Efficacy of initial combination antiretroviral therapy for HIV-1: a meta-analysis Frederick J. Lee 1, Janaki Amin 2, Andrew Carr 1 Centre for Applied Medical.

Efficacy of initial combination antiretroviral therapy for HIV-1:

a meta-analysis

Frederick J. Lee1, Janaki Amin2, Andrew Carr1

Centre for Applied Medical Research, St Vincent’s Hospital 1

Kirby Institute, University of New South Wales 2

Sydney, Australia

7th IAS Conference on HIV Pathogenesis, Treatment & InfectionJuly 2013, Kuala Lumpur, Malaysia

Initial antiretroviral therapy (ART)− ‘backbone’ (2 NRTIs) + third drug

(NNRTI / rPI / INSTI)

DHHS guidelines: when to start− mostly driven by CD4 count / clinical stage− HIV viral load not a criterion since 2007

DHHS guidelines: what to start− ‘Preferred’ &‘Alternative’ regimens− current ‘Preferred’ regimens:• TDF-FTC/3TC + EFV / rDRV / rAZV / RAL

BackgroundOverview

Guidelines based on serial assessment of individual trials

Systematic review / meta-analysis− more patients / regimens, so more power to • evaluate subpopulations• identify predictors of ART success

Limitations of previous ART meta-analyses− only some regimens− short follow-up durations− more recent studies:• new drugs / studies• longer follow-up

BackgroundOverview

Primary = overall efficacy− determined by undetectable viral load− all studies over maximum follow-up period

Secondary efficacy over time− 48, 96, & 144 weeks

efficacy by 2012 DHHS guidelines− ‘Preferred’ vs. ‘Alternative’ ART

efficacy by baseline viral load− ≥100,000 vs. <100,000 copies/mL

predictors of efficacy and of failure

ObjectivesPrimary and secondary

Inclusion criteria− treatment-naïve, HIV-1+ adults− prospective design− ≥48 weeks duration− intent-to-treat (ITT) efficacy analysis

Exclusion criteria− retrospective or cross-sectional design− combinations not recommended for

toxicity/poor efficacy (e.g. monotherapy)− directly observed therapy

MethodsStudy selection

Databases sourced (to Dec 31, 2012)− MEDLINE− clinical trial registries (Cochrane, NIH, ISRCT) − conference abstracts & presentations (CROI,

IAS, ICAAC, Glasgow)− product labels & medical reviews (FDA,

EMA)− study synopses from manufacturers

Manufacturers approached for missing data, kindly provided by:− BMS, Gilead, MSD, ViiV Healthcare

MethodsData sources

Database construction− study characteristics− eligibility criteria− participant & disease characteristics− ART characteristics

MethodsData collection

Descriptive− unit of analysis = treatment group− variables expressed as• percentage• mean, weighted for group size

Predictive− linear regression approach• multivariable• backwards, step-wise variable selection

Analyses performed using STATA (v.11)− parameters not displayed if not significant

or not of particular interest

MethodsStatistics

Characteristics 

Groups(n=216)

Participants(n=40,124)

Mean,%

Randomised yes 196 36,534 91.1Placebo yes 68 17,630 43.9Phase 2 50 4,386 10.9  3 96 26,325 65.6  4 70 9,413 23.5Sponsorship academic 55 10,681 26.6 industry 123 26,547 66.2  both 38 2,896 7.2Year commenced

pre-1996 10 641 1.61997-1999 53 8,108 20.2

  2000-2002 43 9,331 23.3  2003-2005 61 13,062 32.6  2006-2008 31 6,597 16.4  2009-2010 17 2,346 5.8

Study characteristics

Characteristics 

Groups(n=216)

Participants(n=40,124)

Mean,%

Eligibility restrictions

viral load 184 33,915 84.5ALT / AST 173 31,536 78.6haemoglobin 133 24,224 60.4CD4 count 122 19,428 48.4genotype 62 12,563 31.3AIDS (CDC C) 11 1,436 3.6prior IDU 5 223 0.6

Duration (weeks) 

48 131 20,165 50.396 60 11,629 29.0144 25 8,330 20.8

Efficacy analysis

ITT M=F 62 7,127 17.8ITT NC=F 84 13,676 34.1

  TLOVR 70 19,321 48.2

Study characteristics

Characteristic Mean (SD)

Age 37 (2)

Sex men 76% (15)

Race white 65% (17)

black 27% (17)

Risk factors MSM 52% (19)

heterosexual 38% (15)

IDU 10% (9)

Previous AIDS 12% (13)

CD4 count 248 (81)

HIV RNA log10cp/mL 4.9 (0.2)

≥100,000 cp/mL 43% (11)

Hepatitis C 10% (9)

Participant characteristics

Characteristics Groups,n

Participants, n

Mean,%

Pills per day, mean (SD) 216 40,124 6.3 (3.6)

Doses per day, mean (SD) 216 40,124 2.0 (0.7)

Dosing with food, %

fasting only 59 9,754 24.3

fasting + food 22 5,108 12.7

food only 65 11,947 29.8

no restriction 70 13,315 33.2

ART characteristicsDosing

  Groups, n

Participants, n

Mean,%

NRTI backbonesAZT-3TC 56 10,832 27.0TDF-FTC 45 10,123 25.2d4T-3TC 27 3,988 9.9ABC-3TC 26 5,516 13.7d4T-ddI 20 2,349 5.9TDF-3TC 9 1,970 4.9Third drug classesNNRTI 94 19,512 48.6PI (boosted) 56 9,724 24.2PI (unboosted) 38 5,686 14.2NRTI 12 1,771 4.4INSTI 9 2,150 5.4

ART characteristicsKey NRTI backbones & third drug classes

EfficacyAll studies

   All

studies 

Follow-up, weeks

48 96 144

Groups, n 216 216 85 25

Participants, n 40,124 40,124 19,959 8,330

Follow-up, weeks (SD) 82 (38) 48 96 144

ART efficacy, % (SD) 60 (16) 66 (16) 60 (16) 52 (18)

EfficacyAll studies

   All

studies 

Follow-up, weeks

48 96 144

Groups, n 216 216 85 25

Participants, n 40,124 40,124 19,959 8,330

Follow-up, weeks (SD) 82 (38) 48 96 144

ART efficacy, % (SD) 60 (16) 66 (16) 60 (16) 52 (18)

ART cessation, % (SD) 25 (11) 20 (9) 28 (11) 34 (10)

adverse events 8.1 6.9 7.5 10

patient decision 11 8.5 14 15

virological failure 3.5 2.4 4.8 4.4

other 4.7 3.3 6.4 8.3

Efficacy: all studies from 1994 to 2010

EfficacyPredictors (all studies): NRTI backbone

  Efficacy,

%, (SD)

Multivariable analysis

  Coeff 95% CI p p group

TDF-FTC 73 (10) Ref    ABC-3TC 63 (7) -7.6 -12.7, -2.6 0.003  AZT-3TC 48 (15) -13.3 -18.0, -8.5 <0.001ddI-FTC 78 (-) 7.9 -11.6, 27.4 0.426TDF-3TC 69 (5) -1.2 -8.5, 6.2 0.758  ddI-3TC 65 (8) -7.9 -16.6, 0.8 0.075d4T-3TC 55 (12) -11.4 -16.8, -5.9 <0.001  d4T-ddI 44 (13) -18.4 -24.9, -12.0 <0.001  AZT-ddI 42 (4) -35.3 -51.9, -18.7 <0.001  <0.001 

r2,NRTI backbone type = 35.3%

EfficacyPredictors (all studies): third drug class

 Efficacy,

%, (SD)

Multivariable analysis

  Coeff 95% CI p p group

NNRTI 61 (15) Ref    

INSTI 84 (5) 11.9 4.6, 19.2 0.002  

PI (boosted) 67 (9) -0.9 -4.7, 3.0 0.660  

NRTI 51 (12) -10.7 -17.4, -4.1 0.002  

PI (unboosted) 42 (11) -15.0 -19.4, -10.6 <0.001  

r2, third drug class = 43.0%

EfficacyPredictors (all studies): study design

    Efficacy,

% (SD)r2

(%)

Multivariable analysis

    Coeff 95% CI p p group

Study phase

2 64 (15)          3 62 (16)          

  4 54 (16) 3.8        Analysis ITT M=F 53 (17)   Ref        ITT NC=F 59 (15)   -6.4 -10.1, -2.7 0.001    TLOVR 64 (15) 2.1 -7.5 -11.5, -3.6 <0.001 <0.001Eligibility restriction             Genotype yes 72 (10)            no 55 (15) 21.7         CD4 yes 54 (18)            no 66 (11) 6.2        Treatment     Pills / day   19.2 Doses / day   22.3

EfficacyBy pre-treatment viral load

All studies 

Pre-treatment viral load

<100,000 ≥100,000

Groups, n 216 98

Participants, n 40,124 13,184 9,694

Follow-up, weeks (SD) 82 (38) 81 (36)

ART efficacy, % (SD) 60 (16) 70 (15) 62 (15)

ART cessation, % (SD) 25 (11) no data

Mean difference for <100,000 vs. ≥100,000 subgroups = 8.4% (95% CI 6.0 to 10.9), p<0.001

EfficacyPredictors (all studies): viral load ≥100,000

    Efficacy,

% (SD)r2

(%)

Multivariable analysis

    Coeff 95% CI p p group

Placebo yes 67 (13)   Ref      

  no 57 (15) 7.9 -6.3 -12.0, -0.5 0.034 0.034

Pills per day   24.0 -1.8 -2.8, -0.8 <0.001 <0.001

Third drug class

NNRTI 64 (11) Ref    

INSTI 81 (5)   14.5 4.5, 24.4 0.005

PI (boosted) 65 (11)   6.5 0.2, 12.8 0.042  

NRTI 43 (17)   -20.0 -29.1, -10.8 <0.001

  PI (unboosted) 43 (11)   -10.0 -19.9, -0.2 0.045

EfficacyBy DHHS regimen

Mean difference for ‘Preferred’ vs. ‘Alternative’ regimens = 10% (95% CI 7.6 to 15.4), p<0.001

DHHS recommendation‘Preferred’ ‘Alternative’ other

Groups, n 27 36 153Participants, n 5,677 8,556 25,891Follow-up, weeks (SD) 99 (41) 86 (35) 77 (37)

ART efficacy, % (SD) 75 (8) 65 (7) 55 (17)

EfficacyBy DHHS regimen

DHHS recommendation‘Preferred’ ‘Alternative’ other

Groups, n 27 36 153Participants, n 5,677 8,556 25,891Follow-up, weeks (SD) 99 (41) 86 (35) 77 (37)

ART efficacy, % (SD) 75 (8) 65 (7) 55 (17)

ART cessation, % (SD) 20 (8) 25 (8) 27 (12)

adverse events 5.3 7.3 9.0 patient decision 9.0 11.0 11.0 virological failure 3.6 2.8 3.7 other 3.4 4.5 5.0

EfficacyBy DHHS regimen

TDF-FTC/3TC plus

Groups, n

Participants, n

Follow-up, weeks

Efficacy, % (SD)

EFV 14 2,729 108 72 (8)

rAZV 9 1,776 87 75 (7)

rDRV 1 343 96 79 (-)

RAL 3 829 99 82 (8)

Similar efficacy across DHHS-’Preferred’ regimens, although trend to superior efficacy with raltegravir

Cessation less likely in industry-sponsored studies

Cessation less likely in industry-sponsored and phase 2 studies

Cessation: all studies, 1994 to 2010(overall cessation 25%)

Adverse events (8%)

Participant decision (11%)

Overall mean efficacy of initial ART is low− only 60% over 82 weeks− higher with ‘Preferred’ regimens

(75% over 99 weeks)

Treatment determinants of greater success− TDF-FTC (vs. ABC-3TC)− INSTI (vs. NNRTI or boosted PI) - including

when pre-treatment viral load ≥100,000 cp/mL

Suboptimal efficacy− most patients will interrupt initial ART− TDF-FTC + INSTI efficacy 81% when pre-

treatment viral load ≥100,000 cp/mL• need for study of 3 vs. 4 drugs?

Conclusions

Ongoing loss in efficacy over time− participant decision > adverse events >>

virological failure

Significant 8.4% difference in efficacy between higher & lower viral load groups− similar to 10% difference between ‘Preferred’

& ‘Alternative’ DHHS regimens− guidelines should recommend initiating ART

before viral load reaches 100,000 cp/mL

Despite focus on co-formulation, fewer daily pills & doses not independent predictors of overall efficacy

Conclusions

Groups the base unit, not individuals Only some unpublished data available,

mostly from industry-sponsored studies Efficacy by viral load not randomised No analysis of:− individual drugs within third drug class

e.g. NVP vs. EFV; rLPV vs. other PI− clinical outcomes or resistance

Multivariable method of analysis− clinically irrelevant associations may

emerge, relevant associations missed− dependent upon data completeness

Limitations

Data:Fraser Drummond (ViiV) Silke Schweizer (BMS) Carolee Welebob (MSD)

Howard Wraight (Gilead) Rebekah Puls, Kathy Petoumenos (UNSW)

Funding: NHMRC of Australia (FJL)

Potential conflicts of interest (AC)

• research funding - Baxter, Gilead, MSD, Pfizer• consultancies - Gilead, MSD, ViiV• lectures - Gilead, MSD, Serono, ViiV• advisory boards - Gilead, MSD, ViiV

Acknowledgements