This randomized clinical trial studies the Beating Lung Cancer in Ohio protocol in improving survival in patients with stage IV non-small cell lung cancer. The Beating Lung Cancer in Ohio protocol may help in evaluating immunotherapies and targeted therapies that prolong survival, have more favorable toxicity profiles than conventional chemotherapy and impact quality of life.
PRIMARY OBJECTIVES: 1a. Establish a 3 month observation period for newly diagnosed stage IV non-small cell lung cancer patients (NSCLC)(n=300), using the statewide research network, documenting usual care (UC) practices, survival and quality of life and patients previously diagnosed with stage IV NSCLC within one year prior to initiating the study, (n=300). 1b. Establish a cohort of newly diagnosed stage IV non-small cell lung cancer patients (NSCLC), documenting usual care (UC) practices, survival and quality of life and patients previously diagnosed with stage IV NSCLC within one year prior to initiating the study, (n=800). This cohort will be limited to subjects directly recruited from Ohio State University for the duration of the study. 2\. Following the 3 month observation period, conduct a two-phase, cluster-randomized 21 month clinical trial in stage IV NSCLC patients (n=2100). Phase 1: Over 9 months, sites will be randomized to offer patients either UC (70% of sites) or free advanced genomic and immunotherapy testing (AGIT) (next generation sequencing tumor or blood circulating tumor DNA and PD-L1 testing immunohistochemistry staining, 30% of sites), followed by medical record review and recontacting of patients, (n=900). Phase 2: Over 12 months, sites will be randomized to offer patients AGIT or AGIT with decision support (DS) through a genomics board, followed by medical record review and recontacting of patients, (n=1200). 3\. Following the Aim 1 three month observation period, for subjects enrolled in Aim 2 (both phases) who smoke or have recently quit smoking (n=336), and their household members who smoke (n=84), to conduct a 1 year smoking cessation intervention trial where subjects are randomized by site to receive UC or National Cancer Center Network (NCCN)-driven centralized telephone counseling and decision support (CTC/DS). 4\. Separately, we will identify epigenetic biomarkers as prognostic and predictive biomarkers and analyze immune profile as biomarkers for immune-related adverse events. Assays will be performed using samples and data from subjects who consent to the repository. 4a. We will identify tumor epigenetic biomarkers (DNA methylation by Illumina methylation profiling) for immunotherapy (IOT) response in stage IV NSCLC (n=50 participants each with PD-L1 expression \<1% and \>50%) and extend the results to the study of blood cell-free DNA (cfDNA). 4b. We will identify immune profile using blood transcriptomics as biomarkers for IOT Immune-Related Adverse Events (irAE) (n=50). OUTLINE: Patients are randomized to 1 of 2 arms. ARM I (UC): Patients receive usual care and undergo collection of tumor tissue and blood sample for the repository. Patients who smoke or have recently quit smoking and their household members who smoke may also undergo smoking cessation via usual care or NCCN driven-CTC/DS. ARM II (AGIT/DS): Patients undergo collection of tumor tissue for analysis using FoundationOne assay and blood sample for analysis using FoundationACT blood circulating tumor DNA assay. Patients who smoke or have recently quit smoking and their household members who smoke may also undergo smoking cessation via usual care or NCCN driven-CTC/DS.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
3,584
Receive usual care
Undergo collection of tumor tissue and blood sample for repository
Undergo tumor tissue and blood sample for AGIT/DS
Correlative studies
Undergo medical record abstraction
Ancillary studies
Ancillary studies
Undergo usual care or NCCN-driven CTC/DS
Ohio State University Comprehensive Cancer Center
Columbus, Ohio, United States
RECRUITINGCost-Effectiveness Analysis
Using the payer perspective, Incremental Cost-Effectiveness Ratio (ICER) will be calculated based on estimates of overall survival/health care resource costs associated with treatment and the EQ5D questionnaire.
Time frame: Up to 24 months
Overall survival (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves) and Kaplan-Meier plots to display survival curves.
Time frame: Up to 3 years
Percent of patients receiving first line targeted therapy (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves).
Time frame: Up to 3 years
Percent of patients receiving genomic testing at diagnosis and type of genomic testing (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves).
Time frame: Up to 3 years
Percent of patients receiving genomic testing later in treatment (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves).
Time frame: Up to 3 years
Percent of patients receiving off label therapy (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves).
Time frame: Up to 3 years
Percent of patients referred to clinical trials (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves) and Kaplan-Meier plots to display survival curves.
Time frame: Up to 3 years
Percent of patients who enroll in therapeutic clinical trials (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves).
Time frame: Up to 3 years
Progression free survival (Aim I observational phase)
Descriptive statistics (summaries, distributions, 95% confidence intervals) will be reported and compared with the two arms in the randomized trial phase. Graphical displays will be used to show distributions (boxplots, density curves) and Kaplan-Meier plots to display survival curves.
Time frame: Up to 3 years
Quality of life assessed using European Organization for Research and Treatment-quality of life questionnaire
For aim II, a linear mixed model will be used to model change in quality of life as subjects are transitioned from one therapy to the next, with a main effect for treatment group and random effect for hospital and patient nested within hospital. To allow for possible changes in trajectories over time (e.g., a change-point analysis) the 'segmented' package in R will be used. Trajectories for each treatment will be modeled using a segmented mixed model with random change points as implemented in R. Variables associated with missing values will be evaluated and potentially included in the mixed m
Time frame: Up to 24 months
Smoking cessation (Aim III centralized telephone counseling/decision support)
Primary analysis will focus on smoking cessation at six months follow-up using generalized linear mixed models with a random effect for practice. The odds ratio and 95% confidence interval between smoking cessation and intervention arm will be reported based on the generalized linear mixed models model. As an alternative, we will also fit competing risks regression models (e.g., using the R package 'cmprsk') with death and smoking cessation as competing events. Subdistribution function hazard ratios for smoking cessation based on the intervention will be reported.
Time frame: Up to 6 months
Survival (Aim 2 advanced genomic and immunotherapy testing/decision support)
Overall differences in survival between the advanced genomic and immunotherapy testing and usual care arms will be assessed using the log-rank test. Cox proportional hazards model will be fit with a random effect for hospital and time to obtain the hazard ratio and 95% confidence interval for the treatment effect (advanced genomic and immunotherapy testing versus usual care). Interaction between treatment and time (e.g., via a time-dependent treatment effect) will be evaluated to assess possible evolution in usual care over time. To assess clinical decision making and clinical trial referral.
Time frame: Up to 3 years
The Ohio State University Comprehensive Cancer Center
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