Evidence map›Paper›PMID 38688714›Full record

ArticleLupus science & medicine2024

Interpreting hydroxychloroquine blood levels for medication non-adherence: a pharmacokinetic study.

Stephen Balevic, Kai Sun, Jennifer L Rogers, Amanda Eudy, Rebecca Eli Sadun, Mithu Maheswaranathan, Jayanth Doss, Lisa Criscione-Schreiber, Tyler O'Malley, Megan Clowse and 1 more

Abstract read
In one paragraph

Article in Lupus science & medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Observational
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Stephen BalevicDepartment of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA stephen.balevic@duke.edu.ORCID 0000-0002-4016-1680
Kai SunDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0002-8406-2932
Jennifer L RogersDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0001-5524-8642
Amanda EudyDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0002-3107-5545
Rebecca Eli SadunDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Mithu MaheswaranathanDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0003-0866-0022
Jayanth DossDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Lisa Criscione-SchreiberDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Tyler O'MalleyExagen, Vista, California, USA.ORCID 0000-0002-4439-1395
Megan ClowseDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0002-8579-3470
Daniel WeinerUNC Eshelman School of Pharmacy, Chapel Hill, North Carolina, USA.

Funding

Optimal Dosing for Biologic Agents in Obese Patients with Rheumatoid and Juvenile ArthritisK23AR075874 · NIAMS · DUKE UNIVERSITY · PI BALEVIC, STEPHEN JOSEPH · 2020 to 2024
$830k
NIAMS NIH HHS K23 AR075874
6 · The paper itself

Abstract

objectiveCharacterise the relationship between hydroxychloroquine (HCQ) blood levels and the number of missed doses, accounting for dosage, dose timing and the large variability in pharmacokinetics (PK) between patients.

methodsWe externally validated a published PK model and then conducted dosing simulations. We developed a virtual population of 1000 patients for each dosage across a range of body weights and PK variability. Using the model, 10 Monte Carlo simulations for each patient were conducted to derive predicted whole blood concentrations every hour over 24 hours (240 000 HCQ levels at steady state). To determine the impact of missed doses on levels, we randomly deleted a fixed proportion of doses.

resultsFor patients receiving HCQ 400 mg daily, simulated random blood levels <200 ng/mL were exceedingly uncommon in fully adherent patients (<0.1%). In comparison, with 80% of doses missed, approximately 60% of concentrations were <200 ng/mL. However, this cut-off was highly insensitive and would miss many instances of severe non-adherence. Average levels quickly dropped to <200 ng/mL after 2-4 days of missed doses. Additionally, mean levels decreased by 29.9% between peak and trough measurements.

conclusionsWe propose an algorithm to optimally interpret HCQ blood levels and approximate the number of missed doses, incorporating the impact of dosage, dose timing and pharmacokinetic variability. No single cut-off has adequate combinations of both sensitivity and specificity, and cut-offs are dependent on the degree of targeted non-adherence. Future studies should measure trough concentrations to better identify target HCQ levels for non-adherence and efficacy.

Indexed as

Drug MonitoringHydroxychloroquineMonte Carlo MethodAntirheumatic AgentsComputer SimulationHumansLupus Erythematosus, SystemicModels, BiologicalAntirheumatic AgentsHydroxychloroquineAntirheumatic AgentsLupus Erythematosus, SystemicPharmacokinetics

Identifiers

PMID38688714
PMCPMC11086411

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.