Monitoring of antiretroviral therapy and mortality in HIV programmes in Malawi, South Africa and Zambia: mathematical modelling study

Estill, Janne; Egger, Matthias; Johnson, Leigh F.; Gsponer, Thomas; Wandeler, Gilles; Davies, Mary-Ann; Boulle, Andrew; Wood, Robin; Garone, Daniela; Stringer, Jeffrey S. A.; Hallett, Timothy B.; Keiser, Olivia (2013). Monitoring of antiretroviral therapy and mortality in HIV programmes in Malawi, South Africa and Zambia: mathematical modelling study. PLoS ONE, 8(2), e57611. Public Library of Science 10.1371/journal.pone.0057611

[img]
Preview
Text
Estill PLoSOne 2013.pdf - Published Version
Available under License Creative Commons: Attribution (CC-BY).

Download (244kB) | Preview
[img]
Preview
Text
Estill PLoSOne 2013_suppl.pdf - Published Version
Available under License Creative Commons: Attribution (CC-BY).

Download (820kB) | Preview

OBJECTIVES

Mortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference.

DESIGN

Mathematical modelling study based on data from ART programmes.

METHODS

We used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained.

RESULTS

RRs comparing VL with CD4 cell count monitoring were 0.94 (0.74-1.03) in scenario A, 0.94 (0.77-1.02) with delayed switching (scenario B) and 0.80 (0.44-1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality.

CONCLUSIONS

VL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Infectiology

UniBE Contributor:

Estill, Janne Anton Markus, Egger, Matthias, Gsponer, Thomas, Wandeler, Gilles, Keiser, Olivia

Subjects:

300 Social sciences, sociology & anthropology > 360 Social problems & social services
600 Technology > 610 Medicine & health

ISSN:

1932-6203

Publisher:

Public Library of Science

Language:

English

Submitter:

Doris Kopp Heim

Date Deposited:

12 Feb 2014 14:15

Last Modified:

05 Dec 2022 14:27

Publisher DOI:

10.1371/journal.pone.0057611

PubMed ID:

23469035

BORIS DOI:

10.7892/boris.40599

URI:

https://boris.unibe.ch/id/eprint/40599

Actions (login required)

Edit item Edit item
Provide Feedback