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Personalized Warfarin Dosing by Genomics and Computational Intelligence

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ClinicalTrials.gov Identifier: NCT00872079
Recruitment Status : Terminated (Lack of Funding)
First Posted : March 31, 2009
Results First Posted : February 24, 2014
Last Update Posted : February 24, 2014
Sponsor:
Information provided by (Responsible Party):
VA Office of Research and Development ( US Department of Veterans Affairs )

Study Type Interventional
Study Design Intervention Model: Single Group Assignment;   Masking: None (Open Label);   Primary Purpose: Health Services Research
Conditions Venous Thrombosis
Atrial Fibrillation
Myocardial Infarction
Intervention Device: Genomics
Enrollment 175
Recruitment Details  
Pre-assignment Details Participants were not enrolled into the randomized clinical trial for Aim 4 due to lack of funding.
Arm/Group Title Genomics
Hide Arm/Group Description Model Predictive Control: Model predictive control is a computer based algorithm that can be applied to drug dosing. This computer tool uses a model of how a patient will respond to a drug dose based on demographic and historical dosing information to predict a new drug response. A drug dose controller applies all possible doses to the response model and selects the one dose that best meets the stated goals of the drug therapy. In the case of warfarin, we will calculate an INR value within a specific target range.
Period Title: Overall Study
Started 175
Completed 175
Not Completed 0
Arm/Group Title Genomics
Hide Arm/Group Description

The specific aims of this research are:

  1. Determine the structure and the type of neural network model for predictions from historically obtained data. (Computer Model)
  2. Prospectively develop an individualized neural network and NONMEM model capable of predicting erythropoietin dosing for chronic in-center hemodialysis patients using adaptive techniques.
  3. Develop computer programs based on neural computing that can be used in a clinical setting. (Computer Model)
  4. Determine the utility of the computer programs prospectively in the clinical setting.
Overall Number of Baseline Participants 175
Hide Baseline Analysis Population Description
[Not Specified]
Age, Categorical  
Measure Type: Count of Participants
Unit of measure:  Participants
Number Analyzed 175 participants
<=18 years
0
   0.0%
Between 18 and 65 years
50
  28.6%
>=65 years
125
  71.4%
Sex: Female, Male  
Measure Type: Count of Participants
Unit of measure:  Participants
Number Analyzed 175 participants
Female
10
   5.7%
Male
165
  94.3%
Race (NIH/OMB)  
Measure Type: Count of Participants
Unit of measure:  Participants
Number Analyzed 175 participants
American Indian or Alaska Native
0
   0.0%
Asian
0
   0.0%
Native Hawaiian or Other Pacific Islander
1
   0.6%
Black or African American
17
   9.7%
White
157
  89.7%
More than one race
0
   0.0%
Unknown or Not Reported
0
   0.0%
1.Primary Outcome
Title Patient Genomics
Hide Description During Aim 2, Determined Patient Genotypes: CYP2C9 and VKORC1.
Time Frame Baseline
Hide Outcome Measure Data
Hide Analysis Population Description
[Not Specified]
Arm/Group Title Genomics
Hide Arm/Group Description:

Model Predictive Control: Model predictive control is a computer based algorithm that can be applied to drug dosing. This computer tool uses a model of how a patient will respond to a drug dose based on demographic and historical dosing information to predict a new drug response. A drug dose controller applies all possible doses to the response model and selects the one dose that best meets the stated goals of the drug therapy. In the case of warfarin, we will calculate an INR value within a specific target range.

There are 4 Aims in this study.

  1. To collect historical data on warfarin dosing in subjects.
  2. To collect genotype information on up to 300 subjects receiving warfarin anticoagulation.
  3. to develop a computer model incorporating the information from aim 1 and aim 2.
  4. To conduct a randomized clinical trial.
Overall Number of Participants Analyzed 175
Measure Type: Number
Unit of Measure: participants
CYP2C9: *1/*1 112
CYP2C9: *1/*2 23
CYP2C9: *1/*3 19
CYP2C9: *2/*2 3
CYP2C9: *2/*3 3
CYP2C9: *3/*3 2
CYP2C9: Not Determined 13
VKORC1: AA 23
VKORCI:GA 72
VKORCI:GG 67
VKORCI: Not Determined 13
Time Frame [Not Specified]
Adverse Event Reporting Description [Not Specified]
 
Arm/Group Title Genomics
Hide Arm/Group Description Model Predictive Control: Model predictive control is a computer based algorithm that can be applied to drug dosing. This computer tool uses a model of how a patient will respond to a drug dose based on demographic and historical dosing information to predict a new drug response. A drug dose controller applies all possible doses to the response model and selects the one dose that best meets the stated goals of the drug therapy. In the case of warfarin, we will calculate an INR value within a specific target range.
All-Cause Mortality
Genomics
Affected / at Risk (%)
Total   --/-- 
Show Serious Adverse Events Hide Serious Adverse Events
Genomics
Affected / at Risk (%)
Total   0/0 
Show Other (Not Including Serious) Adverse Events Hide Other (Not Including Serious) Adverse Events
Frequency Threshold for Reporting Other Adverse Events 0%
Genomics
Affected / at Risk (%)
Total   0/0 
Certain Agreements
All Principal Investigators ARE employed by the organization sponsoring the study.
Results Point of Contact
Name/Title: Michael Brier
Organization: University of Louisville
Phone: 502-852-0246
Responsible Party: VA Office of Research and Development ( US Department of Veterans Affairs )
ClinicalTrials.gov Identifier: NCT00872079     History of Changes
Other Study ID Numbers: CAMM-04-07S
First Submitted: March 27, 2009
First Posted: March 31, 2009
Results First Submitted: February 21, 2014
Results First Posted: February 24, 2014
Last Update Posted: February 24, 2014