Cost-effectiveness of point-of-care testing with task-shifting for HIV care in South Africa: a modelling study.
Journal
The lancet. HIV
ISSN: 2352-3018
Titre abrégé: Lancet HIV
Pays: Netherlands
ID NLM: 101645355
Informations de publication
Date de publication:
04 2021
04 2021
Historique:
received:
05
04
2020
revised:
07
10
2020
accepted:
13
10
2020
pubmed:
22
12
2020
medline:
23
4
2021
entrez:
21
12
2020
Statut:
ppublish
Résumé
The number of people on antiretroviral therapy (ART) requiring treatment monitoring in low-resource settings is rapidly increasing. Point-of-care (POC) testing for ART monitoring might alleviate burden on centralised laboratories and improve clinical outcomes, but its cost-effectiveness is unknown. We used cost and effectiveness data from the STREAM trial in South Africa (February, 2017-October, 2018), which evaluated POC testing for viral load, CD4 count, and creatinine, with task shifting from professional to lower-cadre registered nurses compared with laboratory-based testing without task shifting (standard of care). We parameterised an agent-based network model, EMOD-HIV, to project the impact of implementing this intervention in South Africa over 20 years, simulating approximately 175 000 individuals per run. We assumed POC monitoring increased viral suppression by 9 percentage points, enrolment into community-based ART delivery by 25 percentage points, and switching to second-line ART by 1 percentage point compared with standard of care, as reported in the STREAM trial. We evaluated POC implementation in varying clinic sizes (10-50 patient initiating ART per month). We calculated incremental cost-effectiveness ratios (ICERs) and report the mean and 90% model variability of 250 runs, using a cost-effectiveness threshold of US$500 per disability-adjusted life-year (DALY) averted for our main analysis. POC testing at 70% coverage of patients on ART was projected to reduce HIV infections by 4·5% (90% model variability 1·6 to 7·6) and HIV-related deaths by 3·9% (2·0 to 6·0). In clinics with 30 ART initiations per month, the intervention had an ICER of $197 (90% model variability -27 to 863) per DALY averted; results remained cost-effective when varying background viral suppression, ART dropout, intervention effectiveness, and reduction in HIV transmissibility. At higher clinic volumes (≥40 ART initiations per month), POC testing was cost-saving and at lower clinic volumes (20 ART initiations per month) the ICER was $734 (93 to 2569). A scenario that assumed POC testing did not increase enrolment into community ART delivery produced ICERs that exceeded the cost-effectiveness threshold for all clinic volumes. POC testing is a promising strategy to cost-effectively improve patient outcomes in moderately sized clinics in South Africa. Results are most sensitive to changes in intervention impact on enrolment into community-based ART delivery. National Institutes of Health.
Sections du résumé
BACKGROUND
The number of people on antiretroviral therapy (ART) requiring treatment monitoring in low-resource settings is rapidly increasing. Point-of-care (POC) testing for ART monitoring might alleviate burden on centralised laboratories and improve clinical outcomes, but its cost-effectiveness is unknown.
METHODS
We used cost and effectiveness data from the STREAM trial in South Africa (February, 2017-October, 2018), which evaluated POC testing for viral load, CD4 count, and creatinine, with task shifting from professional to lower-cadre registered nurses compared with laboratory-based testing without task shifting (standard of care). We parameterised an agent-based network model, EMOD-HIV, to project the impact of implementing this intervention in South Africa over 20 years, simulating approximately 175 000 individuals per run. We assumed POC monitoring increased viral suppression by 9 percentage points, enrolment into community-based ART delivery by 25 percentage points, and switching to second-line ART by 1 percentage point compared with standard of care, as reported in the STREAM trial. We evaluated POC implementation in varying clinic sizes (10-50 patient initiating ART per month). We calculated incremental cost-effectiveness ratios (ICERs) and report the mean and 90% model variability of 250 runs, using a cost-effectiveness threshold of US$500 per disability-adjusted life-year (DALY) averted for our main analysis.
FINDINGS
POC testing at 70% coverage of patients on ART was projected to reduce HIV infections by 4·5% (90% model variability 1·6 to 7·6) and HIV-related deaths by 3·9% (2·0 to 6·0). In clinics with 30 ART initiations per month, the intervention had an ICER of $197 (90% model variability -27 to 863) per DALY averted; results remained cost-effective when varying background viral suppression, ART dropout, intervention effectiveness, and reduction in HIV transmissibility. At higher clinic volumes (≥40 ART initiations per month), POC testing was cost-saving and at lower clinic volumes (20 ART initiations per month) the ICER was $734 (93 to 2569). A scenario that assumed POC testing did not increase enrolment into community ART delivery produced ICERs that exceeded the cost-effectiveness threshold for all clinic volumes.
INTERPRETATION
POC testing is a promising strategy to cost-effectively improve patient outcomes in moderately sized clinics in South Africa. Results are most sensitive to changes in intervention impact on enrolment into community-based ART delivery.
FUNDING
National Institutes of Health.
Identifiants
pubmed: 33347810
pii: S2352-3018(20)30279-4
doi: 10.1016/S2352-3018(20)30279-4
pmc: PMC8284441
mid: NIHMS1659067
pii:
doi:
Substances chimiques
Anti-HIV Agents
0
Creatinine
AYI8EX34EU
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
e216-e224Subventions
Organisme : NIMH NIH HHS
ID : K01 MH115789
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI147752
Pays : United States
Organisme : NIAID NIH HHS
ID : R21 AI124719
Pays : United States
Informations de copyright
Copyright © 2021 Elsevier Ltd. All rights reserved.
Références
J R Soc Interface. 2013 Aug 28;10(88):20130613
pubmed: 23985734
AIDS. 2013 Jun 1;27(9):1483-92
pubmed: 23462219
Lancet Glob Health. 2014 Jan;2(1):e23-34
pubmed: 25104632
South Afr J HIV Med. 2017 Jul 27;18(1):694
pubmed: 29568630
PLoS One. 2019 Aug 26;14(8):e0221586
pubmed: 31449559
Value Health. 2016 Dec;19(8):929-935
pubmed: 27987642
Lancet. 2010 Jan 9;375(9709):123-31
pubmed: 20004464
Lancet HIV. 2019 Feb;6(2):e116-e127
pubmed: 30503325
PLoS Med. 2014 Sep 16;11(9):e1001725
pubmed: 25225800
AIDS. 2017 Jul 31;31(12):1755-1764
pubmed: 28590328
J Infect Dis. 2012 Feb 1;205(3):358-65
pubmed: 22241800
PLoS One. 2019 Oct 16;14(10):e0223669
pubmed: 31618220
MMWR Morb Mortal Wkly Rep. 2016 Dec 02;65(47):1332-1335
pubmed: 27906910
PLoS Med. 2020 Feb 14;17(2):e1003028
pubmed: 32059023
Lancet HIV. 2020 Apr;7(4):e229-e237
pubmed: 32105625
PLoS One. 2019 Feb 26;14(2):e0210497
pubmed: 30807573
AIDS. 2017 Sep 10;31(14):1989-1997
pubmed: 28650383
Trop Med Int Health. 2010 Jun;15 Suppl 1:1-15
pubmed: 20586956
J Int AIDS Soc. 2019 Sep;22(9):e25337
pubmed: 31515967
Lancet HIV. 2017 Jan;4(1):e41-e50
pubmed: 27914874
N Engl J Med. 2011 Aug 11;365(6):493-505
pubmed: 21767103
J Int AIDS Soc. 2019 Aug;22(8):e25393
pubmed: 31454178
J Int AIDS Soc. 2017 Jul 21;20(Suppl 4):21647
pubmed: 28770599
Clin Infect Dis. 2010 Sep 1;51(5):600-8
pubmed: 20649436
Trop Med Int Health. 2015 Apr;20(4):518-26
pubmed: 25442109
Pathog Dis. 2018 Jul 1;76(5):
pubmed: 29986020
J Int AIDS Soc. 2017 Apr 10;20(1):21317
pubmed: 28406595
Trop Med Int Health. 2016 Jun;21(6):743-9
pubmed: 27097834