Adherence to antiretroviral therapy and its impact on clinical outcome in HIV-infected patients

Individual longitudinal compliance to neglected tropical disease mass drug administration programmes, a systematic review

Repeated distribution of preventative chemotherapy (PC) by mass drug administration forms the mainstay of transmission control for five of the 20 recognised neglected tropical diseases (NTDs); soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. The efficiency of such programmes is reliant upon participants swallowing the offered treatment consistently at each round. This is measured by compliance, defined as the proportion of eligible participants swallowing treatment. Individually linked longitudinal compliance data is important for assessing the potential impact of MDA-based control programmes, yet this accurate monitoring is rarely implemented in those for NTDs. Longitudinal compliance data reported by control programmes globally for the five (PC)-NTDs since 2016 is examined, focusing on key associations of compliance with age and gender. PubMed and Web of Science was searched in January 2022 for articles written in English and Spanish, and the subsequent extraction adhered to PRISMA guidelines. Study title screening was aided by Rayyan, a machine learning software package. Studies were considered for inclusion if primary compliance data was recorded for more than one time point, in a population larger than 100 participants. All data analysis was conducted in R. A total of 89 studies were identified containing compliance data, 57 were longitudinal studies, of which 25 reported individually linked data reported by varying methods. The association of increasing age with the degree of systematic treatment was commonly reported. The review is limited by the paucity of data published on this topic. The varying and overlapping terminologies used to describe coverage (receiving treatment) and compliance (swallowing treatment) is reviewed. Consequently, it is recommended that WHO considers clearly defining the terms for coverage, compliance, and longitudinal compliance which are currently contradictory across their NTD treatment guidelines. This review is registered with PROSPERO (number: CRD42022301991).

Pharmacological data of a successful 4-days-a-week regimen in HIV antiretroviral therapy (ANRS 162-4D trial)

INTRODUCTION

Few data are available on plasma concentrations of antiretroviral therapy (ARV) during intermittent treatment.

OBJECTIVE

To compare plasma concentrations in OFF vs ON treatment periods at several time points during treatment.

METHODS

During a successful 48-week multicenter study (ANRS 162-4D trial) of 4 days with treatment (ON) followed by 3 days without treatment (OFF) in adults treated by two nucleoside analogues and a third agent belonging to a boosted protease-inhibitor (PI, darunavir [DRV], atazanavir [ATV], lopinavir [LPV]) or a non-nucleoside-reverse-transcriptase inhibitor (NNRTI, efavirenz [EFV], etravirine [ETR], rilpivirine [RPV]) conducted in 100 patients (96% success), we determined the plasma concentrations of ARV. Blood samples were collected for analysis at inclusion (W0, 7/7 strategy for all patients), W16 and W40 (ON) and at W4, W8, W12, W24, W32 and W48 (OFF).

RESULTS

A total of 866 samples was analysed. Plasma concentrations were not statistically lower after 4 days (ON) vs 7/7 days of treatment except for RPV (-30 ng/mL at 4/7, P = 0.003). Significant lower plasma concentrations were observed for OFF vs ON except for ETR (n = 5, P = 0.062). Overall, 87.1% of ON concentrations (ATV 92.1%, DRV 51.1%, LPV 62.5%, EFV 94.4%, ETR 100% and RPV 94.9%) and 21.8% of OFF concentrations (ATV 1.4%, DRV 0.0%, LPV 0.0%, EFV 16.0%, ETR 92.6% and RPV 39.0%) were above the theoretical limit of efficacy of the molecule. In the OFF period, 85.8% of PI concentrations were under the limit of quantification, while 98.0% of NNRTI concentrations were quantifiable.

CONCLUSION

Despite low/undetectable PI/NNRTI plasma concentrations in the OFF period, patients maintained an undetectable viral load. The mechanistic explanation should be investigated.

Health related quality of life of people receiving highly active antiretroviral therapy in Southwest Ethiopia

BACKGROUND

Highly Active Antiretroviral Therapy (HAART) is a standard of HIV management to suppress viral load and delay progression to AIDS. However, questions have been raised about the use of antiretroviral therapy and how it affects quality of life (QoL) of people living with HIV/AIDS (PLWHA). The study hence aimed to assess the QoL of PLWHA who were taking HAART at Mizan-Tepi University Teaching Hospital (MTUTH) and identify factors associated with QoL.

METHODS

A cross sectional study was conducted among PLWHA receiving HAART at MTUTH from March 04-April 1, 2018. Patients were recruited consecutively and interviewed with structured questionnaire. A data abstraction tool was used to extract data from patient medical records. Quality of life was assessed using the World Health Organization Quality of Life HIV- BREF (WHOQOL-HIV-BREF) standard tool. Data was entered to Epi-Info version 3.5.3 and analyzed using SPSS version 22 for windows. A multivariable logistic regression analysis was fitted to identify factors associated with QoL. A statistical significance was established at a p value <0.05.

RESULTS

A total of 240 participants with the mean age of 35.11 (SD = 9.08) years were included in the study. This study found that 57.1% of the patients had high global score of QoL. Patients with normal current health (AOR = 3.38, 95% CI = 1.56-7.31)) and having family support (AOR = 3.12, 95% CI = 1.51-6.46) were positively associated with high global score of QoL, while patients with low HAART adherence (AOR = 0.40, 95%, CI = 0.19-0.86) were negatively associated with high global score of QoL.

CONCLUSION

The study revealed that more than half of the participants had high global score of QoL. Normal current health and family support were associated with better global score of QoL, while low HAART adherence was found to be associated with the lower global score of QoL.

Health outcomes and cost-effectiveness of treating depression in people with HIV in Sub-Saharan Africa: a model-based analysis

High prevalence of depression among people living with HIV (PLHIV) impedes antiretroviral therapy (ART) adherence and viral suppression. We estimate the effectiveness and cost-effectiveness of strategies to treat depression among PLHIV in Sub-Saharan Africa (SSA). We developed a microsimulation model of HIV disease and care in Uganda which captured individuals' depression status and the relationship between depression and HIV behaviors. We consider a strategy of screening for depression and providing antidepressant therapy with fluoxetine at ART initiation or re-initiation (if a patient has dropped out). We estimate that over 10 years this strategy would reduce prevalence of depression among PLHIV by 16.0% [95% uncertainty bounds 15.8%, 16.1%] from a baseline prevalence of 28%, increase adherence to ART by 1.0% [1.0%, 1.0%], and decrease rates of loss to followup by 3.7% [3.4%, 4.1%]. This would decrease first-line ART failure rates by 2.5% [2.3%, 2.8%] and increase viral suppression rates by 1.0% [1.0%, 1.0%]. This strategy costs $15/QALY compared to the status quo, and was highly cost-effective over a broad range of sensitivity analyses. We conclude that screening for and treating depression among PLHIV in SSA with fluoxetine would be effective in improving HIV treatment outcomes and would be highly cost-effective.

Getting less of what you want: reductions in statistical power and increased bias when categorizing medication adherence data

Medication adherence is thought to be the principal clinical predictor of positive clinical outcomes, not only for serious mental illnesses such as schizophrenia, bipolar disorder, or depression, but also for physical conditions such as diabetes. Consequently, research on medication often looks not only at medication condition (e.g., placebo, standard medication, investigative medication), but also at adherence in taking those medications within each medication condition. The percentage (or proportion) scale is one of the more frequently employed and easily interpretable measures. Patients can be 0 % adherent, 100 % adherent, or somewhere in between. For simplicity, many reported adherence analyses dichotomize or trichotomize the adherence predictor when estimating its effect on outcomes of interest. However, the methodological literature shows that the practice of categorizing continuously distributed predictors reduces statistical power at best and, at worst, can severely bias parameter estimates. This can result in inflated Type I errors (false positive acceptance of null adherence effects) or Type II errors (false negative rejection of true adherence effects). We extend the methodological literature on categorization to the construct of adherence. The measurement scale of adherence leads to a diverse family of potential distributions including uniform, n-shaped, u-shaped (i.e., bimodal), positively skewed, and negatively skewed. Using a simulation study, we generated negative, null, and positive "true" effects of adherence on simulated continuous and binary outcomes. We then estimated the adherence effect with and without categorizing the adherence variable. We show how parameter estimates and standard errors can be severely biased when categorizing adherence. The categorization of adherence is shown to cause null effects to become positive or negative depending on the distribution of the simulated adherence variable, inflating Type I errors. When the adherence effect was significantly different from zero, categorization can render the effect null, inflating Type II errors. We recommend that adherence be measured continuously and analyzed without categorization when using it as a predictor in regression models.

Novel Approaches for Visualizing and Analyzing Dose-Timing Data from Electronic Drug Monitors, or "How the 'Broken Window' Theory Pertains to ART Adherence"

Adherence to antiretroviral medications is usually expressed in terms of the proportion of doses taken. However, the timing of doses taken may also be an important dimension to overall adherence. Little is known about whether patients who mistime doses are also more likely to skip doses. Using data from the completed Adherence for Life randomized controlled trial, we created visual and statistical models to capture and analyze dose timing data collected longitudinally with electronic drug monitors (EDM). From scatter plots depicting dose time versus calendar date, we identified dominant patterns of dose taking and calculated key features [slope of line over calendar date; residual mean standard error (RMSE)]. Each was assessed for its ability to categorize subjects with 'sub-optimal' (<95 % of doses taken) using area under the receiver operating characteristic (AROC) curve analysis. Sixty eight subjects contributed EDM data, with ~300 to 400 observations/subject. While regression line slopes did not predict 'sub-optimal' adherence (AROC 0.51, 95 % CI 0.26-0.75), the variability in dose timing (RMSE) was strongly predictive (AROC 0.79, 95 % CI 0.62-0.97). Compared with the lowest quartile of RMSE (minimal dose time variability), each successive quartile roughly doubled the odds of 'sub-optimal' adherence (OR 2.1, 95 % CI 1.3-3.4). Patterns of dose timing and mistiming are strongly related to overall adherence behavior. Notably, individuals who skip doses are more likely to mistime doses, with the degree of risk positively correlated with the extent of dose timing variability.

Psychiatric disorders and adherence to antiretroviral therapy among a population of HIV-infected adults in Nigeria

Psychiatric disorders are common among people living with HIV in Nigeria. Adherence is necessary to optimise the outcome of antiretroviral therapy. In this study, we aimed to identify associations between antiretroviral adherence, measured by one-week and one-month self-reported missed doses, and psychiatric illness in a cohort previously assessed for psychiatric disorders using the Composite International Diagnostic Interview. The study participants comprised 151 adults with major depression, anxiety or suicidal symptoms, and 302 matched-control participants. Two controls were randomly selected for each case within the same gender and education level. We compared participants with psychiatric disorders (WPDs) and no psychiatric disorders (NPDs) on selected demographic and clinical variables, in addition to adherence. Participants with one or more missed doses in the preceding month had twice the odds of having a major depressive episode as those with no missed doses during this period (OR 2.22, 95% CI 1.03, 4.79). This association remained significant after adjusting for selected risk factors. There was no statistically significant difference between WPD and NPD groups on either one-week or one-month adherence, or on age, marital status, occupational class, HIV viral load at enrolment or current CD4 cell count. Among Nigerian adults with HIV, suboptimal antiretroviral adherence is associated with, and could be a sign of, depression. Routine self-report adherence assessments may potentially be utilised in identifying individuals at risk among this population.

Four days a week or less on appropriate anti-HIV drug combinations provided long-term optimal maintenance in 94 patients: the ICCARRE project

Short, intraweekly cycles of anti-HIV combinations have provided intermittent, effective therapy (on 48 patients) (1). The concept is now extended to 94 patients on treatment, 4 days per week or less, over a median of 2.7 discontinuous treatment years per patient. On suppressive combinations, 94 patients volunteered to treatment, 5 and 4 days per week, or reduced stepwise to 4, 3, 2, and 1 days per week in 94, 84, 66, and 12 patients, respectively, on various triple, standard, antiviral combinations, or nonregistered, quadruple, antiviral combinations. Ninety-four patients on treatment 4 days per week aggregated 165 intermittent treatment years; no viral breakthrough was observed over 87 average treatment weeks per patient, 63 of 94 having passed 2.5 intermittent treatment years on any of the antiviral combinations prescribed. On the hyperintermittent treatment of 3, 2, and 1 days per week, HIV RNA surged >50 copies, 4 weeks apart, in 18 instances (6.8 viral escapes/100 hyperdiscontinuous maintenance years). Viral escapes could have been a result of erratic adherence (EA) to regimen or follow-up (3 patients)--drug taken at half of the daily recommended dosage (8 patients) and/or overlooked archival-resistant HIVs from antecedent treatment failures (6 patients). Aside from the above circumstances, HIV unexpectedly rebounded in 3 patients on 2 days per week treatment and 1 patient on 1 day per week treatment, posting 2.2 intrinsic viral escapes/100 highly discontinuous treatment years. All 18 escapes were eventually reversed by 7 days per week salvage combinations, and 11 of 18 patients have been back for a second course of intermittent therapy, 4 days per week or less. Both cell-activation markers on the surface of T lymphocytes and cell-bound HIV DNA levels remained stable or declined. CD4/CD8 ratios rose to ≥1 in 35% of patients, whereas CD4 counts went ≥500/µl in 75%. These values were previously 7 and 40%, respectively, on 7 days per week therapy. In our aging, long, HIV-enduring, multitreated patient cohort, treatment 4 days per week and less over 421 intermittent treatment years reduced prescription medicines by 60%--equivalent to 3 drug-free/3 virus-free remission year per patient--actually sparing €3 million on just 94 patients at the cost of 2.2 intrinsic viral failure/100 hyperintermittent treatment years. At no risk of viral escape, maintenance therapy, 4 days per week, would quasiuniversally offer 40% cuts off of current overprescriptions.

Modeling antiretroviral drug responses for HIV-1 infected patients using differential equation models

We review mathematical modeling and related statistical issues of HIV dynamics primarily in response to antiretroviral drug therapy in this article. We start from a basic model of virus infection and then review a number of more advanced models with consideration of pharmacokinetic factors, adherence and drug resistance. Specifically, we illustrate how mathematical models can be developed and parameterized to understand the effects of long-term treatment and different treatment strategies on disease progression. In addition, we discuss a variety of parameter estimation methods for differential equation models that are applicable to either within- or between-host viral dynamics.

Adherence profiles and therapeutic responses of treatment-naive HIV-infected patients starting boosted atazanavir-based therapy in the ANRS 134-COPHAR 3 trial

The adherence profile of HIV-infected patients predicts the therapeutic outcome, in particular during the early phase of antiretroviral therapy (ART). We conducted a prospective observational multicenter trial monitoring adherence and virological and immunological parameters over the initial 6 months of treatment. Thirty-five subjects were starting a treatment regimen including atazanavir, ritonavir, and emtricitabine-tenofovir. Adherence was assessed using self-completed questionnaires, announced pill counts, and the medication event monitoring system (MEMS) for each drug. Three MEMS measures were defined: the percentages of doses taken, days with the correct dosing, and doses taken on time (± 3 h). Dynamic virological suppression (DVS) was defined as a reduction in the plasma HIV-RNA level of >1 log10 per month or <40 copies/ml. The cumulative treatment time was 5,526 days. A high level of adherence was observed. The MEMS-defined adherence for correct dosing (-0.68% per 4-week period, P < 0.03) and timing compliance (-1.60% per 4-week period, P < 0.003) decreased significantly over time. The MEMS-defined adherence data were concordant with the pill counts during the trial but not with the data from the questionnaires. The median [range] percentages of doses taken (100% [50 to 102]), days with the correct dosing (95% [41 to 100]), and doses taken on time (86% [32 to 100]) were significantly associated with DVS in separate models. Among these three measures, the percentage of doses taken on time had the greatest ability to predict DVS. Timing compliance should be supported to optimize DVS during the early phase of treatment by once-daily boosted protease inhibitor-based ART. (This study has been registered at ClinicalTrials.gov under registration no. NCT00528060.).

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

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.

Assessing the impact of adherence to anti-retroviral therapy on treatment failure and resistance evolution in HIV

The adherence of patients to therapy is a crucial factor for successful HIV anti-retroviral therapy. Imperfect adherence may lead to treatment failure, which can cause the emergence of resistance within viral populations. We have developed a stochastic model that incorporates compartments of latently infected cells and virus genotypes with different susceptibilities to three simultaneously used drugs. With this model, we study the impact of several key parameters on the probability of treatment failure, i.e. insufficient viral suppression, and the emergence of resistance. Specifically, we consider the impact of drug dosage, drug half-lives, fitness costs for resistance, different basic reproductive numbers of the virus and the influence of pre-existing mutations under various levels of adherence. Furthermore, we also investigate the influence of different temporal distributions of non-adherent days (drug holidays) during a treatment. Factors that promote resistance evolution include a high reproductive number, extended drug holidays and poor adherence. Pre-existing mutations only have a substantial effect if they confer resistance against more than one drug. Overall, our study highlights the importance of the interactions between imperfect adherence, pharmacodynamics, pharmacokinetics and latently infected cells for our understanding of drug resistance and therapy failure in HIV anti-retroviral therapy.

Basic PK/PD principles of drug effects in circular/proliferative systems for disease modelling

Disease progression modelling can provide information about the time course and outcome of pharmacological intervention on the disease. The basic PK/PD principles of proliferative and circular systems within the context of modelling disease progression and the effect of treatment thereupon are illustrated with the goal to better understand/predict eventual clinical outcome. Circular/proliferative systems can be very complex. To facilitate the understanding of how a dosing regimen can be defined in such systems we have shown the derivation of a system parameter named the Reproduction Minimum Inhibitory Concentration (RMIC) which represents the critical concentration at which the system switches from growth to extinction. The RMIC depends on two parameters (RMIC = (R₀ − 1) × IC₅₀): the basic reproductive ratio (R₀) a fundamental parameter of the circular/proliferative system that represents the number of offspring produced by one replicating species during its lifespan, and the IC₅₀, the potency of the drug to inhibit the proliferation of the system. The RMIC is constant for a given system and a given drug and represents the lowest concentration that needs to be achieved for eradication of the system. When exposure is higher than the RMIC, success can be expected in the long term. Time varying inhibition of replicating species proliferation is a natural consequence of the time varying inhibitor drug concentrations and when combined with the dynamics of the circular/proliferative system makes it difficult to predict the eventual outcome. Time varying inhibition of proliferative/circular systems can be handled by calculating the equivalent effective constant concentration (ECC), the constant plasma concentration that would give rise to the average inhibition at steady state. When ECC is higher than the RMIC, eradication of the system can be expected. In addition, it is shown that scenarios that have the same steady state ECC whatever the dose, dosage schedule or PK parameters have also the same average R₀ in the presence of the inhibitor (i.e. R_0-INH) and therefore lead to the same outcome. This allows predicting equivalent active doses and dosing schedules in circular and proliferative systems when the IC₅₀ and pharmacokinetic characteristics of the drugs are known. The results from the simulations performed demonstrate that, for a given system (defined by its RMIC), treatment success depends mainly on the pharmacokinetic characteristics of the drug and the dosing schedule.

Modelling imperfect adherence to HIV induction therapy

Background

Induction-maintenance therapy is a treatment regime where patients are prescribed an intense course of treatment for a short period of time (the induction phase), followed by a simplified long-term regimen (maintenance). Since induction therapy has a significantly higher chance of pill fatigue than maintenance therapy, patients might take drug holidays during this period. Without guidance, patients who choose to stop therapy will each be making individual decisions, with no scientific basis.

Methods

We use mathematical modelling to investigate the effect of imperfect adherence during the inductive phase. We address the following research questions: 1. Can we theoretically determine the maximal length of a possible drug holiday and the minimal number of doses that must subsequently be taken while still avoiding resistance? 2. How many drug holidays can be taken during the induction phase?

Results

For a 180 day therapeutic program, a patient can take several drug holidays, but then has to follow each drug holiday with a strict, but fairly straightforward, drug-taking regimen. Since the results are dependent upon the drug regimen, we calculated the length and number of drug holidays for all fifteen protease-sparing triple-drug cocktails that have been approved by the US Food and Drug Administration.

Conclusions

Induction therapy with partial adherence is tolerable, but the outcome depends on the drug cocktail. Our theoretical predictions are in line with recent results from pilot studies of short-cycle treatment interruption strategies and may be useful in guiding the design of future clinical trials.

Optimal drug treatment regimens for HIV depend on adherence

Drug therapies aimed at suppressing the human immunodeficiency virus (HIV) are highly effective, often reducing the viral load to below the limits of detection for years. Adherence to such antiviral regimens, however, is typically far from ideal. We have previously developed a model that predicts optimal treatment regimens by weighing drug toxicity against CD4+ T-cell counts, including the probability that drug resistance will emerge. We use this model to investigate the influence of adherence on therapy benefit. For a drug with a given half-life, we compare the effects of varying the dose amount and dose interval for different rates of adherence, and compute the optimal dose regimen for adherence between 65% and 95%. Our results suggest that for optimal treatment benefit, drug regimens should be adjusted for poor adherence, usually by increasing the dose amount and leaving the dose interval fixed. We also find that the benefit of therapy can be surprisingly robust to poor adherence, as long as the dose interval and dose amount are chosen accordingly.

Emergence of HIV-1 Drug Resistance During Antiretroviral Treatment

Treating HIV-infected patients with a combination of several antiretroviral drugs usually contributes to a substantial decline in viral load and an increase in CD4(+) T cells. However, continuing viral replication in the presence of drug therapy can lead to the emergence of drug-resistant virus variants, which subsequently results in incomplete viral suppression and a greater risk of disease progression. In this paper, we use a simple mathematical model to study the mechanism of the emergence of drug resistance during therapy. The model includes two viral strains: wild-type and drug-resistant. The wild-type strain can mutate and become drug-resistant during the process of reverse transcription. The reproductive ratio [Symbol: see text](0) for each strain is obtained and stability results of the steady states are given. We show that drug-resistant virus is more likely to arise when, in the presence of antiretroviral treatment, the reproductive ratios of both strains are close. The wild-type virus can be suppressed even when the reproductive ratio of this strain is greater than 1. A pharmacokinetic model including blood and cell compartments is employed to estimate the drug efficacies of both the wild-type and the drug-resistant strains. We investigate how time-varying drug efficacy (due to the drug dosing schedule and suboptimal adherence) affects the antiviral response, particularly the emergence of drug resistance. Simulation results suggest that perfect adherence to regimen protocol will well suppress the viral load of the wild-type strain while drug-resistant variants develop slowly. However, intermediate levels of adherence may result in the dominance of the drug-resistant virus several months after the initiation of therapy. When more doses of drugs are missed, the failure of suppression of the wild-type virus will be observed, accompanied by a relatively slow increase in the drug-resistant viral load.

Modeling within-host HIV-1 dynamics and the evolution of drug resistance: trade-offs between viral enzyme function and drug susceptibility

There are many biological steps between viral infection of CD4(+) T cells and the production of HIV-1 virions. Here we incorporate an eclipse phase, representing the stage in which infected T cells have not started to produce new virus, into a simple HIV-1 model. Model calculations suggest that the quicker infected T cells progress from the eclipse stage to the productively infected stage, the more likely that a viral strain will persist. Long-term treatment effectiveness of antiretroviral drugs is often hindered by the frequent emergence of drug resistant virus during therapy. We link drug resistance to both the rate of progression of the eclipse phase and the rate of viral production of the resistant strain, and explore how the resistant strain could evolve to maximize its within-host viral fitness. We obtained the optimal progression rate and the optimal viral production rate, which maximize the fitness of a drug resistant strain in the presence of drugs. We show that the window of opportunity for invasion of drug resistant strains is widened for a higher level of drug efficacy provided that the treatment is not potent enough to eradicate both the sensitive and resistant virus.

Adherence to antiretroviral HIV drugs: how many doses can you miss before resistance emerges?

The question of determining how many doses may be skipped before HIV treatment response is adversely affected by the emergence of drug-resistance is addressed. Impulsive differential equations are used to develop a prescription to minimize the emergence of drug-resistance for protease-sparing regimens. A threshold for the maximal number of missable doses is determined. If the number of missed doses is below this threshold, then resistance levels are negligible and dissipate quickly, assuming perfect adherence subsequently. If the number of missed doses exceeds this threshold, even for 24h, resistance levels are extremely high and will not dissipate for weeks, even assuming perfect adherence subsequently. After this interruption, the minimum number of successive doses that should be taken is determined. Estimates are provided for all protease-sparing drugs approved by the US Food and Drug Administration. Estimates for the basic reproductive ratios for the wild-type and mutant strains of the virus are also calculated, for a long-term average fractional degree of adherence. There are regions within this fraction of adherence where the outcome is not predictable and may depend on a patient's entire history of drug-taking.