Lung Carcinoma Clinical Trial
Official title:
Lung Cancer Risk Assessment &Amp; Etiology
Verified date | March 2024 |
Source | City of Hope Medical Center |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
This study examines the biological and social determinants that may increase the risk for lung cancer in patients and never-smoking individuals. Biological characteristics of a person can include their genetics and social determinants of a person can include their education, income, and environment, all of which can impact their health. Information collected in this study may help increase early detection of lung cancer.
Status | Recruiting |
Enrollment | 200 |
Est. completion date | June 15, 2029 |
Est. primary completion date | June 15, 2029 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Have had clinical germline genetic testing and/or have consented or expressed a willingness to consent to the City of Hope (COH) General Research Protocol COH IRB # 07047 - Age >= 18 years - Willing to have about 30 mL of blood (approximately 2 tablespoons) drawn during the aspiration visit - Speak English, Spanish, or Mandarin - Lung cancer patients: meeting at least one of the following criteria: - Be a never-smoker with lung cancer (excludes atypical/typical carcinoid and small cell tumors) - Be diagnosed with lung cancer =< 50 years of age - Have a germline alteration known/suspected to be associated with elevated lung cancer risk - Have a strong family history of lung cancer (>= one first, second or third degree relative with never-smoking lung cancer, >= three first, second or third degree relative with lung cancer in one lineage [side of the family], >= one first, second or third degree relative diagnosed with lung cancer under the age of 50. Patients may also be considered eligible if they meet the family history criteria in part and have a truncated family structure [e.g., only one first and one second degree relative with lung cancer in a small family]) - Unaffected patients (i.e., those without a lung cancer diagnosis and other cancer diagnosis for the past 5 years) who are at least 50 years of age or at most age 10 years younger than the first case of lung cancer in the family, meeting at least one of the following criteria: - Have a germline alteration known/suspected to be associated with elevated lung cancer risk - Have a strong family history of lung cancer (>= one first, second or third degree relative with never-smoking lung cancer, >= three first, second or third degree relative with lung cancer in one lineage [side of the family], >= one first, second or third degree relative diagnosed with lung cancer under the age of 50. Patients may also be considered eligible if they meet the family history criteria in part and have a truncated family structure [e.g., only one first and one second degree relative with lung cancer in a small family]) - Of East Asian descent with any family history of lung cancer - Documented informed consent of the participant Exclusion Criteria: - Unable to provide informed consent - Patients who fall under the unaffected cohort criteria but received chest imaging (except chest x-ray) within the last year |
Country | Name | City | State |
---|---|---|---|
United States | City of Hope Medical Center | Duarte | California |
Lead Sponsor | Collaborator |
---|---|
City of Hope Medical Center | National Cancer Institute (NCI) |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Other | Frequency of abnormal radiographic findings | Will assess the frequency of abnormal radiographic findings in high-risk individuals unaffected with cancer who undergo low-dose computed tomography (CT) screening. Will summarize data related to the frequency of abnormal radiographic findings in high-risk individuals who undergo low-dose CT screening. | Through study completion, an average of 5 years | |
Other | Associations between molecular phenotypes, social determinants of health, and the presence of lung cancer and related outcomes | Identification of associations of social determinants of health and risk factors with lung cancer using lung cancer cases and non cases (survey and medical record data). | Up to study completion | |
Other | Liquid biopsy (LB) test sensitivity | Calculated by comparing the LB results with known cancer status. Results will be reported with their corresponding 95% confidence intervals. | Through study completion, an average of 5 years | |
Other | LB test specificity | Calculated by comparing the LB results with known cancer status. Results will be reported with their corresponding 95% confidence intervals. | Through study completion, an average of 5 years | |
Other | LB test positive predictive value | Calculated by comparing the LB results with known cancer status. Results will be reported with their corresponding 95% confidence intervals. | Through study completion, an average of 5 years | |
Other | LB test negative predictive value | Calculated by comparing the LB results with known cancer status. Results will be reported with their corresponding 95% confidence intervals. | Through study completion, an average of 5 years | |
Other | LB test accuracy comparing LB genetic mutations to those found on next generation sequencing (NGS) | LB test sensitivity and specificity, will be calculated by comparing the LB results with known cancer status. In addition to sensitivity and specificity, we will also examine other confusion matrix statistics, such as positive predictive value, negative predictive value, and test accuracy. Results will be reported with their corresponding 95% confidence intervals. | Through study completion, an average of 5 years | |
Primary | Frequency of germline alterations | We will explore the relationships between variables, examining correlations (Pearson or Spearman where appropriate). Summarization of data using univariate distributions of the outcomes of interest (presence of lung cancer and molecular phenotypes) and their bivariate distributions with social determinants of health will be carried out. We will examine whether financial hardship, low levels of education, and traffic proximity are associated with presence of lung cancer and molecular phenotypes by using T-tests to compare means and Fisher's exact test to compare proportions. We will also conduct logistic regression modeling to adjust for relevant covariates like race/ethnicity, age, and sex. If appropriate, we will use standard techniques such as sensitivity analyses or multiple imputation to handle missing data. | Through study completion, an average of 5 years |
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