This phase II trial studies ziv-aflibercept in treating and perfusion computed tomography perfusion imaging in predicting response in patients with pancreatic neuroendocrine tumors that have spread to other parts of the body or cannot be removed by surgery. Ziv-aflibercept may stop the growth of tumor cells by blocking blood flow to the tumor. Diagnostic procedures, such as computed tomography perfusion, imaging may help measure a patient's response to ziv-aflibercept treatment.
PRIMARY OBJECTIVES: I. Estimate the objective response rate (RR) of ziv-aflibercept among patients with advanced pancreatic neuroendocrine tumors (NET)s according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. II. Test the following hypotheses: that baseline perfusion computed tomography (CT) parameters can predict which patients with advanced pancreatic neuroendocrine tumors (pNETs) will respond to treatment with ziv-aflibercept. SECONDARY OBJECTIVES: I. Estimate progression free survival (PFS) duration among patients treated with ziv-aflibercept. II. Evaluate the relationship between response rate and baseline blood volume (BV) and between response rate and baseline permeability surface (PS). TERTIARY OBJECTIVES: I. Determine whether post-treatment changes in BV expressed as relative change from baseline correlate with response to ziv-aflibercept. II. Determine whether post-treatment tumor blood flow (BF) (absolute measurement) correlates with response to ziv-aflibercept. III. Determine whether post-treatment changes in BF and, BV, expressed as relative change from baseline, correlate with relative change in sum of tumor diameters (RECIST 1.1 measurements). IV. Determine the effect of ziv-aflibercept therapy on post-treatment blood flow (BF), BV, mean transit time (MTT), and PS at 4 weeks after treatment. V. Evaluate the changes in tumor perfusion parameters at time of progression. OUTLINE: Patients receive ziv-aflibercept intravenously (IV) over 60-120 minutes on day 1. Courses repeat every 21 days in the absence of disease progression or unacceptable toxicity. Patients undergo computed tomography perfusion imaging at baseline, day 21 of course 1, and at time of progression. After completion of study treatment, patients are followed up periodically.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
TREATMENT
Masking
NONE
Enrollment
22
Moffitt Cancer Center-International Plaza
Tampa, Florida, United States
Moffitt Cancer Center
Tampa, Florida, United States
M D Anderson Cancer Center
Houston, Texas, United States
Objective Response Rate According to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1
90% exact confidence interval was constructed for the overall group. Per Response EvaluationCriteria In SolidTumors Criteria (RECIST v1.1) for target lesions and assessed by CT or MRI: Complete Response (CR), Disappearance of all target lesions; Partial Response (PR), \>=30% decrease in the sum of the longest diameter of target lesions; Overall Response (OR)=CR+PR,
Time frame: Through study completion an average of 19 months
Progression Free Survival (PFS)
Calculated for all eligible participants using the Kaplan Meier method and reported with confidence interval.
Time frame: Through study completion an average of 19 months
Baseline Blood Volume (BV)
The relationship between response rate and baseline BV will be evaluated. In addition to hypothesis testing using externally generated cut-points, refinement of optimal cut points in baseline BV separating responders and non-responders will be performed. Receiver operating characteristic (ROC) curves will be generated. Response rates of perfusion computed tomography (pCT) subgroups defined by these cut-points will be compared using chi-square test. Response profiles of pCT subgroups defined by these cut-points will be compared using non-parametric test (Wilcoxon rank sum test).
Time frame: Baseline
Baseline Permeability Surface (PS)
The relationship between response rate and baseline PS will be evaluated. In addition to hypothesis testing using externally generated cut-points, refinement of optimal cut points in baseline PS separating responders and non-responders will be performed. ROC curves will be generated. Response rates of pCT subgroups defined by these cut-points will be compared using chi-square test. Response profiles of pCT subgroups defined by these cut-points will be compared using non-parametric test (Wilcoxon rank sum test).
Time frame: Baseline
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