Antiretroviral Drug Resistance
• Basic Knowledge
• Global Impact
• Utility of Global Surveillance
• Anthony Amoroso, MD
Assistant Professor of Medicine
University of Maryland School of Medicine
Institute of Human Virology
Chief of Infectious Diseases, VA Maryland Health Care System
“ Living with HIV used to be like playing
checkers and now it’s like playing chess.”
Becky Trotter, POZ
HIV-1 Viral Dynamics : Basis of
resistance
• In an HIV-1 infected individual, it is
estimated that:
– 10.3 x 109 virons are produced
each day
– Average life span of an HIV-1
viron in plasma is 5.6hours
– Average HIV-1 generation time is
2.6 days
HIV-1
Viral Dynamics - Mutations
• Genome Size - 104 base pairs
• Mutation rate of HIV-1 is estimated to be
3.4 x 105 per base pair per replication
cycle
• If true, then every mutation at every
position on the genome would occur
numerous times each day
How Quickly Resistance Can Occur
Depends on the Viral Load
300,000
Days Before Mutation
Arises
0.1
30,000
1
3,000
10
300
100
30
1,000
Viral Load
Adapted from Siliciano, 2002
Development of Viral Resistance
VIRUS
• High replication rate
• Error prone
• Latent reservoir
PATIENT
mutations
DRUG
• Non adherence
• Side effects
• Subtherapeutic concentrations
• Selective pressure of
less potent ARV therapy
Ctrough
Intrinsic activity
Barrier to resistance
HIV RNA Level
Viral Resistance is the Outcome of Viral Replication, Mutation and
Selection
New Virus
Quasispecies
Original Virus
Quasispecies
Selection Pressure
exerted by Drugs
Minority Quasispecies with
reduced susceptibility
Resistant virus
Time
HIV-1 RNA Response in Subjects With M184V (M184V
Present by Week 12)
Median decrease
HIV RNA log copies/mL
0
3TC monotherapy
300 mg BID (n=14)
0.5
1
1.5
0
2
4
8
12
16
20
24
Weeks
Kuritzkes D, et al. AIDS 1996;10:975-81.
HIVNET-012: Prevalence of NVP
Resistance Mutations at 6 to 8 Weeks
Postpartum
% with resistance mutations
60
46
40
19
20
0
Mothers
Infected infants
(n=111)
(n=24)
Eshleman SH, et al. 8th CROI; February 4-8, 2001; Chicago, IL. Abstract 516.
Case # 9 – Gulu, Uganda
16 year old female
Pre-ARV HX
• No previous ARV exposure
• OIs prior to ARV – Diarrhea and wasting, Genital
ulcerative disease
• Baseline weight – 35 kg
• WHO stage – III
• Baseline CD4 – 37 c/mm3 (11/2004)
• ARV start date – 22/12/04
• Baseline labs – Hb – 10.3g/dl, AST – 22, ALT –18, Cr –
0.7
ARV therapy
• 14 month duration of therapy
• Start 22/12/04: TDF/3TC/EFV
• Switch 21/07/0:
TDF/FTC/EFV (current)
OIs since ARV start
•
•
•
•
•
Herpes Simplex
Genital Ulcerative Disease
Tonsillitis – 22/02/05
Anal sores – 16/11/05
Perinatal viral warts – 14/03/06
CD4 Trend
CD4 count
100
88
80
60
40
Series1
37
20
0
Nov- Dec- Jan- Feb- Mar- Apr- May- Jun04 04 05 05 05 05
05 05
Date
50
45
40
35
30
25
20
15
10
5
0
Ju
l-0
5
Se
p05
No
v05
Ja
n06
M
ar
-0
6
No
v04
Ja
n05
M
ar
-0
5
M
ay
-0
5
Weight (kg)
Weight Trend
44
Date
46 45
35
Series1
Adherence
• Patient had treatment preparation, home visits
and DOT
• Dispensing frequency – Monthly
• No subjective history of missed doses in the past
6 months
• No history of missed refills in past 6 months
• No history of missed appointments in past 6
months
Viral Load?
• >750,000 copies/ml
Why?
• Poor adherence to safe sexual practices is been
closely linked to poor adherence to ARVs.
• Adolescents are notoriously horrible at taking
chronic medications
What is major concern in this case?
• This pt is at high risk for spreading resistance virus.
• Is secondary prevention counseling going to have any effect
on this patient’s behavior?
Surveillance
Rise in ARV Resistance Among
Treatment-Naive Patients
Patients With >10-Fold Resistance
N = 408
1996-1998
10
1999-2000
Patients (%)
8
P = .001
>10-Fold Resistance
1 drug
2 drugs
P = .05
6
4
2
0
NNRTIs
Little. 8th CROI; 2001; Chicago. Abstract 756
PIs
1999-2000
Reduced Susceptibility (>10 Fold) of
Transmitted HIV during Primary Infection
20
NRTI
NNRTI
PI
Percentage
15
10
5
0
n
1996
1997
1998
1999
2000
32
106
88
71
15
Year
Little SJ. 8th CROI, Chicago, 2001. #756
Total Study
Population*
100%
80%
60%
40%
20%
0%
Population with
HIV RNA >500 copies/mL**
78%
70%
51%
42%
31%
50%
cl
as
s
3
s
cl
as
3
TI
2-
N
R
N
ny
A
ny
A
PI
dr
ug
N
R
TI
14%
dr
ug
Drug resistance
Prevalence of Drug Resistance
1080/1906 patients
Drug resistance detected
* Assumes no resistance in samples with HIV RNA <500 copies/mL
** Represents 63% of total study population
Causes of Resistance: Lessons Learned
• Learning curve during applications of consensus
treatment guidelines
– AZT monotherapy
– Sequential monotherapy
– 2NRTI and PI ( i.e. AZT, 3TC and non-boosted PI)
• Borderline therapeutic drug levels and significant drug
interactions
• High Adherence Requirements
Global resistance in naïve patients study
• WATCH: Worldwide Analysis of resistance Transmission over time of
Chronically and acute infected HIV-1 Patients1
• RT & PI mutations from 6,054 naïve pts
• Source: Europe 3252, Africa 1162, Asia 653, Latin America 806, North
America 290
• Results: 8.9% >1 mutation
– Europe 11.3%; NA 9.3%, Africa 5.7%, Latin America 5%, East Asia 9.4%,
S/SE Asia 5.3%, 1.8% multiclass resistance
Resistance by ARV class
1. Bowles E, et al. XVI IAS, Toronto 2006, MOPE0388; 2. Bowles E, et al. 4th EHDRW, Monte Carlo 2006, #7
Primary resistance
in ARV-naïve adolescents
•
•
•
•
Study of resistance in pts age 12-24 from 15 US cities (n=55)
HIV-infected w/in 180 days using “detuned” assay
Genotype (GT) and Phenotype (PT) obtained
Major mutations defined by IAS-USA Drug Resistance
Mutations Group
Overall
NRTI
NNRTI
PI
Genotype Phenotype
18%
22%
4%
15%
3.6%
4%
18%
5.5%
• 1 pt had GT + PT resistance to ARV in all 3 classes
Viani R, et al. 13th CROI, Denver, CO, February 5-8, 2006. Abst. 21
The HIV Family
HIV-1
HIV-1
HIV-2
less pathogenic
Group:
O
M
N
(Cameroon)
Clade:
A,C,F
B
(Africa)
(US, Europe)
E
Others
(SE Asia)
Levy JA. HIV and the Pathogenesis of AIDS. 2nd ed. Washington, DC: American Society for
Microbiology; 1998:152-158.
Distribution of HIV-1 Subtypes in Africa
North
0.2
Horn
11.0
A/G
C
A/G
Western
5.0
A
Central
6.0
Southern
20.0
C
Eastern
10.5
Can Resistance Testing Be Used for
Non-Clade B HIV-1 Subtypes?
• Do the assays yield any results?
– Yes, at least for kit-based genotyping assays
• Do the results have the same interpretation?
– Mostly yes
– Exception
• Some secondary PI mutations are more common in non-clade B
viruses
• M36I, for example, is wild type for clade C
SDNVP and Resistance
2005
• Resistance in child: 13% - 52%
• Resistance in mothers: 39% - 75% resistance
– Clade A 19%
– Clade D 36%
– Clade C 69%
Conclusions
• Different HIV-1 subtypes seem to possess distinct
potentials for drug related resistance mutation
acquisition, including alternative routes and
substitutions.
• This may affect the future design of antiretroviral
regimens and salvage regimens in distinct areas of
the world where non-B isolates dominate the
HIV/AIDS epidemic.
Why new strategies are needed to avoid
resistance
The mainstream strategy of sequencing, as a whole,
has not been successful.
– Cross-resistance is a major problem and can prevent
rational sequencing of drugs
– Novel drugs or “new drugs” in a class may not be
available or effective once resistance develops
The Impact of Cross Resistance
“First shot is your best shot”
Rate of Treatment Failure in EuroSIDA Cohort (n = 8507)
Regimen
Cohort
Virologic
failure (VL
>500 c/ml)
Immune and
clinical failure
(composite)
Clinical
events
1st HAART
40%
20%
5%
2nd HAART
50%
30%
24%
3rd HAART
67%
40%
25%
Mocroft, et al, Antivir Ther, 2000.
Viral Suppression by Country (by Year 1 Sites)
K
en
ya
(n
R
w
=8
an
)
da
(n
U
ga
=2
nd
)
a
(n
Za
=5
m
)
bi
a
(n
G
uy
=5
)
an
a
(n
=1
)
100
90
80
70
60
50
40
30
20
10
0
ART drug resistance mutations in ART experienced patients in Nigeria
E. Idigbe, T. Salawu, B. Osotimehin, B. Chaplin,
J-L Sankalé, J Idoko, E Ekong, R Murphy , PJ Kanki
Nigerian Institute of Medical Research (NIMR), Lagos Nigeria
Federal Ministry of Health, Abuja, Nigeria
National Action Committee AIDS, Abuja, Nigeria
Harvard School of Public Health, Boston, MA, USA
Jos University Teaching Hospital, Jos, Nigeria
Harvard PEPFAR (APIN Plus), Lagos, Nigeria.
Northwestern University, Chicago USA
Supported by AIDS Prevention Initiative Nigeria – funded by the Bill & Melinda
Gates Foundation, DAIDS-NIAID/NIH, the Federal Ministry of Health and NACA.
Resistance Patterns to the Baseline Regimen of
Patients with viral loads greater 3000 c/ml .
Lam
Res
Res
Stav
Res
Int
NVP
Res
Res
Res Susc Res
Susc Susc Res
Susc Susc Susc
#
TOTAL
19%
26%
40%
3%
11%
144
% With Virologic Suppression
Response to d4T/3TC/NVP in mothers based on
previous history of single-dose NVP
68%*
80
70
52%*
60
50
38%*
40
30
No NVP
NVP no mutation
NVP +mutation
20
10
N=47
N=143 N=66
N=40 N=119 N=61
0
Baseline
6 months
*significant
Joudain et al. NEJM 4/04
What will we do with surveillance information?
DHHS Guidelines: Recommendations for Using
Drug-resistance Assays (Updated 5/04/06)
Drug-resistance assay recommended
• In acute HIV infection*
– If the decision is made to initiate therapy at this time, testing is recommended prior to
initiation of treatment. A genotypic assay is generally preferred
– If treatment is deferred, resistance testing at this time should still be considered
• In chronic HIV infection*
– Drug resistance testing is recommended prior to initiation of therapy. A genotypic assay
is generally preferred
– Resistance testing earlier in the course of HIV infection may be considered
• With virologic failure during combination antiretroviral therapy
• With suboptimal suppression of viral load after antiretroviral
therapy initiation
*New recommendations as of DHHS Guidelines update 5/04/06.
Adapted from DHHS Guidelines (5/04/06). Available at: http://aidsinfo.nih.gov. Accessed May 9, 2006.
Regimen Selection by Line of Therapy
Q1 2006
Other
3NRTIs
PI/r-based
PI-based
NNRTI-based
Percentage
100%
80%
60%
40%
20%
0%
1st
n=951
2nd
3rd
4th+
n=601
n=369
n=451
Line of Therapy
Base: All treated patients Q1 2006 data
Line of therapy change defined as a switch of any component of the patient’s ARV regimen.
ISIS market research data, Synovate US HIV Monitor Q1 2006.
Public Health Approach to Treatment
• Utilize 1st line regimens with predictable mutations
and “dead end mutational pattern”
• Utilize 1st line regimens which allow for rational 2nd
line therapies
• Be willing to change 1st line therapeutic approach
based on resistance data despite costs
• Invest more heavily on community treatment
support/adherence programs to ensure high level
initial adherence