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

• 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: Brigham and Women's Hospital
• 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

Participant Flow

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
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

Baseline Characteristics

Arm/Group Title		Dosing Algorithm A	Dosing Algorithm B	Dosing Algorithm C	Total
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
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

Outcome Measures

1. Primary Outcome

Title	Mean Percentage of Time That INR Within Therapeutic Range Using Linear Interpolation (Rosendaal et al).
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

Outcome Measure Data

Analysis Population Description

[Not Specified]

Arm/Group Title	Dosing Algorithm A	Dosing Algorithm B	Dosing Algorithm C
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.
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

Outcome Measure Data

Analysis Population Description

[Not Specified]

Arm/Group Title	Dosing Algorithm A	Dosing Algorithm B	Dosing Algorithm C
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
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

Outcome Measure Data

Analysis Population Description

[Not Specified]

Arm/Group Title	Dosing Algorithm A	Dosing Algorithm B	Dosing Algorithm C
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).
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

Outcome Measure Data

Analysis Population Description

[Not Specified]

Arm/Group Title	Dosing Algorithm A	Dosing Algorithm B	Dosing Algorithm C
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.
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

Outcome Measure Data

Analysis Population Description

[Not Specified]

Arm/Group Title	Dosing Algorithm A	Dosing Algorithm B	Dosing Algorithm C
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

Adverse Events

Time Frame	90 Days
Adverse Event Reporting Description	[Not Specified]
Arm/Group Title	Dosing Algorithm A		Dosing Algorithm B		Dosing Algorithm C
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	--/--		--/--		--/--
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
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%)

Limitations and Caveats

[Not Specified]

More Information

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

• Name/Title: Mark A. Creager
• Organization: Brigham and Women's Hospital
• Phone: 617-732-5267
• EMail: mcreager@partners.org

Publications:

Fennerty A, Dolben J, Thomas P, Backhouse G, Bentley DP, Campbell IA, Routledge PA. Flexible induction dose regimen for warfarin and prediction of maintenance dose. Br Med J (Clin Res Ed). 1984 Apr 28;288(6426):1268-70.

Cooper MW, Hendra TJ. Prospective evaluation of a modified Fennerty regimen for anticoagulating elderly people. Age Ageing. 1998 Sep;27(5):655-6.

Nebert DW, Russell DW. Clinical importance of the cytochromes P450. Lancet. 2002 Oct 12;360(9340):1155-62. Review.

Aithal GP, Day CP, Kesteven PJ, Daly AK. Association of polymorphisms in the cytochrome P450 CYP2C9 with warfarin dose requirement and risk of bleeding complications. Lancet. 1999 Feb 27;353(9154):717-9.

Higashi MK, Veenstra DL, Kondo LM, Wittkowsky AK, Srinouanprachanh SL, Farin FM, Rettie AE. Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. JAMA. 2002 Apr 3;287(13):1690-8.

Joffe HV, Goldhaber SZ. Effectiveness and safety of long-term anticoagulation of patients >/=90 years of age with atrial fibrillation. Am J Cardiol. 2002 Dec 15;90(12):1397-8.

Fanikos J, Grasso-Correnti N, Shah R, Kucher N, Goldhaber SZ. Major bleeding complications in a specialized anticoagulation service. Am J Cardiol. 2005 Aug 15;96(4):595-8.

Joffe HV, Xu R, Johnson FB, Longtine J, Kucher N, Goldhaber SZ. Warfarin dosing and cytochrome P450 2C9 polymorphisms. Thromb Haemost. 2004 Jun;91(6):1123-8.

Voora D, Eby C, Linder MW, Milligan PE, Bukaveckas BL, McLeod HL, Maloney W, Clohisy J, Burnett RS, Grosso L, Gatchel SK, Gage BF. Prospective dosing of warfarin based on cytochrome P-450 2C9 genotype. Thromb Haemost. 2005 Apr;93(4):700-5.

Rieder MJ, Reiner AP, Gage BF, Nickerson DA, Eby CS, McLeod HL, Blough DK, Thummel KE, Veenstra DL, Rettie AE. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med. 2005 Jun 2;352(22):2285-93.

• 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