Laboratory monitoring to guide switching antiretroviral therapy in resource-limited settings: clinical benefits and cost-effectiveness.
BACKGROUND
As second-line antiretroviral therapy (ART) availability increases in resource-limited settings, questions about the value of laboratory monitoring remain. We assessed the outcomes and cost-effectiveness (CE) of laboratory monitoring to guide switching ART.


METHODS
We used a computer model to project life expectancy and costs of different strategies to guide ART switching in patients in Côte d'Ivoire. Strategies included clinical assessment, CD4 count, and HIV RNA testing. Data were from clinical trials and cohort studies from Côte d'Ivoire and the literature. Outcomes were compared using the incremental CE ratio. We conducted multiple sensitivity analyses to assess uncertainty in model parameters.


RESULTS
Compared with first-line ART only, second-line ART increased life expectancy by 24% with clinical monitoring only, 46% with CD4 monitoring, and 61% with HIV RNA monitoring. The incremental CE ratio of switching based on clinical monitoring was $1670 per year of life gained (YLS) compared with first-line ART only; biannual CD4 monitoring was $2120 per YLS. The CE ratio of biannual HIV RNA testing ranged from $2920 ($87/test) to $1990 per YLS ($25/test). If second-line ART costs were reduced, the CE of HIV RNA monitoring improved.


CONCLUSIONS
In resource-limited settings, CD4 count and HIV RNA monitoring to guide switching to second-line ART improve survival and, under most conditions, are cost-effective.
Kimmel
April D
AD
Department of Public Health, Weill Cornell Medical College, New York, NY 10065, USA. adk2010@med.cornell.edu
Weinstein
Milton C
MC
Anglaret
Xavier
X
Goldie
Sue J
SJ
Losina
Elena
E
Yazdanpanah
Yazdan
Y
Messou
Eugène
E
Cotich
Kara L
KL
Walensky
Rochelle P
RP
Freedberg
Kenneth A
KA
D000328:Adult; D019380:Anti-HIV Agents / Q000008:administration & dosage / Q000191:economics* / Q000627:therapeutic use*; D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D018450:Disease Progression; D016527:Drug Costs; D005260:Female; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D008297:Male; D008954:Models, Biological; D018803:Models, Economic
D019380:Anti-HIV Agents
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