Whole-Food Plant-Based Diet to Control Weight and MetaboInflammation in Overweight/Obese Men With Prostate Cancer

N/AActive Not RecruitingNCT05471414

Weill Medical College of Cornell University76 enrolled

Overview

The study is comparing the effect on weight of providing home-delivered whole-food, plant-based meals versus standard, general nutritional counseling to men with prostate cancer on androgen-deprivation therapy (ADT).

Prostate cancer is the most common cancer diagnosis for men in the United States. For patients with advanced or recurrent disease, ADT has is the cornerstone of systemic treatment. Overall, almost half of prostate cancer patients will undergo ADT at some point during their treatment. Unfortunately, ADT has metabolic side effects, including weight gain, central adiposity, and insulin resistance. This study is a multi-site randomized phase II trial comparing a home-delivered whole food, plant-based diet (WFPBD) with specialized behavioral coaching to standard dietary intervention with general nutritional counseling to assess the efficacy of a WFPBD in promoting weight loss in overweight/obese men receiving ADT. The home-delivered WFPBD will be for 28 days with 12 meals a week followed by 28 days with 6 meals a week; followed by self-prepared WFPBD for 18 weeks (for a total of 26 weeks). The study hypothesis is that a WFPBD will decrease body weight and decrease systemic metabo-inflammation in overweight/obese men (BMI \> 27) with prostate cancer receiving ADT. Secondary objectives will be to assess the effects of a WFPBD on adiposity, markers of inflammation (hsCRP, IL-6), metabolism (insulin, glucose, leptin, adiponectin), and fecal microbiota that may contribute to prostate cancer progression; to assess the effects of a WFPBD on quality of life; and to assess the durability of any observed effect (weight, adiposity, markers of inflammation and metabolism, fecal microbiota) of the intervention after cessation of the meal-delivery service.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

TREATMENT

Masking

NONE

Enrollment

Conditions

Prostate Cancer

Interventions

Whole-food, Plant-Based DietBEHAVIORAL

Pre-packaged, freshly made plant-based meals (provided by either Plantable or CookUnity) will be delivered weekly to participants' homes for 8 weeks. Meals are made with whole ingredients including whole grains, vegetables, legumes, nuts and seeds. Added sugar, animal-based products, refined grains, and processed foods are not used in any meal. Participants will be coached via phone calls, SMS, emails, and the app throughout the intervention to prepare meals in accordance with the diet. Participants will have access to a Registered Dietitian. During the first 4 weeks, 12 meals/week will be provided to participants; followed by 6 meals/week for the next 4 weeks; followed by 18 weeks where participants will continue to receive coaching, but will be expected to make all their own whole-food, plant-based meals with staff assistance available.

General Nutritional CounselingBEHAVIORAL

All study participants will receive consult with a Registered Dietitian at the Baseline visit and visit 1 study assessments. After visit 1, study participants assigned to the general nutritional counseling arm will receive an additional in-person or telehealth consultation with a Registered Dietitian that will consist of identification and counseling to improve diet quality and achieve a healthy body weight consistent with American Cancer Society guidelines. Study participants in the control group will continue to receive general nutritional counseling and education with weekly scheduled telephone consultations with a Registered Dietitian for the first 4 weeks of the study period. For the remainder of the study period, they will receive counseling and education from Registered Dietitians via monthly scheduled phone calls.

Eligibility

Sex: MALEMin age: 45 YearsMax age: 99 Years

Medical Language ↔ Plain English

Inclusion Criteria 1. Histologically or cytologically confirmed adenocarcinoma of the prostate 2. Receiving androgen deprivation therapy (ADT) with an LHRH/GnRH analogue (agonist/antagonist); or have undergone bilateral orchiectomy. Patients with localized prostate cancer, non-metastatic castrate resistant prostate cancer (CRPC), metastatic hormone sensitive prostate cancer and metastatic CRPC are all eligible. 3. On ADT for at least 24 weeks pre-study with anticipation of at least 26 more weeks of therapy from the date of initiation of the dietary intervention 4. Patients receiving an anti-androgen (including, but not limited to drugs such as bicalutamide, abiraterone, enzalutamide or apalutamide) are eligible if they have been on therapy for at least 3 months and plan to continue for the duration of the study 5. At least 3 months post completion of chemotherapy and/or radiation 6. Bone resorptive agents such as bisphosphanates and denosumab are allowed. 7. Testosterone level \<50 ng/dL 8. Age ≥ 45 years 9. BMI ≥ 27 10. ECOG performance status of 0 to 1 11. Adequate organ and marrow function, based upon meeting all of the following laboratory criteria: 1. White blood cell count ≥ 2500/mm3 (≥ 2.5 GI/L) 2. Platelets ≥ 100,000/mm3 (≥ 100 GI/L) without transfusion 3. Hemoglobin ≥ 9 g/dL (≥ 90 g/L) 4. Alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin ≤ 2x ULN (or for subjects with Gilbert's disease direct bilirubin WNL) Note: Subjects with elevated alanine aminotransferase (ALT) or aspartate aminotransferase (AST) (up to 5x ULN) will be eligible if elevation is felt to be due to fatty liver disease related to obesity. 5. Serum albumin ≥ 2.8 g/dl 12. Willingness and ability to comply with all study-related procedures 13. Capable of understanding and complying with the protocol requirements and must have signed the informed consent document Exclusion Criteria 1. Insulin-dependent diabetes mellitus 2. Nut or legume allergy, gluten intolerance or celiac disease 3. Currently consuming a vegetarian or vegan diet 4. Concurrent participation in other nutrition or weight loss programs 5. Expected changes in chronic medications, including statins or oral diabetes medication during the study period (including a change in medication dosage) 6. Expected radiation, chemotherapy, bone resorptive agents or anti-androgen within 2 months of beginning the diet intervention 7. Expected changes in exercise patterns during the study period 8. Psychiatric illnesses or social situations that would limit compliance with study requirements, including a living situation that does not allow for the delivery of Plantable prepared meals, or the inability or lack of equipment to perform basic cooking tasks 9. Known history of electrolyte imbalance or micronutrient deficiency, e.g., magnesium, cobalamin 10. Ongoing use of warfarin anticoagulants 11. Diagnosed, active inflammatory bowel disease 12. Inability to receive Emails or have a smart phone

Locations (3)

Johns Hopkins Sidney Kimmel Comprehensive Cancer Center

Baltimore, Maryland, United States

Weill Cornell Medicine

New York, New York, United States

Columbia University Medical Center

New York, New York, United States

Outcomes

Primary Outcomes

Change in weight from baseline to 4 weeks post-randomization

All participates will be weighed at the baseline visit and at 4 weeks. A two-sample t-test will be used to compare the average change in weight (baseline weight minus 4-week weight).

Time frame: Baseline; 4 weeks post-randomization

Secondary Outcomes

Change in levels of serum hsCRP from baseline to 4, 8, and 26 weeks post-randomization

hsCRP is being measured as a marker of inflammation. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of serum IL-6 from baseline to 4, 8, and 26 weeks post-randomization

IL-6 is being measured as a marker of inflammation. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Data from ClinicalTrials.gov

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Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of serum glucose from baseline to 4, 8, and 26 weeks post-randomization

Glucose is being measured as a marker of insulin resistance. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of serum leptin from baseline to 4, 8, and 26 weeks post-randomization

Leptin is being measured as a marker of metabolism. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of serum adiponectin from baseline to 4, 8, and 26 weeks post-randomization

Adiponectin is being measured as a marker of metabolism. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of serum direct LDL from baseline to 4, 8, and 26 weeks post-randomization

Direct LDL is being measured as a marker of cardiovascular risk. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of HDL from baseline to 4, 8, and 26 weeks post-randomization

HDL is being measured as a marker of cardiovascular risk. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of fasting triglycerides from baseline to 4, 8, and 26 weeks post-randomization

Fasting triglycerides are being measured as a marker of cardiovascular risk. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in levels of serum insulin from baseline to 4, 8, and 26 weeks post-randomization

Insulin is being measured as a marker of insulin resistance. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in FACT-P score as an indicator of quality of life from baseline to 4, 8, and 26

The FACT-P is a self-administered questionnaire that asks patients with prostate cancer about well-being in different aspects of life. It provides different statements and patients record how much they agree or disagree on a Likert scale. FACT-P scores will be calculated based on the participant responses to the questionnaire given at baseline, 4 weeks, 8 weeks, and 26 weeks. Scores can range from 0 to 156 with higher scores indicating a higher quality of life. Mean scores for all participants in each arm will be calculated and compared using a two-way ANOVA.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in mean measures of body fat percentage, as determined by DEXA scan, from baseline to 4 and 26 weeks post-randomization

All participants will receive a DEXA scan at baseline, 4 weeks, and 26 weeks to determine body fat percentage. Average body fat percentage will be calculated for each study arm and compared using a two-way ANOVA.

Time frame: Baseline; 4 weeks and 26 weeks post-randomization

Change in the diversity of the fecal microbiome from baseline to 4 and 26 weeks post-randomization

For the microbiome data obtained through 16S rRNA sequencing, DADA2 based approach will be used to generate the counts data for the amplicon sequence variants (ASVs). Taxonomy assignment will be based on commonly used reference databases. Alpha diversity such as the Shannon index will be calculated for each sample and summarized and evaluated similarly as other continuous endpoints. Between sample composition differences will be assessed based on beta diversity measures such as weighted/unweighted Unifrac and Bray-Curtis distances and evaluated using PERMANOVA type of approaches such as adonis. Differential abundance analysis will be carried out using DESeq2 or a non-parametric approach such as Wilcoxon signed rank test on the data with variance stabilizing transformation.

Time frame: Baseline; 4 weeks and 26 weeks post-randomization

Change in mean fat free body mass, as determined by DEXA scan, from baseline to 4 and 26 weeks post-randomization.

All participants will receive a DEXA scan at baseline, 4 weeks, and 26 weeks to determine fat free body mass. Average fat free body mass will be calculated for each study arm and compared using a two-way ANOVA.

Time frame: Baseline; 4 weeks and 26 weeks post-randomization

Change in mean body mass including fat, as determined by DEXA scan, from baseline to 4 and 26 weeks post-randomization.

All participants will receive a DEXA scan at baseline, 4 weeks, and 26 weeks to determine body mass including fat. Average body mass including fat will be calculated for each study arm and compared using a two-way ANOVA.

Time frame: Baseline; 4 weeks and 26 weeks post-randomization

Change in levels of hemoglobin A1c from baseline to 4, 8, and 26 weeks post-randomization

Hemoglobin A1C is being measured as a marker of insulin resistance. All participants will have a blood draw at baseline, and 4, 8, and 26 week visits. Serum marker levels will be measured in a CLIA-approved laboratory. Graphical displays will be used to illustrate the change in values over time for continuous measures. There will be a line for each patient. A different color will be used for each treatment group. The average at each timepoint for each group will be computed. A two-way ANOVA will be used (or Kruskal-Wallis test if more appropriate) will be used to determine whether there are changes in the measures over time as well as between groups. The first analysis will be to determine whether there is a significant interaction between time and treatment. Subsequent analyses will depend on whether the interaction is statistically significant or not. Effect sizes will be summarized with point estimates and 95% confidence intervals.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization

Change in BMI from baseline to 4, 8, and 26 weeks post-randomization.

Height (in meters) and weight (in kilograms) will be measured at baseline, 4 weeks, 8 weeks, and 26 weeks. BMI (kg/m\^2) will be derived from these measures. Average BMI will be calculated for each study arm and compared using a two-way ANOVA.

Time frame: Baseline; 4, 8, and 26 weeks post-randomization