Emergence of HIV-1 Drug Resistance in South Africa – evidence over past 24 months

Gillian HuntCentre for HIV and STI

National Institute for Communicable Diseases

FIDSSA - November 2015

Formation of the SA HIVDR Working Group

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Prevention, attention to early warning indicators, capacitation of HIVDR for individual patient management,

strengthening surveillance and prompt reporting on national data

HIV Drug ResistanceStrategy

EWI

HIV DR

Clinical

Mx

HIVDR

Surveill-ance

Data Manage-

ment

MnE

Reporting

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HIVDR testing algorithm in strategy

HIV RNA >1000 copies/ml on PI-based

ART

Repeat VL after 6 months

VL ≤1000 copies/ml

Continue second-line regimen

VL >1000 copies/ml

Specialist referral

Genotypic resistance

testing

Specialist decision regarding further

management

Check for adherence, compliance, tolerability and drug- drug interaction and assess psychological issues

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National Surveillance of Transmitted DR: 2012 ANSUR

Province

Number of

specimens

amplifiable by

genotyping

PCR

Genotyping

amplification

rate

Number of

sequences

with PI

mutations

PI Point

Prevalence

(95% CI)

Number of

sequences

with NRTI

mutations

NRTI Point

Prevalence

(95% CI)

Number of

sequences

with NNRTI

mutations

NNRTI Point

Prevalence

Eastern Cape 99 88.4% 0 0% (0 - 3.7) 0 0% (0 - 3.7) 3 3% (1.0 - 8.5)

Free State 54 76.1% 0 0% (0 - 6.6) 1 1.9% (0.3 - 9.8) 4 7.4% (2.9 - 17.6)

Gauteng 65 69.1% 1 1.5% (0.3 - 8.2) 0 0% (0 - 5.6) 6 9.2% (4.3 - 18.7)

KwaZulu

Natal196 64.5% 0 0% (0 - 1.9) 4 2% (0.8 - 5.1) 8 4.1% (2.1 - 7.8)

Limpopo 20 47.6% 0 0% (0 - 16.1) 0 0% (0 - 16.1) 2 10% (2.8 - 30.1)

Mpumalanga 45 76.3% 0 0% (0 - 7.9) 1 2.2% (0.4 - 11.6) 2 4.4% (1.2 - 14.8)

North West 21 44.7% 2 9.5% (2.7 - 28.9) 0 0% (0 - 15.5) 1 4.8% (0.8 - 22.7)

Northern

Cape4 57.1% 0 0% (0 - 49.0) 0 0% (0 - 49.0) 0 0% (0 - 49.0)

Western

Cape28 82.4% 0 0% (0 - 12.1) 0 0% (0 - 12.1) 2 7.1% (2.0 - 22.6)

National 532 69.1% 3 0.6% (0.1 - 1.6) 6 1.1% (0.5 - 2.4) 28 5.3% (3.7 - 7.5)

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Hunt G et al, NICD Bulletin, April 2015

• Pre-screening resistance rates 7.4%

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Parikh U et al, Pone 2013

ART naïve surveyAre patients initiating treatment susceptible to the 1st line ART regimen?

• Specimens collected from 45 health care facilities, in 34 districts and all 9 provinces

• Sample size of 336 calculated, using PPS sampling

• 277 sequences included in analysis (82.4% of target)

• 25 out of 277 patients presented with ≥ 1 surveillance drug resistance mutation (SDRM, WHO 2009)

• Prevalence of SDRM 9.0% (95% CI: 6.1-13.0%)– NNRTI mutations most common, n=23

– NRTI mutations, n=7

– PI mutations, n=2

– In 4 patients ≥ 4 SDRMs detected, which might indicate they were not truly ART-naïve7

Steegen K et al, IAS 2015: TUPEB232

Germs-SA: Sentinel site surveillance of HIVDR and TBDR(INH) at initiation of treatment

• 1 clinic per province

• To measure HIV/TB co-infection in patients initiating therapy

• To measure levels of HIV and TB DR at initiation of therapy

• Recruitment ~30%

• NNRTI+NRTI resistance: 2.3%

• NNRTI resistance: 16.9%

• ~1/3rd of participants are re-entering into care

0.0%

20.0%

40.0%

60.0%

80.0%

100.0%

Prior ART (PMTCT orHAART) n=64

No Prior ART n=150

No amplification

No Resistance

NNRTI Resistance

Dual-class resistance

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Pillay, ARHR 2008: n=26 2000-03 GP

Marconi, CID 2008: n=115 2005-06 KZN

Hoffmann, CID 2009: n=68 2002-06 GP

Orrell, AT 2009: n=120 2002-07 WC

Wallis, JAIDS 2010: n=226 2005-09 GP

Murphy, AIDS 2010: n=141 2005-09 KZN

El Khatib, AIDS 2010: n=129 2008 GP

Singh, JAIDS 2011: n=45 <2010 KZN

Sunpath, AIDS 2012: n=33 2010-11 KZN

Sigaloff, ARHR 2012: n=43 2006-09 GP

Manasa, POne 2013: n-242 2010-2012 KZN

Resistance mutations among 1st-line failures in SA

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Different patterns of resistance within NRTI drug class…

Van Zyl et al, PLoS ONE2013

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Different patterns of resistance within NRTI drug class…

Skhosana L et al, PLoS ONE 2015

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Different patterns of resistance within NNRTI drug class…

Van Zyl et al, PLoS ONE2013

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Different patterns of resistance within NNRTI drug class…

Skhosana L et al, PLOS One 2015

KZN pilot cross sectional ADR survey

• To estimate the proportion of adult patients failing 1st-line ART after 1 year and after 2 years on treatment, and the proportion of paediatric patients failing first-line ART at 15 ART clinics in KZN

• To describe the patterns of HIV DRM in patients with detectable viral load

• Viral Suppression rates:– I year (n=540): 93%

– 2-3 years (n=760): 89%

– Paeds (n=106): 69%

• Factors associated with viral failure: – Male gender, initiation of ART at CD4 <200, NVP vs EFV, d4T and

AZT vs TDF

• Resistance detected in 89% of viral failures

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Hunt G et al, XXIII International HIV Drug Resistance Workshop, Berlin, 2014

KZN ADR: HIVDR patterns

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Hunt G et al, XXIII International HIV Drug Resistance Workshop, Berlin, 2014

ART-experienced surveyAre patients who fail 1st line treatment susceptible to the 2nd line ART regimen?

• Specimens collected from 91 health care facilities, in 37 districts and 8 provinces (excl NC).

• 793 sequences included in analysis (88.1% of target 900)

• VL 4.7log cp/ml

• Median time on ART: 36 months

• 3.7% of patients presented with wild-type virus (indication for non-adherence)

• Most common NNRTI mutations: K103N (48.8%), V106M (34.9%), Y181C (26.2%), G190A (21.7%)

• Most common NRTI mutations: M184V/I (82.7%), K65R (45.8%)

• K65R in TDF-exposed patients: 57.5%16

Steegen K et al, IAS 2015: TUPEB238

ART-experienced surveyAre patients who fail 2nd- line treatment susceptible to the 3rd- line ART regimen?

• Specimens collected from 72 health care facilities, in 38 districts and all 9 provinces.

• 354 sequences included in analysis (78.6% of target 450)

• VL 4.8log cp/ml

• Median time on PI-ART: 25months

• Median time on ART: 62 months

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Steegen K et al, IAS 2015: TUPEB289

National 3rd-line committee• ~n=163 patients

• Median age 40 years

• DRV/r +3TC/FTC+AZT/TDF ± RAL ± ETR

• Facility completes motivation form and submits to:

– the Secretariat: Third Line ARV Peer Review Committee (PRC)

– TLART@health.gov.za

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FInHDER: Finding infants with HIV disease:evaluation of resistance

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Kuhn et al, AIDS, 2014

Resistance in infants What are the resistance profiles in infants <18 months who failed PMTCT?

• Stored 6w remnant DBS for routine HIV early infant diagnosis (EID) were collected from September 2014 to January 2015 from all 9 NHLS EID laboratories in South Africa

• 408 cases of which 51% were female infants

• Median age of 81 days (IQR 45-240) at the time of diagnosis

• HIVDR amplification and sequencing was achieved in 350 (85.8%) specimens

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• NNRTI resistance was detected in 60.8% (n=213)

• NRTI resistance was observed in 13.1% (n=25)

• Only three infants presented with single PI mutation

Carmona S et al, IAS 2015: TUPEB231

• PASER: 2579 participants, 5.5% had pretreatment drug resistance.

• PDR was associated with increased risk of regimen switch (aHR 3.80 p=0.005)

• PDR was not associated with mortality (aHR 0.75 p=0.617) or new AIDS events (aHR 1.06 p=0.807)

• VL monitoring can improve the accuracy of failure detection and efficiency of switching practices

Boender TS et al, CID,2015

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• 76.2% vs 90.5% suppression with vs without PDR @12mo

• 81.4% vs 91.3% suppression with vs without PDR @36mo

Paton NI et al, NEJM 2014

• 0 predicted active NRTIs in 230 (59%, PI/NRTI(0))

• 1 active NRTI in 128 (33%, PI/NRTI(1))

• ≥2 active NRTIs in 33 (8%, PI/NRTI(2))

• Even with little or no predicted drug susceptibility, NRTIs make a major contribution to efficacy of PI/

• Suggests this contribution is not due to direct drug activity but possibly a viral fitness effect NRTI second-line therapy

• Algorithmic NRTI drug selection and appropriate adherence measures are likely to achieve optimal outcomes in standardized PI/NRTI second-line therapy in RLS

• Resistance testing to select NRTIs is of little value.

Paton et al, CROI 2015 Abstract No 119

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Global epidemiology of drug resistance following failure of WHO recommended tenofovir containing first line regimens for adult HIV-1

infection – an international collaborative study

J Gregson; M Tang; N Ndembi; RLHamers; SY Rhee; VC Marconi; L Diero; K Brooks; K Theys; TF Rinke de Wit; M Arruda; F Garcia; S Monge; HF Günthard; CJ Hoffmann; PJ Kanki; N Kumarasamy ; B Kerschberger; O Mor; C Charpentier; E Todesco; C Rokx; L Gras; EK Halvas; H Sunpath; D Di Carlo; A Antinori; M Andreoni; A Latin; C Mussini; A Aghokeng; A Sonnerborg; U Neogi; WJ Fessels; S Agolory; C Yang; JL Blanco; JMc Juma; E Smit; D Schmidt; C Watera; J Asio; W Kirungi; A Tostevin; T El-Hay; N Clumeck; D Goedhals; C van Vuuren; A Bester; C Sabin; I Mukui; MM Santoro; CF Perno; G Hunt; L Morris; R Camacho; T de Oliveira; D Pillay; E Schulter; A Murakami-Ogasawara; G Reyes-Terán; K Romero; S Avila-Rios; S Sirivichayakul; K Ruxrungtham; S Mekprasan; D Dunn; P Kaleebu; E Raizes; R Kantor; RW Shafer; RK Gupta (The TenoRes Study Group)

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Conclusions

• HIVDR levels are increasing but not to alarming levels

• Evidence-based justification for adherence to treatment algorithms

• Scale-up and adherence of testing algorithms

• Future strategies and regimens supported and encouraged

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Acknowledgements

• National HIV Drug Resistance Working Group and Steering Group including all members and affiliates

• National Health Laboratory Service

• National Institute for Communicable Diseases

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