Ohio State University Comprehensive Cancer Center
Columbus, Ohio, 43210, United States
NCT Number: NCT04954885
This study evaluates gut microbiome and functional status as modifiable biomarkers in predicting immunotherapy response and toxicity in patients with stage IV non-squamous non-small cell lung cancer receiving pembrolizumab alone or in combination with pemetrexed and carboplatin on the INSIGNIA trial. The goal of this study is to estimate the extent to which future interventions that seek to rationally modify the gut microbiome and/or functional status can improve outcomes.
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Notify Me18 year and older
All sexes
Observational
Columbus, Ohio, 43210, United States
PRIMARY OBJECTIVE:
I. To quantify the performance of two modifiable biomarkers -- the microbiome and functional status - to use as predictive and/or prognostic indicators of clinical benefit (overall survival, progression-free survival) in lung cancer patients who receive randomized treatment combinations prescribed by the INSIGNA protocol.
SECONDARY OBJECTIVE:
I. To quantify the predictive power of two modifiable biomarkers - the microbiome and functional status -- for the development of immune-related adverse events (irAEs).
OUTLINE:
Patients receive treatment by their treating physician as described in the INSIGNA protocol based on their designated treatment arm. Patients then undergo stool sample collection, complete questionnaires and functional status assessments, such as short physical performance battery over 10 minutes and 6 minute walk test, at baseline, days 40 (cycle 3), day 80 (cycle 5), day 180 (cycle 10) and end of treatment (up to 2 years).
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Undergo stool sample
Undergo short physical performance battery
Other names: Physical Fitness Testing, Physical Function Testing
Complete questionnaires
Time frame: Baseline up to 2 years
Count tables derived from the Kraken/Bracken pipeline output will be used to calculate the diversity metric Simpson's Index to quantify the number of species and evenness of the stool microbiome samples. Diversity will be binarized into high versus (vs) low at the median value, and then this variable used to stratify a Kaplan-Meier survival curve (predictive indicator). This will be further stratified by first-line treatment type (Arms A&B vs Arm C) to evaluate microbe diversity predicts response by treatment (prognostic indicator).
Time frame: Baseline up to 2 years
The calculation will follow the methods described above but performed within treatment type (Arms A&B separately from Arm C). The interpretation will rely on the comparison between treatments. For example, if a highly diverse microbiome is significantly predictive of overall survival in Arms A&B but not within Arm C, then it would be a prognostic indicator of outcome in the context of treatment with ICIs. If it is predictive of response in both treatment groups then we will be unable to discern whether it is prognostic.
Time frame: Baseline up to 2 years
Functional status will be measured using a variety of methods including the 6 minute walk test (6MWT), for which they will be stratified by the median distance walked. This stratification will be used in a Kaplan-Meier survival curve to measure time to event, where the event is progression free survival.
Time frame: Baseline up to 2 years
Physical activity will also be measured using a Short Physical Performance Battery (SPPB). Patients will be stratified by =< 7 and > 7 via grouping those assigned to the "very low physical function (0-3)" and "low physical function (4-6)" groups together, and the "moderate physical function (7-9)" and "high physical function (10-12)" groups together, assuming roughly equal split in the populations assigned by the stratification.
Time frame: Baseline up to 2 years
Diversity will be calculated and stratified as described above, and the stratification will be used in a Kaplan-Meier survival curve to measure time to event, where the event is development of an immune related adverse events (irAEs).
Time frame: Baseline up to 2 years
The relative abundance of Bacteroidetes will be used as a continuous variable in a Cox proportional hazards model where the event is development of an irAE as described above. Uni-and multi-variate tests will be performed controlling for the effects of age, body mass index and smoking status. Additional covariates will be explored in an exploratory fashion.
Time frame: Baseline up to 2 years
Will be quantified for the development in irAEs. Diversity will be calculated and stratified as described above, and the stratification will be used in a Kaplan-Meier survival curve to measure time to event, where the event is development of an irAE.
Time frame: Baseline up to 2 years
Will be compared. Will show significant associations with the outcomes of interest and particularly with markers of the immune system and inflammation.
Time frame: Baseline up to 2 years
Linear mixed-effects models will be used to characterize functional status trajectories through the course of treatment. This model allows for the estimation of intercept and slopes for each patient and group. Participants' functional status scores will be modeled using a segmented mixed model with random change points to estimate when functional status scores change during treatment. Will calculate Somers' Dxy and the c-statistic, in the case of the Cox regression models, and area under receiver-operating characteristic curves in the case of the logistic regression, to identify the model with the highest prediction accuracy in the hold-out data. Co-linearity would be indicated by variables with alternating inclusion in the model.
Ohio State University Comprehensive Cancer Center
Other
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