Outcome
Type |
Measure |
Description |
Time frame |
Safety issue |
Primary |
Consent rate |
Will calculate the rates, frequencies, and 90% confidence intervals (CIs) of means by group, as well as for the differences between intervention groups as applicable. Will also examine demographic factors such as age, marital status, number of children, and employment status as they related to feasibility in terms of consent, adherence to the intervention, and retention in the study. |
Up to 1 year |
|
Primary |
Treatment group compliance rate |
Will be defined as attending at least 50% of sessions during the intervention delivery weeks (first 26 weeks) in the integrative oncology (IO) group. Will calculate the rates, frequencies, and 90% CIs of means by group, as well as for the differences between intervention groups as applicable. Will also examine demographic factors such as age, marital status, number of children, and employment status as they related to feasibility in terms of consent, adherence to the intervention, and retention in the study. |
Up to 1 year |
|
Primary |
Retention rate |
Will calculate the rates, frequencies, and 90% CIs of means by group, as well as for the differences between intervention groups as applicable. Will also examine demographic factors such as age, marital status, number of children, and employment status as they related to feasibility in terms of consent, adherence to the intervention, and retention in the study. |
Up to 1 year |
|
Secondary |
Group differences over time in biological pathways |
Will first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use generalized linear mixed model regression (GLMM). Separate sets of analyses will be conducted for each criterion variable. |
Up to 1 year |
|
Secondary |
Group differences over time in dietary patterns |
Will first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable. |
Up to 1 year |
|
Secondary |
Group differences over time in fitness levels |
Will first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable. |
Up to 1 year |
|
Secondary |
Group differences over time in percent body fat |
Will first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable. |
Up to 1 year |
|
Secondary |
Group differences over time in anthropometrics |
Will first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable. |
Up to 1 year |
|
Secondary |
Gut microbiome |
Sequence processing and analysis will be performed using specific software for comparison and analysis of microbial communities. |
Up to 1 year |
|