Virological suppression/rebound, ART discontinuation

and weight gain in children switching to dolutegravir

while virally suppressed in the UK/Ireland: a propensity

score analysis

Siobhan Crichton, Intira Jeannie Collins, Anna Turkova, Alasdair

Bamford, Caroline Foster, Hermione Lyall, Ali Judd on behalf of the

Collaborative HIV Paediatric Study (CHIPS) Steering Committee

19th July 2019

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Conflicts of interest

Nothing to disclose

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Background

• Dolutegravir (DTG) was approved in Europe for treatment of HIV-1 for individuals age

≥12 years in January 2014 and extended to 6-<12 year olds in December 2016.

• It is part of the World Health Organization (WHO) recommended preferred first-line

and second/subsequent-line regimens in children.

• 30% of children and adolescents in paediatric care in the UK and Ireland and now on

DTG.

• Rapid weight gain has been reported in some adults starting DTG but data on

treatment outcomes in routine paediatric care are limited.

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Aim

To describe virological suppression, viral rebound, discontinuations and weight gain in

children switching to DTG with suppressed viral load and compare to outcomes in

children suppressed at switch to a new protease inhibitor (PI)-based regimen.

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Methods

Population: All children receiving paediatric HIV care in the UK and Ireland

followed up in the Collaborative HIV Paediatric Study (CHIPS).

Inclusion criteria:

– aged 6-<18 years

– treatment experienced at switch to 2NRTIs+DTG or boosted PI

– suppressed viral load (VL) (<50c/ml or <lower limit of detection) at time of switch (3 month before to 1 week after)

– switched between 2010 and 2018

Where there was >1 eligible PI regimen per child, the most recent was used

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Propensity scores (1)

• Randomised controlled trials (RCTs) are the gold standard for

assessing the effectiveness of an intervention.

- Randomisation ensures differences on observed and unobserved factors are

due to chance

• Propensity scores offer a method of estimating treatment effects in

non-randomised data.

• A propensity score (PS) is an individual’s probability of receiving a

specific treatment based on their (observed) characteristics.

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Propensity scores (2)

• In a group of individuals with the same propensity scores the

distribution of characteristics will be the same in those who were and

were not treated.

• PS often used to match individuals who are ‘treated’ to similar

‘untreated’ individuals.

• Other uses include weighting, stratification and adjustment.

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• We estimated propensity scores based on the following

characteristics at start of DTG/PI

– age

– sex

– time since ART initiation

– history of treatment failure

– prior AIDS event

– CD4 count

– BMI-for-age z-score

Propensity scores (3)

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Statistical analysis

• PS used to estimate the differences between DTG and PI regimens in

• Proportion suppressed (VL<50 or <LLD) at 6 and 12 months

• Hazard of confirmed viral rebound (2 consecutive VL≥50c/ml) or discontinuation in first 12 months

• Mean change in BMI-for-age z-score (zBMI*) at 6 and 12 months

• In sensitivity analyses, the analysis was repeated using a threshold of 400 to

define viral suppression/rebound.

*World Health Organization. Growth reference data for 5-19 years. WHO reference 2007.

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Ever on DTG

N=302

VL<50c/ml

n=119

on PI*

N=797

On PI+2NRTIs

aged 6 to <18 years

n=408

VL<50c/ml

n=181

* started new boosted PI since 2010

** children who also started an eligible DTG containing regimen with VL≤50c/ml were excluded

On DTG+2NRTIs

aged 6 to <18 years

n=175

n=32 aged ≥ 18 years

n=45 aged <6 years

n=136 ineligible regimens

n=117 treatment naïve

n=59 on DTG**

n=27 VL≥50c/ml

N=29 VL unknown n=187 VL≥50c/ml

N=40 VL unknown

n=28 aged ≥ 18 years

n=1 aged <6 years

n=2 exact age unknown

n=72 ineligible regimen

n=24 treatment naive

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Characteristics of young people on

DTG and PI based regimens

DTGN=119

PIN=181

Median[IQR] or n(%)

Male sex 56 (47%) 90 (50%)

Age (years) at first ART 4.9 [1.2, 9.8] 4.7 [1.1,8.7]

At start of regimen

Age (years) 14.6 [11.9, 16.2] 13.3 [11.0, 15.3]

Calendar year 2016 [2016, 2017] 2013 [2012, 2014]

Prior AIDS event 29 (24%) 52 (29%)

CD4 count (cells/mm3) 789 [580, 997] 854 [646,1144]

History of treatment failure 49 (41%) 84 (46%)

Follow-up on regimen (months) 14.0 [5.9,20.7] 35.2 [17.7,48.6]

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DTGN=119

PIN=181

Reason for switch (n=108, 130)Simplified or more effective treatment 78 (72%) 83 (64%)Toxicity/side effects 20 (19%) 29 (22%)Other 10 (9%) 25 (14%)

Part of a fixed dose combination 91 (76%) 24 (13%)Frequency (n=112, 179)

Once daily 112 (100%) 174 (97%)Twice daily 0 5 (3%)

PI

DRV/r 110 (61%)

ATV/r 68 (38%)

LPV/r 3 (2%)

Back bone

3TC+ABC 110 (92%) 94 (52%)

FTC+TDF 4 (3%) 57 (31%)

FTC+TAF 4 (3%) 4 (2%)

ABC+TDF 0 8 (4%)

Other 0 18 (9%)

Characteristics of DTG and PI

based regimens

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Balance before and after PS matching

6 months (n=64 DTG, 145

PI)

Standardised difference

Raw Matched

Time on ART 0.20 0.05

Age at regimen 0.52 0.05

Sex -0.10 -0.10

Prior CDC C event 0.00 0.04

CD4 at regimen -0.10 0.07

Previous treatment failure -0.49 -0.12

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Viral suppression

After matching, VL suppression was 11.8%(95%CI 0.5,18.1%)

higher in children on DTG at 6m and 10.2%(0.1,18.9%) at 12m.

In sensitivity analysis defining

VL suppression as

VL<400c/ml the difference

was 5.9%(2.2,9.6%) at 6m

and 0.6%(-5.9,7.1%) at 12m.

n= 87 158 62 140

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Viral rebound and discontinuation

3 patients discontinued DTG within 1st 12m

2 toxicity (1 also had confirmed rebound)

1 switch back to previous regimen

7 patients discontinued PI within 1st 12m

2 Non-compliance

1 Toxicity predominantly abdomen/G-I tract

1 Hypersensitivity reaction

3 Other/unspecified

18 had confirmed VL≥50c/ml within 12 months

# at riskPI

DTG

96.9%

(95% CI 90.7, 99.0)

84.9%

(95% CI 78.4,89.5)The hazard of rebound/discontinuation, after weighting by

PS, was 3.5 (1.0,12.8) times higher on PI than DTG.

In sensitivity analysis defining

VL rebound as VL≥400c/m

the hazard ratio was

2.7(0.7,9.6).

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Change in zBMI

zBMI at start of DTG/PI Change in zBMI6 months 12 months 6 months 12 months

After matching, there was no significant difference in change in

zBMI (mean difference = -0.08(-0.22, 0.07) and 0.00(-0.10,0.11) at 6 and 12m on

DTG compared to PI )

n=155 n=98n=60 n=39 n=124 n=108

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Limitations

• No information on adherence.

• Relatively small sample size and low duration of follow up for those on DTG.

• Strict inclusion criteria – analysis was restricted to those switching for

maintenance.

• PS analysis only adjusts for differences in observed characteristics.

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Summary

• DTG was well tolerated with few discontinuations.

• A higher proportion of patients switching to DTG with a suppressed VL

had sustained suppression at 6 and 12 months compared to PI.

• No evidence of increases in zBMI after 12 months on DTG.

• Further follow-up is needed to explore long-term differences in time to

failure/discontinuation of ART and changes in zBMI.

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Poster 42

“Children and

adolescents in the UK/

Ireland CHIPS cohort

on integrase

inhibitors: safety and

effectiveness”

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Acknowledgements

All contributing clinics and patients

CHIPS Steering Committee: Hermione Lyall (Chair), Alasdair Bamford, Karina Butler, Katja Doerholt, Conor

Docherty, Caroline Foster, Ian Harrison, Julia Kenny, Nigel Klein, Gillian Letting, Paddy McMaster, Fungai Murau, Edith

Nsangi, Katia Prime, Andrew Riordan, Fiona Shackley, Delane Shingadia, Sharon Storey, Gareth Tudor-Williams, Anna

Turkova, Steve Welch.

MRC Clinical Trials Unit, UCL: Intira Jeannie Collins, Claire Cook, Siobhan Crichton, Donna Dobson, Keith Fairbrother,

Di Gibb, Ali Judd, Marthe Le Prevost, Francesca Schiavone, Nadine Van Looy.

National Study of HIV in Pregnancy and Childhood, UCL Great Ormond Street Institute of Child Health: Kate Francis,

Helen Peters, Claire Thorne.

Funding: NHS England (London Specialised Commissioning Group) and has received additional support from the

PENTA Foundation as well as Abbott, Bristol-Myers Squibb, Boehringer Ingelheim, Gilead Sciences, GlaxoSmithKline,

Janssen, Roche, and ViiV Healthcare. This work was supported by the MRC programme grant MC_UU_12023/26.