Format

Send to

Choose Destination
  • PMID: 26181811 was deleted because it is a duplicate of PMID: 26470034
J Acquir Immune Defic Syndr. 2015 Nov 1;70(3):e110-9. doi: 10.1097/QAI.0000000000000748.

Implementation and Operational Research: Risk Charts to Guide Targeted HIV-1 Viral Load Monitoring of ART: Development and Validation in Patients From Resource-Limited Settings.

Author information

1
*Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; †Kheth'Impilo, Cape Town, South Africa; ‡Centre for Infectious Disease Research in Zambia, Lusaka, Zambia; §Aurum Institute for Health Research, Johannesburg, South Africa; ‖Gugulethu ART Programme and Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa; ¶Division of Infectious Diseases, Department of Medicine, University of Stellenbosch and Tygerberg Academic Hospital, Cape Town, South Africa; #Médecins Sans Frontières, Khayelitsha, Cape Town, South Africa; **Sinikithemba Clinic, McCord Hospital, Durban, South Africa; ††Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Somkhele, South Africa; ‡‡Health Economics and Epidemiology Research Office, University of the Witwatersrand, Johannesburg, South Africa; §§Center for Global Health & Development and Department of Epidemiology, Boston University, Boston, MA; ‖‖Biostatistics and Databases Program, The Kirby Institute, Faculty of Medicine, The University of New South Wales, Sydney, Australia; and ¶¶Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, South Africa.

Abstract

BACKGROUND:

HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing.

METHODS:

We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20%, or 40% of patients in 7 cohorts of patients starting ART in South Africa, and plotted cutoffs for VL testing on colour-coded risk charts. We assessed the accuracy of risk chart-guided VL testing to detect virologic failure in validation cohorts from South Africa, Zambia, and the Asia-Pacific.

RESULTS:

In total, 31,450 adult patients were included in the derivation and 25,294 patients in the validation cohorts. Positive predictive values increased with the percentage of patients tested: from 79% (10% tested) to 98% (40% tested) in the South African cohort, from 64% to 93% in the Zambian cohort, and from 73% to 96% in the Asia-Pacific cohort. Corresponding increases in sensitivity were from 35% to 68% in South Africa, from 55% to 82% in Zambia, and from 37% to 71% in Asia-Pacific. The area under the receiver operating curve increased from 0.75 to 0.91 in South Africa, from 0.76 to 0.91 in Zambia, and from 0.77 to 0.92 in Asia-Pacific.

CONCLUSIONS:

CD4-based risk charts with optimal cutoffs for targeted VL testing maybe useful to monitor ART in settings where VL capacity is limited.

PMID:
26470034
PMCID:
PMC5395665
DOI:
10.1097/QAI.0000000000000748
[Indexed for MEDLINE]

Supplemental Content

Loading ...
Support Center