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Trial record 6 of 142 for:    warfarin AND therapeutic range

Study to Develop a Reliable Nomogram That Incorporates Clinical and Genetic Information

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ClinicalTrials.gov Identifier: NCT00401414
Recruitment Status : Completed
First Posted : November 20, 2006
Results First Posted : August 30, 2013
Last Update Posted : August 30, 2013
Sponsor:
Collaborators:
Massachusetts General Hospital
Newton-Wellesley Hospital
Spaulding Rehabilitation Hospital
Information provided by (Responsible Party):
Mark Alan Creager, MD, Brigham and Women's Hospital

Study Type Interventional
Study Design Allocation: Non-Randomized;   Intervention Model: Single Group Assignment;   Masking: None (Open Label);   Primary Purpose: Treatment
Conditions Pulmonary Embolism
Deep Vein Thrombosis
Atrial Fibrillation
Intervention Drug: Warfarin
Enrollment 344
Recruitment Details Warfarin naïve patients undergoing initiation of warfarin anticoagulation at participating Partners anticoagulation clinics, including Brigham and Women's Hospital, Massachusetts General Hospital, North Shore Medical Center, Faulkner Hospital, Spaulding Rehabilitation Hospital, and Newton Wellesley Hospital.
Pre-assignment Details We enrolled patients over 9 months, following each patient for 3 months with twice weekly coagulation testing of the prothrombin time standardized to the International Normalized Ratio, and adjusted monthly the nomogram (if necessary) to improve the fit with emerging data from the cohort.
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Hide Arm/Group Description

Algorithm A was a dosing decision-tree that included both clinical and genetic factors. It was based upon optimal clinical practice at the Brigham and Women's Hospital's Anticoagulation Management Service as well as published literature that has utilised warfarin pharmacogenetics.

Doses were subsequently adjusted based on serial INR measurements.

Dosing Algorithm B was generated from an analysis of warfarin dose, INR, genetic factors, demographic factors and concomitant drug therapy from an initial prospective group of 74 patients treated using Algorithm A. Using these data, a mechanistic concentration-INR model was constructed to refine the estimates of the effect of CYP2C9 genotypes, VKORC1 haplotypes, age, and concomitant medications. Dosing Algorithm C was generated as an update of dosing Algorithm B and was based upon additional patient data, similar to what was described above for Algorithm B, from the prospective accrual of 203 patients in the CROWN trial. The major difference between Algorithm B and Algorithm C was an update of the half maximal inhibitory concentration (IC50) estimate for each VKORC1 haplotype in the model used to generate Algorithm B to reflect warfarin’s PD effect as evident in the acquired patient data. Simulations using Algorithm C were repeated using the clinical endpoints described above to derive the optimal starting warfarin doses and titration scheme that was tested prospectively in subsequent patients enrolled in the CROWN study.
Period Title: Overall Study
Started 118 147 79
Completed 118 147 79
Not Completed 0 0 0
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C Total
Hide Arm/Group Description

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Algorithm A was a dosing decision-tree that included both clinical and genetic factors. It was based upon optimal clinical practice at the Brigham and Women's Hospital's Anticoagulation Management Service as well as published literature that has utilised warfarin pharmacogenetics.

Doses were subsequently adjusted based on serial INR measurements.

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm B was generated from an analysis of warfarin dose, INR, genetic factors, demographic factors and concomitant drug therapy from an initial prospective group of 74 patients treated using Algorithm A. Using these data, a mechanistic concentration-INR model was constructed to refine the estimates of the effect of CYP2C9 genotypes, VKORC1 haplotypes, age, and concomitant medications. Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm C was generated as an update of dosing Algorithm B and was based upon additional patient data, similar to what was described above for Algorithm B, from the prospective accrual of 203 patients in the CROWN trial. The major difference between Algorithm B and Algorithm C was an update of the half maximal inhibitory concentration (IC50) estimate for each VKORC1 haplotype in the model used to generate Algorithm B to reflect warfarin's PD effect as evident in the acquired patient data. Total of all reporting groups
Overall Number of Baseline Participants 118 147 79 344
Hide Baseline Analysis Population Description
[Not Specified]
Age, Categorical  
Measure Type: Count of Participants
Unit of measure:  Participants
Number Analyzed 118 participants 147 participants 79 participants 344 participants
<=18 years
0
   0.0%
0
   0.0%
0
   0.0%
0
   0.0%
Between 18 and 65 years
118
 100.0%
147
 100.0%
79
 100.0%
344
 100.0%
>=65 years
0
   0.0%
0
   0.0%
0
   0.0%
0
   0.0%
Age Continuous  
Mean (Standard Deviation)
Unit of measure:  Years
Number Analyzed 118 participants 147 participants 79 participants 344 participants
64.7  (16.6) 57.9  (16.5) 57.2  (15.6) 60.1  (16.7)
Sex: Female, Male  
Measure Type: Count of Participants
Unit of measure:  Participants
Number Analyzed 118 participants 147 participants 79 participants 344 participants
Female
60
  50.8%
64
  43.5%
38
  48.1%
162
  47.1%
Male
58
  49.2%
83
  56.5%
41
  51.9%
182
  52.9%
Region of Enrollment  
Measure Type: Number
Unit of measure:  Participants
United States Number Analyzed 118 participants 147 participants 79 participants 344 participants
118 147 79 344
1.Primary Outcome
Title Mean Percentage of Time That INR Within Therapeutic Range Using Linear Interpolation (Rosendaal et al).
Hide Description

Primary end point: mean percentage of time INR is within therapeutic range. Though target INR was 2.0-3.0, therapeutic INR is considered 1.8-3.2 (allows for INR measurement error and avoids problems inherent in overcorrection).

The international normalized ratio (INR) is one way of presenting prothrombin time test results for people taking the blood-thinning medication warfarin. The INR formula adjusts for variation in laboratory testing methods so that test results can be comparable.

Time Frame 90 Days
Hide Outcome Measure Data
Hide Analysis Population Description
[Not Specified]
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Hide Arm/Group Description:

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Algorithm A was a dosing decision-tree that included both clinical and genetic factors. It was based upon optimal clinical practice at the Brigham and Women's Hospital's Anticoagulation Management Service as well as published literature that has utilised warfarin pharmacogenetics.

Doses were subsequently adjusted based on serial INR measurements.

[Not Specified]
[Not Specified]
Overall Number of Participants Analyzed 118 147 79
Mean (Standard Deviation)
Unit of Measure: percentage of time
58.9  (22) 59.7  (23) 65.8  (16.9)
2.Secondary Outcome
Title Time to the First Therapeutic INR.
Hide Description The INR (international normalized ratio) is a derived measure of the prothrombin time. In this trial, a therapeutic INR was considered 1.8 to 3.2
Time Frame 90 Days
Hide Outcome Measure Data
Hide Analysis Population Description
[Not Specified]
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Hide Arm/Group Description:

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Algorithm A was a dosing decision-tree that included both clinical and genetic factors. It was based upon optimal clinical practice at the Brigham and Women's Hospital's Anticoagulation Management Service as well as published literature that has utilised warfarin pharmacogenetics.

Doses were subsequently adjusted based on serial INR measurements.

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm B was generated from an analysis of warfarin dose, INR, genetic factors, demographic factors and concomitant drug therapy from an initial prospective group of 74 patients treated using Algorithm A. Using these data, a mechanistic concentration-INR model was constructed to refine the estimates of the effect of CYP2C9 genotypes, VKORC1 haplotypes, age, and concomitant medications.
Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm C was generated as an update of dosing Algorithm B and was based upon additional patient data, similar to what was described above for Algorithm B, from the prospective accrual of 203 patients in the CROWN trial. The major difference between Algorithm B and Algorithm C was an update of the half maximal inhibitory concentration (IC50) estimate for each VKORC1 haplotype in the model used to generate Algorithm B to reflect warfarin's PD effect as evident in the acquired patient data.
Overall Number of Participants Analyzed 118 147 79
Mean (Standard Deviation)
Unit of Measure: Days
9.1  (4.5) 10.4  (4.9) 9.7  (4.4)
3.Secondary Outcome
Title Per-patient Percentage of INRs Out of the Therapeutic Range
Hide Description The INR (international normalized ratio) is a derived measure of the prothrombin time. In this trial, a therapeutic INR was considered 1.8 to 3.2
Time Frame 90 Days
Hide Outcome Measure Data
Hide Analysis Population Description
[Not Specified]
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Hide Arm/Group Description:

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Algorithm A was a dosing decision-tree that included both clinical and genetic factors. It was based upon optimal clinical practice at the Brigham and Women's Hospital's Anticoagulation Management Service as well as published literature that has utilised warfarin pharmacogenetics.

Doses were subsequently adjusted based on serial INR measurements.

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm B was generated from an analysis of warfarin dose, INR, genetic factors, demographic factors and concomitant drug therapy from an initial prospective group of 74 patients treated using Algorithm A. Using these data, a mechanistic concentration-INR model was constructed to refine the estimates of the effect of CYP2C9 genotypes, VKORC1 haplotypes, age, and concomitant medications.
Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm C was generated as an update of dosing Algorithm B and was based upon additional patient data, similar to what was described above for Algorithm B, from the prospective accrual of 203 patients in the CROWN trial. The major difference between Algorithm B and Algorithm C was an update of the half maximal inhibitory concentration (IC50) estimate for each VKORC1 haplotype in the model used to generate Algorithm B to reflect warfarin's PD effect as evident in the acquired patient data.
Overall Number of Participants Analyzed 118 147 79
Mean (Standard Deviation)
Unit of Measure: percentage of INRs out of range
42.2  (21.6) 37.7  (22.8) 33.3  (16.8)
4.Secondary Outcome
Title Time to Stable Anticoagulation (in Days).
Hide Description Defined as two consecutive INRs within the therapeutic range >7 days apart and with no dose change during this time.
Time Frame 90 Days
Hide Outcome Measure Data
Hide Analysis Population Description
[Not Specified]
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Hide Arm/Group Description:

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Algorithm A was a dosing decision-tree that included both clinical and genetic factors. It was based upon optimal clinical practice at the Brigham and Women's Hospital's Anticoagulation Management Service as well as published literature that has utilised warfarin pharmacogenetics.

Doses were subsequently adjusted based on serial INR measurements.

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm B was generated from an analysis of warfarin dose, INR, genetic factors, demographic factors and concomitant drug therapy from an initial prospective group of 74 patients treated using Algorithm A. Using these data, a mechanistic concentration-INR model was constructed to refine the estimates of the effect of CYP2C9 genotypes, VKORC1 haplotypes, age, and concomitant medications.
Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm C was generated as an update of dosing Algorithm B and was based upon additional patient data, similar to what was described above for Algorithm B, from the prospective accrual of 203 patients in the CROWN trial. The major difference between Algorithm B and Algorithm C was an update of the half maximal inhibitory concentration (IC50) estimate for each VKORC1 haplotype in the model used to generate Algorithm B to reflect warfarin's PD effect as evident in the acquired patient data.
Overall Number of Participants Analyzed 118 147 79
Mean (Standard Deviation)
Unit of Measure: Days
50.8  (20.1) 34.6  (14.9) 31.5  (13.1)
5.Secondary Outcome
Title Proportion of Patients With Serious Adverse Clinical Events.
Hide Description Defined as an INR>4.0, use of vitamin K, major bleeding events (as defined by the Thrombolysis in Myocardial Infarction [TIMI] criteria), thromboembolic events, stroke (all cause), myocardial infarction, and death (all cause).
Time Frame 90 Days
Hide Outcome Measure Data
Hide Analysis Population Description
[Not Specified]
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Hide Arm/Group Description:

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Algorithm A was a dosing decision-tree that included both clinical and genetic factors. It was based upon optimal clinical practice at the Brigham and Women's Hospital's Anticoagulation Management Service as well as published literature that has utilised warfarin pharmacogenetics.

Doses were subsequently adjusted based on serial INR measurements.

Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm B was generated from an analysis of warfarin dose, INR, genetic factors, demographic factors and concomitant drug therapy from an initial prospective group of 74 patients treated using Algorithm A. Using these data, a mechanistic concentration-INR model was constructed to refine the estimates of the effect of CYP2C9 genotypes, VKORC1 haplotypes, age, and concomitant medications.
Three dosing algorithms (A, B, and C, respectively) were used in this investigation. The algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximise the likelihood of achieving and maintaining the target INR. The algorithms were refined using adaptive methods that allow for continual reassessment of patient-level data to optimize the predictive power of the algorithms. Dosing Algorithm C was generated as an update of dosing Algorithm B and was based upon additional patient data, similar to what was described above for Algorithm B, from the prospective accrual of 203 patients in the CROWN trial. The major difference between Algorithm B and Algorithm C was an update of the half maximal inhibitory concentration (IC50) estimate for each VKORC1 haplotype in the model used to generate Algorithm B to reflect warfarin's PD effect as evident in the acquired patient data.
Overall Number of Participants Analyzed 118 147 79
Measure Type: Number
Unit of Measure: participants
43 41 24
Time Frame 90 Days
Adverse Event Reporting Description [Not Specified]
 
Arm/Group Title Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Hide Arm/Group Description [Not Specified] [Not Specified] [Not Specified]
All-Cause Mortality
Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Affected / at Risk (%) Affected / at Risk (%) Affected / at Risk (%)
Total   --/--      --/--      --/--    
Show Serious Adverse Events Hide Serious Adverse Events
Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Affected / at Risk (%) # Events Affected / at Risk (%) # Events Affected / at Risk (%) # Events
Total   43/118 (36.44%)      41/147 (27.89%)      24/79 (30.38%)    
Investigations       
Vitamin K administration  2/118 (1.69%)  2 0/147 (0.00%)  0 0/79 (0.00%)  0
Vascular disorders       
INR ≥ 4  39/118 (33.05%)  39 36/147 (24.49%)  36 22/79 (27.85%)  22
Major bleeding events (TIMI definition)  2/118 (1.69%)  2 3/147 (2.04%)  3 2/79 (2.53%)  2
Thrombotic events (MI, stroke, VTE)  0/118 (0.00%)  0 2/147 (1.36%)  2 0/79 (0.00%)  0
Show Other (Not Including Serious) Adverse Events Hide Other (Not Including Serious) Adverse Events
Frequency Threshold for Reporting Other Adverse Events 5%
Dosing Algorithm A Dosing Algorithm B Dosing Algorithm C
Affected / at Risk (%) # Events Affected / at Risk (%) # Events Affected / at Risk (%) # Events
Total   0/118 (0.00%)      0/147 (0.00%)      0/79 (0.00%)    
Certain Agreements
Principal Investigators are NOT employed by the organization sponsoring the study.
There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed.
Results Point of Contact
Layout table for Results Point of Contact information
Name/Title: Mark A. Creager
Organization: Brigham and Women's Hospital
Phone: 617-732-5267
EMail: mcreager@partners.org
Publications:
Layout table for additonal information
Responsible Party: Mark Alan Creager, MD, Brigham and Women's Hospital
ClinicalTrials.gov Identifier: NCT00401414     History of Changes
Other Study ID Numbers: 2006-P-001896
First Submitted: November 16, 2006
First Posted: November 20, 2006
Results First Submitted: March 20, 2013
Results First Posted: August 30, 2013
Last Update Posted: August 30, 2013