Publication:
Optimal sampling designs for estimation of Plasmodium falciparum clearance rates in patients treated with artemisinin derivatives

Issued Date

2013-11-13

Resource Type

Article

ISSN

14752875

DOI

10.1186/1475-2875-12-411

Other identifier(s)

2-s2.0-84887365151

Rights

Mahidol University

Rights Holder(s)

SCOPUS

Bibliographic Citation

Malaria Journal. Vol.12, No.1 (2013)

Suggested Citation

Jennifer A. Flegg, Philippe J. Guérin, Francois Nosten, Elizabeth A. Ashley, Aung Pyae Phyo, Arjen M. Dondorp, Rick M. Fairhurst, Duong Socheat, Steffen Borrmann, Anders Björkman, Andreas Mårtensson, Mayfong Mayxay, Paul N. Newton, Delia Bethell, Youry Se, Harald Noedl, Mahamadou Diakite, Abdoulaye A. Djimde, Tran T. Hien, Nicholas J. White, Kasia Stepniewska Optimal sampling designs for estimation of Plasmodium falciparum clearance rates in patients treated with artemisinin derivatives. Malaria Journal. Vol.12, No.1 (2013). doi:10.1186/1475-2875-12-411 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/31839

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Title

Optimal sampling designs for estimation of Plasmodium falciparum clearance rates in patients treated with artemisinin derivatives

Author(s)

Jennifer A. Flegg
 Philippe J. Guérin
 Francois Nosten
 Elizabeth A. Ashley
 Aung Pyae Phyo
 Arjen M. Dondorp
 Rick M. Fairhurst
 Duong Socheat
 Steffen Borrmann
 Anders Björkman
 Andreas Mårtensson
 Mayfong Mayxay
 Paul N. Newton
 Delia Bethell
 Youry Se
 Harald Noedl
 Mahamadou Diakite
 Abdoulaye A. Djimde
 Tran T. Hien
 Nicholas J. White
 Kasia Stepniewska

Other Contributor(s)

University of Oxford
 Nuffield Department of Clinical Medicine
 Mahidol University
 National Institute of Allergy and Infectious Diseases
 National Center for Parasitology, Entomology and Malaria Control
 Wellcome Trust Research Laboratories Nairobi
 Karolinska Institutet
 Mahosot Hospital
 Armed Forces Research Institute of Medical Sciences, Thailand
 Armed Forces Research Institute of Medical Sciences
 Medizinische Universitat Wien
 University of Bamako
 Oxford University Clinical Research Unit (OUCRU)

Abstract

Abstract. Background: The emergence of Plasmodium falciparum resistance to artemisinins in Southeast Asia threatens the control of malaria worldwide. The pharmacodynamic hallmark of artemisinin derivatives is rapid parasite clearance (a short parasite half-life), therefore, the in vivo phenotype of slow clearance defines the reduced susceptibility to the drug. Measurement of parasite counts every six hours during the first three days after treatment have been recommended to measure the parasite clearance half-life, but it remains unclear whether simpler sampling intervals and frequencies might also be sufficient to reliably estimate this parameter. Methods. A total of 2,746 parasite density-time profiles were selected from 13 clinical trials in Thailand, Cambodia, Mali, Vietnam, and Kenya. In these studies, parasite densities were measured every six hours until negative after treatment with an artemisinin derivative (alone or in combination with a partner drug). The WWARN Parasite Clearance Estimator (PCE) tool was used to estimate "reference" half-lives from these six-hourly measurements. The effect of four alternative sampling schedules on half-life estimation was investigated, and compared to the reference half-life (time zero, 6, 12, 24 (A1); zero, 6, 18, 24 (A2); zero, 12, 18, 24 (A3) or zero, 12, 24 (A4) hours and then every 12 hours). Statistical bootstrap methods were used to estimate the sampling distribution of half-lives for parasite populations with different geometric mean half-lives. A simulation study was performed to investigate a suite of 16 potential alternative schedules and half-life estimates generated by each of the schedules were compared to the "true" half-life. The candidate schedules in the simulation study included (among others) six-hourly sampling, schedule A1, schedule A4, and a convenience sampling schedule at six, seven, 24, 25, 48 and 49 hours. Results: The median (range) parasite half-life for all clinical studies combined was 3.1 (0.7-12.9) hours. Schedule A1 consistently performed the best, and schedule A4 the worst, both for the individual patient estimates and for the populations generated with the bootstrapping algorithm. In both cases, the differences between the reference and alternative schedules decreased as half-life increased. In the simulation study, 24-hourly sampling performed the worst, and six-hourly sampling the best. The simulation study confirmed that more dense parasite sampling schedules are required to accurately estimate half-life for profiles with short half-life (≤three hours) and/or low initial parasite density (≤10,000 per μL). Among schedules in the simulation study with six or fewer measurements in the first 48 hours, a schedule with measurements at times (time windows) of 0 (0-2), 6 (4-8), 12 (10-14), 24 (22-26), 36 (34-36) and 48 (46-50) hours, or at times 6, 7 (two samples in time window 5-8), 24, 25 (two samples during time 23-26), and 48, 49 (two samples during time 47-50) hours, until negative most accurately estimated the "true" half-life. For a given schedule, continuing sampling after two days had little effect on the estimation of half-life, provided that adequate sampling was performed in the first two days and the half-life was less than three hours. If the measured parasitaemia at two days exceeded 1,000 per μL, continued sampling for at least once a day was needed for accurate half-life estimates. Conclusions: This study has revealed important insights on sampling schedules for accurate and reliable estimation of Plasmodium falciparum half-life following treatment with an artemisinin derivative (alone or in combination with a partner drug). Accurate measurement of short half-lives (rapid clearance) requires more dense sampling schedules (with more than twice daily sampling). A more intensive sampling schedule is, therefore, recommended in locations where P. falciparum susceptibility to artemisinins is not known and the necessary resources are available. Counting parasite density at six hours is important, and less frequent sampling is satisfactory for estimating long parasite half-lives in areas where artemisinin resistance is present. © 2013 Flegg et al.; licensee BioMed Central Ltd.

Keyword(s)

Immunology and Microbiology
 Medicine

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URI

https://repository.li.mahidol.ac.th/handle/20.500.14594/31839

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