Validation of Useful Markers Generated by Next Generation Bio-data Based Genome Research and Cohort Study

CHANGHEE LEE232 enrolled

Overview

Multiple biomarker development through validation of useful markers generated by next generation bio-data based genome research and cohort study

1. Objectives The study will be performed to develop the integrated analytical methods of genomic data and clinical data and the bio-control network analysis, through which knowledge-based integrated analysis system can be developed and then biomarker for early diagnosis and treatment of pancreatic cancer and bile duct cancer, and finally the customized disease management system. Also, it is to confirm the effectiveness of diagnostic chip for research purpose by applying pancreatic/bile duct cancer-specific biomarker, miRNA, found through the integrated analysis of genomic data and clinical data of patients with pancreatic/bile duct cancer to the blood of patients with pancreatic/bile duct cancer. 2. Effective evaluation method The discrimination and calibration for algorithm through the diagnostic chip of each cancer type will all be examined using 10-fold cross-validation (100 repetitions). In the 10-fold cross-validation, the data is randomly divided into 10 same sized data, among which 9 are used in making a model for training and the remaining 1 is applied for test, and this process is randomly and independently repeated for 100 times. The 10-fold cross-validated AUC is calculated to see the discrimination of diagnostic chip of each cancer type, and the 95% confidence interval is presented by non-parametric method. The 10-fold cross-validated calibration plot is presented to see the calibration of diagnostic chip of each cancer type. The calibration plot visually demonstrate the degree of prediction by comparing the prediction probability of each group and the ratio of actual cancer patients after listing the prediction probability in the order and dividing it with regular intervals. Then, for the same subjects, the AUC of the CA 19-9, the existing cancer diagnostic tool, is calculated and the 95% confidence interval is presented. To compare the diagnostic chip of each cancer type and the AUC of CA 19-9, p-value is calculated by non-parametric method of 10-fold cross-validated AUC.

Study Type

OBSERVATIONAL

Enrollment

232

Conditions

BCL2 Gene mRNA Overexpression

Interventions

OTHER

This study is cohort.

Eligibility

Sex: ALLMin age: 20 YearsMax age: 80 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Patients with histologically or cytologically diagnosed pancreatic cancer or bile duct cancer * Patient age: 20\~80 years old * Patients who voluntarily determined to participate in the clinical trial and signed the informed consent for compliance * Korean race Exclusion Criteria: * Patients with previous history of chemotherapy or radiation therapy for pancreatic cancer and/or bile duct cancer * Patients who had treatment or surgery for cancer of other organ within 5 years before the clinical trial

Locations (1)

Severance Hospital, Yonsei University

Seoul, South Korea

Outcomes

Primary Outcomes

AUC(area under curve)

The AUC(area under curve) is calculated as an index for discrimination to see how well it discriminates algorithm through diagnostic chip for each cancer type. The calibration plot will be presented for the evaluation of calibration to see how well it calibrates algorithm through diagnostic chip for each cancer type, and the comparison of CA 19-9 by each cancer type and AUC differences of the diagnostic chip will be evaluated.

Time frame: within 1week

Secondary Outcomes

cut-off of each biomarker, accuracy

The cut-off of each biomarker expression for maximizing the discrimination of diagnostic chips is calculated and presented as an index for analytical sensitivity. The accuracy considering the characteristics of diagnostic chip is calculated and presented.

Time frame: within 1week

Data from ClinicalTrials.gov

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