Costs per Diagnosis of Acute HIV Infection in Community-based Screening Strategies: A Comparative Analysis of Four Screening Algorithms.
Journal: 2016/December - Clinical Infectious Diseases
ISSN: 1537-6591
Abstract:
BACKGROUND
In nonhealthcare settings, widespread screening for acute human immunodeficiency virus (HIV) infection (AHI) is limited by cost and decision algorithms to better prioritize use of resources. Comparative cost analyses for available strategies are lacking.
METHODS
To determine cost-effectiveness of community-based testing strategies, we evaluated annual costs of 3 algorithms that detect AHI based on HIV nucleic acid amplification testing (EarlyTest algorithm) or on HIV p24 antigen (Ag) detection via Architect (Architect algorithm) or Determine (Determine algorithm) as well as 1 algorithm that relies on HIV antibody testing alone (Antibody algorithm). The cost model used data on men who have sex with men (MSM) undergoing community-based AHI screening in San Diego, California. Incremental cost-effectiveness ratios (ICERs) per diagnosis of AHI were calculated for programs with HIV prevalence rates between 0.1% and 2.9%.
RESULTS
Among MSM in San Diego, EarlyTest was cost-savings (ie, ICERs per AHI diagnosis less than $13.000) when compared with the 3 other algorithms. Cost analyses relative to regional HIV prevalence showed that EarlyTest was cost-effective (ie, ICERs less than $69.547) for similar populations of MSM with an HIV prevalence rate >0.4%; Architect was the second best alternative for HIV prevalence rates >0.6%.
CONCLUSIONS
Identification of AHI by the dual EarlyTest screening algorithm is likely to be cost-effective not only among at-risk MSM in San Diego but also among similar populations of MSM with HIV prevalence rates >0.4%.
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Clin Infect Dis 62(4): 501-511

Costs per Diagnosis of Acute HIV Infection in Community-based Screening Strategies: A Comparative Analysis of Four Screening Algorithms

Division of Infectious Diseases, University of California–San Diego
Division of Pulmonology
Section of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Medical University of Graz, Austria
School of International Relations and Pacific Studies and Department of Economics, University of California–San Diego
Correspondence: M. Hoenigl, Antiviral Research Center, Division of Infectious Diseases, Department of Medicine, University of California, San Diego, 200 West Arbor Drive #8208, San Diego, CA 92103; Section of Infectious Diseases and Tropical Medicine & Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 15, A- 8036 Graz, Austria (ta.zarginudem@lgineoh.nitram; ude.dscu@lgineohm).
Correspondence: M. Hoenigl, Antiviral Research Center, Division of Infectious Diseases, Department of Medicine, University of California, San Diego, 200 West Arbor Drive #8208, San Diego, CA 92103; Section of Infectious Diseases and Tropical Medicine & Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 15, A- 8036 Graz, Austria (ta.zarginudem@lgineoh.nitram; ude.dscu@lgineohm).
Received 2015 Aug 3; Accepted 2015 Oct 20.

Abstract

Background. In nonhealthcare settings, widespread screening for acute human immunodeficiency virus (HIV) infection (AHI) is limited by cost and decision algorithms to better prioritize use of resources. Comparative cost analyses for available strategies are lacking.

Methods. To determine cost-effectiveness of community-based testing strategies, we evaluated annual costs of 3 algorithms that detect AHI based on HIV nucleic acid amplification testing (EarlyTest algorithm) or on HIV p24 antigen (Ag) detection via Architect (Architect algorithm) or Determine (Determine algorithm) as well as 1 algorithm that relies on HIV antibody testing alone (Antibody algorithm). The cost model used data on men who have sex with men (MSM) undergoing community-based AHI screening in San Diego, California. Incremental cost-effectiveness ratios (ICERs) per diagnosis of AHI were calculated for programs with HIV prevalence rates between 0.1% and 2.9%.

Results. Among MSM in San Diego, EarlyTest was cost-savings (ie, ICERs per AHI diagnosis less than $13.000) when compared with the 3 other algorithms. Cost analyses relative to regional HIV prevalence showed that EarlyTest was cost-effective (ie, ICERs less than $69.547) for similar populations of MSM with an HIV prevalence rate >0.4%; Architect was the second best alternative for HIV prevalence rates >0.6%.

Conclusions. Identification of AHI by the dual EarlyTest screening algorithm is likely to be cost-effective not only among at-risk MSM in San Diego but also among similar populations of MSM with HIV prevalence rates >0.4%.

Keywords: acute HIV, MSM, testing, cost analysis, NAT
Abstract

Ambitious recommendations for universal human immunodeficiency virus (HIV) testing in the United States are supported by observations that HIV diagnoses are frequently linked to reduced sexual risk behaviors and earlier uptake of antiretroviral therapy, both of which are expected to result in decreased HIV transmission [14]. Diagnosis of HIV infection during the acute stage of infection is especially important since transient levels of extremely high titer HIV RNA during acute HIV infection (AHI) are associated with rapid immune destruction and significantly greater infectivity than during chronic infection [5, 6].

The recognition that persons with AHI contribute disproportionately to population-level HIV transmission supports the updated recommendations for laboratory diagnosis of HIV infection in healthcare settings that use fourth-generation immunoassays to detect HIV-1/HIV-2 antibody (Ab) and HIV-1 p24 antigen (Ag) to detect AHI [7]. Detection of p24 Ag by the ARCHITECT Ag/Ab Combo assay is currently the most widely used approach for detecting AHI [813]. Alternative approaches for detecting and differentiating p24 Ag and HIV Ab include the rapid Alere Determine HIV-1/2 Combo assay and more sensitive HIV-1 nucleic acid amplification tests (NATs) [14, 15].

While AHI screening in healthcare settings is now recommended, one might wonder whether routine AHI screening should be the standard of care in community HIV screening programs, where about 40% of new HIV infections are diagnosed in the United States [16]. The main deterrents of widespread use of community HIV screening algorithms to detect AHI appear to be the elevated costs, need for venipuncture, concerns about turnaround time, and lack of laboratory capacity [6, 1719]. Absence of point-of-care (POC) tests that reliably detect AHI may be the major cost-contributing factor, as AHI screening strategies in community-based settings frequently require second visits or alternative approaches to inform clients of their test results. However, detailed cost analyses to compare testing strategies that identify acutely HIV-infected (ie, before seroconversion) and nonacutely HIV-infected (ie, after seroconversion) persons have not been performed. Therefore, there is uncertainty about the HIV prevalence rate needed to justify the cost of these testing algorithms compared with strategies that rely on POC HIV Ab testing only.

We developed and evaluated the first economic model to estimate the annual cost of a community-based AHI screening algorithm that consists of POC Ab plus individual donation qualitative NAT (ID-NAT; ie, the EarlyTest algorithm, I). We compared EarlyTest to 2 p24 Ag–based algorithms that detect AHI by either using Architect (II) or Determine (III). We further compared costs of these algorithms to an algorithm that relies on Ab testing alone (Antibody, IV).

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Notes

Disclaimer. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Financial support. This work was supported by funds from the following: the Max Kade Foundation (Max Kade postdoctoral research grant), International Research Fellowship in NeuroAIDS (grant number R25-MH081482), and grants from the National Institutes of Health (grant numbers AI43638, AI074621, AI106039).

Potential conflicts of interest. M. H. served on the speakers' bureau of Merck. S. J. L. reported grant funding from Gilead Sciences, Inc. J. G.-Z. reports no conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Notes

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