Machine Learning Algorithms Using Routinely Collected Data Do Not Adequately Predict Viremia to Inform Targeted Services in Postpartum Women Living With HIV.


Journal

Journal of acquired immune deficiency syndromes (1999)
ISSN: 1944-7884
Titre abrégé: J Acquir Immune Defic Syndr
Pays: United States
ID NLM: 100892005

Informations de publication

Date de publication:
15 12 2021
Historique:
received: 05 05 2021
accepted: 18 08 2021
pubmed: 15 9 2021
medline: 27 1 2022
entrez: 14 9 2021
Statut: ppublish

Résumé

Adherence to antiretroviral treatment (ART) among postpartum women with HIV is essential for optimal health and prevention of perinatal transmission. However, suboptimal adherence with subsequent viremia is common, and adherence challenges are often underreported. We aimed to predict viremia to facilitate targeted adherence support in sub-Saharan Africa during this critical period. Data are from PROMISE 1077BF/FF, which enrolled perinatal women between 2011 and 2014. This analysis includes postpartum women receiving ART per study randomization or country-specific criteria to continue from pregnancy. We aimed to predict viremia (single and confirmed events) after 3 months on ART at >50, >400, and >1000 copies/mL within 6-month intervals through 24 months. We built models with routine clinical and demographic data using the least absolute shrinkage and selection operator and SuperLearner (which incorporates multiple algorithms). Among 1321 women included, the median age was 26 years and 96% were in WHO stage 1. Between 0 and 24 months postpartum, 42%, 31%, and 28% of women experienced viremia >50, >400, and >1000 copies/mL, respectively, at least once. Across models, the cross-validated area under the receiver operating curve ranged from 0.74 [95% confidence interval (CI): 0.72 to 0.76] to 0.78 (95% CI: 0.76 to 0.80). To achieve 90% sensitivity predicting confirmed viremia >50 copies/mL, 64% of women would be classified as high risk. Using routinely collected data to predict viremia in >1300 postpartum women with HIV, we achieved moderate model discrimination, but insufficient to inform targeted adherence support. Psychosocial characteristics or objective adherence metrics may be required for improved prediction of viremia in this population.

Sections du résumé

BACKGROUND
Adherence to antiretroviral treatment (ART) among postpartum women with HIV is essential for optimal health and prevention of perinatal transmission. However, suboptimal adherence with subsequent viremia is common, and adherence challenges are often underreported. We aimed to predict viremia to facilitate targeted adherence support in sub-Saharan Africa during this critical period.
METHODS
Data are from PROMISE 1077BF/FF, which enrolled perinatal women between 2011 and 2014. This analysis includes postpartum women receiving ART per study randomization or country-specific criteria to continue from pregnancy. We aimed to predict viremia (single and confirmed events) after 3 months on ART at >50, >400, and >1000 copies/mL within 6-month intervals through 24 months. We built models with routine clinical and demographic data using the least absolute shrinkage and selection operator and SuperLearner (which incorporates multiple algorithms).
RESULTS
Among 1321 women included, the median age was 26 years and 96% were in WHO stage 1. Between 0 and 24 months postpartum, 42%, 31%, and 28% of women experienced viremia >50, >400, and >1000 copies/mL, respectively, at least once. Across models, the cross-validated area under the receiver operating curve ranged from 0.74 [95% confidence interval (CI): 0.72 to 0.76] to 0.78 (95% CI: 0.76 to 0.80). To achieve 90% sensitivity predicting confirmed viremia >50 copies/mL, 64% of women would be classified as high risk.
CONCLUSIONS
Using routinely collected data to predict viremia in >1300 postpartum women with HIV, we achieved moderate model discrimination, but insufficient to inform targeted adherence support. Psychosocial characteristics or objective adherence metrics may be required for improved prediction of viremia in this population.

Identifiants

pubmed: 34520443
doi: 10.1097/QAI.0000000000002800
pii: 00126334-202112150-00003
pmc: PMC8585692
mid: NIHMS1739613
doi:

Substances chimiques

Anti-HIV Agents 0
Anti-Retroviral Agents 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

439-447

Subventions

Organisme : NIAID NIH HHS
ID : UM1 AI069423
Pays : United States
Organisme : NIMH NIH HHS
ID : K01 MH119910
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI069518
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI069536
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI069469
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI069530
Pays : United States

Informations de copyright

Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

The authors have no conflicts of interest to disclose.

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Auteurs

Pamela M Murnane (PM)

Department of Epidemiology and Biostatistics, University of California, San Francisco, CA.
Institute for Global Health Sciences, University of California, San Francisco, CA.

James Ayieko (J)

Center for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya.

Eric Vittinghoff (E)

Department of Epidemiology and Biostatistics, University of California, San Francisco, CA.

Monica Gandhi (M)

Department of Medicine, University of California, San Francisco, CA.

Chaplain Katumbi (C)

Blantyre Clinical Research Site, Johns Hopkins-College of Medicine Research Project, Blantyre, Malawi.

Beteniko Milala (B)

University of North Carolina-Project Malawi, Lilongwe, Malawi.

Catherine Nakaye (C)

Makerere University-Johns Hopkins University Research Collaboration, Kampala, Uganda.

Peter Kanda (P)

Clinical Trials Research Centre, University of Zimbabwe, Harare, Zimbabwe.

Dhayendre Moodley (D)

Centre for the AIDS Programme of Research in South Africa and Department of Obstetrics and Gynaecology, School of Clinical Medicine, University of KwaZulu Natal, Durban, South Africa.

Mandisa E Nyati (ME)

Perinatal HIV Research Unit, University of the Witwatersrand, Soweto, South Africa.

Amy J Loftis (AJ)

Institute for Global Health and Infectious Diseases, University of North Carolina Chapel Hill, Chapel Hill, NC.

Mary G Fowler (MG)

Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.

Pat Flynn (P)

Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, TN.

Judith S Currier (JS)

Division of Infectious Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA; and.

Craig R Cohen (CR)

Institute for Global Health Sciences, University of California, San Francisco, CA.
Department of Obstetrics, Gynecology & Reproductive Sciences, University of California, San Francisco, CA.

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