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Background: The level of anticoagulation in response to a fixed-dose regimen of warfarin is difficult to predict during the initiation of therapy. We prospectively compared the effect of genotype-guided dosing with that of standard dosing on anticoagulation control in patients starting warfarin therapy. Methods: We conducted a multicenter, randomized, controlled trial involving patients with atrial fibrillation or venous thromboembolism. Genotyping for CYP2C9*2, CYP2C9*3, and VKORC1 (-1639G→A) was performed with the use of a point-of-care test. For patients assigned to the genotype-guided group, warfarin doses were prescribed according to pharmacogenetic-based algorithms for the first 5 days. Patients in the control (standard dosing) group received a 3-day loading-dose regimen. After the initiation period, the treatment of all patients was managed according to routine clinical practice. The primary outcome measure was the percentage of time in the therapeutic range of 2.0 to 3.0 for the international normalized ratio (INR) during the first 12 weeks after warfarin initiation. Results: A total of 455 patients were recruited, with 227 randomly assigned to the genotype-guided group and 228 assigned to the control group. The mean percentage of time in the therapeutic range was 67.4% in the genotype-guided group as compared with 60.3% in the control group (adjusted difference, 7.0 percentage points; 95% confidence interval, 3.3 to 10.6; P<0.001). There were significantly fewer incidences of excessive anticoagulation (INR ≥4.0) in the genotype-guided group. The median time to reach a therapeutic INR was 21 days in the genotype-guided group as compared with 29 days in the control group (P<0.001). Conclusions: Pharmacogenetic-based dosing was associated with a higher percentage of time in the therapeutic INR range than was standard dosing during the initiation of warfarin therapy. (Funded by the European Commission Seventh Framework Programme and others; ClinicalTrials.gov number, NCT01119300.).
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original article
The
new england journal
of
medicine
n engl j med 369;24 nejm.org december 12, 2013
2294
A Randomized Trial of
Genotype-Guided Dosing of Warfarin
Munir Pirmohamed, Ph.D., F.R.C.P., Girvan Burnside, Ph.D., Niclas Eriksson, Ph.D.,
Andrea L. Jorgensen, Ph.D., Cheng Hock Toh, M.D., Toby Nicholson, F.R.C.Path.,
Patrick Kesteven, M.D., Christina Christersson, M.D., Ph.D., Bengt Wahlström, M.D.,
Christina Stafberg, M.D., J. Eunice Zhang, Ph.D., Julian B. Leathart, M.Phil.,
Hugo Kohnke, M.Sc., Anke H. Maitland-van der Zee, Pharm.D., Ph.D.,
Paula R. Williamson, Ph.D., Ann K. Daly, Ph.D., Peter Avery, Ph.D.,
Farhad Kamali, Ph.D., and Mia Wadelius, M.D., Ph.D., for the EU-PACT Group*
From the University of Liverpool (M.P.,
G.B., A.L.J., C.H.T., J.E.Z., P.R.W.) and
Royal Liverpool and Broadgreen Univer-
sity Hospital National Health Service
(NHS) Trust (M.P., C.H.T.), Liverpool,
Whiston Hospital, Prescot (T.N.), and
Newcastle upon Tyne NHS Trust (P.K.)
and Newcastle University ( J.B.L., A.K.D.,
P.A., F.K.), Newcastle upon Tyne — all in
the United Kingdom; Uppsala University,
Department of Medical Sciences (N.E.,
C.C., H.K., M.W.), Uppsala Clinical Re-
search Cente r (N.E.) and Uppsala Univer-
sity Hospit al (C.C., B.W., M.W.), Uppsala,
and Enköping Hospital, Enköping (C.S.)
— all in Sweden; and Utrecht University,
Utrecht , the Netherlands (A .H.M.Z.). Ad-
dress reprint r equests to Dr. Pirmohame d
at the Wolfson Centre for Personalised
Medicine, Institute of Translational Med-
icine, University of Liverpool, Block A:
Waterhouse Bldg., 1-5 Brownlow St.,
Liver pool L69 3GL, Uni ted Kingdom, or at
munirp@liverpool.ac.uk.
*A complete list of the members of the
European Pharmacogenetics of Anti-
coagulant Therapy (EU-PACT) group is
provided in the Supplementary Appen-
dix, available at NEJM.org.
Drs. Kamali and Wadelius contributed
equally to this ar ticle.
This arti cle was published on Novemb er 19,
2013, at NEJM.org.
N Engl J Med 2013;369:2294-303.
DOI: 10.1056/NEJMoa1311386
Copyright © 2013 Massachusetts Medical Society
ABSTRACT
Background
The level of anticoagulation in response to a fixed-dose regimen of warfarin is diffi-
cult to predict during the initiation of therapy. We prospectively compared the effect
of genotype-guided dosing with that of standard dosing on anticoagulation control
in patients starting warfarin therapy.
Methods
We conducted a multicenter, randomized, controlled trial involving patients with
atrial fibrillation or venous thromboembolism. Genotyping for CY P2C9*2, CYP2C9*3,
and VKORC1 (−1639G→A) was performed with the use of a point-of-care test. For
patients assigned to the genotype-guided group, warfarin doses were prescribed
according to pharmacogenetic-based algorithms for the first 5 days. Patients in the
control (standard dosing) group received a 3-day loading-dose regimen. After the
initiation period, the treatment of all patients was managed according to routine
clinical practice. The primary outcome measure was the percentage of time in the
therapeutic range of 2.0 to 3.0 for the international normalized ratio (INR) during
the first 12 weeks after warfarin initiation.
Result s
A total of 455 patients were recruited, with 227 randomly assigned to the genotype-
guided group and 228 assigned to the control group. The mean percentage of time
in the therapeutic range was 67.4% in the genotype-guided group as compared with
60.3% in the control group (adjusted difference, 7.0 percentage points; 95% confidence
interval, 3.3 to 10.6; P<0.001). There were significantly fewer incidences of excessive
anticoagulation (INR ≥4.0) in the genotype-guided group. The median time to reach
a therapeutic INR was 21 days in the genotype-guided group as compared with
29 days in the control group (P<0.001).
Conclusions
Pharmacogenetic-based dosing was associated with a higher percentage of time in
the therapeutic INR range than was standard dosing during the initiation of
warfarin therapy. (Funded by the European Commission Seventh Framework Pro-
gramme and others; ClinicalTrials.gov number, NCT01119300.)
The New England Journal of Medicine
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Genotype-Guided Dosing of Warfarin
n engl j med 369;24 nejm.org december 12, 2013
2295
W
arfarin has proved to be effec-
tive in the management of thrombo-
embolic disease
1
but has a narrow
therapeutic index, with wide variation among
patients in the daily doses required; this varia-
tion can lead to either excessive or insufficient
anticoagulation.
2
An increase in the international
normalized ratio (INR) above the therapeutic
range confers a predisposition to bleeding,
3
which
is a common cause of hospital admission.
4
Polymorphisms in two genes, CYP2C9 (involved
in the metabolism of the pharmacologically more
potent S-enantiomer of warfarin) and VKORC1
(involved in the vitamin K cycle),
5,6
together with
age and body-surface area, account for about
50% of the variability in the individual daily
dose requirement.
1
Data showing the importance
of these polymorphisms led the Food and Drug
Administration to change the drug label for
warfarin
7
and include the statement, “The pa-
tient’s CYP2C9 and VKORC1 genotype informa-
tion, when available, can assist in selection of
the starting dose.”
8
However, genotyping before
prescription of warfarin is not recommended in
clinical practice guidelines
9
because of the lack
of data from randomized trials and is not per-
formed routinely in clinical practice.
1
A number of prospective studies and random-
ized, controlled trials have failed to show that
genotyping improves ant icoagulation control.
1,10-14
These studies have had limitations with respect
to sample size, dosing algorithms, or genotyping
strategy.
10
Although a recent study showed that
genotype-guided dosing led to superior control
of anticoagulation, the finding was based on a
comparison with a nonrandomized, real-world
parallel control group.
15
In order to fill this
evidence gap, our group, as part of the Euro-
pean Pharmacogenetics of Anticoagulant Therapy
(EU-PACT) consortium,
16
performed a random-
ized, controlled trial of genotype-guided dosing of
warfarin as compared with standard clinical care.
Methods
Trial Design
The EU-PACT warfarin trial was a pragmatic,
single-blind, randomized, controlled trial that
was designed to determine whether genotype-
guided warfarin dosing was superior to standard
dosing. The trial methods have been described
previously.16 The protocol (available with the full
text of this article at NEJM.org) was approved by
the local research ethics committee in Liverpool,
United Kingdom, and by the regional ethical re-
view board in Uppsala, Sweden. Oversight was
provided by a data and safety monitoring board.
Data were collected by the investigators and were
analyzed by a statistician (the second author),
who vouches for the accuracy and completeness
of the data reported. All the authors vouch for
adherence of the study to the protocol. LGC (for-
merly the Laboratory of the Government Chemist)
provided the point-of-care genotyping assay with
funding from the European Union.
Trial Participants
We recruited patients in the United Kingdom
(three centers) and Sweden (two centers). Eligi-
ble patients had not received previous treatment
with warfarin and had either atrial fibrillation
or venous thromboembolism that was deemed
by their attending physician to require antico-
agulation with warfarin with a target INR of 2.0
to 3.0. Recruitment occurred only after the deci-
sion to start warfarin had been made by the pa-
tient’s clinician. Detailed inclusion and exclu-
sion criteria are listed in the Supplementary
Appendix, available at NEJM.org.16 All partici-
pants gave written informed consent before
taking part in the trial.
Trial Procedures
Patients were randomly assigned to either the geno-
type-guided dosing group or the standard dosing
(control) group, with the use of a randomization
schedule incorporated into online software for the
case-report form. Block randomization was strat-
ified according to center and indication (atrial fi-
brillation or venous thromboembolism). Patients
were unaware of the study-group assignments.
Genotyping for the CY P2C9*2, C YP2C9*3, and
VKORC1 (−1639G→A) alleles was performed on a
point-of-care platform with the use of HyBeacon
probes (LGC), which provided results in approxi-
mately 2 hours.
17
Genotyping was performed
immediately after randomization for patients in
the genotype-guided group and after trial com-
pletion for patients in the control group. Details
concerning genotyping are provided in the Sup-
plementary Appendix.
The dosing regimen in the genotype-guided
group was determined in the following way: for
days 1 through 3, the doses were determined on
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2296
the basis of a loading-dose algorithm
18
; this algo-
rithm incorporated predicted maintenance doses
from a slightly modified version of the Interna-
tional Warfarin Pharmacogenetics Consortium
algorithm
19
with the estimated half-life for the
S-enantiomer of warfarin according to CYP2C9
genotype. For days 4 and 5, the doses were deter-
mined on the basis of a dose-revision algorithm
that was based on the INR value on day 4.
20
Both
algorithms incorporated clinical and genetic fac-
tors (Table S1 in the Supplementary Appendix).
The doses after day 5 were determined according
to usual local clinical practice.
In the control group, patients 75 years of age
or younger received 10 mg of warfarin on day 1,
5 mg on day 2, and 5 mg on day 3, whereas pa-
tients older than 75 years of age received 5 mg
per day on days 1 through 3. The doses on days 4
and 5 and thereafter were determined according
to usual local clinical practice.
All patients were followed for 3 months, with
INR measured on days 1, 4, 6, 8, 15, 22, 57, and
Table 1. Demographic and Baseline Clinical Characteristics of the Study Patients.*
Characteristic All Patients Patients Included in Primary Analysis
Genotype-
Guided Group
(N = 227) Control Group
(N = 228) Total
(N = 455)
Genotype-
Guided Group
(N = 211) Control Group
(N = 216) Total
(N = 427)
Center — no. (%)
Enköping, Sweden 16 (7.0) 14 (6.1) 30 (6.6) 14 (6.6) 13 (6.0) 27 (6.3)
Liverpool, U.K. 97 (42.7) 98 (43.0) 195 (42.9) 89 (42.2) 94 (43.5) 183 (42.9)
Newcastle, U.K. 39 (17.2) 37 (16.2) 76 (16.7) 38 (18.0) 37 (17.1) 75 (17.6)
St. Helens, U.K. 40 (17.6) 42 (18.4) 82 (18.0) 35 (16.6) 37 (17.1) 72 (16.9)
Uppsala, Sweden 35 (15.4) 37 (16.2) 72 (15.8) 35 (16.6) 35 (16.2) 70 (16.4)
Indication — no. (%)
Atrial fibrillation 164 (72.2) 164 (71.9) 328 (72.1) 153 (72.5) 157 (72.7) 310 (72.6)
Venous thromboembolism 63 (27.8) 64 (28.1) 127 (27.9) 58 (27.5) 59 (27.3) 117 (27.4)
Age — yr
Mean 67.8±14.5 66.9±12.9 67.3±13.7 67.6±14.3 67.3±12.7 67.5±13.5
Range 23.7 to 90.2 22.0 to 90.2 22.0 to 90.2 24.5 to 90.2 22.0 to 90.2 22.0 to 90.2
Sex — no./total no. (%)
Male 145/226 (64.2) 132/228 (57.9) 277/454 (61.0) 138/211 (65.4) 127/216 (58.8) 265/427 (62.1)
Female 81/226 (35.8) 96/228 (42.1) 177/454 (39.0) 73/211 (34.6) 89/216 (41.2) 162/427 (37.9)
Height — cm
Mean 171.6±10.2 170.4±10.2 171.0±10.2 172.1±9.9 170.4±10.3 171.3±10.2
Range 142 to 195 147 to 194 142 to 195 142 to 195 147 to 194 142 to 195
Weight — kg
Mean 85.6±19.9 87.4±21.0 86.5±20.4 86.3±19.6 87.6±21.4 87.0±20.5
Range 42.9 to 158.8 43.5 to 182.8 42.9 to 182.8 42.9 to 158.8 43.5 to 182.8 42.9 to 182.8
Race — no./total no. (%)†
Black 3/226 (1.3) 2/228 (0.9) 5/454 (1.1) 2/211 (0.9) 2/216 (0.9) 4/427 (0.9)
White 222/226 (98.2) 225/228 (98.7) 447/454 (98.5) 208/211 (98.6) 213/216 (98.6) 421/427 (98.6)
Asian 1/226 (0.4) 1/228 (0.4) 2/454 (0.4) 1/211 (0.5) 1/216 (0.5) 2/427 (0.5)
Smoking status — no./total
no. (%)
Current smoker 23/223 (10.3) 29/227 (12.8) 52/450 (11.6) 20/210 (9.5) 27/215 (12.6) 47/425 (11.1)
Former smoker 93/223 (41.7) 105/227 (46.3) 198/450 (44.0) 88/210 (41.9) 101/215 (47.0) 189/425 (44.5)
Never smoked 107/223 (48.0) 93/227 (41.0) 200/450 (44.4) 102/210 (48.6) 87/215 (40.5) 189/425 (44.5)
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Genotype-Guided Dosing of Warfarin
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2297
85. Some patients had additional clinic visits and
INR measurements, but these were determined
by clinical need.
Outcome Measures
The primary outcome measure was the percent-
age of time in the therapeutic INR range of 2.0 to
3.0, calculated with the use of the method of
Rosendaal et al.,21 during the 12 weeks after the
initiation of warfarin therapy. The secondary
outcome measures included the incidence of INR
values of 4.0 or higher, the percentage of time
with an INR of 4.0 or higher, the percentage of
time with an INR of less than 2.0, the time to
reach a therapeutic INR, and the time to reach a
stable warfarin dose. Additional secondary out-
come measures included major and minor bleed-
ing events, defined according to the International
Society on Thrombosis and Haemostasis (ISTH)
classification22; thromboembolic events; sensitiv-
ity to warfarin; resistance to warfarin; the num-
ber of adjustments in the dose of warfarin; and
the clinical usefulness of the rapid point-of-care
genotyping test. Definitions of the secondary
outcome measures are detailed in the Supple-
mentary Appendix.
Statistical Analysis
The original sample size was calculated with the
use of data on time in the therapeutic range dur-
ing the first 3 months of warfarin therapy from
studies of warfarin use in patients with atrial fi-
brillation or venous thromboembolism.23,24 The
standard deviation of the primary outcome was
estimated at 26.5%. We calculated that 442 pa-
tients would need to be enrolled in each group
Table 1. (Continued.)
Characteristic All Patients Patients Included in Primary Analysis
Genotype-
Guided Group
(N = 227) Control Group
(N = 228) Total
(N = 455)
Genotype-
Guided Group
(N = 211) Control Group
(N = 216) Total
(N = 427)
VKORC1 genotype — no./total
no. (%)‡
G/G 91/226 (40.3) 93/212 (43.9) 184/438 (42.0) 86/211 (40.8) 90/202 (44.6) 176/413 (42.6)
A/G 91/226 (40.3) 90/212 (42.5) 181/438 (41.3) 83/211 (39.3) 85/202 (42.1) 168/413 (40.7)
A/A 44/226 (19.5) 29/212 (13.7) 73/438 (16.7) 42/211 (19.9) 27/202 (13.4) 69/413 (16.7)
CYP2C9 genotype — no./total
no. (%)
*1/*1 150/226 (66.4) 141/213 (66.2) 291/439 (66.3) 142/211 (67.3) 133/203 (65.5) 275/414 (66.4)
*1/*2 47/226 (20.8) 45/213 (21.1) 92/439 (21.0) 42/211 (19.9) 45/203 (22.2) 87/414 (21.0)
*1/*3 21/226 (9.3) 20/213 (9.4) 41/439 (9.3) 20/211 (9.5) 18/203 (8.9) 38/414 (9.2)
*2/*2 6/226 (2.7) 2/213 (0.9) 8/439 (1.8) 5/211 (2.4) 2/203 (1.0) 7/414 (1.7)
*2/*3 2/226 (0.9) 4/213 (1.9) 6/439 (1.4) 2/211 (0.9) 4/203 (2.0) 6/414 (1.4)
*3/*3 0/226 1/213 (0.5) 1/439 (0.2) 0/211 1/203 (0.5) 1/414 (0.2)
Time from randomization to
start of treatment —
days§
Median (interquartile range) 1 (0 to 2) 1 (0 to 1) 1 (0 to 2) 1 (0 to 2) 1 (0 to 1) 1 (0 to 2)
Range –1 to 134 –1 to 46 –1 to 134 –1 to 134 –1 to 46 –1 to 134
* Plus–minus values are means ±SD. Patients included in the primary analysis were those for whom at least 13 days of data on the interna-
tional normalized ratio were available. Unless otherwise indicated, there were no significant differences between the two groups in any
baseline characteristic.
Race was self-reported.
Persons with the G/G genotype have the highest dose requirements, and those with the A/A genotype have the lowest.
§ P = 0.02 for the comparison between the genotype-guided and control groups. The difference was due primarily to logistic and medical rea-
sons (see Table S2 in the Supplementary Appendix). Of the patients included in the analysis, 19 in the genotype-guided group (9.0%) and
21 in the control group (9.7%) received a dose before randomization on day 1, so the doses on days 2 and 3 were adjusted to ensure that
the total dose over a period of 3 days equaled the predicted genotype-determined dose or the standard 3-day dose.
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for the study to have 80% power to show an im-
provement with genotyping of 5 percentage points
in the percentage of time in the therapeutic range,
at a 5% significance level. Owing to challenges
in recruitment, the sample size was recalculated,
with the use of blinded data from the first
222 patients recruited, to give a new estimate of
the standard deviation of 23%. The revised mini-
mum target sample size was set at 200 patients
per study group, which would provide 80% pow-
er to detect a slightly larger improvement in the
primary outcome of 7 percentage points.
Participants who remained in the study on
day 13 or later were included in the analysis ac-
cording to the groups to which they were ran-
domly assigned. Those who dropped out before
day 13 were excluded from the analysis. A per-
protocol analysis was also performed. The INR
value for day 1 (the start of warfarin therapy) was
assumed to be that measured at visit 1 (the ran-
domization visit). If the INR at visit 1 was unavail-
able, it was assumed to be 1.0. When two differ-
ent INR measurements were performed on the
same day, the higher of the two values was used.
Linear regression was used for the statistical
between-group comparison of the primary out-
come and other numerical secondary outcomes.
Categorical outcomes were compared with the
use of logistic regression. Time-to-event outcomes
are shown with the use of Kaplan–Meier curves
and were compared between groups with the use
of Cox regression. The number of dose adjust-
ments was compared between groups with the
use of Poisson regression. All regression analy-
ses included the stratification factors of center
and indication.
Three sensitivity analyses were performed for
the primary outcome. The first included all pa-
tients with at least two INR measurements, in-
cluding those who dropped out before day 13.
The second excluded those who received a dose
of warfarin before randomization, and the third
analyzed the percentage of time in the therapeu-
tic range from randomization to the end of the
3-month follow-up period rather than from the
initiation of treatment to the end of the follow-
up period. The model created for the regression
analyses was assessed by examination of residu-
als. All analyses were performed with the use of
SAS software, version 9.3.
Results
Patients
Recruit ment took place from January 2011 through
January 2013, with final follow-up in April 2013.
A total of 455 patients (353 in the United Kingdom
and 102 in Sweden) underwent randomization,
with 227 assigned to the genotype-guided group
and 228 to the control group (Fig. S1 in the Sup-
plementary Appendix). Most of the patients were
men (61.0%), and 98.5% were white; the mean age
was 67.3 years. The majority of patients (72.1%)
had atrial fibrillation; those with venous throm-
boembolism received heparin for at least 5 days
after the initial diagnosis. The two groups were
well balanced with respect to the baseline char-
acteristics (Table 1). The genotype distributions in
the two groups were similar to those described in
the literature.5
We included in the analysis only the 427 pa-
tients who had at least 13 days of INR data: 211
in the genotyped-guided group and 216 in the
control group (
Table 1
). The reasons that patients
dropped out of the study are shown in Figure S1
in the Supplementary Appendix, and the protocol
deviations are shown in Table S2 in the Supple-
mentary Appendix. There were 7 deaths (5 in the
genotype-guided group and 2 in the control group)
during the trial, none of which were judged to be
due to the use of, or indication for, warfarin
Primary Outcome
The unadjusted percentage of time with an INR
of 2.0 to 3.0 was 67.4% in the genotype-guided
group as compared with 60.3% in the control
group. This represents a difference of 7.0 per-
centage points (95% confidence interval, 3.3 to
10.6; P<0.001) (Table 2) after adjustment for cen-
ter and indication. In the per-protocol analysis,
the corresponding values in the genotype-guided
group (166 patients) and control group (184 pa-
tients) were 68.9% and 62.3%, with an adjusted
difference of 6.6 percentage points (P = 0.001).
The findings of the sensitivity analyses were con-
sistent with those of the primary analysis.
The differences in the mean INR between the
two groups were greatest soon after the initia-
tion of anticoagulation and became less pro-
nounced during the 3-month follow-up period
(Fig. 1A). The difference between the two groups
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Genotype-Guided Dosing of Warfarin
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2299
in the mean percentage of time in the therapeutic
range became apparent between 5 and 10 days
after the initiation of warfarin therapy (Fig. 1B),
with significant differences observed for weeks 1
through 4 and 5 through 8 but not for weeks 9
through 12 (
Table 3
). There was some variation
among centers in the control of anticoagulation
in both trial groups, with the between-group
difference in the time in the therapeutic range
ranging from 1.7 to 11.4 percentage points
(Table S3 in the Supplementary Appendix).
Secondary Outcomes
Patients in the genotype-guided group were less
likely to have an INR of 4.0 or higher than were
those in the control group (Table 3). The median
time to reach a therapeutic INR — which was
calculated as the median time to the first of two
INR values, measured at least 1 week apart, that
were within the target range — was shorter in
the genotype-guided group than in the control
group (Fig. 2A). A total of 173 patients (82.0%) in
the genotype-guided group reached a stable dose
by 3 months, as compared with 152 patients
(70.4%) in the control group, with patients in the
genotype-guided group reaching a stable dose
more quickly than those in the control group
(Table 3 and Fig. 2B). There were also fewer ad-
justments in the dose of warfarin in the geno-
type-guided group than in the control group.
There was no significant difference between the
two groups in the median number of additional
INR measurements (four in each group) above
those required by the protocol.
No major bleeding events according to the
ISTH classification
22
were reported in the trial,
and there was no significant difference in over-
all bleeding events between the two groups.
Three bleeding events (all in the control group)
were classified as clinically significant and re-
quired admission to the hospital. The majority
of the minor bleeding episodes consisted of
bruising (Table S4 in the Supplementary Appen-
dix). There was only one thromboembolic event
(in the control group). There were no significant
differences in the other secondary outcomes
between the two groups (
Table 3
).
An analysis performed at the end of the study
showed that the genotyping by means of the
point-of-care assay was incorrect in the case of
six patients. This affected VKORC1 genotyping only
and was due either to problems with the stability
Table 2. Percentage of Time in the Therapeutic Range for International Normalized Ratio (INR).*
Analysis Genotype-Guided Group Control Group Least-Squares Mean Difference†
No. of
Patients
% Time in
Therapeutic
Range‡ No. of
Patients
% Time in
Therapeutic
Range‡
Percentage
Points
(95% CI)§ P Value
Patients with ≥13 days of INR data 211 67.4±18.1 216 60.3±21.7 7.0 (3.3–10.6) <0.001
Per-protocol analysis¶ 166 68.9±16.9 184 62.3±21.2 6.6 (2.7–10.5) 0.001
Sensitivity analyses
All randomly assigned patients with
≥1 subsequent INR measurement 215 66.6±19.1 223 59.2±22.5 7.3 (3.5–11.1) <0.001
Percentage of time in therapeutic
range from day of randomization‖ 211 65.9±17.8 216 58.9±21.2 6.9 (3.3–10.5) <0.001
Exclusion of patients who underwent
randomization after 1 dose of
warfarin
192 67.1±18.2 195 60.1±21.9 7.1 (3.2–11.0) <0.001
* Plus–minus values are means ±SD. The percentage of time in the therapeutic INR range of 2.0 to 3.0 was calculated with the use of general-
ized linear models. Except in a sensitivity analysis, the time in the therapeutic INR was calculated from the time of initiation of therapy.
The differences between groups were adjusted for center and indication (atrial fibrillation or venous thromboembolism).
The percentage of time in the therapeutic range is the least-squares mean.
§ The difference in least-squares means is for the genotype-guided group minus the control group.
The per-protocol analysis included all patients without a major protocol deviation.
‖ Patients underwent randomization at visit 1, which ranged from 7 days before the start of warfarin therapy to 1 day after the start of warfarin
therapy.
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2300
of the genotyping reagents or operator error in the
interpretation of results (Table S2 in the Supple-
mentary Appendix). Despite these errors, the sen-
sitivity and specificity values for genotyping for all
three alleles were high (Table S5 in the Supple-
mentary Appendix).
Discussion
Our trial showed that genotype-based dosing at
the initiation of warfarin therapy increased the
time in the therapeutic range (the primary out-
come) by 7 percentage points and reduced the
incidence of excessive anticoagulation, the time
required to reach a therapeutic INR, the time re-
quired to reach a stable dose, and the number of
adjustments in the dose of warfarin. However,
the median number of additional INR measure-
ments did not differ between the two groups be-
cause the protocol required eight INR measure-
ments over a period of 3 months after the
initiation of warfarin. Our findings are consis-
tent with those of observational studies of the
effect of the VKORC1 and CYP2C9 genotypes on
warfarin dose requirement,5,6 and the prospec-
tive, nonrandomized, parallel-group comparison
performed by Anderson et al.,15 which showed a
mean time in the therapeutic range of 71% in the
genotype-guided group and 59% in the control
group at 3 months.
In order to achieve rapid but safe anticoagula-
tion, a new pharmacogenetic loading-dose algo-
rithm
18
was developed that took into account the
effect of CY P2C9 allelic variants on the pharmaco-
kinetics of warfarin. Our algorithmic strategy re-
duced the likelihood of excessive anticoagulation
(INR ≥4.0) in the early stages of anticoagulation,
while reducing the time to achieve a therapeutic
INR, suggesting that genotype-guided dosing may
not only prove to be safer but may also reduce
the time required for stabilization when adopting
a loading-dose strategy. The difference in mean
INR between the two groups was greatest near
the start of the trial (Fig. 1A), a finding that is
consistent with previous findings that genotype-
guided dosing has the greatest effect during the
early stages of warfarin therapy.
25
Our trial design was consistent with clinical
practice in the United Kingdom and Sweden in
two major respects. First, clinical algorithms are
not used in either country; thus, the study was
designed pragmatically to ref lect clinical prac-
tice, assessing the potential benefits of genotype-
guided dosing as compared with standard dosing.
Although our trial could be criticized for not
having compared a genotype-guided dosing al-
gorithm with a clinical algorithm, the values for
the percentage of time in the therapeutic range in
the control group were either equivalent to or ex-
ceeded those observed in previous studies (Table S6
in the Supplementary Appendix). Second, we used
loading doses that follow the American College
of Chest Physicians guidelines.
9
This strategy has
the advantage of reducing the time to reach a
therapeutic INR
26
but increases the risk of exces-
sive anticoagulation, particularly in the elderly.
27
INR
3.0
2.5
1.5
2.0
1.0
0 5 10 15 20 25 8530 35 40 45 50 65 70 75 8055 60
Day
B
A
Control group
Control group
Genotype-guided group
Time in Therapeutic Range (%)
60
50
40
20
10
30
0
0 5 10 15 20 25 8530 35 40 45 50 65 70 75 8055 60
Day
Genotype-guided group
Figure 1. Mean International Normalized Ratio (INR) and Percentage
of Time in the Therapeutic INR Range.
The differences between the genotype-guided dosing group and the stan-
dard dosing (control) group in the mean INR (Panel A) and the percentage
of time in the therapeutic INR range of 2.0 to 3.0 (Panel B) are shown over
a follow-up period of 3 months.
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Genotype-Guided Dosing of Warfarin
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2301
A major limitation of our trial is that the
primary outcome measure was the time in the
therapeutic range, rather than the clinical out-
come measures of bleeding and thrombosis. On
the basis of our finding that approximately 37%
of the patients in the control group had bleeding
events, we would have had to enroll 2916 pa-
tients to show a reduction of 5 percentage points
in the rate of bleeding events (to 32%) in the
genotype-guided group, with 80% power. How-
ever, bleeding events increase when the INR is
4.0 or higher,
28
and genotype-guided dosing in
our trial reduced the incidence of, and the time
with, an INR of 4.0 or higher.
Our trial did not use a double-blind design.
Although this design would have been possible,
it would have been more complex to implement.
However, because dosing was based on a de-
fined regimen in the genotype-guided group for
the first 5 days and in the control group for the
first 3 days and did not differ between the groups
thereafter, we believe that the clinical care of pa-
tients was not influenced by treatment assign-
ment. In addition, because we were using an ob-
jective and measurable end point (i.e., INR), we
do not believe that the outcome assessment was
biased.
The majority of our patients were of European
ethnic background, and we cannot generalize
our findings to other ethnic groups. Although
the same genes determine warfarin dose re-
quirements in different ethnic groups,
29
the
frequency of the individual gene variants dif-
fers,
29,30
and algorithms that are specific to
ethnic groups will need to be developed. The
development of a robust evidence-based algo-
rithmic strategy is crucial for improving warfa-
rin dosing in all ethnic groups.
Table 3. Secondary Outcome Measures and Time-Dependent Analyses of the Primary Outcome Measure.*
Outcome
Genotype-
Guided Group
(N = 211) Control Group
(N = 216) Comparison
(95% CI) P Value
INR ≥4.0 — % of patients 57 (27.0) 79 (36.6) 0.63 (0.41 to 0.97)† 0.03
Percentage of time with INR ≥4.0 2.3±6.4 5.3±10.3 –2.9 (–4.5 to –1.4)‡ <0.001
Percentage of time with INR <2.0 20.0±14.9 21.9±16.9 –2.0 (–4.9 to 1.0)‡ 0.20
Time to reach therapeutic INR — days 1.43 (1.17 to 1.76)§ <0.001
Median 21 29
Interquartile range 8 to 36 14 to 58
Time to reach stable dose — days 1.40 (1.12 to 1.74)§ 0.003
Median 44 59
Interquartile range 35 to 70 41 to 86
Dose adjustments — no. 4.9±2.6 5.4±3.0 0.91 (0.83 to 0.99)¶ 0.02
Major bleeding events — no. of patients‖ 0 0
Bleeding events — no. of patients (%) 78 (37.0) 82 (38.0) 0.96 (0.62 to 1.49)† 0.87
Thromboembolic events — no. of patients (%)‖ 01 (0.5)
Warfarin sensitivity — no. of patients (%)‖ 4 (1.9) 2 (0.9)
Warfarin resistance — no. of patients (%)‖ 4 (1.9) 3 (1.4)
Percentage of time in therapeutic INR range**
During wk 1–4 54.6±23.0 45.7±24.3 8.8 (4.4 to 13.1)‡ <0.001
During wk 5–8 73.9±28.0 63.5±33.1 10.2 (4.4 to 16.0)‡ <0.001
During wk 9–12 74.5±25.2 72.9±29.8 1.4 (–3.8 to 6.6)‡ 0.61
* Plus–minus values are means ±SD. All comparisons were adjusted for center and indication (atrial fibrillation or venous thromboembolism).
The value is the odds ratio for the genotype-guided group.
The value is the difference in percentage points (genotype-guided group minus the control group).
§ The value is the Cox proportional-hazards ratio for the genotype-guided group.
The value is the incidence rate ratio for the genotype-guided group.
A statistical comparison was not performed owing to an insufficient number of events.
** This was a post hoc analysis.
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The
new england journal
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n engl j med 369;24 nejm.org december 12, 2013
2302
In conclusion, we found that genotype-guid-
ed warfarin dosing was superior to standard
dosing with respect to both the primary out-
come measure (time in the therapeutic INR
range) and a number of secondary outcome
measures. Whether this will translate to im-
proved clinical outcomes is unclear.
Supported by funding from the European Commission Sev-
enth Framework Programme (FP7-223062); the Cheshire and
Merseyside National Institute for Health Research (NIHR) Com-
prehensive Local Research Network (CLRN) and the Stroke Re-
search Network (to Dr. Pirmohamed); the NIHR Biomedical
Research Centre and the Northern CLRN (to Dr. Kamali); a Se-
nior Investigator Award from the NIHR, the NHS Chair of Phar-
macogenetics from the U.K. Department of Health, and the
Medical Research Council Centre for Drug Safety Science (all to
Dr. Pirmohamed); and the Swedish Research Council (Medicine
523-2008-5568 and 521-2011-2440), the Swedish Heart–Lung
Foundation, and Uppsala University (all to Dr. Wadelius).
Disclosure forms provided by the authors are available with
the full text of this article at NEJM.org.
Probability
1.0
0.8
0.9
0.7
0.6
0.4
0.3
0.1
0.5
0.2
0.0
0 20 40 60 80 100
Days to Reach Therapeutic INR
B
A
No. at Risk
Control group
Genotype-guided group
216
211
205
194
169
139
161
127
141
112
117
78
97
69
95
60
85
49
73
41
67
33
62
30
46
25
29
16
44
23
38
22
30
18
0
0
21
9
3
1
Genotype-guided group
Genotype-guided group
Control group
Control group
Probability
1.0
0.8
0.9
0.7
0.6
0.4
0.3
0.1
0.5
0.2
0.0
0 20 40 60 80 100
Days to Reach Stable Dose
No. at Risk
Control group
Genotype-guided group
216
211
216
211
216
211
216
210
214
210
206
201
188
175
176
161
160
133
132
102
120
85
109
75
99
71
56
38
87
59
75
55
66
43
037
18
4
0
Figure 2. Kaplan–Meier Plots of the Time to Reach a Therapeutic INR and to Reach a Stable Warfarin Dose.
The plus signs indicate censored data.
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Genotype-Guided Dosing of Warfarin
n engl j med 369;24 nejm.org december 12, 2013
2303
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References
We thank all the patients who participated in this trial, all
staff at the anticoagulation clinics in all the hospitals used for
recruitment, and Rita Barallon and Paul Debenham of LGC,
Teddington, United Kingdom, for providing the point-of-care
genotyping assay. Additional acknowledgments of trial con-
tributors are included in the Supplementary Appendix.
2013
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... More than a third (40%) of the participants randomized to RCTs evaluating the clinical utility of genotype guided dosing identified as White. The three largest trials that recruited this population were the Genetic Informatics Trial (GIFT) conducted in the United States (Gage et al., 2017), the Clarification of Optimal Anticoagulation through Genetics (COAG) trial also conducted in the United States (Kimmel et al., 2013) and the European Pharmacogenetics of Anticoagulant Therapy (EU-PACT) trial conducted in the United Kingdom and Sweden (Pirmohamed et al., 2013). Two of these trials (COAG and EU-PACT) were published at the same time in 2013 and many comparisons were made between them because of contradictory results. ...
... As the COAG trial (Kimmel et al., 2013) demonstrated, using pharmacogenomic dosing algorithms that do not include ethnospecific genetic factors can lead to sub-optimal anticoagulation for these populations, which could exacerbate healthcare disparities (Martin et al., 2017). For example, in previous work we have conducted in sub-Saharan Africa (South Africa and Uganda), we observed that fixed-dose initiation was associated with a median time in therapeutic range (TTR) of 41% (Semakula et al., 2020), which is much lower than that observed in an European (Sweden and United Kingdom) cohort (mean TTR 60%) (Pirmohamed et al., 2013). Implementing a pharmacogenomic-dosing algorithm in the European cohort increased the mean TTR to 67% (Pirmohamed et al., 2013), which makes the anticoagulation quality gap with sub-Saharan Africa even wider as there is no validated pharmacogenomic dosing algorithm in this region at the moment . ...
... For example, in previous work we have conducted in sub-Saharan Africa (South Africa and Uganda), we observed that fixed-dose initiation was associated with a median time in therapeutic range (TTR) of 41% (Semakula et al., 2020), which is much lower than that observed in an European (Sweden and United Kingdom) cohort (mean TTR 60%) (Pirmohamed et al., 2013). Implementing a pharmacogenomic-dosing algorithm in the European cohort increased the mean TTR to 67% (Pirmohamed et al., 2013), which makes the anticoagulation quality gap with sub-Saharan Africa even wider as there is no validated pharmacogenomic dosing algorithm in this region at the moment . Moreover, Europe which is wealthier than sub-Saharan Africa is able to afford the more costly new direct oral anticoagulants (DOACs), whereas sub-Saharan Africa's choices are mainly limited to warfarin due to its low cost . ...
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Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.
... The resulting economic burden in the United States has been estimated at $30 billion to $136 billion annually (Johnson and Bootman, 1995). Several prospective studies support the clinical impact of individual gene-drug interactions (DGIs) to either optimize dosing (Pirmohamed et al., 2013;Verhoef et al., 2013;Coenen et al., 2015;Wu, 2015;Henricks et al., 2018) or drug selection (Mallal et al., 2008;Claassens et al., 2019a). Additionally, both the Clinical Pharmacogenetics Implementation Consortium (CPIC) (Relling and Klein, 2011;Relling et al., 2020) and the Dutch Pharmacogenetics Working Group (DPWG) (Swen et al., 2008;Swen et al., 2011;Swen et al., 2018) have developed guidelines on incorporating PGx results into drug prescribing. ...
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Aim: Prospective studies support the clinical impact of pharmacogenomics (PGx)-guided prescribing to reduce severe and potentially fatal adverse effects. Drug-gene interactions (DGIs) preventing potential drug-related deaths have been categorized as “essential” by the Dutch Pharmacogenetics Working Group (DPWG). The collective clinical impact and cost-effectiveness of this sub-set is yet undetermined. Therefore, we aim to assess impact and cost-effectiveness of “essential” PGx tests for prevention of gene-drug-related deaths, when adopted nation-wide. Methods: We used a decision-analytic model to quantify the number and cost per gene-drug-related death prevented, from a 1-year Dutch healthcare perspective. The modelled intervention is a single gene PGx-test for CYP2C19, DPYD, TPMT or UGT1A1 to guide prescribing based on the DPWG recommendations among patients in the Netherlands initiating interacting drugs (clopidogrel, capecitabine, systemic fluorouracil, azathioprine, mercaptopurine, tioguanine or irinotecan). Results: For 148,128 patients initiating one of seven drugs in a given year, costs for PGx-testing, interpretation, and drugs would increase by €21.4 million. Of these drug initiators, 35,762 (24.1%) would require an alternative dose or drug. PGx-guided prescribing would relatively reduce gene-drug related mortality by 10.6% (range per DGI: 8.1–14.5%) and prevent 419 (0.3% of initiators) deaths a year. Cost-effectiveness is estimated at €51,000 per prevented gene-drug-related death (range per DGI: €-752,000–€633,000). Conclusion: Adoption of PGx-guided prescribing for “essential” DGIs potentially saves the lives of 0.3% of drug initiators, at reasonable costs.
... [222]. In addition, testing for warfarin/CYP2C9/VKORC-1 and carbamazepine/HLA-A is expected to be introduced imminently for certain patients [222,323]. ...
Thesis
In this thesis, I investigate the impact of genetic variation on adverse drug reactions to psychotropic medications, with a focus on the metabolic and sleep related side effects of psychotropic drugs. In addition to reviewing published literature, I have considered this research topic in three main ways. Chapter one is a systematic review and meta-analysis of the impact of CYP2D6 genetic variation on antipsychotic-induced hyperprolactinaemia and weight gain, which are a relatively common but understudied adverse-drug reactions. Chapters two, three and four are based on data from UK Biobank, where I have conducted a hypothesis-driven analyses of known pharmacogenes and their association with two common adverse drug reactions: increased diabetes risk and sleep disturbance. In working on this thesis, two key limitations became apparent. Firstly, inconsistencies in genotyping and phenotyping make some findings difficult to interpret. Secondly, the nature of my analysis using cross-sectional UK Biobank data makes it difficult to draw firm conclusions on the causal direction of any observations. Chapter five aim to address these limitations. Here, I describe the set-up of a clinical study to assess pharmacogenetic interventions in a psychiatric patient population. Although only pilot data is available, due to a pause in recruitment during the Covid-19 pandemic, I describe the scientific rationale for the study and outline the work conducted to set-up and gain ethical approvals for the study. In addition, I outline my contribution to drafting clinical guidelines for the implementation of pharmacogenetic testing in the NHS.
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Background: Warfarin is a commonly used anticoagulant drug in clinical practice. Rapidly achieving the first therapeutic international normalized ratio (INR) of warfarin may reduce the hospital length of stay. However, little research has been carried out to evaluate the influencing factors and the safety of rapidly achieving the first therapeutic INR target of warfarin. Aim: To investigate the associated factors and the safety of rapidly achieving the first therapeutic INR target of warfarin. Method: A retrospective cohort study was conducted in inpatients who took warfarin from November 2018 to October 2019. Patients' information was retrieved from medical records. Results: 487 patients were included. The mean achieving first therapeutic target time was 6.0 ± 3.2 days (median, 5.0 days). Age > 65 years, body mass index < 24 kg/m2, and initial warfarin dose ≥ 3 mg/d were independent factors associated with the rapidly achieving first INR target of warfarin therapy. The incidence of INR ≥ 4 was higher in patients achieving the first INR target rapidly than those achieving the first INR target slowly, while there were no significant differences in bleeding events between the two groups. Conclusions: Hospitalized patients aged > 65 years, with a body mass index < 24 kg/m2, or receiving an initial warfarin dose ≥ 3 mg/d were more likely to achieve the first INR target of warfarin rapidly. Closer INR monitoring and appropriate warfarin dose adjustment are recommended to improve the safety for patients achieving the first INR ≥ 1.8 within 6 days after beginning oral warfarin.
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Background For decades, vitamin K antagonists and specifically warfarin, have been the sole agents used orally to manage thromboembolic conditions, including stroke and venous thromboembolism (VTE). Several factors lead to warfarin dose variability, including genetic and non-genetic factors which made warfarin management challenging especially at the initiation phase. To overcome the challenges with warfarin dosing at initiation, strategies other than conventional or fixed dosing were introduced and explored. Aim In this narrative review, we aim to discuss and critique the different dosing strategies for warfarin at initiation with more focus on genotype-guided warfarin dosing and the most recent supporting evidence for and against its use. Method Medline database was searched from 1965 to July 2021. Articles addressing different warfarin dosing methods were screened for inclusion. Results A number of methods exist for warfarin initiation. Studies comparing different dosing methods for initiation yielded conflicting outcomes due to differences in study design, population studied, comparator, and outcomes measured. Conclusions Looking at the big picture, the use of genetic dosing for warfarin initiation can lead to better outcomes. Whether these better outcomes are clinically or economically beneficial remains controversial.
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Well-characterized genes that affect warfarin metabolism (cytochrome P450 (CYP) 2C9) and sensitivity (vitamin K epoxide reductase complex 1 (VKORC1)) explain one-third of the variability in therapeutic dose before the international normalized ratio (INR) is measured. To determine genotypic relevance after INR becomes available, we derived clinical and pharmacogenetic refinement algorithms on the basis of INR values (on day 4 or 5 of therapy), clinical factors, and genotype. After adjusting for INR, CYP2C9 and VKORC1 genotypes remained significant predictors (P < 0.001) of warfarin dose. The clinical algorithm had an R2 of 48% (median absolute error (MAE): 7.0 mg/week) and the pharmacogenetic algorithm had an R2 of 63% (MAE: 5.5 mg/week) in the derivation set (N = 969). In independent validation sets, the R2 was 26–43% with the clinical algorithm and 42–58% when genotype was added (P = 0.002). After several days of therapy, a pharmacogenetic algorithm estimates the therapeutic warfarin dose more accurately than one using clinical factors and INR response alone.
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Background: Warfarin is a highly effective anticoagulant however its effectiveness relies on maintaining INR in therapeutic range. Finding the correct dose is difficult due to large inter-individual variability. Two genes, CYP2C9 and VKORC1, have been associated with this variability, leading to genotype-guided dosing tables in warfarin labeling. Nonetheless, it remains unclear how genotypic information should be used in practice. Navigating the literature to determine how genotype will influence warfarin response in a particular patient is difficult, due to significant variation in patient ethnicity, outcomes investigated, study design, and methodological rigor. Our systematic review was conducted to enable fair and accurate interpretation of which variants affect which outcomes, in which patients, and to what extent. Methodology/principal findings: A comprehensive search strategy was applied and 117 studies included. Primary outcomes were stable dose, time to stable dose and bleeding events. Methodological quality was assessed using criteria of Jorgensen and Williamson and data synthesized in meta-analyses using advanced methods. Pooled effect estimates were significant in most ethnic groups for CYP2C9*3 and stable dose (mutant types requiring between 1.1(0.7-1.5) and 2.3 (1.6-3.0)mg/day). Effect estimates were also significant for VKORC1 and stable dose for most ethnicities, although direction differed between asians and non-asians (mutant types requiring between 0.8(0.4-1.3) and 1.5(1.1-1.8)mg/day more in asians and between 1.5(0.7-2.2) and 3.1(2.7-3.6)mg/day less in non-asians). Several studies were excluded due to inadequate data reporting. Assessing study quality highlighted significant variability in methodological rigor. Notably, there was significant evidence of selective reporting, of outcomes and analysis approaches. Conclusions/significance: Genetic associations with warfarin response vary between ethnicities. In order to achieve unbiased estimates in different populations, a high level of methodological rigor must be maintained and studies should report sufficient data to enable inclusion in meta-analyses. We propose minimum reporting requirements, suggest methodological guidelines and provide recommendations for reducing the risk of selective reporting.
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Genotype-based dosing recommendations are provided in the US FDA-approved warfarin labeling. However, data that informed these recommendations were from predominately Caucasian populations. Studies show that variants contributing to warfarin dose requirements in Caucasians provide similar contributions to dose requirements in US Hispanics, but significantly lesser contributions in African-Americans. Further data demonstrate that variants occurring commonly in individuals of African ancestry, but rarely in other racial groups, significantly influence dose requirements in African-Americans. These data suggest that it is important to consider variants specific for African-Americans when implementing genotype-guided warfarin dosing in this population.
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Objective: To explore the rational use of anticoagulants, especially among the elderly, balancing antithrombotic efficacy and risk for hemorrhage. Previous prospective studies have not provided powerful assessments of risk factors for intracranial hemorrhage, the dominant complication in reversing the anticoagulant decision. Design: Case-control analysis. Setting: A large general hospital and its anticoagulant therapy unit. Patients: 121 consecutive adult patients taking warfarin who were hospitalized with intracranial hemorrhage were each matched to three contemporaneous controls randomly selected from among outpatients managed by our hospital anticoagulant therapy unit. Results: 77 patients had intracerebral hemorrhage (46% fatal) and 44 had subdural hemorrhage (20% fatal). The prothrombin time ratio (PTR) was the dominant risk factor for intracranial hemorrhage. For each 0.5 increase in PTR over the entire range, the risk for intracerebral hemorrhage doubled (odds ratio, 2.1; 95% CI, 1.4 to 2.9). For subdural hemorrhage, the risk was unchanged over the PTR range from 1.0 to 2.0 but rose dramatically above a PTR of 2.0 (approximate international normalized ratio, 4.0). Age was the only other significant independent risk factor for subdural hemorrhage (odds ratio, 2.0 per decade; CI, 1.3 to 3.1). For intracerebral hemorrhage, age was of borderline significance (odds ratio, 1.3 per decade; CI, 1.0 to 1.6) after controlling for PTR and the two other independent risk factors: history of cerebrovascular disease (odds ratio, 3.1; CI, 1.7 to 5.6) and presence of a prosthetic heart valve (odds ratio, 2.8; CI, 1.3 to 5.8). Conclusions: The results emphasize the importance of maintaining the prothrombin time ratios under 2.0 and the need for especially careful use of warfarin in the elderly.
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Background: The main challenge for warfarin anticoagulation is the risk for hemorrhagic complications. Although certain pharmacogenetic factors may explain the individual variabilities about the therapeutic warfarin dose requirement, the genetic factors to warfarin hemorrhagic complications due to over-anticoagulation are largely unknown. To interpret the potential role of warfarin-related genotypes on over-anticoagulation and hemorrhagic complications, we conducted a meta-analysis based on 22 published studies. Methods: A comprehensive search was applied to the reports on over-anticoagulation and hemorrhagic complications published prior to December 31, 2012 in PubMed and EMBASE. References were identified by strict inclusion and exclusion criteria, with additional information obtained by consulting with the authors of primary studies. The roles of genotypes in CYP2C9 and VKORC1 on over-anticoagulation (INR > 4) and hemorrhagic complications were analyzed by Revman 5.0.2 software. Results: A total of 6272 patients in 22 reports were included in the meta-analysis, including studies of 18 from Caucasians (3 from both Caucasian and African-American), 3 from Asians, and 1 from Brazilians. Compared to CYP2C9 wild genotype (CYP2C9*1), both CYP2C9*2 (rs 1799853, c. 430 C > T, p. Arg144Cys) and *3 (rs 1057910, c. 1075 A >C, p. Ile359Leu) confer significantly higher risk for warfarin over-anticoagulation and hemorrhagic complications. After stratification by CYP2C9 allele status, significantly higher risk for hemorrhagic complications was found only in carriers of at least 1 copy of CYP2C9*3 [For total hemorrhages: *1/*3 HR: 2.05 (1.36-3.10), p < 0.001; *3/*3 HR: 4.87 (1.38-17.14), p = 0.01; For major hemorrhages: *1/*3 HR: 2.43 (1.17-5.06), p = 0.02; *3/*3 HR: 4.81 (0.95-24.22), p = 0.06]. Furthermore, similar susceptibility of total hemorrhage by CYP2C9 genotypes was observed in Caucasians and Asians. After stratification by the occurrence time, both CYP2C9*2 and *3 are risk factors for over-anticoagulation within 30 days of warfarin treatment [*2 HR: 1.64 (1.11-2.43), p = 0.01; *3 HR: 2.48 (1.56-3.96), p < 0.001], and only CYP2C9*3 showed higher risk for over-anticoagulation after 30 days [HR: 1.86 (1.08-3.20), P = 0.03]. For VKORC1 c. -1639G > A (rs 9923231) genotypes, GA and AA contributed significantly higher risk for over-anticoagulation within 30 days [HR: 2.14 (1.75-2.62), p < 0.001], but not for over-anticoagulation after 30 days [HR:0.78 (0.46-1.33), p = 0.36]. No significant association was found between VKORC1 genotypes and hemorrhagic complications. Conclusions: Both CYP2C9 and VKORC1 genotypes are associated with an increased risk for warfarin over-anticoagulation, with VKORC1 c. -1639G > A more sensitive early in the course of anticoagulation. CYP2C9*3 is the main genetic risk factor for warfarin hemorrhagic complications.
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Background: VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans. Methods: We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 -1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10(-8) in the discovery cohort and p<0·0038 in the replication cohort. Findings: The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10(-8)). This association was confirmed in the replication cohort (p=5·04×10(-5)); analysis of the two cohorts together produced a p value of 4·5×10(-12). Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement). Interpretation: A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population. Funding: National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.
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Coumarin anticoagulants, which include warfarin, acenocoumarol and phenprocoumon, are among the most widely prescribed drugs worldwide. There is now a large body of published data showing that genotype for certain common polymorphisms in the genes encoding the target vitamin K epoxide reductase (G-1639A/C1173T) and the main metabolizing enzyme CYP2C9 (CYP2C9*2 and *3 alleles) are important determinants of the individual coumarin anticoagulant dose requirement. Additional less common polymorphisms in these genes together with polymorphisms in other genes relevant to blood coagulation such as the cytochrome P450 CYP4F2, gamma-glutamyl carboxylase, calumenin and cytochrome P450 oxidoreductase may also be significant predictors of dose, especially in ethnic groups such as Africans where there have been fewer genetic studies compared with European populations. Using relevant genotypes to calculate starting dose may improve safety during the initiation period. Various algorithms for dose calculation, which also take patient age and other characteristics into consideration, have been developed for all three widely used coumarin anticoagulants and are now being tested in ongoing large randomised clinical trials. One recently completed study has provided encouraging results suggesting that calculation of warfarin dose on the basis of individual patient genotype leads to few adverse events and a higher proportion of time within the therapeutic coagulation rate window, but these findings still need confirmation.
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Background: Warfarin is used as an oral anticoagulant. However, there is wide variation in patient response to warfarin dose. This variation, as well as the necessity of keeping within a narrow therapeutic range, means that selection of the correct warfarin dose at the outset of treatment is not straightforward. Objectives: To assess the effectiveness of different initiation doses of warfarin in terms of time in-range, time to INR in-range and effect on serious adverse events. Search methods: We searched CENTRAL, DARE and the NHS Health economics database on The Cochrane Library (2012, Issue 4); MEDLINE (1950 to April 2012) and EMBASE (1974 to April 2012). Selection criteria: All randomised controlled trials which compared different initiation regimens of warfarin. Data collection and analysis: Review authors independently assessed studies for inclusion. Authors also assessed the risk of bias and extracted data from the included studies. Main results: We identified 12 studies of patients commencing warfarin for inclusion in the review. The overall risk of bias was found to be variable, with most studies reporting adequate methods for randomisation but only two studies reporting adequate data on allocation concealment. Four studies (355 patients) compared 5 mg versus 10 mg loading doses. All four studies reported INR in-range by day five. Although there was notable heterogeneity, pooling of these four studies showed no overall difference between 5 mg versus 10 mg loading doses (RR 1.17, 95% CI 0.77 to 1.77, P = 0.46, I(2) = 83%). Two of these studies used two consecutive INRs in-range as the outcome and showed no difference between a 5 mg and 10 mg dose by day five (RR 0.86, 95% CI 0.62 to 1.19, P = 0.37, I(2 )= 22%); two other studies used a single INR in-range as the outcome and showed a benefit for the 10 mg initiation dose by day 5 (RR 1.49, 95% CI 1.01 to 2.21, P = 0.05, I(2 )= 72%). Two studies compared a 5 mg dose to other doses: a 2.5 mg initiation dose took longer to achieve the therapeutic range (2.7 versus 2.0 days; P < 0.0001), but those receiving a calculated initiation dose achieved a target range quicker (4.2 days versus 5 days, P = 0.007). Two studies compared age adjusted doses to 10 mg initiation doses. More elderly patients receiving an age adjusted dose achieved a stable INR compared to those receiving a 10 mg initial dose (and Fennerty regimen). Four studies used genotype guided dosing in one arm of each trial. Three studies reported no overall differences; the fourth study, which reported that the genotype group spent significantly more time in-range (P < 0.001), had a control group whose INRs were significantly lower than expected. No clear impacts from adverse events were found in either arm to make an overall conclusion. Authors' conclusions: The studies in this review compared loading doses in several different situations. There is still considerable uncertainty between the use of a 5 mg and a 10 mg loading dose for the initiation of warfarin. In the elderly, there is some evidence that lower initiation doses or age adjusted doses are more appropriate, leading to fewer high INRs. However, there is insufficient evidence to warrant genotype guided initiation.
Article
Background: In this prospective cohort study, we have undertaken a comprehensive evaluation of clinical parameters along with variation in 29 genes (including CYP2C9 and VKORC1) to identify factors determining interindividual variability in warfarin response. Methods: Consecutive patients (n=311) were followed up prospectively for 26 weeks. Several outcomes chosen to capture both warfarin efficacy and toxicity were assessed. Univariate and multiple regression analyses were undertaken to assess the combined effect of clinical and genetic factors. Results: CYP2C9 was the most important gene determining initial anticoagulant control, whereas VKORC1 was more important for stable anticoagulation. Novel associations with some clinical outcomes were found with single nucleotide polymorphisms in the cytochrome 450 genes CYP2C18 and CYP2C19, which were independent of the associations observed with CYP2C9 and in genes encoding CYP3A5, protein S and clotting factor V, although the variability explained by these genes was small. On the basis of the results of microcosting, adverse events were shown to be a significant predictor of total cost. Conclusion: Accurate prediction of warfarin dose requirement needs to take into account multiple genetic and environmental factors, the contributions of which vary in the induction and maintenance phases of treatment.