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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT02807896
Other study ID # miRNA_Chip
Secondary ID
Status Completed
Phase
First received
Last updated
Start date September 2016
Est. completion date September 2016

Study information

Verified date January 2020
Source LG Electronics Inc.
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

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


Description:

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.


Recruitment information / eligibility

Status Completed
Enrollment 232
Est. completion date September 2016
Est. primary completion date September 2016
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 20 Years to 80 Years
Eligibility 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

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
Korea, Republic of Severance Hospital, Yonsei University Seoul

Sponsors (3)

Lead Sponsor Collaborator
CHANGHEE LEE JAEBIN, LEE / Statistics - Math Emphasis in Purdue University, YOON SOOK, KIM / Chief Research Engineer in LG Electronics Inc.

Country where clinical trial is conducted

Korea, Republic of, 

Outcome

Type Measure Description Time frame Safety issue
Primary 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.
within 1week
Secondary 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.
within 1week
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