Evidence map›Paper›PMID 24225303›Full record

ArticleMalaria journal2013

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

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 and 11 more

Open access · goldAbstract readEvaluation Study
In one paragraph

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 27 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 3 pooled it
4.2field-weighted citation impact, top 6% of its field
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

27 citing papers in PubMed, 3 syntheses or guidelines pooled it, 40 citations in OpenAlex.

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  13. Discrete Survival Model Analysis ofPathogens (Basel, Switzerland) · 2021
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  16. Different Plasmodium falciparum clearance times in two Malian villages following artesunate monotherapy.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020
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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

21 authors at 14 institutions in 10 countries.

Jennifer A FleggWorldWide Antimalarial Resistance Network (WWARN), University of Oxford, Oxford, UK. jennifer.flegg@wwarn.org.
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
Mahidol University · THKarolinska Institutet · SELao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit · LANuffield Orthopaedic Centre · GBUniversity of Bamako · MLUniversity of Oxford · GBArmed Forces Research Institute of Medical Science · THCambodia National Malaria Center · KHCambodia-Oxford Medical Research Unit · KHKenya Medical Research Institute · KEMahidol Oxford Tropical Medicine Research Unit · THMedical University of Vienna · ATNational Institutes of Health · USOxford University Clinical Research Unit · VN

Funding

International Research in Cambodia: Tropical Medicine and Vector Research ZIAAI001066 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI YEK, CHRISTINA · 2009 to 2025
$10.8M
Malaria Pathogenesis and Human ImmunityZIAAI001000 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI FAIRHURST, RICK · 2009 to 2017
$9.3M
Wellcome Trust 089275Wellcome Trust 093956
6 · The paper itself

Abstract

backgroundThe 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.

methodsA 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.

resultsThe 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.

conclusionsThis 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.

Indexed as

AfricaArtemisininsAsiaHumansMalaria, FalciparumParasite LoadParasitemiaPlasmodium falciparumSpecimen HandlingTime FactorsartemisininArtemisinins

Identifiers

PMID24225303
PMCPMC3842737
OpenAlexW2146238956

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.