opening remarks - virology educationregist2.virology-education.com/2015/9interest/sat_abbvie.pdf ·...

Opening remarks Dr. Joseph Murungu

In memory of

Joep Lange and Jacqueline van Tongeren

and their contribution to the field of HIV

Scientific Agenda

Managing HIV in resource-limited settings: Growing the momentum

Viral load monitoring in RLS: Challenges and lessons; A South African perspective

Dr. Francesca Conradie South Africa

Acquired drug resistance in RLS: The causes, patterns and implications

Dr. Andrew Kambugu Uganda

Second-line therapies in RLS: The choices and evidence

Prof. Nick Paton Singapore

Closing remarks Dr. Joseph Murungu

Zimbabwe

AbbVie Commitment

• This scientific exchange symposium is sponsored by AbbVie. The presentations and content have been developed by the presenters with a medical education agency specifically for this symposium.

• During the course of today’s symposium, the presenters may be providing information and data on some uses of products that have not been approved by relevant health agencies. The presenters will indicate when a use we are discussing is not approved. AbbVie reviewed the slides and in no way intends to recommend or imply that the products should be used for such unapproved uses.

Disclosures

Speakers have acted as an advisor, received speaker fees/meeting expenses, or received research grants/drug support from:

• Dr. Joseph Murungu: AbbVie

• Dr. Francesca Conradie: AbbVie, GSK, Janssen, Merck

• Dr. Andrew Kambugu: AbbVie, MSD

• Prof. Nick Paton: AbbVie, GSK, Janssen, Merck, Roche

Viral Load Monitoring in RLS: Challenges and Lessons; A South African Perspective Dr. Francesca Conradie

Southern African HIV Clinicians Society

What does the WHO have to say about it?

• Viral suppression refers to the aim of antiretroviral therapy (ART) to maintain viral load below the level of detection of available assays, generally less than 50 copies/mL

– The current WHO virologic criterion for treatment failure is 1000 copies/mL or more

• Viral load (VL) testing is now recommended as the preferred approach to monitoring ART success and diagnosing treatment failure, complementing clinical and immunological monitoring of people receiving ART

WHO, 2013 ART guidelines. Available at: http://apps.who.int/iris/bitstream/10665/85321/1/9789241505727_eng.pdf

Recommended and desirable laboratory tests at HIV diagnosis and monitoring on ART

Phase of HIV management

Recommended Desirable (if feasible)

HIV diagnosis HIV serology, CD4+ cell count TB screening

HBV (HBsAg) serology HCV serology Cryptococcus antigen if CD4+ cell count ≤100 cells/mm3

Screening for sexually transmitted infections Assessment for major non-communicable chronic diseases and comorbidities

Follow-up before ART

CD4+ cell count (every 6–12 months)

ART initiation CD4+ cell count Hemoglobin test for AZT Pregnancy test Blood pressure measurement Urine dipsticks for glycosuria and estimated glomerular filtration rate (eGFR) and serum creatinine for TDF Alanine aminotransferase for NVP

Receiving ART CD4+ cell count (every 6 months) HIV viral load (at 6 months after initiating ART and every 12 months thereafter)

Urine dipstick for glycosuria and serum creatinine for TDF

Treatment failure

CD4+ cell count HIV viral load

HBV (HBsAg) serology (before switching ARV regimen if this testing was not done or if the result was negative at baseline)



Targeted viral load monitoring (suspected clinical or

immunological failure)

Routine viral load monitoring (early detection of virological failure)

Test viral load

Viral load >1000 copies/mL

Evaluate for adherence concerns

Repeat viral load testing after 3–6 months

Viral load >1000 copies/mL Viral load ≤1000 copies/mL

Switch to second-line therapy Maintain first-line therapy

Why do we need viral loads?

• Monitoring of response to treatment

• Decisions on when to change therapy

• Choice of therapy

• Infant diagnosis

• (Prognosis)

• (Measure of infectiousness)

The South African experience

• National ART program began in April 2004

• CD4+ cell count entry 200 or AIDS defining

• VL tested at treatment initiation and every 6 months

• Failure defined as two VL above 5000 copies/mL

The South African experience

• Guideline updates 2008

– CD4+ cell count threshold increased to 350 cells/mm3 for pregnant women and TB

– Initiation VL dropped

– VL done every six months

• Guideline updates 2010

– CD4+ cell count threshold increased to 350 cells/mm3 for all

– VL tested at 6 months, one year and every year thereafter

– Failure defined as two VL above 1000 copies/mL

Numbers on National ART program

0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

1 2 3 4 5 6 7 8

Number on treatment

Years since start of program

Nu

mb

er

on

tre

atm

ent

• Based on current guidelines, global viral load need is expected to grow as countries scale up treatment

• Current CHAI country estimates suggest 16 million by 2020, depending on algorithm may reach 40 million

Quantitating needs: Global VL market need: Donor perspective

CHAI, 2012, Trevor Peter personal cummunication

# tests

Other

Zimbabwe

Zambia

Uganda

Thailand

Tanzania

Swaziland

South Africa

Rwanda

Nigeria

Namibia

Mozambique

Malawi

Lesotho

Kenya

India 0 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

2

4

6

8

10

12

14

16

18

Viral Load (VL) Response

Note: Always check hepatitis B before stopping TDF. If patient has chronic hepatitis B, stopping TDF may lead to a fatal hepatitis flare. If hepatitis B positive, TDF should be continued as a 4th drug in the second-line regimen

<400 copies/mL • VL monitoring according to duration of ART and routine adherence support

• Continue routine VL monitoring as it may be 12 monthly depending on how long patient is on treatment

400–1000 copies/mL • Assess and manage adherence carefully • Repeat VL in 6 months and manage accordingly

>1000 copies/mL • Adherence assessment and intense adherence support • Repeat VL in 2 months and check HBV status and Hb, if not

already done • If <1000 copies/mL, repeat in 6 months and then reassess • If >1000 copies/mL and adherence issues addressed, switch

to second-line therapy after checking HBV status and Hb

Site Malawi

(Hosseinipour et al. 2009)

South Africa Cape Town

(Orrell et al. 2009)

South Africa Johannesburg

(Wallis et al. 2010)

South Africa Durban

(Marconi et al. 2008)

South Africa CIPRA-SA

Sample size Clinical sites

94 2

110 (2002–2007) 1

226 2

115 (2005–2006) 2

812 (83 failures) 2

Switch criteria

CD4+ decrease >30% or WHO staging

Viral load >5000 RNA c/mL

Viral load >5000 or 1000 RNA c/mL



Frequency of monitoring

Irregular 6 monthly-VL & CD4+ cell count

6 monthly-VL & CD4+ cell count



Median time on first-line (months)

36.5 (8–127) Unknown Unknown 10.8 (6.7–18.6) 15 (3–33)

% with failure & resistance

95% 85% 83% 83.5% 82%

Subtype C 100% 98% 96.5% 97.4% 100% M184V 81% 78% 72% 64.3% 67.2% NNRTI K103N V106M

93% 28% 6%

86% 55% 31%

78% 38% 17%

Unknown 51% 19%

75% 50% 14%

TAMs >3 K65R

56% 19%

23% 9%

11% 4.5%

13% 2.6%

1.5% 3%

Clinical case 1

• 45-year-old male started on AZT, 3TC and EFV

– CD4+ cell count = 178 cells/mm3

– VL = 134,000 copies/mL

• Within 8 weeks undetectable VL

• At Week 96, VL was 6800 copies/mL

• Repeated in 4 weeks 8900 copies/mL

Clinical case 1

• Transmitted resistance

• Acquired resistance

Clinical case 2

• 34-year-old female

– CD4+ cell count = 345 cells/mm3

– VL = 10,000 copies/mL

• 8 week VL 1200 copies/mL

• 16 week VL 6800 copies/mL

• Repeated in 4 weeks 8900 copies/mL

Clinical case 2

• Transmitted resistance

• Acquired resistance

HIV-1 drug resistance in antiretroviral-naïve individuals in sub-Saharan Africa after roll-out of antiretroviral therapy: A multicentre observational study

• Cross-sectional analysis of ARV-naïve individuals in 2007–2009 in 11 regions in Kenya (2), Uganda (3), Nigeria, South Africa (3), Zambia (3)

• 2436 (94%) of 2590, 57% women; CD4+ median: 133 cells/mm3; >18 years

• Sample weighted drug prevalence of resistance was: 5.6%: ranged from 1.1% in Pretoria (SA) to 12.3% in Kampala (Uganda)

• Pooled prevalence for 3 sites in Uganda was 11.6% compared to 3.5% for all other sites

• 2.5% NRTI, 3.3% NNRTIs, 1.3% for PIs and 1.1% for dual NRTI and NNRTI

• Odds ratio for drug resistance-associated with each additional year since ART roll-out was 1.3 (95% CI: 1.13–1.68)

Hamers RL, et al. Lancet 2011;11:750–9

Interpretation: The higher prevalence of primary drug resistance in Uganda than in other Africa countries is probably related to the earlier start of ART roll-out in Uganda Resistance surveillance and prevention should be prioritized in settings where ART programs are scaled up

Lab challenges

• 3-tiered laboratory infrastructure exists with only tertiary facilities and, to some extent, secondary laboratories able to implement

• Challenges

– High sample volumes

– Transportation logistics from remote sites

– Costs

– Phlebotomy in children

–National skills shortage

– Sample throughput of technology platforms

Laboratory type Assays

Tertiary reference NAT strategies (Roche Amplicor [COBAS and Taqman] and bDNA, NucliSENS EasyQ); Abbott RealTime in-house real-time PCR options; flow-based options*

Secondary (medium-tier) May do NAT; Exavir load assay; flow-based options*

Primary care POC technologies* or sample preparation for referral

NAT, nucleic acid testing; PCR, polymerase chain reaction; POC, point of care *Not available for implementation n at time of program initiation (in research and development)

Assays considered for viral load testing and the appropriate laboratory tier at the time of implementation of an antiretroviral therapy program

Stevens WS. and Marshall TM. J Infect Dis 2010;201:S78–S84

© 2010 by the Infectious Diseases Society of America

Clinical challenges

• No VL done at initiation

• Adherence to the guidelines

• What to do with a VL between 50 and 1000 copies/mL?

• Emphasis in the program on CD4+ cell count

• Lack of urgency around detectable VLs including “myths”

Decisions on when to change therapy

First-line: Fixed dose combination with EFV

– Simplicity

– TB friendly

– Low but predictable barrier to resistance

Second-line: Appropriate NRTIs and a boosted PI

– Higher barrier to resistance

–Unpredictable barrier to resistance

– Twice a day dosage

Third-line: Combination of DRV/r ETR and RAL based on genotype test with appropriate NRTIs

1 3 2 5 4

“Low Genetic Barrier” for ARV resistance (3TC or FTC, NNRTIs)

Number of mutations

Re

lati

ve r

esi

stan

ce

1 3 2 5 4

Re

lati

ve r

esi

stan

ce

1 3 2 5 4

“High Genetic Barrier” for ARV resistance (TDF, AZT, d4T, boosted PI)

Number of mutations

Time to repeat VL

• From an NNRTI regimen: 2–3 months

• For a PI regimen: 6 months

Choice of therapy

• In most cases the starting VL does not make a difference

• Two exceptions to this

Rilpivirine

Rilpivirine

• Novel NNRTI

• Single daily dosage

• Co-formulated with TDF and FTC as FTC/RVP/TDF

• Should only be used when the VL is less than 100,000 copies/mL

• Randomized, double-blind phase III trials

*THRIVE only †Selected by investigator from ABC/3TC, TDF/FTC, ZDV/3TC

ECHO, THRIVE: Rilpivirine vs. EFV in treatment-naïve patients

Cohen C, et al. AIDS 2010. Abstract THLBB206

Rilpivirine 25 mg QD + TDF/FTC 300/200 mg QD

(n=346)

EFV 600 mg QD + TDF/FTC 300/200 mg QD

(n=344)

Stratification by BL HIV-1 RNA <100,000

vs. ≥100,000 copies/mL, NRTI use*

Week 96 final analysis

Week 48 primary analysis

Rilpivirine 25 mg QD + 2 NRTIs†

(n=340)

EFV 600 mg QD + 2 NRTIs†

(n=338)

ECHO (N=690)

THRIVE (N=678)

Treatment-naive, HIV-1 RNA ≥5000 copies/mL

no NNRTI RAMs, susceptible to NRTIs

ECHO, THRIVE: Rilpivirine vs. EFV in treatment-naïve patients

Cohen C, et al. AIDS 2010. Abstract THLBB206. Graphics used with permission

*P<0.0001 for noninferiority at -12% margin

Rilpivirine

EFV

HIV-1 RNA <50 copies/mL (ITT-TLOVR) at Wk 48

40

0

100

20

80 82.3 84.3

60

682 686 n =

ECHO THRIVE Pooled

Pat

ien

ts (

%)

82.8 82.9 85.6

81.7

338 340 344 346

-3.6 (-9.8 to +2.5)

>100,000 copies/mL

125/ 165

121/ 153

246/ 318

149/ 181

136/ 171

285/ 352

77 81 79 80 76 82

Pat

ien

ts (

%)

40

0

100

20

80

60

Pooled THRIVE ECHO

HIV-1 RNA <50 copies/mL at Wk 48 by BL VL

6.6 (1.6 to 11.5)

≤100,000 copies/mL

162/ 181

170/ 187

332/ 368

136/ 163

140/ 167

276/ 330

90 83

91 84

90 84

Pat

ien

ts (

%)

40

0

100

20

80

60

ECHO THRIVE Pooled

ECHO, THRIVE: Treatment failure, resistance, and adverse events

Cohen C, et al. AIDS 2010. Abstract THLBB206. Table used with permission.

Wk 48 outcome Rilpivirine

(n=686) Efavirenz (n=682)

VF with resistance data, n 62 28

No NNRTI or NRTI RAMs,% 29 43

1 Emergent NNRTI RAM,% 63 54

Most frequent NNRTI RAM E138K K103N

1 Emergent NRTI RAMs, % 68 32

Most frequent NRTI RAM M184I M184V

Adverse events and discontinuation

Resistance at virologic failure

Wk 48 outcome, % Rilpivirine (n=686)

Efavirenz (n=682)

P Value

DC for AE 3 8 0.0005

Most common AEs of interest, %

Any neurologic AE 17 38 <0.0001

Any psychiatric AE 15 23 0.0002

Any rash 3 14 <0.0001

EFV

686

6

0

3

9

Treatment failure in ECHO and THRIVE 15

12

4.8

n =

VF

9.0

682 686

6.7

AE

2.0

682

Pat

ien

ts (

%)

Rilpivirine

Triple nucleosides

• ABC, 3TC and AZT

• Or any other combination

• Should only be used when the VL is less than 100,000 copies/mL

Early infant diagnosis (EID)

• At ~6 weeks of age

• 270,000 HIV-exposed infants are born annually in SA

• Bottleneck was addressed during 2005 by the introduction of dried blood spot sampling (DBS)

• By 2006, approximately half of the public health facilities submitted HIV PCR tests

• 2012 virtually all 4000 public sector facilities submitted PCR tests

Early vertical transmission in infants ≤2 months of age in South Africa

350,000

300,000

250,000

200,000

150,000

100,000

50,000

0

23.2%

20.9%

17.0% 16.4%

13.6%

9.7%

6.4%

4.4%

2.8% 2.4%

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

HIV

DN

A P

CR

tes

ts, n

Po

sitivity, %

25

0

20

15

10

5

≤2 months: positive tests All ages: total tests ≤2 months: total tests ≤2 months: % positivity

Illustration of the rapid scale-up of PCR testing nationally with marked reduction in early vertical transmission of HIV over a decade

(KwaZulu-Natal data missing from 2003 to 2005)

Measure of infectiousness

Attia S, et al. AIDS 2009;23:1397–404

Summary of HIV transmission rates according to use of ART and plasma viral load

Attia S, et al. AIDS 2009;23:1397–404

All studies

0 0.01 0.2 0.1 0.5 1 2 5 10 20

≥50,000

10,000–49,999

3500–9999

400–3499

<400

All studies

≥400

<400

HIV-1 RNA copies/mL On ART

Not on ART

No. of studies

No. of events

No. of persons

years

Rate (95% CI)

10

5

6

8

6

6

5

1

2

456

48

47

18

7

1

5

0

0

9998

534

668

456

457

631

1098

52

291

5.64 (3.28–9.70)

9.03 (3.87–21.09)

8.12 (2.78–23.77)

4.17 (0.84–20.65)

2.06 (0.57–7.47)

0.16 (002–1.13)

0.46 (0.19–1.09)

0 (0–5.79)

0 (0–1.27)

Rate per 100 person-years

Acquired Drug Resistance: Causes, Patterns and Implications Dr. Andrew D. Kambugu, FRCP

Infectious Diseases Institute

Makerere University College of Health Sciences

Outline

• Epidemiology of acquired drug resistance (ADR) in Africa (First-line antiretroviral therapy [ART])

– East Africa

– South Africa

• Consequences of ADR in first-line ART

– Treatment failure

– Transmitted drug resistance (TDR)

• Drivers/associations of ADR

– Patient factors

– Programmatic factors

• Strategies to minimize ADR in resource-limited settings (RLS)

Definitions

• Acquired Drug Resistance (ADR): A mechanism of HIV drug resistance (HDR) driven by drug selection pressure occurring in patients on ART

• Transmitted Drug Resistance (TDR): A mechanism of HDR resulting from infection by a resistant strain

• HIV Drug Resistance Mutations (DRMs)/Resistance-Associated Mutations (RAMs): Changes in the HIV genome that result in reduced susceptibility to ART

Common HDR mutation sites

Nucleosides (NRTIs) Non-nucleosides (NNRTIs)

The epidemiology of ADR in Africa

• ADR rates lower in African ART cohorts compared with the West

• ADR rates increase with duration on ART

– ADR emergence mirrors the peculiar characteristics of HIV (high mutation rates driven by high replication/ replication errors)

ADR extract of World Health Organization (WHO) HDR report

• 9.4% of patients on ART experience treatment failure at 12 months

• 60% of these are associated with HDR mutations

• 5.1% of patients on ART for 12 months had ADR

WHO HIV Drug Resistance Report 2012. Available at: http://www.who.int/hiv/pub/drugresistance/report2012/en/

• 40 surveys: 2006–2010 • 12 countries (Africa & SE Asia)

• 29 survey subsets with 12 ART follow-up data

Geographical distribution of 12 countries reporting results from WHO surveys of acquired HIV drug resistance, 2006–2010

Country reporting results from WHO surveys of acquired drug resistance, 2006–2010 No data available or not participating in the surveys

Not applicable

WHO Report ADR extract: Prevalence of RAMs at 12 months of ART

WHO HIV Drug Resistance Report 2012. Available at: http://www.who.int/hiv/pub/drugresistance/report2012/en/

Mutations were defined using the 2009 WHO surveillance drug resistance mutations list

% o

f en

dp

oin

t ge

no

typ

es 80%

70%

60%

50%

40%

30%

20%

10%

0%

Endpoint characteristics at 12 months in 3 sentinel ART cohorts: Uganda

Characteristics Masaka n (%) Mbale n (%) Nsambya n (%) Total N (%)

Status at endpoint

Dead 8 (5.7) 7 (4.9) 5 (3.5) 20 (4.7)

Lost to follow-up 23 (16.3) 23 (16.1) 20 (14.2) 66 (15.3)

Still on first-line 103 (73.0) 105 (73.4) 105 (74.5) 313 (73.7)

Stop 0 (0) 0 (0.0) 1 (0.7) 1 (0.2)

Switch 2 (1.4) 2 (1.4) 4 (2.8) 8 (1.9)

Transfer – out 5 (3.6) 6 (4.2) 6 (4.3) 17 (4.0)

Drug pick-up

≥90% on-time 35 (27.3) 18 (13.8) 3 (2.3) 56 (14.4)

RNA viral load (copies/mL)

<1000 83 (79.0) 95 (88.2) 94 (86.2) 272 (84.7)

≥1000 22 (21.0) 12 (11.2) 15 (13.8) 49 (15.3)

Potential HIV drug resistance 29 (22.6) 26 (20.0) 26 (20.0) 81 (20.9)

HIV drug resistance 16 (12.5) 9 (6.9) 10 (7.7) 35 (9.0)

HIV DRMs at endpoint

NRTI only 0 (0) 3 (2.3) 1 (0.8) 4 (1.0)

NNRTI only 1 (0.8) 1 (0.8) 1 (0.8) 3 (0.8)

Both NRTI & NNRTI 15 (11.7) 5 (3.8) 8 (6.2) 28 (7.2) Kapaata et al: Manuscript in preparation

HDR mutations at endpoints in 3 cohorts

Kapaata et al: Manuscript in preparation

2 3

17

7

1

27

2 5

13

4 5 1

6 3

21

0

10

20

30

40

50

Freq

ue

ncy

(%

)

NRTI NNRTI Mutations

ART resistance among 38 individuals with ART failure in Rakai

n (%) of individuals Baseline (n=31) First-line failure (n=36) Second-line failure (n=6) NRTI mutations: Any TAMs 1 (3%) 8 (22%) 3 (50%)

1 TAM 1 (3%) 5 (14%) 2 (33%) 2 TAMs 0 (0%) 3 (8%) 0 (0%) 3+ TAMs 0 (0%) 0 (0%) 1 (17%) 41L 0 (0%) 2 (6%) 1 (17%) 65R 0 (0%) 2 (6%) 0 (0%) 67N 0 (0%) 1 (3%) 1 (17%) 70R 0 (0%) 2 (6%) 0 (0%) 184I/V 1 (3%) 28 (78%) 5 (83%) 210W 0 (0%) 1 (3%) 1 (17%) 215F/Y 1 (3%) 5 (14%) 2 (33%)

NNRTI mutations: Any NNRTI mutation 4 (13%) 31 (86%) 5 (83%) 103N 1 (3%) 9 (25%) 2 (33%) 108I 0 (0%) 3 (8%) 1 (17%) 181C/I 3 (10%) 14 (39%) 1 (17%) 188L/H 0 (0%) 2 (6%) 0 (0%) 190A/S 1 (3%) 10 (28%) 2 (33%) 225H 0 (0%) 3 (8%) 3 (50%)

PI mutations: Any PI mutation 2 (6%) 2 (6%) 0 (0%) 46L 1 (3%) 1 (3%) 0 (0%) 50V 1 (3%) 1 (3%) 0 (0%)

Reynolds SJ, et al. AIDS Res Hum Retroviruses 2012;28:1739–44 TAMs, thymidine analogue mutations

Cross-sectional study on virologic failure and acquired ARV resistance (on ART >6/12) in PEPFAR-supported clinics in Uganda and Nigeria

• Uganda 7% (23/325) – Viral load (VL)

• 2012–1,833,084 – No drug resistance-associated

mutations (DRAMs)

• 14.8% – TAMs

• <1 year: 12% • >1 year: 50%

– 3TC resistance (M184V)

• All

– NNRTI mutations

• All patients with DRAMs – Subtype

• A 43.6%, D 38%, C 14.3%

• Nigeria 13.8% (45/325) – VL

• 1120–405,000 – No DRAMs

• 14.3% – TAMs

• 60% – 3TC resistance (M184V)

• 90% – NNRTI mutations

• All patients with DRAMs except one – Subtype

• CRF02_AG 62.8%, G 34.2%, A1 2.8%

Crawford KW, et al. AIDS Res Hum Retroviruses 2014;30:796–9

PEPFAR: President’s emergency plan for AIDS relief

ADR epidemiology: Southern Africa

Manasa J, et al. Plos One 2013;8:e72152

90 80

70

60

50

40

30

20

10

0

Freq

uen

cy (

%)

100

80

70

60

50

40

30

20

10

0

90

ADR studies in South Africa: A summary

Manasa J, et al, Plos One 2013;8:e72152

Dates Criteria N ART duration (months)

≥1 DRM NNRTI M184V TAM TAM ≥3 K65R Q151M %

Limpopo (rural clinic) - 1xVL>1000 21 9.0 90.5 85.8 52.4 0.0 0.0 0.0 0.0 Durban (2 urban hospitals)

Jun 05 1xVL>1000 115 10.8 83.5 78.3 64.3 32.2 13.0 2.6 0.9

Cape Town (8 urban clinics)

Jul 02 1xVL>1000 110 8.9 88.2 88.2 78.2 22.7 NR 9.1 0.0

Johannesburg (urban workplace clinic)

Aug 02 1xVL>1000 68 - 66.2 61.8 36.8 5.9 NR 0.0 0.0

Johannesburg (urban hospitals)

- 2xVL>1000 or 2xVL>5000

226 - 83.0 77.9 72.1 31.0 12.0 3.5 2.2

Soweto (urban hospital)

2008 ART>12M & VL>400

94 - 80.8 80.8 61.7 16.0 NR 1.1 0.0

Johannesburg (urban hospital)

Sept 06 2xVL>5000 43 22.0 88.4 86.1 74.4 53.5 16.3 7.0 2.3

Western Cape (urban hospital & community health centre)

Oct 07 1xVL>400 167 13.5 83.0 82.0 60.5 12.0 2.4 4.2 0.0

Johannesburg & Cape Town (urban clinical trial)

- 2xVL>1000 83 8.5 73.0 71.0 57.0 1.0 NR 3.0 0.0

Soweto (urban hospital) 2008 ART>12M & VL>400

38 45 81.6 81.6 65.8 21.0 10.5 2.6 0.0

Durban (urban hospital) - 1xVL>5000 43 29 95.0 95.0 87.0 55.0 NR NR NR Hlabisa (rural clinics) Dec 10 1xVL>1000 222 42 86.0 83.0 78.0 40.0 18.0 6.0 1.0

Summary of acquired drug resistance studies in adults treated with first-line ARV therapy in South Africa

Resistance in children failing first-line ART at the Joint Clinical Research Centre

• Of 109 genotypic resistance profiles analysed, the commonest

–NNRTI RAMs were: • K103N: 59 (54%)

• Y181C: 36 (27%)

• G190A: 26 (24%)

–NRTI RAMs were: • M184V: 89 (81%)

• T215Y: 36 (24%)

• M41L: 23 (21%)

• K70R: 22 (20%)

• D67N: 15 (14%)

• K219Q/E: 14 (13%)

• L210W: (9%)

Sebunya R, et al. AIDS Res Ther 2013;10:25

NNRTI-based regimen (n=73)

PI-based regimen (n=16)

NNRTI mutations N % N %

Any NNRTI DRM 60 82.2 4 25

L100I 5 6.9 0 0

K101EP 6 8.2 0 0

K103NRS 46 63.0 2 12.5

V106M 23 31.5 2 12.5

V108I 7 9.6 1 6.3

Y181C 2 2.7 0 0

Y188HCL 7 9.6 1 6.3

G190AS 9 12.3 1 6.3

P225H 14 19.2 0 0

M230L 3 4.1 0 0

NNRTI-based regimen (n=73)

PI-based regimen (n=16)

NRTI mutations N % N % Any mutation 63 86.3 10 62.5 M41L 7 9.6 0 0 K65NR 4 5.5 1 6.3 D67NG 8 11.0 0 0 K70ER 7 9.6 0 0 L74VI 4 5.5 1 6.3 Y115F 3 4.1 2 12.5 M184VI 60 82.2 10 62.5 L210W 1 1.4 0 0 T215FYI 9 12.3 0 0 K219QREN 5 6.9 0 0 Any TAMs 22 30.1 0 0 1 TAM 11 15.1 0 0 2 TAMs 7 9.6 0 0 ≥3 TAMs 4 5.5 0 0

ADR mutations pediatrics cohort: South Africa

Pillay S, et al. AIDS Res Ther 2014;11:3

Frequency of major drug resistance mutations and resistance complexes associated with PIs, NRTIs and NNRTIs of the 89 genotyped patients

Drivers of ADR: Patient factors

• Suboptimal drug adherence leads to resistance

– Suboptimal adherences associated with emergence of ADR Odds Ratio of 4.9 in Namibia

Decreased risk

NNRTI resistance

80–99% adherence

0–79% adherence

0.1

Increased risk

10 1

PI resistance

80–99% adherence

0–79% adherence NRTI resistance

80–99% adherence

0–79% adherence Any resistance

80–99% adherence

0–79% adherence

NNRTI strategy

Decreased risk

0.1

Increased risk

10 1

PI strategy

Risk of virologic failure with resistance 100

60

80

40

20

Pro

po

rtio

n w

ith

re

sist

ance

at

failu

re

0 0–79% 80–99% 100%

Cumulative adherence

NNRTI resistance on NNRTI

PI resistance on non-boosted PI

PI resistance on boosted PI

60

80

40

20

Pro

po

rtio

n w

ith

re

sist

ance

at

failu

re

100

0 0–79% 80–99% 100%

Cumulative adherence

NRTI resistance on NNRTI

NRTI resistance on non-boosted PI

NRTI resistance on boosted PI

Gardner EM, et al. AIDS 2009;23:1035–46 Hong SY, et al. J Acquir Immune Defic Syndr 2015;68:463–71

Drivers of ADR: Programmatic factors

• Drug stock-outs leading to unstructured treatment interruption

• 10–28% of treatment

discontinuation due to stock-outs • Stock-outs increased the odds of

interruptions in care or death by 2.8

Drivers of ADR: Programmatic factors

Gupta RK, et al. Lancet Infect Dis 2009;9:409–17

ART monitoring strategy and the emergence of resistance

Gupta et al, Lancet Infect Dis 2009;9: 409-17

Any thymidine analogue mutations NNRTI clinical trials

Cohort (frequent monitoring) Cohort (infrequent or no monitoring)

M184V/I mutation NNRTI clinical trials


Major NNRTI NNRTI clinical trials


K65R mutation NNRTI clinical trials


0% 1% 2% 3% 4% 5% 6% 7% 8%

% of all patients starting HAART with resistance at 48 weeks (95% CI)

Consequences of ADR: 1

• The emergence of DRMs is associated with treatment failure

• Virologic failure: Immunologic failure: Clinical Failure

• DRMs acquired cumulatively

– Specific patterns of emergence

0 5 10 15 20 25 30 35

0.00

0.02

0.04

0.06

0.08

0.10

Time since virologic failure (months)

Pro

bab

ility

of

dea

th

Immediate switch Switch 6th month Switch 12th month Switch 24th month No switch

0 5 10 15 20 25 30 35

0.00

0.02

0.04

0.06

0.08

0.10 All patients with virologic failure: Immediate switch All patients with virologic failure: No switch Patients without immunologic failure: immediate switch Patients without immunologic failure: No switch

Delayed switch of antiretroviral therapy after virologic failure associated with elevated mortality among HIV-infected adults in Africa

Petersen ML, et al. AIDS 2014;28:2097–107

Counterfactual mortality curves following confirmed virologic failure on first-line NNRTI-based ART

First-line ART failure associated with poor neurocognitive performance which improves on second-line: The EARNEST study

Kambugu A, et al. CROI 2015: Abstract 57

Global GEE P=0.35 PI/RAL vs. PI/NRTI GEE P=0.20 Pl-mono vs. PI/NRTI GEE P=0.42

PI/NRTI PI/RAL PI-mono

0

-3

48 96

-2.5

-2

-1.5

Weeks from randomisation

Ove

rall

z-sc

ore

Initiating second-line ART may be associated with IRIS events

• 40 year old male

• Failing first-line with CD4+ count of 46 cells/mm3

• Started on second-line ART in study

• Week 12 presented with headache and left sided weakness

Consequences of ADR: 2

Gupta RK, et al.

WEST & CENTRAL AFRICA

EAST AFRICA

LATIN AMERICA & CARIBBEAN

SOUTHERN AFRICA

Prevalence of TDR (NNRTI) with years since roll out of public program in Africa

0 2 4 6 8

10 12 14 16 18 20

2 4 6 8 0

0

5

10

15

20

25

30

35

2 4 6 8 0 10 12 14 16

% o

f p

arti

cip

ants

wit

h d

rug

resi

stan

ce

Years since rollout

0 2 4 6 8

10 12 14 16 18 20

2 4 6 0

0 2 4 6 8

10 12 14 16 18 20

2 4 6 8 0 10

Intervention component

Number of studies

% with positive results for ≥1

outcome measure

% with positive results for ≥1 positive effect each for a biological and a subjective

or objective adherence outcome

CBT 60 67 20

Education 28 79 21

Treatment supporter 26 62 19

DOT 20 85 30

ARD 20 75 25

Structural 10 70 10

Counselling 8 88 63

Nutrition-support 7 71 43

PRD 5 60 0

Financial incentives 5 60 0

Drug use treatment 5 80 40

Depression treatment 1 0 0

ARD, active reminder device; CBT, cognitive-behavioural therapy; DOT, directly observe therapy; PRD, passive reminder device

Strategies to minimize ADR

• Optimizing adherence: Systematic review

Chaiyachati KH, et al. AIDS 2014;28:S187–S204

Summary of effects of adherence-enhancing interventions

Mobile phone text messages improve ART adherence

Horvath T, et al. Cochrane Database Syst Rev 2012;3:CD009756

0.01 0. 1 1 10 100 Weekly messages Daily messages

ART adherence at 48 weeks: Weekly vs. daily messages (overall)

ART adherence at 48 weeks: Short vs. long messages (overall)

2 Mobile phone text messages (intervals and durations), outcome: 2.2

2 Mobile phone text messages (intervals and durations), outcome: 2.3

Risk ratio (non-event)

0.01 0. 1 1 10 100 Short messages Long messages

Risk ratio (non-event)

Strategies to minimize ADR

• Ensuring consistent ART drug supplies:

– Coordinated (donor/country) forecasting

– Secured multi-year funding commitments

– Multi-year procurement arrangements

– Prompt payment by national programs

– Access accurate consumption information

Lalvani P, et al. Center for Global Development. Available at: http://www.cgdev.org/doc/HIVAIDSMonitor/ARV_Background-FINAL1.pdf

Medicines supply chain for Kenya

Conclusions

• 5.4% of patients have ADR mutations within 12 months of first-line ART

• Common mutations include: M184V, K103N, Y181C and K65R (if TDF is used in first-line ART)

• Above mutations are observed across the different regions of Africa and in both adult and pediatric populations

• ADR is driven by both patient and programmatic factors

• Emergence of ADR to first-line leads to poor patient outcomes in the absence of timely switch to second-line

• TDR is rising with increasing ART experience, especially in East Africa

• Optimization of adherence and public ART supply chain is needed to prevent ADR with first-line ART

Acknowledgements

• Joint Clinical Research Centre (JCRC)

– F. Ssali

– C. Kityo

– V. Musiime

• Uganda Virus Research Institute (UVRI)

– P. Kaleebu

– C. Waters

– A. Kapaata

• Francois Venter (WRHI, SA)

Second-line treatment options in RLS: The choices and evidence Prof. Nicholas Paton, MD FRCP

Professor of Medicine

National University of Singapore

Second-line treatment options in resource-limited settings (RLS)

• World Health Organization (WHO) recommendations

• Second-line randomized controlled trials (RCTs)

• Summary of evidence-based choices

• Generalizing beyond the evidence of RCTs

• Conclusions

Second-line treatment options in RLS

• WHO recommendations

• Second-line RCTs



• Conclusions

Second-line RCTs

N (total) PI/RAL

vs. PI/NRTIs

PI-mono vs.

PI/NRTIs

Which PI and

NRTIs?

EARNEST 1277 √ √

SECOND-LINE 541 √

SELECT 600 (max) √

STAR 200 √

2LADY 454 √

A pragmatic randomized controlled strategy trial of three second-line treatment options for use in public health

rollout program settings:

The Europe-Africa Research Network for Evaluation of Second-line Therapy (EARNEST) Trial

NRTI

NRTI

The EARNEST question

“moderate quality evidence” for second-line regimen

Standardized first-line Standardized second-line ≈ 3% fail/year

NNRTI NRTI

NRTI PI ?


PI RAL

NRTI

NRTI

Standardized first-line Standardized second-line

NNRTI NRTI

NRTI PI ?

≈ 3% fail/year


PI RAL

NRTI

NRTI

Standardized first-line Standardized second-line

NNRTI NRTI

NRTI PI ?

PI

≈ 3% fail/year

EARNEST aims

• EARNEST hypotheses: 1) PI/r + RAL superior efficacy (↓ toxicity? ↑cost)

2) PI/r mono. non-inferior efficacy (↓toxicity ↓complexity ↓cost )

• EARNEST aims:

– Compare these 3 options for second-line therapy

– A pragmatic trial that replicates typical public health approach settings (i.e. without all the monitoring)

HIV-positive adolescents / adults (n=1200) First-line NNRTI-based regimen >12 months;

Failure by WHO (2010) clinical, CD4+ cell count (VL-confirmed) or VL criteria

RANDOMIZE

PI + 2–3 NRTIs (NRTIs according to

local standard of care)

PI + RAL (12 week induction)

PI (monotherapy)

FOLLOW-UP FOR 144 WEEKS

Primary outcome at Week 96: Good HIV disease control – defined as all of: • Alive and no new WHO4 events from 0–96 weeks AND • CD4+ cell count >250 cells/mm3 at 96 weeks AND • VL <10,000 c/mL OR >10,000 c/mL without PI resistance mutations at 96 weeks

PI + RAL

Trial design (1)

Paton NI, et al. N Engl J Med 2014;371:234–47

Trial design (2)

• Visits

– Weeks 0–24: 4-weekly



• Adherence

– Assessed each visit by structured questions

– Intensive counseling at baseline and follow-up


Trial design (3)

• Monitoring

– Clinical: FBC, Cr, ALT at Week 12 and annually; local lab; open

– CD4+ cell count: every 12–16 weeks; local lab; open

– VL: annual visits; batched analysis in central lab (JCRC Kampala, Abbott m2000rt assay); blinded with DMC review

– Resistance: annual visits (all VL >1000 c/mL); batched analysis in central lab (Janssen Diagnostics); blinded with DMC review


Sites and recruitment

April 2010–April 2011: 1277 patients randomized


Sites Initial Added

Uganda 6 3

Zimbabwe 1

Malawi 1 1

Kenya 1

Zambia 1

Baseline characteristics (at randomization/switch to second-line)

PI/NRTI PI/RAL PI-mono Total

Randomized 426 433 418 1277

Female 264 (62%) 263 (61%) 215 (51%) 742 (58%)

Age (years) 37 (31–43) 37 (30–43) 38 (32–44) 37 (31–44)

Years since started ART 4.0

(2.8–5.4) 4.0

(2.9–5.5) 3.9

(2.7–5.4) 4.0

(2.8–5.4)

CD4+ (cells/mm3) 72 (29–143) 70 (27–142) 70 (33–149) 71 (30–146)

Pre-ART CD4+ 62 (23–144) 63 (23–135) 63 (22–152) 62 (23–145)

VL (c/mL) 67,515 (23,065–175,800)

74,500 (25,004–205,000)

70,874 (21,584–210,000)

69,782 (23,183–194,690)

VL ≥100,000 c/mL 168 (40%) 181 (41%) 181 (43%) 530 (42%)

Note: n (%) or median (interquartile range [IQR])


Initial EARNEST NRTIs


Randomized 426 433 418 1277

NRTIs

TDF + 3TC/FTC (+ ZDV*) 336 (79%)

ABC + ddI/3TC 67 (16%)

ZDV + ddI/3TC 20 (8%)

Other 3 (<1%)

PI

LPV 426 (100%) 433 (100%) 418 (100%) 1277 (100%)

*Malawi National Guidelines suggested 3 NRTIs This changed to 2 in August 2011

Adherence to ART and follow-up


Randomized 426 433 418 1277

Regimen compatible with strategy (% time)

99.5% 97.1% 97.4% 98.0%

Visits with complete ART adherence*

87% 89% 88% 88%

Protocol-mandated visits attended¶ 98% 98% 98% 98%

LTFU / withdrawn 4 (0.9%) 7 (1.6%) 7 (1.7%) 18 (1.3%)

*Complete adherence defined as report of no pills missed in the last month ¶19,448 mandated protocol visits

Primary endpoint at 96 weeks

• Good disease control: PI/NRTI: 60%

Note: using multiple imputation for missing CD4+ cell count (10%), VL (10%) and resistance (11% with VL >1000 c/mL) at Week 96

0%

20%

40%

60%

80%

100%


%

Good disease control

Alive & no new WHO4

CD4>250

VL<10,000 or no PIresistant mutations

%


• Good disease control: PI/NRTI: 60% PI/RAL: 64%

• Risk diff (95% CI): PI/RAL – PI/NRTI: +4.2% (-2.4%, +10.8%; P=0.21)


0%

20%

40%

60%

80%

100%


%


Alive & no new WHO4

CD4>250


%


• Good disease control: PI/NRTI: 60% PI/RAL: 64% PI-mono: 56%


• Risk diff (95% CI): PI-mono – PI/NRTI: -4.1% (-10.8%, +2.6%; P=0.23)


0%

20%

40%

60%

80%

100%


%


Alive & no new WHO4

CD4>250


%






0%

20%

40%

60%

80%

100%


%


Alive & no new WHO4

CD4+ >250


%





Note: using multiple imputation for missing CD4 (10%), VL (10%) and resistance (11% with VL >1000 c/ml ) at Week 96

0%

20%

40%

60%

80%

100%


%


Alive & no new WHO4

CD4+ >250

VL <10,000 or no PIresistant mutations

P<0.0001

%

VL suppression at 96 weeks

91% 88% 86%

74%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

<10,000 c/mL <1000 c/mL <400 c/mL <50 c/mL

% s

up

pre

sse

d

PI/NRTI PI/RAL PImono+


91% 88% 86%

74%

93% 87% 86%

73%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

<10,000 c/mL <1000 c/mL <400 c/mL <50 c/mL

% s

up

pre

sse

d

PI/NRTI PI/RAL PImono+

PI/RAL vs. PI/NRTI P=0.36 P=0.87 P=0.97 P=0.88


91% 88% 86%

74%

93% 87% 86%

73%

83%

67% 61%

44%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

<10,000 c/mL <1000 c/mL <400 c/mL <50 c/mL

% s

up

pre

sse

d

PI/NRTI PI/RAL PI-mono+

PI/RAL vs. PI/NRTI P=0.36 P=0.87 P=0.97 P=0.88 PI-mono+ vs. PI/NRTI P=0.002 P<0.0001 P<0.0001 P<0.0001

Resistance at 96 weeks (predicted in whole population)

4

0 0

2 2

1

18

0

2

4

6

8

10

12

14

16

18

20

PI/NRTIs PI/RAL PI-mono

% o

f ra

nd

om

ize

d p

atie

nts

wit

h

inte

rme

dia

te/h

igh

leve

l re

sist

ance

TDF/ZDV/ABC/ddI RAL LPV

Note: assuming susceptible if VL<1000 c/mL at week 96; and using inverse probability weighting for VL>1000 c/mL with missing genotype at week 96 based on those with observed genotypes

*One patient in PI/RAL with intermediate/high level resistance to TDF moved to 3TC TDF LPV/r at week 4 due to rash

X X *

Mean CD4+ cell count through 96 weeks

PI/RAL vs. PI/NRTI Week 96 P=0.05 Global P=0.05 PI-mono vs. PI/NRTI Week 96 P=0.99 Global P=0.19

100

200

300

400

Me

an a

bso

lute

CD

4+

cell

cou

nt

(95

% C

I)

0 12 24 36 48 64 80 96

Weeks from randomization (switch to second-line)

PI-mono PI/NRTI PI/RAL

HR (PI/RAL: PI/NRTI) = 1.08 (0.81, 1.43) HR (PI-mono: PI/NRTI) = 1.09 (0.82, 1.45)

Global P=0.54

Grade 3/4 adverse events


Total participants 426 433 418 1277

Gr3/4 AEs (participants) 94 (22%) 100 (23%) 100 (24%) 294 (23%)

Rate per 100 PY 14.4 15.1 13.8 14.5

Pro

bab

ility

of

rem

ain

ing

gra

de

3/4

ad

vers

e e

ven

t-fr

ee

0.00

0.25

0.50

0.75

1.00

0 24 48 72 96 Weeks from randomization


Mean eGFR through 96 weeks

eGFR, estimated glomerular filtration rate

PI/RAL vs. PI/NRTI Week 96 P=0.02 Global P=0.03 PI-mono vs. PI/NRTI Week 96 P=0.06 Global P=0.14

-15

-10

-5

0

Me

an c

han

ge e

GFR

mL/

min

/1.7

3m

2

95

% C

I)

Weeks from randomization


0 12 48 96

EARNEST conclusions (1)

PI/NRTI

• Excellent clinical outcome: – 90% WHO4 event-free survival

– 86% VL suppression <400 c/mL at 96 weeks, even in advanced first-line failure

• Well-tolerated and safe

• Given with laboratory monitoring approach widely attainable in this setting: – Modest safety monitoring

– Clinical and CD4+ monitoring

– No real-time VL monitoring

– No resistance testing - NRTIs selected by clinical algorithm

• PI/NRTI merits its place as standardized regimen in second-line therapy in public health approach


• PI/RAL was not superior to PI/NRTI (“good disease control” and VL suppression)

• With cost differential, PI/RAL not suited for a standardized second-line regimen for large-scale use in WHO public health approach

• But PI/RAL non-inferior across range of outcomes and safe/ well-tolerated

• May represent an alternative regimen for some patients in resource-rich settings where individualized therapy is possible


PI-mono

• Inferior to PI/NRTI: Lower VL suppression, more resistance

• Unsuitable for public health approach

EARNEST conclusions (4) – the marvel of “recycled” NRTIs

• NRTIs retain substantial virologic activity in second-line

• Even in patient population with advanced first-line failure expected to have extensive cross-resistance

• Low incidence of NRTI-attributable toxicity (e.g. renal failure)

Other second-line trials: PI/RAL vs. PI/2NRTIs

SECOND-LINE trial: Design

(n=270)

(n=271)

Setting: Middle/high income countries Entry criteria: On first-line 2NRTI + NNRTI for ≥24 weeks Virologic failure (VL >500 c/mL) x 2 LPV/r 400/100 mg BID + RAL

96 weeks 48 0

LPV/r 400/100 mg BID + 2–3 NRTIs

Primary endpoint: HIV RNA <200 c/mL at Week 48

Hypothesis: PI/RAL non-inferior to PI/NRTI, margin 12%

Lab monitoring: CD4+ cell count + VL at each visit (12-weekly) Resistance testing allowed for NRTI selection

Boyd MA, et al. Lancet 2013;381:2091–99

SECOND-LINE trial: VL suppression at Week 48

Boyd MA, et al. Lancet 2013;381:2091–99

<200 c/mL <50 c/mL

0

30

70

100

%, m

od

ifie

d IT

T p

op

ula

tio

n

10

40

80

20

50

90 80.8% 82.6%

LPV/r + NRTIs

LPV/r + RAL

LPV/r + RAL

LPV/r + NRTIs

70.5% 71.1%

SECOND-LINE trial: Bone mineral density (BMD) change

• Bone loss: LPV/r + NRTIs > LPV/r + RAL at 48 weeks

• No difference in osteopenia (7%) or osteoporosis (2%) between groups Martin A, et al. AIDS 2013;27:2403–11

LPV/r + 2–3 NRTI LPV/r + RAL

Proximal femur Lumbar spine

-6

-3

0

Me

an %

ch

ange

in

BM

D f

rom

We

ek

0 t

o 4

8

-5

-2

-4

-1

P=0.0001

P=0.0006

Week 144 EARNEST results: VL suppression

Hakim et al. CROI 2015

0

100

80

60

40

20

0 4 12 24 36 48 64 80 96 144


% w

ith

VL

<40

0 c

op

ies/

mL


Week 144 EARNEST results: CD4+ change

Hakim et al. CROI 2015

300

100

0

0 4 12 24 36 48 64 80 96 144

200

112 128

Me

an c

han

ge C

D4

+ ce

lls/m

m3 (

95

% C

I)



Does the choice of NRTI matter? – for PI/2NRTI option

Does the choice of PI matter?

– for PI/2NRTI or PI/RAL option

NRTI resistance at baseline

• Baseline sequences obtained in 92% of those randomized to PI/NRTI arm

• Figure shows resistance data from 792 randomized patients

Kityo et al. CROI 2015; Poster 595

0

20

40

60

80

100

%

3TC FTC ABC TDF ZDV ddI D4T

Susceptible

Potential low

Low

Intermediate

High

Predicted activity of NRTIs in regimens

• Number of predicted “active” NRTIs in prescribed second-line therapy*: 0 230 (59%) 1 128 (33%) ≥2 33 (8%)

• GSS for NRTIs in prescribed second-line therapy: 0 114 (29%) 0.25–0.75 177 (45%) 1–1.75 73 (19%) ≥2 27 (7%)

*NRTI predicted “active” if no int./high level resistance by Stanford

Paton NI, et al. CROI 2015; Abstract 119

VL response by number of active NRTIs in the regimen


PI + RAL (N>280) PI-mono (N>374)

0

20

40

60

80

100

0 4 12 24 36 48 64 80 96 144

81%

61%

% w

ith

VL

<40

0 c

op

ies/

mL

Weeks from switch to second-line



PI/NRTI(0) (N>149)

PI + RAL (N>280) PI-mono (N>374)

0

20

40

60

80

100

0 4 12 24 36 48 64 80 96 144

81%

88%

61%

% w

ith

VL

<40

0 c

op

ies/

mL

Weeks from switch to second-line Global P<0.0001 NRTI() = number of active (susceptible-low resistance) NRTIs


PI/NRTI(0) (N>149)

PI/NRTI(1) (N>86) PI + RAL (N>280) PI-mono (N>374)

0

20

40

60

80

100

0 4 12 24 36 48 64 80 96 144

81%

88%

61%


85%

% w

ith

VL

<40

0 c

op

ies/

mL

Global P<0.0001 NRTI() = number of active (susceptible-low resistance) NRTIs




77%

PI/NRTI(0) (N>149)

PI/NRTI(1) (N>86) PI/NRTI(2–3) (N>17) PI + RAL (N>280) PI-mono (N>374)

0

20

40

60

80

100

0 4 12 24 36 48 64 80 96 144

81%

88%

61%


85%

% w

ith

VL

<40

0 c

op

ies/

mL


VL response by GSS of NRTIs in the regimen


83%

PI + 0 GSS (N>86) PI + 0.25–0.75 GSS (N>140) PI + 1–1.75 GSS (N>59) PI + 2 + GSS (N>21) PI + RAL (N>280) PI-mono (N>374)

0

20

40

60

80

100

0 4 12 24 36 48 64 80 96 144

81%

89%, 89%

73%

61%


% w

ith

VL

<40

0 c

op

ies/

mL


Factors associated with VL <400 c/mL in PI/NRTI

Unadjusted

Odds ratio (95% CI)

P

value

Adjusted

Odds ratio (95% CI)

P

value

GSS of second-line regimen

0

0.25–0.75

1–1.75

2–3

1

0.59 (0.26, 1.33)

0.60 (0.23, 1.61)

0.28 (0.09, 0.89)

0.19

(trend

0.08)

1

0.46 (0.19, 1.09)

0.39 (0.13, 1.19)

0.23 (0.06, 0.88)

0.12

(trend

0.03)

Viral load at baseline (per doubling) 0.70 (0.60, 0.83) <0.001 0.66 (0.55, 0.80) <0.001

Proportion non-adherent visits (per 5% higher)* 0.89 (0.82, 0.96) 0.003 0.89 (0.81, 0.98) 0.01

Unemployed at baseline 0.51 (0.28, 0.94) 0.03 0.48 (0.24, 0.98) 0.04

Age (per 10 years older) 1.45 (1.10, 1.92) 0.008 1.60 (1.15, 2.22) 0.005

Note: Multivariable regression modeling for VL suppression at week 96. N=346, excluding those with missing week 96 VL, baseline genotype or baseline employment status. Factors with P>0.1 sex, center, baseline CD4+ cell count, diabetes, cardiovascular disease, prior tuberculosis, smoking, alcohol consumption, hours worked per week, household income, food availability, presence of M184V in the baseline genotype, years on first-line, eGFR, hemoglobin, and glucose, previous CNS disease; viral subtype

*Non-adherent visit defined as missed, more than 7 days late, or reported any missing ART in the last month


Conclusions

• Paradoxical relationship between resistance and VL suppression

– Confounding by adherence (although persists after adjustment)

– Also consistent with fitness/fidelity effect

–May be be better to base NRTI choice on tolerability/convenience than predicted activity?

• Algorithmic NRTI drug selection and attention to adherence can achieve excellent outcomes from second-line therapy in public health approach

– Resistance testing to select NRTIs is of little added value

Does the choice of NRTI matter? – for PI/2NRTI option

Does the choice of PI matter?

– for PI/2NRTI or PI/RAL option

Second-line studies with PI/r + 2NRTI

Ajose O, et al. AIDS 2012;26:929–38

Characteristics of included studies

2LADY Trial

• Arm A: emtricitabine/tenofovir + lopinavir/ritonavir

• Arm B: didanosine + abacavir + lopinavir/ritonavir (+ lamivudine 150 mg if HBsAg positive)

• Arm C: emtricitabine/tenofovir + darunavir/ritonavir

Ciaffi et al, 7th EDCTP forum

2LADY Trial

Ciaffi et al. 7th EDCTP forum

ITT: Proportion in each arm of patients with VL <50 copies/mL with 95% CI

65.2%

0

20

40

60

80

100

-2 4 12 24 36 48

Time (weeks)

C: FTC + TDF + DRV/r (n=154)

A: FTC + TDF + LPV/r (n=152) B: ABC + ddl + LPV/r (n=145)

%

2LADY Trial

Ciaffi et al, 7th EDCTP forum

A: TDF/FTC + LPV/r B: ddI/ABC + LPV/r C: TDF/FTC + DRV/r

Primary endpoint Difference in proportion of patients with VL <50 copies/mL

across arms at Week 48 with IC 95%

-15 -10 -5 0 5 10 15 20

ITT A-B

ITT A-C

PP A-B

PP A-C

5.6% (-5.1; 16.4)

6.1% (-4.5; 16.7)

2.3% (-8.4; 13.1)

4.9% (-5.7; 15.5)

Evidence for ATV/r vs. LPV/r in second-line

• No RCTs in second-line!

• Circumstantial evidence from other settings….

• CASTLE: treatment-naïve

• BMS-045: salvage

CASTLE trial

Molina JM, et al. J Acquir Immune Defic Syndr 2010;53:323–32

ATV/RTV LPV/RTV

HIV RNA <100,000 copies/mL HIV RNA ≥100,000 copies/mL

0

30

70

100

Re

spo

nd

er (

%)

<5

0 c

op

ies/

mL

10

40

80

20

50

90

75% 70%

74%

66%

Proportion of patients with HIV RNA <50 c/mL at Week 96 (ITT; CVR, NC=F analysis), by qualifying HIV-1 RNA

n= 217 218 223 225

CASTLE trial (2)

Molina JM, et al. J Acquir Immune Defic Syndr 2010;53:323–32

Treatment-emergent resistance through Week 96 in isolates from patients with virologic failure

ATV/RTV n=438

LPV/RTV n=443

Virologic failure (HIV RNA ≥400 c/mL) 28 (6%) 29 (7%)

Paired genotypes 26 26

Major PI substitution 1 0

Minor PI substitution 1 1

PI polymorphisms (without major or minor PI substitutions) 11 14

Wild type 14 11

M184I/V 5 7

K65R 1 0

TAM (M41I, D67N, K70R, L210W, T215FY, K219EQ) 1 3

Paired phenotypes 25 23

PI phenotypic resistance ATV/RTV >5.2 1 0

LPV/RTV FC >9 0 1

Other boosted PIs 2 4

RTI phenotypic resistance FTC FC >3.5 or 3TC FC >3.5 5 5

TDF FC >1.4 0 2

Other NRTIs 3 5

BMS-045

Patients who had failed ≥2 previous regimens (with NRTI, NNRTI and PI) 72% had resistance to 3TC at baseline

Johnson M, et al. AIDS 2006;20:711–8

48 44

36

0

20

40

60

80

100

BL 12 24 48 72 96

Re

spo

nd

ers

(%)

Weeks

ATV/SQV (n=115)

LPV/RTV (n=123) ATV/RTV (n=120)

BMS-045

Naeger LK, Struble KA. AIDS 2006;20:847–53

ATV/RTV (n=110) LPV/RTV (n=112)

Baseline phenotype

0–2 0

30

70

100

Pro

po

rtio

n o

f re

spo

nd

ers

(<4

00

co

pie

s/m

L)

10

40

80

20

50

90

>2–5 >5–10 >10

PI/NRTI (N=426)

PI/RAL (N=433)

PI-mono (N=418)

Global P-value

PI/NRTI vs. RAL PI/NRTI vs. PI-mono Risk difference

(& hazard ratio)* (95% CI)

P value Risk difference (& hazard ratio)*

(95% CI)

P value

Week 48 Alive with no WHO stage 4‡, n (%)

395 (93%) 400 (92%) 390 (93%) 0.86 -0.4 (-4.6, +3.8) HR=0.96 (0.59, 1.56)

0.86 +0.7 (-3.4, +4.8) HR=1.10 (0.66, 1.83)

0.72

Alive, n (%) 405 (95%) 409 (94%) 401 (96%) 0.60 -0.7 (-4.2, +2.7) HR=0.89 (0.49, 1.59)

0.69 +1.0 (-2.2, +4.2) HR=1.22 (0.64, 2.31)

0.55

CD4+ >250 cells/mm3,

n/total with CD4+, n (%) CD4+, mean change (SE)

197/389 (51%)

168 (6)

210/395 (53%)

189 (8)

202/393 (51%)

179 (7)

0.77

0.13

+2.5% (-4.5%, +9.5%)

+21 (+1, +40)

0.48

0.04

+0.8% (-6.3, +7.8%)

+11 (-8, +30)

0.83

0.27 Viral load

Available <50 <400 <1000 <10,000

395

298 (75%) 336 (85%) 350 (89%) 364 (92%)

400

313 (78%) 365 (91%) 372 (93%) 379 (95%)

389

214 (55%) 293 (75%) 317 (81%) 352 (90%)

<0.0001 <0.0001 <0.0001

0.07

+2.8% (-3.1%, +8.7%) +6.2% (+1.7%,

+10.7%) +4.4% (+0.4%, +8.4%) +2.6% (-0.8%, +6.0%)

0.35 0.007 0.03 0.14

-20.4% (-26.9%, -13.9%) -9.7% (-15.3%, -4.2%) -7.1% (-12.1%, -2.1%) -1.7% (-5.6%, +2.3%)

<0.0001 0.0006 0.005 0.41

Any major or minor PI resistance mutation

6 (2%) 0 18 (6%) <0.0001 Not estimable†

+4.1% (+1.0%, +7.1%) 0.009

Intermediate/high level LPV/r resistance

6 (2%) 0 (0%) 13 (4%) 0.0006 Not estimable† +2.4% (-0.3%, +5.1%) 0.09

Week 48 data on LPV in EARNEST PI-mono

Primary and key secondary efficacy outcomes at 48 weeks

*Absolute risk difference and difference in rate per 100 person years for binary and time-to-event outcomes (WHO stage 4/death, death) respectively. Hazard ratio from Cox proportional hazards model also provided for time-to-event outcomes. ‡Including oesophageal candidiasis and mucosal herpes simplex virus infections. †Not estimable using weighted Poisson regression to account for missing genotypes in those with VL >1000 c/mL

Does PI choice matter with PI/RAL option?

• In second-line, no comparative RCTs of PI/RAL options

• Circumstantial evidence from first-line RCTs: – PROGRESS: PI(LPV)/RAL non-inferior to PI/NRTI (but not superior)

– NEAT: PI(DRV)/RAL inferior to PI/NRTI (in CD4+ cell count <200, VL >100K)

– SPARTAN: PI(ATV)/RAL inferior to PI/NRTI

• HARNESS (switch): PI(ATV)/RAL inferior to PI/NRTI

• Uncontrolled naïve studies

– ACTG5262: PI(DRV)/RAL, high VL failure rate at Week 48 (26%)

Conclusions: Options for second-line therapy in resource-limited settings

• Good evidence for LPV/r + 2NRTIs providing excellent outcomes in second-line using public health approach

• Good evidence for LPV/r + RAL being non-inferior to standard of care in second-line – may be attractive in some settings for individualizing therapy

• Choice of NRTIs in second-line may not matter (and probably don’t need resistance testing)

• Choice of PI may matter with the PI/2NRTIs combination (limited evidence)

• Choice of PI probably does matter with PI/RAL combination for second-line

Acknowledgments

Uganda: JCRC Kampala (African trial co-ordinating centre; 231) E Agweng, P Awio, G Bakeinyaga, C Isabirye, U Kabuga, S Kasuswa, M Katuramu, C Kityo, F Kiweewa, H Kyomugisha, E Lutalo, P Mugyenyi, D Mulima, H Musana, G Musitwa, V Musiime, M Ndigendawan, H Namata, J Nkalubo, P Ocitti Labejja, P Okello, P Olal, G Pimundu, P Segonga, F Ssali, Z Tamale, D Tumukunde, W Namala, R Byaruhanga, J Kayiwa, J Tukamushaba. IDI, Kampala (216): G Bihabwa, E Buluma, P Easterbrook, A Elbireer, A Kambugu, D Kamya, M Katwere, R Kiggundu, C Komujuni, E Laker, E Lubwama, I Mambule, J Matovu, A Nakajubi, J Nakku, R Nalumenya, L Namuyimbwa, F Semitala, B Wandera, J Wanyama; JCRC, Mbarara (97): H Mugerwa, A Lugemwa, E Ninsiima, T Ssenkindu, S Mwebe, L Atwine, H William, C Katemba, S Abunyang, M Acaku, P Ssebutinde, H Kitizo, J Kukundakwe, M Naluguza, K Ssegawa, Namayanja, F Nsibuka, P Tuhirirwe, M Fortunate; JCRC Fort Portal (66): J Acen, J Achidri, A Amone, M. Chamai, J Ditai, M Kemigisa, M Kiconco, C Matama, D Mbanza, F Nambaziira, M Owor Odoi, A Rweyora, G. Tumwebaze. San Raphael of St Francis Hospital, Nsambya (48): H Kalanzi, J Katabaazi , A Kiyingi, M Mbidde, M. Mugenyi, R Mwebaze, P Okong, I Senoga. JCRC Mbale (47): M Abwola, D Baliruno, J Bwomezi, A Kasede, M Mudoola, R Namisi, F Ssennono, S Tuhirwe.

JCRC Gulu (43): G Abongomera, G Amone, J Abach, I Aciro, B Arach, P Kidega, J Omongin, E Ocung, W Odong, A Philliam. JCRC Kabale (33): H Alima, B Ahimbisibwe, E Atuhaire, F Atukunda, G Bekusike, A Bulegyeya, D. Kahatano, S Kamukama, J Kyoshabire, A Nassali, A Mbonye, T M Naturinda, Ndukukire, A Nshabohurira, H. Ntawiha, A Rogers, M Tibyasa; JCRC Kakira (31): S. Kiirya, D. Atwongeire, A. Nankya, C. Draleku, D. Nakiboneka, D. Odoch, L. Lakidi, R. Ruganda, R. Abiriga, M. Mulindwa, F. Balmoi, S. Kafuma, E. Moriku

Zimbabwe: University of Zimbabwe Clinical Research Centre, Harare (265): J Hakim, A Reid, E Chidziva, G Musoro, C Warambwa, G Tinago, S Mutsai, M Phiri, S Mudzingwa, T Bafana, V Masore, C Moyo, R Nhema, S Chitongo

Malawi: College of Medicine, University of Malawi, Blanytre (92): Rob Heyderman, Lucky Kabanga, Symon Kaunda, Aubrey Kudzala, Linly Lifa, Jane Mallewa, Mike Moore, Chrissie Mtali, George Musowa, Grace Mwimaniwa, Rosemary Sikwese, Joep van Oosterhout, Milton Ziwoya. Mzuzu Central Hospital, Mzuzu (19): H Chimbaka. B Chitete, S Kamanga, T Kayinga E Makwakwa, R Mbiya, M Mlenga, T Mphande, C Mtika, G Mushani, O Ndhlovu, M Ngonga, I Nkhana, R Nyirenda

Kenya: Moi Teaching and Referral Hospital (52): P Cheruiyot, C Kwobah, W Lokitala Ekiru, M Mokaya, A Mudogo, A Nzioka, A Siika, M Tanui, S Wachira, K Wools-Kaloustian

Zambia: University Teaching Hospital (37): P Alipalli, E Chikatula, J Kipaila, I Kunda, S Lakhi, J Malama, W Mufwambi, L Mulenga, P Mwaba, E Mwamba, A Mweemba, M Namfukwe

The Aids Support Organisation (TASO), Uganda: E Kerukadho, B Ngwatu, J Birungi

MRC Clinical Trials Unit: N Paton, J Boles, A Burke, L Castle, S Ghuman, L Kendall, A Hoppe, S Tebbs, M Thomason, J Thompson, S Walker, J Whittle, H Wilkes, N Young

Monitors: C Kapuya, F Kyomuhendo, D Kyakundi, N Mkandawire, S Mulambo, S Senyonjo

Clinical Expert Review Committee: B Angus, A Arenas-Pinto, A Palfreeman, F Post, D Ishola

European Collaborators: J Arribas, B Colebunders, M Floridia, M Giuliano, P Mallon, P Walsh, M De Rosa, E Rinaldi

Trial Steering Committee: I Weller (Chair), C Gilks, J Hakim, A Kangewende, S Lakhi, E Luyirika, F Miiro, P Mwamba, P Mugyenyi, S Ojoo, N Paton, S Phiri, J van Oosterhout, A Siika, S Walker, A Wapakabulo,

Data Monitoring Committee: T Peto (Chair), N French, J Matenga

Pharmaceutical companies: J van Wyk, M Norton, S Lehrman, P Lamba, K Malik, J Rooney, W Snowden, J Villacian, G Cloherty

Funding and in-kind support: Funded by the European and Developing Countries Clinical Trials Partnership (EDCTP) with contributions from the Medical Research Council, UK, Institito de Salud Carlos III, Spain, Irish Aid, Ireland, Swedish International Development Cooperation Agency (SIDA), Sweden, Instituto Superiore di Sanita (ISS), Italy and Merck, USA. Substantive in-kind contributions were made by the Medical Research Council Clinical Trials Unit, UK, CINECA, Bologna, Italy, Janssen Diagnostics, Mechelen, Belgium; GSK, UK; Abbott Laboratories, USA. Trial medication was donated by AbbVie, Merck, Pfizer, GSK and Gilead

Thanks to all the participants ….

opening remarks - virology educationregist2.virology-education.com/2015/9interest/sat_abbvie.pdf ·...

Documents