Outcomes in ART treatment programmes with and without

access to routine viral load monitoring

Olivia Keiser on behalf of IeDEA Southern Africa

okeiser@ispm.unibe.ch

2

• Debate on place of routine viral load monitoring in scale-up programmes

• South Africa: routine VL monitoring part of national programme

Malawi and Zambia: no routine viral load monitoring

Background

3

Site Country Routine VL Patients

Lighthouse Malawi CIDRZ Zambia

no 9,60471,333

GugulethuKhayelitsha South Tygerberg Africa Thembalethu

yes2,6587,2301,3617,457

• Treatment naïve patients > 15 years, NNRTI-based ART regimen.

Selection of patients/ programmes

All sites participate in IeDEA Southern Africasee: www.iedea-sa.org

Mortality0.

000.

050.

10

0 1 2 3

Years since HAART start

No viral load monitoring(Malawi and Zambia)

Routine viral load monitoring(South Africa)

Cum

ulat

ive

mor

talit

y

5

1) Differences in patient characteristics ?

6

Patient characteristics at start of ART

Non VL sites

VL sites

Age 35 (30-42) 34 (30-41)

CD4 count

132 (66-203)

93 (39-159)

7

Sites with and without (reference) VL monitoring

Hazard ratio(95% CI)

P value

Crude 0.81 (0.76-0.87) <0.001

Adjusted * 0.74 (0.69-0.80) < 0.001

Competing risk regression with loss to follow-up and start of second-line therapy as competing events

*Adjusted for age, sex, CD4 cell count and clinical stage of disease

8

2) Differences in loss to follow-up ?

9

Adjusted* Hazard Ratio (95% CI)

P value

Mortality 0.74 (0.69-0.80) < 0.001

Loss to follow-up

0.70 (0.65-0.75) < 0.001

Competing risk regression

*Adjusted for age, sex, CD4 cell count and clinical stage of disease

• Sites with < 15% loss to follow-up 2 years after ART start

Sites with and without (reference) VL monitoring

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3) Differences in background mortality?

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Expected non-HIV-related death rate per 100 pyrs

SettingObserved

rate/100 pyrs

Assuming identical non-HIV-related mortality*

VL sites 2.12 (1.93-2.34) 2.12 (1.93-2.34)

Non VL sites 3.10 (2.99-3.20) 2.92 (2.82-3.02)

Rate ratio 0.68 (0.62-0.76) 0.73 (0.65-0.81)

* Based on South African rates

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4) Delayed/missed detection of treatment failure and

switching in non-VL sites?

Six months after ART start

Treatment failure - virologic (viral load sites) - immunologic (non viral load sites)

Switch

DeathLoss to follow-up

Multistate model

Putter et al., Stat Medicine 2007

From 6 months after ART start

0 200 400 600 800 0 200 400 600 800

Non VL sites VL sites

Loss to follow-upSecond-line therapyDeathCD4 criteria for switching

Remaining on first-line ART

Time (days) Time (days)

1

0.75

0.5

0.25

Prop

ortio

n of

pa

tient

s

0

From failureNon VL sites VL sites

8000 200 400 600 8000 200 400 600

Loss to follow-upSecond-line therapyDeathCD4 criteria for switching

Time (days) Time (days)

1

0.75

0.5

0.25

Prop

ortio

n of

pa

tient

s

0

From switchNon VL sites VL sites

0 200 400 600 8000 200 400 600 800Time (days) Time (days)

Loss to follow-upSecond-line therapyDeath

1

0.75

0.5

0.25

Prop

ortio

n of

pa

tient

s

0

From switchNon VL sites VL sites

(linkage with death registry)

0 200 400 600 800Time (days) Time (days)

Loss to follow-upSecond-line therapyDeath

0 200 400 600 800

1

0.75

0.5

0.25

Prop

ortio

n of

pa

tient

s

0

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Conclusions Mortality rate higher in sites without routine viral load monitoring

Difference probably not explained by differences in- Patient characteristics- Loss to follow-up- Background mortalityAlternative explanations:- Delayed/missed switching- Diagnostic and treatment capacities (for OIs), other differences in patient management

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Diagnostic capacities Non VL sites

VL sites

Site LH CI TL TB GU KHTuberculosis

Culture MTb/other M.

Cryptococcus Culture Ag test

Amphotericin treatment

Not generally available or off siteyes no

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Limitations - Few sites and countries included

- Mortality in patients lost to follow-up unknown in many sites

- Linkage with death registry only possible for patients with South African ID number available

- Estimates of HIV-free mortality might be inaccurateThis is an observational study - Ideally one would need a randomized

trial

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Acknowledgement University of Bern: Matthias Egger, Thomas Gsponer, Janne Estill, Gilles Wandeler, Franziska Schöni-Affolter, Martin Brinkhof, Fritz Käser, Claire Graber

Data center Cape Town: Andrew Boulle, Morna Cornell, Leigh Johnson, Nicola Maxwell

Site investigators: Benjamin Chi, Matt Fox, Mhairi Maskew, Catherine Orrell, Hans Prozesky, Ralf Weigel, Andrew Westfall