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Persisting long term benefit of genotypic guided treatment in HIV infected patients failing HAART and Importance of Protease Inhibitor plasma levels .Viradapt study, week 48 follow up and Pharmacological data.P.Clevenbergh, J.Durant, R.Garraffo, P. Halfon, P. del Giudice, P. Simonet, N. Montagne, CAB Boucher, JM Schapiro and
P. Dellamonica
Background
• An increasing number of retrospective studies link the presence of resistance mutations with a rebound in viral load .
• Two prospective studies (GART and Viradapt) showed a short term benefit of genotypic adaptation in patients failing combination therapy
VIRADAPT: Trial Design
Inclusion Criteria: HIV-RNA> 10.000 copies/ml
PI > 3 months, NRTI > 6months
Randomization
CONTROL Group GENOTYPIC Group
N= 43
Clinical and Laboratory Evaluation(CD4, HIV-RNA,Genotype ,)
N= 65
Analysis M3 M6 M12
If virological failure, ARV adaptation according to Randomization
12 months Follow up Study
• We report the 12 months follow-up of the patients participating in the Viradapt study
• First 6 months: randomized study with 2 arms
• After 6 months, patients in both arms received treatment changes based on genotyping results which were performed every three months
Patients and Methods
Randomized Openstudy study
Genotypic arm
Control arm
M0 M3 M6 M9 M12
Genotyping treatment
Standard of care
Patients and Methods: Statistical Analysis for the first 6 months randomized study
• Primary End-point: HIV-RNA variation from baseline at Month 3 and 6 (log10 transformed)
• Secondary End-Point
– Proportion of patients with HIV-RNA < 200 copies/ml
– CD4 cell count
• Statistics– Intent to treat analysis (dropout equal failure)
– LOCF
6 - 12 month follow-up study:Patients and Methods
• Primary End-point HIV-RNA changes from baseline at Month 9 and 12
• Secondary End-PointProportion of patients with HIV-RNA < 200 copies/ml
• StatisticsOn treatment analysis
Genotyping Technology
Mutations - Drug Resistance TableMutant(s) codon(s) Drug not suggested
Nucleoside analogs :V75TT215F or K70R ± (M41L, D67N, L210W,K219E)M184VM184V or T215F ± (R211K or L214F orG333D/E)M184V + (K65R ou L74V)L74V ± (K65R,M184V)T69D ± (K65R,L74V,M184V)Q151M ± (A62V, V75I, F77L, F116Y)
StavudineZidovudine
LamivudineZidovudine andLamivudineAbacavirDidanosineZalcitabineMultinucleosideresistance
Non Nucleoside analogs :K103N or V106A or Y181I or Y188C/l orG190A/S or P236L
Nevirapine, Delavirdineor Efavirenz
Protease Inhibitor :G48V and L90MG48V or L90M and any two of thefollowing mutations (L10I/R/V, I54V,A71V/T, G73S, I84V)M46I/L or V82A/F/T/V + any two of thefollowing mutations (L10I, K20M/R,L24/I,V32I, I54V/L, A71V/T, G73S, I84V,L90M)D30N or any three of the followingmutations (M36I, M46I/L, A71V/T, V77I,I84V, N88D, L90M)
SaquinavirSaquinavir and partialResistance toRitonavir or Indinavir
Ritonavir, Indinavir
Nelfinavir
Baseline Characteristics :
Demographic data • Characteristic Control Adapted to p
Genotype
43 65
• Age 40.1±7.5 39.4±8.2 0.43• Sexe Male/Female 34/9 47/18 0.64• Risk Factor : 18/24/1 30/34/1 0.48
IVDU/Sexual/Others • HIV1-RNALog10 4.8±0.5 4.7±0.6 0.45 (range)
(3.7-6) (3.4-6.2)• CD4 x106 201.7±22 220.8±18 0.49 • Stade CDC:A/B/C 5/16/22 16/14/35 0.11
Prior Antiretroviral Treatment
0
10
20
30
40
50
60
70
80
90
100
ZDV ddI ddC D4T 3TC NVP IND SQV RTV NFV
ControlGenotypic
Baseline Characteristics-Frequency of Primary and Secondary RT mutations
0
10
20
30
40
50
60
70
ControlGenotypic
Baseline Characteristics-Frequency of primary and secondary P mutations
0
10
20
30
40
50
60
70
80
90
ControlGenotypic
Results
• 41/43 and 40/43 pts in the control arm were evaluable at month 3 and 6
• 62/65 and 59/65 pts in the genotypic arm were evaluable at month 3 and 6
• 103/108 (95.4%)pts and 99/108 (91.6%) evaluable at 3 and 6 months
• 92/108 (85,2%) were evaluable at 12 months and included in the analysis.
Mean changes in plasma HIV-RNA from baseline throughout 12 months in Control and Genotypic arms
-1,60-1,40-1,20-1,00-0,80-0,60-0,40-0,200,00
Months
ControlGenotypic
Control 0,00 -0,46 -0,67 -0,86 -0,98Genotypic 0,00 -1,00 -1,15 -1,15 -1,15
0 3 6 9 12
Randomized Study Open Study
Percentage of patients with plasma HIV-RNA below the limit of detection (200 copies/ml) in Control and Genotypic arms
0
5
10
15
20
25
30
35
Months
Control
Genotypic
Control 0.00 14.00 14.00 12.5 30.5
Genotypic 0.00 29.20 32.30 31.3 30.4
0 3 6 9 12
Randomized Study Open Study
Correlation of baseline primary protease mutations and randomization arm with changes in HIV RNA
-1,6
-1,4
-1,2
-1
-0,8
-0,6
-0,4
-0,2
00 3 6
Control WTControl MTGenotypic WTGenotypic MT
Months
Conclusions
• Virologic response 1.15 log sustained with genotypic guided therapy throughout 1 year ( heavily experienced population)
• Performance of genotypic guided therapy may have contributed to additional viral load reduction seen in control patients
• Presence of primary protease mutations and performance of genotypic guided treatment, both independently effect virological response
Importance of Protease Inhibitor plasma levels in patients treated with Genotypic
adapted therapy
Background
• Multiple factors determine the response to antiretroviral therapy and causes other than drug resistance must be considered
• Poor efficacy may be due to pharmacological parameters resulting in suboptimal drug exposure
Background
• In contrast to nucleoside reverse transcriptase inhibitors, significant correlations between antiviral activity and plasma drug concentration have been demonstrated for HIV protease inhibitors
• Low plasma PI drug levels have been significantly related to the rebound of viral load
Study Objective
• To correlate Protease Inhibitors plasma levels with the changes in HIV RNA
• To determine the multiple factors contributing to the efficacy of antiretroviral therapy in treatment experienced patients
Methods• Serial protease inhibitor drug levels were analysed in
patients participating in the Viradapt study
• pharmacological substudy N= 87– Control group: standard of care (until 6mns)– Genotypic Group : genotypic guided therapy
• Serial PI plasma trough levels were performed in both arms throughout the 12 months study.
Methods
• Levels of PIs determined by HPLC
• Samples collected before morning dose
• Analysis was performed on batched frozen samples
• Levels determined for all 4 PI ’s utilized in study (saquinavir, nelfinavir, ritonavir, indinavir)
• Data analysed only for patients with at least 3 levels
obtained
Results
• 81 patients evaluated: mean age 39.7±8 years, 59 males, stage CDC C (52,7%)
• 604 PI plasma levels obtained
• Similar to the parent study, the 2 groups were comparable in terms of: risk factor, age, sex, previous treatment, CD4 cells count and baseline HIV RNA
PI drug levelsGlobal
n= 81
Control
n=35
Geno
Type
n=46
p SOC
%
% BLD< O.O5
g/ml
IndinavirMean (g/ml) s.d
Median IC
1.92.6
1.030.05-2.87
1.42.5
0.140.05-1.49
2.22.8
1.440.05-3.67
0.66
0.29
39.5%(15/38)
87%(13/38)
NelfinavirMean (g/ml) s.d
Median IC
2.602.05
2.640.77-3.82
2.632.23
2.380.60-4.10
2.561.87
2.700.87-4.79
0.67
0.81
26.6%(36/135)
39%(14/36)
Saquinavir HgMean (g/ml) s.d
Median IC
0.610.83
0.260.05-0.87
0.690.89
0.280.07-1.1
0.550.79
0.230.05-0.75
0.03
0.16
33.3%(157/471)
81%(127/157)
Ritonavir 400 x 2
Mean (g/ml) s.d
Median IC
2.692.62
2.380.36-4.01
2.972.80
2.730.20-4.03
2.282.30
1.40.41-3.66
0.36
0.41
42.6%(43/101)
49%(21/43)
Correlation HIV-RNA and plasma level
Saquinavir (n= 289, p= .0007) Nelfinavir (n=85, p= .038)
Indinavir (n=21, p= .012) Ritonavir (400 mg bid, n =62, p= .051)
1,5
2
2,5
3
3,5
4
4,5
5
5,5
6
6,5
-2 0 2 4 6 8 10 12
11,52
2,53
3,5
44,55
5,56
6,5
-5 0 5 10 15 20 25 30 35
1
2
3
4
5
6
7
-1 0 1 2 3 4 5 6 7 8 9 10
11,52
2,53
3,5
44,55
5,56
6,5
-1 0 1 2 3 4 5 6
Pharmacokinetic data of P.IDosemg
IC 95 invitro*(µg/ml)
Cmax(µg/ml)
Cmin(µg/ml)
Thres-hold
(µg/ml)
Indinavir 800 x 3 0.075 7.7 0.15 0.15
Nelfinavir 750 x 3 0.045 3.5 1.5 0.1
Saquinavir HgSaquinavir Sg
600 x 31200 x 3
0.04 0.092.1
0.020.25
0.1
Ritonavir 600 x 2500 x 2400 x 2300 x 2100 x 2
0.65 11.210.97.15.71.3
3.02.81.91.2
0.05
1.3
Optimal Drug Concentrations
• Sub optimal concentration (SOC): 2 levels less than 2x IC95
• Optimal concentration (OC):
No more than 1 level less than 2x IC95
• SOC = 32%, OC = 68%
Results
-1,60
-1,40
-1,20
-1,00
-0,80
-0,60
-0,40
-0,20
0,00
Months
SOCOC
SOC 0,00 -0,31 -0,45 -0,49 -0,36OC 0,00 -0,99 -1,21 -1,12 -1,2
0 3 6 9 12
Efficacy analysis based on drug levels and randomization arm
• Patients were categorized in 4 groups:
G1 = SOC/Control (n = 13)G2 = OC/Control (n = 22)
G3 = SOC/Genotype (n = 13) G4 = OC/Genotype (n = 33)
Efficacy analysis based on drug levels and randomization arm
-1,55
-1,35
-1,15
-0,95
-0,75
-0,55
-0,35
-0,15
0,05
0 3 6 Months
Control OCControl SOCGenotypic OCGenotypic SOC
Percentage of patients with plasma HIV-RNA below the limit of detection (200 copies/ml)
0
5
10
15
20
25
30
35
40
45
0 3 6 Months
Control OCControl SOCGenotypic OCGenotypic SOC
Predictive factors of virological response
OR 95%Confidence p Interval
PI Concentration 2.37 [0.02-0.7 ]0.017 > IC95 x 2
Genotypic therapy 2.24 [1.22-19.56 ] 0.025
Primary mutations 2.47 [0.03-0.567 ] 0.014for PI
Conclusions• Drug exposure inversely correlated with plasma HIV
RNA (all 4 PI)
• Genotypic guided therapy, PI concentration, and primary protease mutations: independently effect response to therapy
• Assays to determine drug levels and resistance mutations may both improve responses in experienced patients
Acknowledgements• R.Garraffo: Department of Pharmacology,Nice, France
• P.Halfon.Alphabio laboratory, Marseille, France.
• V.Mondain, P.Puglièse, V.Rahelinirina, I.Perbost, C.Pradier, L.Bentz, H.Etesse: Infectious Diseases
Department,Nice,France
• the study nurses ( M.Massard, J.Charlier, G.Valentini, C.Rascle)
• E.Dohin: Produits Roche France
• C.Sayada, M.Andriamanamihaja : ACT Gene and Visible Genetics Europe
• J.Stevens, R. Gilchrist : Visible Genetics Canada E.Counillon,P. Del Giudice : Bonnet Hospital, Frejus,
France
• P.Simonet, N.Montagne. Cannes Hospital France
• C.A.B Boucher:Department of Virology, University Hospital Utrecht, Netherlands
• J.M.Schapiro National Hemophilia Center, Tel Hashomer, Israel