Literature DB >> 29021399

Modeling of Antilatency Treatment in HIV: What Is the Optimal Duration of Antiretroviral Therapy-Free HIV Remission?

Deborah Cromer1, Mykola Pinkevych1, Thomas A Rasmussen2,3, Sharon R Lewin3,4, Stephen J Kent3,4,5,6, Miles P Davenport7.   

Abstract

A number of treatment strategies are currently being developed to promote antiretroviral therapy-free HIV cure or remission. While complete elimination of the HIV reservoir would prevent recurrence of infection, it is not clear how different remission lengths would affect viral rebound and transmission. In this work, we use a stochastic model to show that a treatment that achieves a 1-year average time to viral remission will still lead to nearly a quarter of subjects experiencing viral rebound within the first 3 months. Given quarterly viral testing intervals, this leads to an expected 39 (95% uncertainty interval [UI], 22 to 69) heterosexual transmissions and up to 262 (95% UI, 107 to 534) homosexual transmissions per 1,000 treated subjects over a 10-year period. Thus, a balance between high initial treatment levels, risk of recrudescence, and risk of transmission should be considered when assessing the "useful" or optimal length of antiretroviral therapy-free HIV remission to be targeted. We also investigate the trade-off between increasing the average duration of remission versus the risk of treatment failure (viral recrudescence) and the need for retreatment. To minimize drug exposure, we found that the optimal target of antilatency interventions is a 1,700-fold reduction in the size of the reservoir, which leads to an average time to recrudescence of 30 years. Interestingly, this is a significantly lower level of reduction than that required for complete elimination of the viral reservoir. Additionally, we show that when shorter periods are targeted, there is a real probability of viral transmission occurring between tests for viral rebound.IMPORTANCE Current treatment of HIV involves patients taking antiretroviral therapy to ensure that the level of virus remains very low or undetectable. Continuous therapy is required, as the virus persists in a latent state within cells, and when therapy is stopped, the virus rebounds, usually within 2 weeks. A major question is how to reduce the amount of persistent virus and therefore allow a delay or remission until the virus returns after ceasing therapy. In this work, we consider the probability that HIV will still rebound even after this reduction and ask what the likelihood of viral transmission would be in this case.
Copyright © 2017 American Society for Microbiology.

Entities:  

Keywords:  HIV; latency; reactivation; remission

Mesh:

Substances:

Year:  2017        PMID: 29021399      PMCID: PMC5709587          DOI: 10.1128/JVI.01395-17

Source DB:  PubMed          Journal:  J Virol        ISSN: 0022-538X            Impact factor:   5.103


  30 in total

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Journal:  Nat Med       Date:  2003-05-18       Impact factor: 53.440

2.  The decay of the latent reservoir of replication-competent HIV-1 is inversely correlated with the extent of residual viral replication during prolonged anti-retroviral therapy.

Authors:  B Ramratnam; J E Mittler; L Zhang; D Boden; A Hurley; F Fang; C A Macken; A S Perelson; M Markowitz; D D Ho
Journal:  Nat Med       Date:  2000-01       Impact factor: 53.440

3.  Panobinostat, a histone deacetylase inhibitor, for latent-virus reactivation in HIV-infected patients on suppressive antiretroviral therapy: a phase 1/2, single group, clinical trial.

Authors:  Thomas A Rasmussen; Martin Tolstrup; Christel R Brinkmann; Rikke Olesen; Christian Erikstrup; Ajantha Solomon; Anni Winckelmann; Sarah Palmer; Charles Dinarello; Maria Buzon; Mathias Lichterfeld; Sharon R Lewin; Lars Østergaard; Ole S Søgaard
Journal:  Lancet HIV       Date:  2014-09-15       Impact factor: 12.767

4.  A low HIV-DNA level in peripheral blood mononuclear cells at antiretroviral treatment interruption predicts a higher probability of maintaining viral control.

Authors:  Lambert Assoumou; Laurence Weiss; Christophe Piketty; Marianne Burgard; Adeline Melard; Pierre-Marie Girard; Christine Rouzioux; Dominique Costagliola
Journal:  AIDS       Date:  2015-09-24       Impact factor: 4.177

5.  Gene editing of CCR5 in autologous CD4 T cells of persons infected with HIV.

Authors:  Pablo Tebas; David Stein; Winson W Tang; Ian Frank; Shelley Q Wang; Gary Lee; S Kaye Spratt; Richard T Surosky; Martin A Giedlin; Geoff Nichol; Michael C Holmes; Philip D Gregory; Dale G Ando; Michael Kalos; Ronald G Collman; Gwendolyn Binder-Scholl; Gabriela Plesa; Wei-Ting Hwang; Bruce L Levine; Carl H June
Journal:  N Engl J Med       Date:  2014-03-06       Impact factor: 91.245

6.  The Tat Inhibitor Didehydro-Cortistatin A Prevents HIV-1 Reactivation from Latency.

Authors:  Guillaume Mousseau; Cari F Kessing; Rémi Fromentin; Lydie Trautmann; Nicolas Chomont; Susana T Valente
Journal:  MBio       Date:  2015-07-07       Impact factor: 7.867

7.  HIV Reactivation from Latency after Treatment Interruption Occurs on Average Every 5-8 Days--Implications for HIV Remission.

Authors:  Mykola Pinkevych; Deborah Cromer; Martin Tolstrup; Andrew J Grimm; David A Cooper; Sharon R Lewin; Ole S Søgaard; Thomas A Rasmussen; Stephen J Kent; Anthony D Kelleher; Miles P Davenport
Journal:  PLoS Pathog       Date:  2015-07-02       Impact factor: 6.823

8.  Modeling of Experimental Data Supports HIV Reactivation from Latency after Treatment Interruption on Average Once Every 5-8 Days.

Authors:  Mykola Pinkevych; Stephen J Kent; Martin Tolstrup; Sharon R Lewin; David A Cooper; Ole S Søgaard; Thomas A Rasmussen; Anthony D Kelleher; Deborah Cromer; Miles P Davenport
Journal:  PLoS Pathog       Date:  2016-08-25       Impact factor: 6.823

9.  HIV-1 DNA predicts disease progression and post-treatment virological control.

Authors:  James P Williams; Jacob Hurst; Wolfgang Stöhr; Nicola Robinson; Helen Brown; Martin Fisher; Sabine Kinloch; David Cooper; Mauro Schechter; Giuseppe Tambussi; Sarah Fidler; Mary Carrington; Abdel Babiker; Jonathan Weber; Kersten K Koelsch; Anthony D Kelleher; Rodney E Phillips; John Frater
Journal:  Elife       Date:  2014-09-12       Impact factor: 8.140

10.  Elimination of HIV-1 Genomes from Human T-lymphoid Cells by CRISPR/Cas9 Gene Editing.

Authors:  Rafal Kaminski; Yilan Chen; Tracy Fischer; Ellen Tedaldi; Alessandro Napoli; Yonggang Zhang; Jonathan Karn; Wenhui Hu; Kamel Khalili
Journal:  Sci Rep       Date:  2016-03-04       Impact factor: 4.379

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  5 in total

1.  How Unavoidable Are Analytical Treatment Interruptions in HIV Cure-Related Studies?

Authors:  David M Margolis; Steven G Deeks
Journal:  J Infect Dis       Date:  2019-07-02       Impact factor: 5.226

2.  Virtual memory CD8+ T cells restrain the viral reservoir in HIV-1-infected patients with antiretroviral therapy through derepressing KIR-mediated inhibition.

Authors:  Jie-Hua Jin; Hui-Huang Huang; Ming-Ju Zhou; Jing Li; Wei Hu; Lei Huang; Zhe Xu; Bo Tu; Guang Yang; Ming Shi; Yan-Mei Jiao; Xing Fan; Jin-Wen Song; Ji-Yuan Zhang; Chao Zhang; Fu-Sheng Wang
Journal:  Cell Mol Immunol       Date:  2020-03-24       Impact factor: 11.530

3.  Predictors of SIV recrudescence following antiretroviral treatment interruption.

Authors:  Mykola Pinkevych; Christine M Fennessey; Deborah Cromer; Carolyn Reid; Charles M Trubey; Jeffrey D Lifson; Brandon F Keele; Miles P Davenport
Journal:  Elife       Date:  2019-10-25       Impact factor: 8.140

Review 4.  Modeling HIV persistence and cure studies.

Authors:  Alison L Hill
Journal:  Curr Opin HIV AIDS       Date:  2018-09       Impact factor: 4.283

5.  Balancing Statistical Power and Risk in HIV Cure Clinical Trial Design.

Authors:  Jillian S Y Lau; Deborah Cromer; Mykola Pinkevych; Sharon R Lewin; Thomas A Rasmussen; James H McMahon; Miles P Davenport
Journal:  J Infect Dis       Date:  2022-08-24       Impact factor: 7.759

  5 in total

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