Stage IV Non-small Cell Lung Cancer Clinical Trial
Official title:
A Pilot Study to Evaluate the Predictive Value of Circulating Tumor DNA for Clinical Outcome in Patients With Advanced Head and Neck and Lung Cancers
Verified date | February 2024 |
Source | Thomas Jefferson University |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
This pilot research trial studies circulating tumor deoxyribonucleic acid (DNA) in predicting outcomes in patients with stage IV head and neck cancer or stage III-IV non-small cell lung cancer. Studying circulating tumor DNA from patients with head and neck or lung cancer in the laboratory may help doctors predict how well patients will respond to treatment.
Status | Completed |
Enrollment | 130 |
Est. completion date | December 8, 2023 |
Est. primary completion date | May 14, 2021 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: 1. Patients older than 18 years age 2. Diagnosis of advanced HNC (Stage III, IVA, IVB, IVC) or NSCLC (Stage IIA, IIB, IIIA, IIIB, IV) (patients with synchronous advanced HNC and NSCLC are eligible) 3. ECOG performance status score of 0-3 4. Life expectancy of 3 months or longer 5. Patients able to provide a written informed consent prior to study entry Exclusion Criteria: 1. Prior chemotherapy or full course of radiotherapy for their present advanced HNC or NSCLC 2. Patients are excluded if they have a history of any other malignancy from which the patient has been disease-free for less than 2 years, with the exception of adequately treated basal or squamous cell carcinoma of skin 3. Other severe acute or chronic medical or psychiatric condition that may increase the risk associated with study participation, and in the judgment of the investigator would make the subject inappropriate for entry into this study |
Country | Name | City | State |
---|---|---|---|
United States | Thomas Jefferson University | Philadelphia | Pennsylvania |
Lead Sponsor | Collaborator |
---|---|
Sidney Kimmel Cancer Center at Thomas Jefferson University |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Predictive value of circulating tumor DNA for disease-free survival (DFS)/progression-free survival (PFS) | To evaluate the predictive value of circulating tumor DNA for DFS/PFS, Cox proportional model will be utilized. Circulating tumor DNA will be treated as either continuous or categorical variables in the regression models. The optimal cut-off value to dichotomize the patients by circulating tumor DNA will be determined by time-dependent receiver operating characteristic curve. | Up to 2 years | |
Secondary | Correlation between plasma tumor DNA levels and salivary tumor DNA levels | The correlation between plasma tumor DNA and salivary tumor DNA levels will be modeled through linear regression with least squares approach or using the Spearman correlation coefficient. | Up to 2 years | |
Secondary | Association between absence and presence of circulating tumor DNA mutation with the tumor burden | Univariate chi-square tests will be used to access the association between absence and presence of circulating tumor DNA mutation with the tumor burden. | Up to 2 years | |
Secondary | Association between absence and presence of circulating tumor DNA mutation with FDG-PET tumor hypermetabolism status | Univariate chi-square tests will be used to access the association between absence and presence of circulating tumor DNA mutation with FDG-PET tumor hypermetabolism status. | Up to 2 years | |
Secondary | Correlation between mutations found in plasma and tissue mutations | The correlation between mutations found in plasma and tissue mutations will be first explored by univariate chi-square test and then multivariable logistic regression. | Up to 2 years | |
Secondary | Correlation between circulating tumor cells and circulating tumor DNA | The correlation between circulating tumor cells and circulating tumor DNA levels will be modeled through linear regression with least squares approach or using the Spearman correlation coefficient. | Up to 2 years |
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