Fatigue and Molecular Mechanisms in Cancer Patients Receiving CCRT
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity of California, San Francisco
About this trial
Cancer-related fatigue (CRF) is a significant problem for cancer patients. This prospective, basic science, observational study will evaluate for changes in CRF associated with molecular characteristics prior to, during, and at the completion of non-investigational, standard-of-care, combined chemotherapy and radiation therapy (CCRT) and to develop and assess predictive models for CRF severity.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Participants have not received any prior treatment (i.e., cancer systemic therapies or radiation therapy) in the month except surgery or inductive Chemotherapy (CTX).
Participants receiving >= 15 fractions.
Participants is male or female and is >18 years of age on the day of signing the informed consent.
Ability to understand a written informed consent document.
Disqualifiers
Contraindication to phlebotomy for removal of approximately 50 mL of peripheral blood within 6 week period (Institutional Review Board (IRB) limit).
Trial population
Adult cancer patients willing to travel to San Francisco, receiving CCRT at University of California, San Francisco (UCSF) for cancers of the head and neck, gynecological, gastrointestinal, or thoracic sites.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Blood Specimen Collection
Procedure/SurgeryBlood samples will be obtained throughout the course of the study
Stool Specimen Collection
Other interventionStool samples will be obtained throughout the course of the study
Quality of Life (QOL) Questionnaires
Other interventionSurveys will be given throughout the course of the study.
Treatment groups
125 Participants
are divided into 1 treatment groupGroup A: Cancer Patients3 interventions
Trial outcomes
Primary outcomes
1
Measure associations between changes in cancer-related fatigue (CRF) and changes in gene expression over time
Association between phenotypic characteristics and initial levels and trajectories of CRF severity will be assessed using a hierarchical linear model (HLM) approach.
Time frame
Up to 34 weeks2
Measure associations between changes in CRF and changes in cytokine levels over time
Association between changes in CRF severity and biomarker levels prior to the initiation and at the end of CCRT. Linear regression will be used to evaluate for associations between fatigue changes and biomarker levels at baseline controlling for covariates identified in the initial primary outcome. Adjustments for multiple comparisons will be conducted using the Benjamini-Hochberg (BH) procedure at a false discovery rate (FDR) of 10%.
Time frame
Up to 34 weeks3
Measure associations between changes in CRF and changes in gene expression over time
Association between changes in CRF severity and gene expression prior to the initiation and at the end of CCRT. Linear regression will be used to evaluate for associations between fatigue changes and biomarker levels at baseline controlling for covariates identified in the initial primary outcome. Adjustments for multiple comparisons will be conducted using the Benjamini-Hochberg (BH) procedure at a false discovery rate (FDR) of 10%.
Time frame
Up to 34 weeks4
Evaluate the predictive utility of gene expression and cytokine data
A validated prediction model of CRF severity will be generated using machine learning (ML) methods to minimize the error between predicted and observed levels of fatigue midway through CCRT, at the completion of CCRT, and at least six months following the completion of CCRT. Evaluation of common ML algorithms for prediction accuracy and evaluation of model performance as compared to simple linear regression. Separate training and testing sets will be created, cross-validated, and repeated and impact of each variable will be determined.
Time frame
Up to 34 weeksSecondary outcomes
1
Evaluate for associations between changes in chemotherapy-induced peripheral neuropathy (CIPN) and changes in gene expression
The association between phenotypic characteristics and initial levels and trajectories of CIPN severity will be evaluated using a hierarchical linear model (HLM) approach.
Time frame
Up to 34 weeks2
Evaluate for associations between changes in CIPN and changes in cytokine levels
The association between phenotypic characteristics and initial levels and trajectories of CIPN severity will be evaluated using a hierarchical linear model (HLM) approach.
Time frame
Up to 34 weeks3
Evaluate the predictive utility of gene expression and severity of CIPN
The association between changes in CIPN severity and gene expression prior to the initiation and at the end of CCRT. Linear regression will be used to evaluate for associations between CIPN changes and gene expression at baseline controlling for covariates identified in previous objectives/endpoints. Adjustments for multiple comparisons will be performed using the Benjamini-Hochberg (BH) procedure at a false discovery rate (FDR) of 10%.
Time frame
Up to 34 weeks4
Evaluate the predictive utility of cytokine levels and severity of CIPN
The association between changes in CIPN severity and cytokine levels prior to the initiation and at the end of CCRT. Linear regression will be used to evaluate for associations between CIPN changes and cytokine levels at baseline controlling for covariates identified in previous objectives/endpoints. Adjustments for multiple comparisons will be performed using the Benjamini-Hochberg (BH) procedure at a false discovery rate (FDR) of 10%.
Time frame
Up to 34 weeksSponsors and contacts
Click on the lead sponsor to view all of their trials.
University of California, San Francisco
Lead sponsor
National Cancer Institute (NCI)
Collaborator
Source ClinicalTrials.gov