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Are untimed antiretroviral drug levels useful predictors of adherence behavior?

2004· article· en· W2051295453 on OpenAlexaff
Cheryl A Liechty, Christopher S. Alexander, P. Richard Harrigan, J David Guzman, Edwin D. Charlebois, Andrew R. Moss, David R. Bangsberg

Bibliographic record

VenueAIDS · 2004
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental Health
KeywordsDrugAntiretroviral drugMedicineHuman immunodeficiency virus (HIV)Antiretroviral therapyInternal medicineIntensive care medicineViral loadPharmacologyVirology

Abstract

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We examined cross-sectionally the relationship between untimed drug levels and adherence in 83 individuals. Abnormally low untimed antiretroviral drug levels were sensitive in identifying individuals adherent to 60% or less of medication doses over a 3–5-week period. An abnormally low drug level was associated with a higher viral load. A single abnormally low untimed antiretroviral drug level can identify an individual with very low adherence at high risk of HIV disease progression and death. Adherence to HIV antiretroviral therapy is a strong predictor of virological suppression, disease progression, and death [1–6]. However, currently available approaches to measuring adherence have notable limitations [7–9], and individual patient assessments by medical providers do not accurately predict adherence [10–12]. Some investigators have assessed the antiretroviral drug level as a measure of adherence [13–16]. With one exception, those studies were limited by a reliance on self-reported measures of adherence [14]. The interpretation of random drug levels is complicated, however, because concentrations reflect drug absorption and metabolism as well as adherence to recent doses. To determine the extent to which untimed drug levels are associated with adherence behavior, we measured these levels in a subset of participants from the REACH Cohort of homeless and marginally housed HIV-positive adults in San Francisco. This analysis included 83 individuals with complete pill count adherence data on combination antiretroviral regimens. Individuals on ritonavir-boosted regimens were excluded. All procedures were approved by the University of California, San Francisco Committee on Human Subjects Research. Adherence assessments for the REACH Cohort have been described previously [17]. We measured adherence at unannounced pill count visits to the subjects’ place of residence every 3–5 weeks. Adherence was the difference between the current and previous pill counts divided by the prescribed number of doses for the same period. We have previously found that this method is closely associated with electronic cap monitoring (r = 0.91, P < 0.001) [18,19]. Procedures for drug level determination and the a priori establishment of concentration cut-offs below which drug levels were classified as ‘abnormally low’ have been described elsewhere [20]. The HIV viral load was measured using the Roche Amplicor assay. Our sample was 85% male, with a high proportion of past and current injection drug use. A total of 59% of study subjects had undetectable viral loads on a variety of antiretroviral regimens. Mean adherence was 70.6% (SD = 31.4%). Drug levels were abnormally low in 31.3% of subjects. The untimed drug level was significantly associated with adherence dichotomized at 90%: mean adherence for those with normal levels was 82.6%, versus 44.4% for those with abnormally low levels (P < 0.0001). The proportion of individuals with a normal drug level was significantly associated with the mean for each quintile of adherence values in a linear regression model with a slope 0.96 and y-intercept −1.3 (R2 = 0.94, P = 0.006). Table 1 summarizes the specificity and sensitivity of the untimed drug level to detect non-adherence based on our data. The sensitivity of abnormally low drug levels to detect adherence of 90% or less was poor, ranging from 31 to 56%. Specificity at this threshold was higher, at least 90% for all drugs except indinavir. Sensitivity improved at lower adherence thresholds: at the 60% or less level, the sensitivity for all drugs pooled was 72%, rising to 83% among those of 50% or less. For efavirenz, a particularly long half-life drug, sensitivity at 90% or less was low at 44%; however, specificity was 100%.Table 1: Abnormally low drug level predicting adherence of 90% or less.We also assessed the relationship between the drug level and viral suppression. Abnormally low drug levels were found to be significantly associated with a higher log viral load using Wilcoxon rank-sum (P = 0.01). Our findings support the concept that abnormally low untimed antiretroviral drug levels are associated with very low levels of adherence. The best test performance characteristics for this measure are in the setting of adherence below 60%. In keeping with this concept, we found that abnormally low untimed drug levels were associated with a higher viral load. A single random drug level can identify patients with very low level adherence. However, a normal range random drug level does not reliably signify high-level adherence. The development of objective measures of pill-taking behavior has been challenging. Drug level assays appeal to the desire for quantitative assessments and can be measured retrospectively on stored specimens in research settings, or at office visits to providers. Several investigators have examined the correlation between antiretroviral drug concentrations and self reported adherence. Murri et al. [21] reported that undetectable protease inhibitor levels were strongly correlated with self-reported non-adherence during the previous day [odds ratio (OR) 15.9, 95% confidence interval (CI) 4.9–50.7] [21]. The OR associated with missing doses more than once in the previous 3 days was 4.4 (95% CI 1.7–11.9). These findings support the concept that drug levels for short half-life medications best reflect adherence patterns over a brief period. In the ATHENA Project, self-reported adherence was compared with antiretroviral drug levels expressed as concentration ratios (CR) [13]. Those reporting any missed medication doses over the previoius 2 days had significantly lower CR than individuals who reported complete adherence. Lower CR have also been correlated with lower levels of protease inhibitor adherence, as measured by electronic medication monitoring [14]. Our results using unannounced pill counts, which assess adherence behavior over a significantly longer interval, are consistent with the observations described above. However, in this case we have used a drug level determination that is not timed with respect to the last antiretroviral dose. At the population level, we found a linear relationship between drug level and adherence across the full range of our adherence data. This suggests that untimed drug levels may be more useful in evaluating adherence in research cohorts than at the individual patient level. In this cross-sectional analysis, we could not assess the impact of abnormally low drug levels on outcomes over time; nor could we examine whether the correlation between low drug levels and non-adherence was consistent over time. In addition, the subgroups in our sample size are relatively small, limiting the ability to study the performance characteristics of drug level measurements for specific drugs. However, our sensitivity and specificity calculations were similar for most drugs, with the exception of indinavir, a particularly short half-life drug. Although adherence in excess of 90% is thought necessary for maximally sustained virological suppression [3], average adherence is considerably less [2,3,5,7, 17,22]. Despite this, dramatic mortality and morbidity benefits have been documented in the era of highly active antiretroviral therapy. Although perfect adherence should be the goal, it may be most important to identify accurately those who are the most non-adherent. Patients in this group are likely to be at the highest risk of HIV disease progression and death. In this regard, even a single untimed drug level of a single agent in a regimen appears to be useful.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.337
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations25
Published2004
Admission routes1
Has abstractyes

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