Clinical Stage IV Cutaneous Melanoma AJCC v8 Clinical Trial
Official title:
A Pilot Study of the Effect of the Microbiome on Immune Checkpoint Inhibitor Response in Melanoma
Verified date | April 2023 |
Source | Ohio State University Comprehensive Cancer Center |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
This pilot trial studies the effect of the microbiome on immune checkpoint inhibitors response in patients with melanoma by collecting stool and blood samples. Gut microbiome plays a critical role in response to immune checkpoint inhibitors. Studying the change in an individual's microbiome due to corticosteroid use may help researchers to determine whether an individual's microbiome can predict their response and toxicity to immune checkpoint inhibitors.
Status | Completed |
Enrollment | 88 |
Est. completion date | May 5, 2022 |
Est. primary completion date | May 5, 2022 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Eligible patients include adults with stage III, IV melanoma, to be treated with pembrolizumab or nivolumab, regardless of other concurrent therapy or line of treatment Exclusion Criteria: - Patients will be excluded if they are undergoing active systemic or oral corticosteroid use at start of immune checkpoint inhibitors (ICI) cycle 1, with the exception of adrenal replacement dosing. |
Country | Name | City | State |
---|---|---|---|
United States | Ohio State University Comprehensive Cancer Center | Columbus | Ohio |
Lead Sponsor | Collaborator |
---|---|
Ohio State University Comprehensive Cancer Center |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Other | Microbes as significant predictors in logistic regressions where the outcomes are binary (clinical response or treatment toxicity requiring corticosteroids), with the inputs as relative abundances of individual microbes | Individual microbe relative abundances will be compared between responders and non-responders with additional filtering to accommodate the sparseness of the microbiome data matrix. Specifically, microbes will be compared that are the most abundant, as well as being present in greater than 50% of the samples. An arcsine root transformation will be applied to the microbe relative abundances to approximate a Gaussian distribution, and then a generalized linear model applied where ''response'' is the response variable and individual microbes are the predictor variables.
P-values will be corrected by the Bonferroni method and then visualized by volcano plot. Microbes and covariates found to be most significant in the model will be combined into a single model to estimate the percent variance explainable by these predictors. Analyses will be performed in R using the stats package. |
At baseline, 12 weeks, or at corticosteroid prescription | |
Primary | Baseline microbiome alpha diversity in responders versus (vs) non-responders | This analysis will follow a logistic regression structure. The dependent variable, response to treatment, will be evaluated using standardized criteria (Response Evaluation Criteria in Solid Tumors [RECIST] version [v] 1.1). Each patient will be classified as "respond", "stable" or "progression'' as a categorical variable and then binarized, with "respond" or "stable" in the category "responders", and "progression" in the category "non-responders". Independent variables will be alpha-diversity. Additional covariates will be included in the model to control for differences in age, sex, body mass index (BMI), Food Frequency Questionnaire (FFQ) dietary index, and medication history. | At 12 weeks | |
Primary | Baseline microbiome alpha diversity in patients prescribed corticosteroids vs those who were not prescribed corticosteroids | This analysis will follow a logistic regression structure. The dependent variable, toxicity, will be evaluated by corticosteroid prescription. Dependent variables including alpha-diversity or individual microbes will be independent variables. | Within the 12-week treatment window | |
Secondary | Recruitment rates for longitudinal biospecimen collection, including stool, in melanoma patients | Recruitment rates will be defined as the fraction of screened adults who are eligible and agree to participate within the Cutaneous Oncology Clinic, with an estimated recruitment of 30%. Will track the monthly collection of data and documented reasons for missing any scheduled collection dates. The recruitment rate will be used in combination with the variance of the biospecimen data in power calculations to estimate the sample size needed for future trials. | 12 weeks | |
Secondary | Compliance rates for longitudinal biospecimen collection, including stool, in melanoma patients | Compliance will be defined as 90% of baseline, endpoint and corticosteroid collection. Will track the monthly collection of data and documented reasons for missing any scheduled collection dates. The compliance rate will be used in combination with the variance of the biospecimen data in power calculations to estimate the sample size needed for future trials. | 12 weeks |
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