs) and 95% confidence intervals (CIs) will be estimated.
Multivariable models will adjust for clinically relevant covariates, including age, ECOG performance status, disease burden, baseline PSA, alkaline phosphatase, hemoglobin, and other trial-specific variables.
Secondary Analyses
Associations between BMI and secondary outcomes (rPFS, MFS, and time to CRPC) will be analyzed using Cox models, consistent with the primary analysis approach.
Modeling of BMI
BMI will be analyzed primarily as a categorical variable. Secondary analyses will include BMI as a continuous variable (per 5 kg/m^2 increase). Non-linear associations will be explored using restricted cubic spline models, if supported by sample size.
Interaction Analysis
To evaluate the predictive role of BMI, interaction terms between BMI and treatment allocation will be included in multivariable models. Statistical significance of interaction terms will be assessed to determine whether BMI modifies treatment effects.
Sensitivity Analyses
Sensitivity analyses may include:
Alternative BMI categorizations
Exclusion of extreme BMI values
Analyses using complete cases and, if appropriate, multiple imputation for missing covariates
Between-Trial Comparison
Results will be compared qualitatively across trials. If appropriate, effect estimates may be synthesized using meta-analytic approaches. No direct pooling of raw data across trials will be performed without appropriate adjustment.
Statistical Considerations
All tests will be two-sided, with a significance level of 0.05. Proportional hazards assumptions will be assessed using standard methods (e.g., Schoenfeld residuals). Analyses will be conducted using validated statistical software.
Narrative Summary:
Prostate cancer that has spread beyond the prostate is referred to as advanced prostate cancer. Depending on its response to hormone therapy, it is classified as hormone-sensitive or castration-resistant prostate cancer (CRPC). Clinical trials such as TITAN and LATITUDE in hormone-sensitive disease and SPARTAN and COU-AA-301 in CRPC have demonstrated the survival benefit of novel therapies.
Body mass index (BMI) is a simple measure based on height and weight. An "obesity paradox" has been reported in several cancers, but its role in advanced prostate cancer remains unclear.
We analyzed individual patient data from multiple trials to assess whether BMI is associated with survival and modifies treatment benefit across disease states, which may help improve risk stratification and guide personalized treatment.
Project Timeline:
The projected timeline for the study is approximately 6 months from data access to manuscript submission.
Month 1: Data Access and Preparation
Obtain and verify access to individual patient data from all trials
Perform data cleaning, harmonization, and variable definition
Define analysis cohorts within each trial
Months 2--3: Primary Analyses
Conduct descriptive analyses of baseline characteristics by BMI categories
Perform primary analyses evaluating the association between BMI and overall survival (OS) using multivariable Cox models within each trial
Months 4--5: Secondary and Sensitivity Analyses
Analyze secondary outcomes (rPFS, MFS, time to CRPC)
Conduct interaction analyses to assess BMI as a treatment effect modifier
Perform sensitivity analyses (alternative BMI categorization, missing data assessment, and continuous modeling)
Month 6: Integration and Manuscript Preparation
Synthesize results across trials and perform cross-trial comparisons
Prepare figures and tables
Draft and finalize the manuscript for submission
Dissemination Plan:
The findings of this study will be disseminated through multiple channels to maximize scientific and clinical impact.
Peer-Reviewed Publication:
The primary results will be submitted to a high-impact, peer-reviewed journal in oncology or urology (prostate cancer and prostatic diseases, european urology oncology).
Scientific Conferences:
Results will be presented at major international conferences, including ASCO Annual Meeting, ESMO Congress, and EAU Congress, to ensure broad visibility among clinicians and researchers.
Bibliography:
The obesity paradox in metastatic castration-resistant prostate cancer A. Martini, Q. N. Shah, N. Waingankar, J. P. Sfakianos, C. K. Tsao, A. Necchi, et al. Prostate Cancer Prostatic Dis 2022 Vol. 25 Issue 3 Pages 472-478