ArticleMalaria journal2013
A robust design for identification of the Parasite Clearance Estimator.
Article in Malaria journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Evaluation of a multiphasic parasite clearance profile after treatment of experimental human infection with the investigational anti-malarial M5717 using segmented mixed effect models.Malaria journal · 2023Pooled it
- Quantification of parasite clearance in Plasmodium knowlesi infections.Malaria journal · 2023Article
- How Robust Are Malaria Parasite Clearance Rates as Indicators of Drug Effectiveness and Resistance?Antimicrobial agents and chemotherapy · 2015Article
- Defining the in vivo phenotype of artemisinin-resistant falciparum malaria: a modelling approach.PLoS medicine · 2015Article
- Making the most of clinical data: reviewing the role of pharmacokinetic-pharmacodynamic models of anti-malarial drugs.The AAPS journal · 2014Review
- Optimal sampling designs for estimation of Plasmodium falciparum clearance rates in patients treated with artemisinin derivatives.Malaria journal · 2013Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 4 countries.
Funding
Abstract
backgroundAnti-malarial efficacy needs to be monitored continually to ensure optimal dosing in the face of emerging anti-malarial drug resistance. The efficacy of artemisinin based combination therapies (ACT) is assessed by repeated measurements of parasite density in the blood of patients following treatment. Parasite density is measured from a capillary or venous blood sample, but this can be logistically and ethically challenging if multiple samples are required within a short time period. The aim of this work was to apply optimal design theory to derive clinically feasible blood sampling schedules from which parasite clearance could be defined using the Parasite Clearance Estimator (PCE), a recently developed tool to identify and quantify artemisinin resistance.
methodsRobust T-optimal design methodology was applied to offer a sampling schedule that allows for discrimination across models that best describe an individual patient's parasite-time profile. The design was based on typical parasite-time profiles derived from the literature combined with key sampling constraints of no more than six samples per patient within 48 hours of initial treatment. The design was evaluated with a simulation-estimation procedure that implemented the PCE.
resultsThe optimal sampling times (sampling windows) were: 0 (0 to 1.1), 5.8 (4.0 to 6.0), 9.9 (8.4 to 11.5), 24.8 (24.0 to 24.9), 36.3 (34.8 to 37.2) and 48 (47.3, 48.0) hours post initial treatment. The simulation-estimation procedure showed that the design supported identification of the appropriate method by the PCE to determine an individual's parasite clearance rate constant (the main output calculation from the PCE).
conclusionsThe proposed sampling design requires six samples per patient within the first 48 hours. The derived design requires validation in a real world setting, but should be considered for future studies that intend to employ the PCE.
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