Publication:
A robust design for identification of the Parasite Clearance Estimator

dc.contributor.authorKris M. Jamsenen_US
dc.contributor.authorStephen B. Duffullen_US
dc.contributor.authorJoel Tarningen_US
dc.contributor.authorRic N. Priceen_US
dc.contributor.authorJulie A. Simpsonen_US
dc.contributor.otherUniversity of Melbourneen_US
dc.contributor.otherUniversity of Otagoen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherNuffield Department of Clinical Medicineen_US
dc.contributor.otherMenzies School of Health Researchen_US
dc.contributor.otherWorldWide Antimalarial Resistance Network (WWARN)en_US
dc.date.accessioned2018-10-19T04:59:59Z
dc.date.available2018-10-19T04:59:59Z
dc.date.issued2013-11-18en_US
dc.description.abstractBackground: Anti-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. Methods. Robust 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. Results: The 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). Conclusions: The 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. © 2013 Jamsen et al.; licensee BioMed Central Ltd.en_US
dc.identifier.citationMalaria Journal. Vol.12, No.1 (2013)en_US
dc.identifier.doi10.1186/1475-2875-12-410en_US
dc.identifier.issn14752875en_US
dc.identifier.other2-s2.0-84887344885en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/31837
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84887344885&origin=inwarden_US
dc.subjectImmunology and Microbiologyen_US
dc.subjectMedicineen_US
dc.titleA robust design for identification of the Parasite Clearance Estimatoren_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84887344885&origin=inwarden_US

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