Transcript Poster - Medical Research Council Clinical Trials Unit

33
The impact of different definitions on the estimated rate of
drug resistance
in the
UKuse for national
The UK HIV Drugtransmitted
Resistance HIV
Database:
Development
and
Hannah Green1, Peter surveillance
Tilston2, Esther Fearnhill1 and David Dunn1
on behalf of the UK Collaborative Group on HIV Drug Resistance
1 HIV
Group, Medical Research Council Clinical Trials Unit, London, UK; 2Department of Clinical Virology, Manchester Royal Infirmary, Manchester, UK.
Background
Methods
Transmitted HIV drug resistance (THDR) has the
potential to limit a patient’s future treatment options,
due to decreased effectiveness of first-line and
subsequent antiretroviral regimens. At a population
level, the surveillance of THDR can provide useful
information on spread of drug resistant HIV and
inform public health policy makers.
Surveillance programs exist in many countries and
provide estimates of the rate of transmitted drug
resistance. However, differences in the definition of
transmitted drug resistance and the use of different
lists of resistance mutations in these studies has
resulted in estimates of THDR that are often not
comparable [1].
To try and overcome this problem a recent list has
been developed specifically for epidemiological
estimates of transmitted drug resistance [2]. In this list
the mutations included should not only be recognised
as causing or contributing to resistance but should
also be non-polymorphic in untreated patients and
should be applicable to all subtypes.
Here we assess the extent to which the estimated
rate of THDR in the UK is altered by using the new
list, compared to the IAS-USA list which has
previously been used in studies in the UK [3,4].
We also compare the rates of THDR estimated by
these 2 lists with rates obtained using the Stanford
HIVdb genotypic interpretation system.
Findings are based on genotypic test results reported to the
UK HIV Drug Resistance Database, which aims to collect
all tests conducted as part of routine clinical care
nationwide. Participating virology laboratories provide data
on an annual basis; this analysis includes resistance tests
reported up to the end of 2005.
Mutations included in the 2 lists are shown below.
Amino acids in bold represent mutations which on
their own would be classified as THDR using the
Stanford HIVdb algorithm definition given opposite.
Protease
L24
I
D30
N
V32*
I
L33
F
I
M46
L
A
I47*
V
G48
V
V
I50
L
F53
L
M
L
V
I54
A
T
S
C
S
G73
T
A
L76
V
A
F
T
V82
S
L
M
V
I84
A
C
S
N88
D
L90
M
Analysis was restricted to the first test on patients older
than 16 years who were ART-naïve at the time of sampling.
Patients’ antiretroviral treatment status was classified from
information recorded on the resistance test request form
and via linkage with UK CHIC [5].
Estimates of transmitted drug resistance were based
on three definitions:
1) One or more major mutations in the latest (2006)
International AIDS Society-USA guidelines [6], plus
selected additional mutations (in reverse transcriptase, any
mutation at G190 or T215; in protease, V32I and I47V/A in
combination, or seven or more minor lopinavir mutations).
2) One or more mutations as proposed by Shafer et al [2].
3) Low level, intermediate or high level resistance to one or
more drugs, as interpreted by the Stanford HIVdb algorithm
(version 4.3.0, July 2007) [7].
The algorithm is based on a matrix of scores for each drugmutation combination; these are summed across all
mutations in the sample and individual drugs susceptibility
is classified as “sensitive” (total score <9), “possible low
level” (10-14), “low level” (15-29), “intermediate” (30-59), or
“high level” resistance (≥60).
RT - NRTI
M41
L
A62
V
K65
R
N
D67
G
del
ins
T69
D
R
K70
E
L74
V
I
A
V75
M
T
S
F77
L
Y115
F
F116
Y
Q151
M
V
M184
I
L210
W
any
Y
F
C
T215
D
E
S
I
V
Q
K219
E
R
RT - NNRTI
L100
I
K101
E
N
K103
S
A
V106
M
V108
I
C
Y181
I
C
Y188
L
H
any
A
G190
S
E
Q
P225
H
M230
L
P236
L
Key
Both
IAS only
Shafer only
*IAS list both V32I and
I47V/A are required in
combination.
NB: IAS list 7 or more
minor LOP mutations are
also counted as a major
mutation
Results
Overall prevalence of transmitted HIV drug resistance
Changes in the rate of THDR over time
• Overall 956 of the 8272 (11.5%) samples available for analysis were classified as
having THDR by at least one of the 3 definitions (Table 1).
• The number of tests on ART-naïve patients has increased rapidly in recent years
(596 in 2002, 935 in 2003, 1786 in 2004 and 2760 in 2005) reflecting changes in
clinical guidelines.
• For 706 samples (74% of 956) the 3 definitions agreed.
• However, 72 (7%) samples were classified as having THDR by IAS only, largely
driven by mutations 62V (n=17) and 108I (n=33) in RT and 33F (n=12) in protease.
• 14 (2%) samples were classified as having THDR by Shafer only; all protease
mutations, 53L (n=11) and 73C/S (n=3).
• The three lists gave similar estimates of THDR (Figure 1). Regardless of which
definition was used, the rate of THDR declined after a peak in 2001-2 and appears
to have now stabilised with no significant change between 2004 and 2005.
.
Figure 1: Prevalence of THDR over time
• 72 (7%) samples were classified as having THDR by Stanford only, largely driven
by low level, intermediate or high level resistance to the NNRTIs (n=61), in particular
low level resistance to TMC125 caused by the 179E mutation (n=28). NB: resistance
to TMC125 is not included on the current IAS or Shafer lists which are updated
annually; the Stanford algorithm is updated regularly as necessary.
any - IAS
NRTI - IAS
NNRTI - IAS
PI - IAS
any - Shafer
NRTI - Shafer
NNRTI - Shafer
PI - Shafer
any - Stanford
NRTI - Stanford
NNRTI - Stanford
PI - Stanford
16
Table 1: Number of samples classified as THDR
IAS
Shafer
Stanford
Any
resistance
NRTI
resistance
NNRTI
resistance
PI
resistance
No
Yes
No
No
Yes
Yes
No
Yes
No
No
Yes
No
Yes
No
Yes
Yes
No
No
No
Yes
No
Yes
Yes
Yes
7316
72
14
72
6
48
38
706
7725
33
7855
38
15
6
15
17
473
61
8054
13
14
7
5
18
295
43
6
135
• 46 (5% of 956) samples showed THDR to all 3 main ART classes by all 3
definitions. The greatest discordance was 72 samples classified as having THDR to
just one class by the Stanford algorithm but not the IAS list or Shafer list (NRTI
n=15, NNRTI n=51, PI n=6), and 71 samples classified as having THDR to just one
class by the IAS list but not the Shafer list or the Stanford algorithm (NRTI n=28,
NNRTI n=34, PI n=9).
Prevalence of resistance
14
• 48 (5%) samples were classified as THDR by IAS and Stanford but not Shafer
(protease mutations; 46L (n=26), 82L (n=17)). 38 (4%) samples were classified as
THDR by Shafer and Stanford but not IAS (RT mutations; 69D (n=8), 101E (n=15)).
12
10
8
6
4
2
0
N
1997
1998
1999
2000
2001
2002
2003
2004
2005
324
355
393
528
595
596
935
1786
2760
Conclusions
•
The choice of the IAS or the Shafer list of drug mutations, or resistance as
defined by the Stanford algorithm had a minor influence on the estimated rate of
THDR; however some discordance in the classification of samples as THDR was
seen.
•
The Shafer list is to be preferred for surveillance as it is specially developed for
epidemiology purposes. However, regular updates are required to capture
resistance to new drugs.
•
Continued surveillance of THDR is warranted to detect any changes from the
currently stable situation.
1
Pillay D. Current patterns in the epidemiology of primary HIV drug resistance in North America and Europe. Antivir Ther 2004;
9:695-702.
2 Shafer RW, Rhee S, Pillay D, Miller V, Sandstrom P, Schapiro JM et al. HIV-1 protease and reverse transcriptase mutations
for drug resistance surveillance. AIDS 2007; 21(2):215-23.
3 HIV Drug Resistance in the United Kingdom. CDR Weekly. Volume 16 Number 4. 26 January 2006.
4 UK Collaborative Group on HIV Drug Resistance, UK Collaborative HIV Cohort Study, and UK Register of Seroconverters.
Evidence of a decline in transmitted HIV-1 drug resistance in the UK. AIDS 2007; 21:1035-1039
5 Sabin CA, Hill T, Lampe F, Matthias R, Bhagani S, Gilson R, et al. Treatment exhaustion of highly active antiretroviral therapy
(HAART) among individuals infected with HIV in the United Kingdom: multicentre cohort study. BMJ 2005; 330:695-98.
6 Johnson VA, Brun-Vezinet F, Clotet B, Kuritzkes DR, Pillay D et al. Update of the Drug Resistance Mutations in HIV-1: Fall
2006. Top HIV Med. 2006; 14(3): 125-130.
7 http://hivdb.stanford.edu/pages/algs/HIVdb.html (version 4.3.0, July 2007)
UK Collaborative Group on HIV Drug Resistance Steering Committee:
Sheila Burns, Sheila Cameron, Pat Cane, Ian Chrystie, Duncan Churchill, Duncan Clark, Valerie Delpech, David Dunn,
Philippa Easterbrook, Esther Fearnhill, Hannah Green, David Goldberg, Mark Gompels, Tony Hale, Steve Kaye, Paul Kellam,
Svilen Konov, Linda Lazarus, Andrew Leigh-Brown, Anna Maria Geretti, Chloe Orkin, Andrew Phillips, Deenan Pillay (chair),
Kholoud Porter, Anton Pozniak, Caroline Sabin, Erasmus Smit, Peter Tilston, Ian Williams, Hongyi Zhang, Mark Zuckerman
Funding: The UK HIV Drug Resistance Database is partly funded by the Department of Health; the views expressed in the
poster are those of the authors and not necessarily those of the Department of Health. Additional financial support is provided
by Boehringer Ingelheim; Bristol-Myers Squibb; Gilead; Tibotec, a division of Janssen-Cilag Ltd; and Roche.
Contact: [email protected]