Literature DB >> 24342475

Costs and outcomes of laboratory diagnostic algorithms for the detection of HIV.

Angela B Hutchinson1, Steven F Ethridge2, Laura G Wesolowski2, Ram K Shrestha2, Michael Pentella3, Berry Bennett4, Paul G Farnham2, Timothy Sullivan5, Pragna Patel2, Bernard M Branson2.   

Abstract

BACKGROUND: An alternative HIV testing algorithm, designed to improve the detection of acute and early infections and differentiate between HIV-1 and HIV-2 antibodies, has been developed by the Centers for Disease Control and Prevention and the Association of Public Health Laboratories. While it promises greater sensitivity, it also raises concerns about costs.
OBJECTIVE: We sought to compare the most commonly used algorithm which was developed in 1989, a third-generation (3G) immunoassay (IA) and Western blot confirmatory test, to a newer algorithm. The new algorithm includes either a 3G or a fourth-generation (4G) initial IA, followed by confirmatory testing with a HIV-1/HIV-2 differentiation IA and, if needed, a nucleic acid amplification test (NAT). STUDY
DESIGN: We conducted an analysis of HIV testing costs from the perspective of the laboratory, and classified costs according to IA testing volume. We developed a decision analytic model, populated with cost data from 17 laboratories and published assay performance data, to compare the cost-effectiveness of the testing algorithms for a cohort of 30,000 specimens with a 1% HIV prevalence and 0.1% acute HIV infection prevalence.
RESULTS: Costs were lower in high-volume laboratories regardless of testing algorithm. For specimens confirmed positive for HIV antibody, the alternative algorithm (IA, Multispot) was less costly than the current algorithm (IA, WB); however, there was wide variation in reported testing costs. For our cohort, the alternative algorithm initiated with a 3G IA and 4G IA identified 15 and 25 more HIV infections, respectively, than the 1989 algorithm. In medium-volume laboratories, the 1989 algorithm was more costly and less effective than the alternative algorithm with a 3G IA; in high-volume laboratories, the alternative algorithm with 3G IA costs $162 more per infection detected. The alternative algorithm with 4G instead of 3G incurred an additional cost of $14,400 and $4865 in medium- and high-volume labs, respectively. DISCUSSION: HIV testing costs varied with IA testing volumes. The additional cost of 4G over 3G IA might be justified by the additional cases of HIV detected and transmissions averted due to earlier detection.
CONCLUSION: The alternative HIV testing algorithm compares favorably to the 1989 algorithm in terms of cost and effectiveness. Published by Elsevier B.V.

Entities:  

Keywords:  Cost-effectiveness; Costs; HIV testing algorithms

Mesh:

Year:  2013        PMID: 24342475     DOI: 10.1016/j.jcv.2013.10.005

Source DB:  PubMed          Journal:  J Clin Virol        ISSN: 1386-6532            Impact factor:   3.168


  9 in total

1.  Acute infections, cost and time to reporting of HIV test results in three U.S. State Public Health Laboratories.

Authors:  Muazzam Nasrullah; Laura G Wesolowski; Steven F Ethridge; Kevin Cranston; Michael Pentella; Robert A Myers; James T Rudrik; Angela B Hutchinson; Spencer B Bennett; Barbara G Werner
Journal:  J Infect       Date:  2016-05-26       Impact factor: 6.072

2.  Nucleic acid testing by public health referral laboratories for public health laboratories using the U.S. HIV diagnostic testing algorithm.

Authors:  Laura G Wesolowski; Kelly Wroblewski; Spencer B Bennett; Monica M Parker; Celia Hagan; Steven F Ethridge; Jeselyn Rhodes; Timothy J Sullivan; Imelda Ignacio-Hernando; Barbara G Werner; S Michele Owen
Journal:  J Clin Virol       Date:  2015-01-24       Impact factor: 3.168

Review 3.  The necessity of and strategies for improving confidence in the accuracy of western blots.

Authors:  Rajeshwary Ghosh; Jennifer E Gilda; Aldrin V Gomes
Journal:  Expert Rev Proteomics       Date:  2014-07-25       Impact factor: 3.940

4.  The Epidemiologic and Economic Impact of Improving HIV Testing, Linkage, and Retention in Care in the United States.

Authors:  Maunank Shah; Kathryn Risher; Stephen A Berry; David W Dowdy
Journal:  Clin Infect Dis       Date:  2015-09-11       Impact factor: 9.079

5.  Potential Contributions of Clinical and Community Testing in Identifying Persons with Undiagnosed HIV Infection in the United States.

Authors:  James G Kahn; Eran Bendavid; Patricia M Dietz; Angela Hutchinson; Hacsi Horvath; Devon McCabe; Richard J Wolitski
Journal:  J Int Assoc Provid AIDS Care       Date:  2020 Jan-Dec

6.  Performance of an Alternative Laboratory-Based HIV Diagnostic Testing Algorithm Using HIV-1 RNA Viral Load.

Authors:  Marc A Pitasi; Shilpa N Patel; Laura G Wesolowski; Silvina Masciotra; Wei Luo; S Michele Owen; Kevin P Delaney
Journal:  Sex Transm Dis       Date:  2020-05       Impact factor: 3.868

7.  Cost-Effectiveness of Frequent HIV Testing of High-Risk Populations in the United States.

Authors:  Angela B Hutchinson; Paul G Farnham; Stephanie L Sansom; Emine Yaylali; Jonathan H Mermin
Journal:  J Acquir Immune Defic Syndr       Date:  2016-03-01       Impact factor: 3.731

8.  Acute Infections, Cost per Infection and Turnaround Time in Three United States Hospital Laboratories Using Fourth-Generation Antigen-Antibody Human Immunodeficiency Virus Immunoassays.

Authors:  Laura G Wesolowski; Muazzam Nasrullah; Robert W Coombs; Eric Rosenberg; Steven F Ethridge; Angela B Hutchinson; Joan Dragavon; Jennifer Rychert; Frederick S Nolte; James E Madory; Barbara G Werner
Journal:  Open Forum Infect Dis       Date:  2015-12-09       Impact factor: 3.835

9.  Problems encountered in conventional HIV 1/2 Algorithms: lack of necessity for immunoblot assays to confirm repeated ELISA reactive results.

Authors:  Pelin Yuksel; Suat Saribas; Mert Kuskucu; Sibel Islak Mutcali; Erdogan Kosan; Zafer Habip; Mehmet Demirci; Eda Salihoglu Kara; Ilhan Birinci; Reyhan Caliskan; Harika Oyku Dinc; Kenan Midilli; Tevhide Ziver; Bekir Kocazeybek
Journal:  Afr Health Sci       Date:  2018-06       Impact factor: 0.927

  9 in total

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