Dataset Information

Predicting short-term interruptions of antiretroviral therapy from summary adherence data: Development and test of a probability model.

ABSTRACT: Antiretroviral therapy (ART) for HIV is vulnerable to unplanned treatment interruptions-consecutively missed doses over a series of days-which can result in virologic rebound. Yet clinicians lack a simple, valid method for estimating the risk of interruptions. If the likelihood of ART interruption could be derived from a convenient-to-gather summary measure of medication adherence, it might be a valuable tool for both clinical decision-making and research. We constructed an a priori probability model of ART interruption based on average adherence and tested its predictions using data collected on 185 HIV-infected, treatment-naïve individuals over the first 90 days of ART in a prospective cohort study in Mbarara, Uganda. The outcome of interest was the presence or absence of a treatment gap, defined as >72 hours without a dose. Using the pre-determined value of 0.50 probability as the cut point for predicting an interruption, the classification accuracy of the model was 73% (95% CI = 66%- 79%), the specificity was 87% (95% CI = 79%- 93%), and the sensitivity was 59% (95% CI = 48%- 69%). Overall model performance was satisfactory, with an area under the receiver operator characteristic curve (AUROC) of 0.85 (95% CI = 0.80-0.91) and Brier score of 0.20. The study serves as proof-of-concept that the probability model can accurately differentiate patients on the continuum of risk for short-term ART interruptions using a summary measure of adherence. The model may also aid in the design of targeted interventions.

SUBMITTER: Harris RA

PROVIDER: S-EPMC5864044 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Predicting short-term interruptions of antiretroviral therapy from summary adherence data: Development and test of a probability model.

Harris Rebecca Arden RA Haberer Jessica E JE Musinguzi Nicholas N Chang Kyong-Mi KM Schechter Clyde B CB Doubeni Chyke A CA Gross Robert R

PloS one 20180322 3

Antiretroviral therapy (ART) for HIV is vulnerable to unplanned treatment interruptions-consecutively missed doses over a series of days-which can result in virologic rebound. Yet clinicians lack a simple, valid method for estimating the risk of interruptions. If the likelihood of ART interruption could be derived from a convenient-to-gather summary measure of medication adherence, it might be a valuable tool for both clinical decision-making and research. We constructed an a priori probability ...[more]

PMID: 29566096

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Project description:IntroductionSuccessful management of pediatric and adult human immunodeficiency virus (HIV) disease includes lifelong administration of antiretroviral therapy (ART). The need for the continuous use of antiretroviral drugs throughout the life course poses a challenge to children, adolescents, and adults living with HIV and their caregivers. Historically, treatment interruptions have been viewed as a negative therapeutic strategy. Recently, however, treatment interruptions or treatment reduction strategies have become a focus of investigations as innovative approaches to the long-term management of HIV disease. Current challenges with treatment interruptions include identifying an appropriate timeframe for length of interruptions and identifying HIV patient populations in whom the treatment interruption can be successful.ObjectiveIn this review, we aimed at summarizing recent studies of planned and unplanned treatment interruptions in children and adults living with HIV.Materials and methodsWe searched two databases (PubMed and Cochrane Controlled Trials Register) using keywords (HIV OR AIDS OR acquired immunodeficiency syndrome OR HIV-1 OR antiretroviral) AND (treatment interruption OR planned interruption OR therapeutic interruption OR unplanned interruption), for published randomized and nonrandomized clinical trials and observational cohort studies in children and adults (from birth to 99 years of age) in global settings covering a period from 2012 to 2018. In this review, only the studies that contained pediatric and adolescent populations with baseline immunological, virological, and clinical characteristics and outcomes after treatment interruption were included.ResultsA total of 174 eligible citations from the two databases were identified. We identified 10 prospective treatment interruption studies on children (five studies) and adults (five studies) during 2012-2018 with a total of 863 pediatric and 273 adult subjects. Collectively, recent studies on children and adults with HIV infection suggest that treatment interruptions with proper monitoring can be successful by instituting well-defined immunological and virological parameters or thresholds such as CD4 count, CD4%, and HIV RNA viral load that identify low-risk populations with treatment failure. In addition to standard virological and immunological outcome measurements, selected biomarkers that help detect early immune activation may also be useful in the monitoring of treatment interruption.ConclusionTreatment interruptions in adult and especially pediatric patients with well-controlled HIV disease may provide an alternative opportunity to optimize long-term HIV management by minimizing drug-associated toxicity and improving long-term adherence and quality of life.

Project description:BackgroundColocalization is a statistical method used in genetics to determine whether the same variant is causal for multiple phenotypes, for example, complex traits and gene expression. It provides stronger mechanistic evidence than shared significance, which can be produced through separate causal variants in linkage disequilibrium. Current colocalization methods require full summary statistics for both traits, limiting their use with the majority of reported GWAS associations (e.g. GWAS Catalog). We propose a new approximation to the popular coloc method that can be applied when limited summary statistics are available. Our method (POint EstiMation of Colocalization, POEMColoc) imputes missing summary statistics for one or both traits using LD structure in a reference panel, and performs colocalization using the imputed summary statistics.ResultsWe evaluate the performance of POEMColoc using real (UK Biobank phenotypes and GTEx eQTL) and simulated datasets. We show good correlation between posterior probabilities of colocalization computed from imputed and observed datasets and similar accuracy in simulation. We evaluate scenarios that might reduce performance and show that multiple independent causal variants in a region and imputation from a limited subset of typed variants have a larger effect while mismatched ancestry in the reference panel has a modest effect. Further, we find that POEMColoc is a better approximation of coloc when the imputed association statistics are from a well powered study (e.g., relatively larger sample size or effect size). Applying POEMColoc to estimate colocalization of GWAS Catalog entries and GTEx eQTL, we find evidence for colocalization of 150,000 trait-gene-tissue triplets.ConclusionsWe find that colocalization analysis performed with full summary statistics can be closely approximated when only the summary statistics of the top SNP are available for one or both traits. When applied to the full GWAS Catalog and GTEx eQTL, we find that colocalized trait-gene pairs are enriched in tissues relevant to disease etiology and for matches to approved drug mechanisms. POEMColoc R package is available at https://github.com/AbbVie-ComputationalGenomics/POEMColoc .

Dataset Information

Predicting short-term interruptions of antiretroviral therapy from summary adherence data: Development and test of a probability model.

Publications

Predicting short-term interruptions of antiretroviral therapy from summary adherence data: Development and test of a probability model.

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