The clinical interpretation of viral blips in HIV patients receiving antiviral treatment: Are we ready to infer poor adherence?

Isaac Chun-Hai Fung, Manoj Gambhir, Ard Van Sighem, Frank De Wolf, Geoffrey P. Garnett

Research output: Contribution to journalArticleResearchpeer-review

13 Citations (Scopus)

Abstract

Objectives: Viral blips may be an indication of poor adherence to antiretroviral treatment. This article studies how the variations of the definitions of viral blips and that of the choice of sampling frame in studies investigating viral blips may contribute to the uncertainty of the associations between viral blips and possible causes. Design: Mathematical modeling study allows us to study the impact of different sampling frames and different definitions of blips upon study results that are usually not feasible in clinical settings. Methods: Using a previously published mathematical model, scenarios of different drug adherence levels and viral blips, with different sampling frames, were modeled. Results: In the case of viral blips as a result of nonadherence to combinational antiretroviral therapy, rather than calculating the incidence of blips directly from the number of blips observed in a given period of time, it is better to report the proportion of observations in a given period of time that are ≥50 copies per milliliter. Therefore, as the denominator, the number of observations in a given period of time is important. However, the proportion of blips is not very informative on the drug adherence level. Conclusions: We should standardize definitions of viral blips and the choice of sampling frame and to report the proportion of observations of a given sampling frame in a given period of time that are ≥50 copies per milliliter, so that comparable data can be generated across different populations.

Original languageEnglish
Pages (from-to)5-11
Number of pages7
JournalJAIDS
Volume60
Issue number1
DOIs
Publication statusPublished - 1 May 2012
Externally publishedYes

Keywords

  • Drug adherence
  • HIV
  • Mathematical modeling
  • Sampling frame
  • Viral blips

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