Risk of sudden unexplained death after use of dihydroartemisinin-piperaquine for malaria: a systematic review and Bayesian meta-analysis.

Dihydroartemisinin-piperaquine is an effective and well tolerated artemisinin-based combination therapy that has been assessed extensively for the prevention and treatment of malaria. Piperaquine, similar to several structurally related antimalarials currently used, can prolong cardiac ventricular repolarisation duration and the electrocardiographic QT interval, leading to concerns about its proarrhythmic potential. We aimed to assess the risk of potentially lethal iatrogenic ventricular arrhythmias in individuals receiving dihydroartemisinin-piperaquine. We did a systematic review and Bayesian meta-analysis. We searched clinical bibliographic databases (last on May 24, 2017) for studies of dihydroartemisinin-piperaquine in human beings. Further unpublished studies were identified with the WHO Evidence Review Group on the Cardiotoxicity of Antimalarials. We searched for articles containing "dihydroartemisinin-piperaquine" as title, abstract, or subject heading keywords, with synonyms and variant spellings as additional search terms. We excluded animal studies, but did not apply limits on language or publication date. Eligible studies were prospective, randomised, controlled trials or cohort studies in which individuals received at least one 3-day treatment course of dihydroartemisinin-piperaquine for mass drug administration, preventive therapy, or case management of uncomplicated malaria, with follow-up over at least 3 days. At least two independent reviewers screened titles, abstracts, and full texts, agreed study eligibility, and extracted information about study and participant characteristics, adverse event surveillance methodology, dihydroartemisinin-piperaquine exposures, loss-to-follow up, and any deaths after dihydroartemisinin-piperaquine treatment into a standardised database. The risk of sudden unexplained death after dihydroartemisinin-piperaquine with 95% credible intervals (CI) generated by Bayesian meta-analysis was compared with the baseline rate of sudden cardiac death. Our search identified 94 eligible primary studies including data for 197 867 individuals who had received dihydroartemisinin-piperaquine: 154 505 in mass drug administration programmes; 15 188 in 14 studies of repeated courses in preventive therapies and case management of uncomplicated malaria; and 28 174 as single-course treatments of uncomplicated malaria in 76 case-management studies. There was one potentially drug-related sudden unexplained death: a healthy woman aged 16 in Mozambique who developed heart palpitations several hours after the second dose of dihydroartemisinin-piperaquine and collapsed and died on the way to hospital (no autopsy or ECG was done). The median pooled risk estimate of sudden unexplained death after dihydroartemisinin-piperaquine was 1 in 757 950 (95% CI 1 in 2 854 490 to 1 in 209 114). This risk estimate was not higher than the baseline rate of sudden cardiac death (0·7-11·9 per 100 000 person-years or 1 in 1 714 280 to 1 in 100 835 over a 30-day risk period). The risk of bias was low in most studies and unclear in a few. Dihydroartemisinin-piperaquine was associated with a low risk of sudden unexplained death that was not higher than the baseline rate of sudden cardiac death. Concerns about repolarisation-related cardiotoxicity need not limit its current use for the prevention and treatment of malaria. Wellcome Trust, UK Medical Research Council, WHO, Bill & Melinda Gates Foundation, and University of Oxford.

Chan XHS ，Win YN ，Mawer LJ ，Tan JY ，Brugada J ，White NJ ... -  《-》

Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.

Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with ongoing transmission (WHO 2020). The World Health Organization (WHO) estimated that, in 2019, approximately 229 million cases of malaria occurred worldwide, with 94% occurring in the WHO's African region (WHO 2020). Of these malaria cases, an estimated 409,000 deaths occurred globally, with 67% occurring in children under five years of age (WHO 2020). Malaria also negatively impacts the health of women during pregnancy, childbirth, and the postnatal period (WHO 2020). Sulfadoxine/pyrimethamine (SP), an antifolate antimalarial, has been widely used across sub-Saharan Africa as the first-line treatment for uncomplicated malaria since it was first introduced in Malawi in 1993 (Filler 2006). Due to increasing resistance to SP, in 2000 the WHO recommended that one of several artemisinin-based combination therapies (ACTs) be used instead of SP for the treatment of uncomplicated malaria caused by Plasmodium falciparum (Global Partnership to Roll Back Malaria 2001). However, despite these recommendations, SP continues to be advised for intermittent preventive treatment in pregnancy (IPTp) and intermittent preventive treatment in infants (IPTi), whether the person has malaria or not (WHO 2013). Description of the intervention Folate (vitamin B9) includes both naturally occurring folates and folic acid, the fully oxidized monoglutamic form of the vitamin, used in dietary supplements and fortified food. Folate deficiency (e.g. red blood cell (RBC) folate concentrations of less than 305 nanomoles per litre (nmol/L); serum or plasma concentrations of less than 7 nmol/L) is common in many parts of the world and often presents as megaloblastic anaemia, resulting from inadequate intake, increased requirements, reduced absorption, or abnormal metabolism of folate (Bailey 2015; WHO 2015a). Pregnant women have greater folate requirements; inadequate folate intake (evidenced by RBC folate concentrations of less than 400 nanograms per millilitre (ng/mL), or 906 nmol/L) prior to and during the first month of pregnancy increases the risk of neural tube defects, preterm delivery, low birthweight, and fetal growth restriction (Bourassa 2019). The WHO recommends that all women who are trying to conceive consume 400 micrograms (µg) of folic acid daily from the time they begin trying to conceive through to 12 weeks of gestation (WHO 2017). In 2015, the WHO added the dosage of 0.4 mg of folic acid to the essential drug list (WHO 2015c). Alongside daily oral iron (30 mg to 60 mg elemental iron), folic acid supplementation is recommended for pregnant women to prevent neural tube defects, maternal anaemia, puerperal sepsis, low birthweight, and preterm birth in settings where anaemia in pregnant women is a severe public health problem (i.e. where at least 40% of pregnant women have a blood haemoglobin (Hb) concentration of less than 110 g/L). How the intervention might work Potential interactions between folate status and malaria infection The malaria parasite requires folate for survival and growth; this has led to the hypothesis that folate status may influence malaria risk and severity. In rhesus monkeys, folate deficiency has been found to be protective against Plasmodium cynomolgi malaria infection, compared to folate-replete animals (Metz 2007). Alternatively, malaria may induce or exacerbate folate deficiency due to increased folate utilization from haemolysis and fever. Further, folate status measured via RBC folate is not an appropriate biomarker of folate status in malaria-infected individuals since RBC folate values in these individuals are indicative of both the person's stores and the parasite's folate synthesis. A study in Nigeria found that children with malaria infection had significantly higher RBC folate concentrations compared to children without malaria infection, but plasma folate levels were similar (Bradley-Moore 1985). Why it is important to do this review The malaria parasite needs folate for survival and growth in humans. For individuals, adequate folate levels are critical for health and well-being, and for the prevention of anaemia and neural tube defects. Many countries rely on folic acid supplementation to ensure adequate folate status in at-risk populations. Different formulations for folic acid supplements are available in many international settings, with dosages ranging from 400 µg to 5 mg. Evaluating folic acid dosage levels used in supplementation efforts may increase public health understanding of its potential impacts on malaria risk and severity and on treatment failures. Examining folic acid interactions with antifolate antimalarial medications and with malaria disease progression may help countries in malaria-endemic areas determine what are the most appropriate lower dose folic acid formulations for at-risk populations. The WHO has highlighted the limited evidence available and has indicated the need for further research on biomarkers of folate status, particularly interactions between RBC folate concentrations and tuberculosis, human immunodeficiency virus (HIV), and antifolate antimalarial drugs (WHO 2015b). An earlier Cochrane Review assessed the effects and safety of iron supplementation, with or without folic acid, in children living in hyperendemic or holoendemic malaria areas; it demonstrated that iron supplementation did not increase the risk of malaria, as indicated by fever and the presence of parasites in the blood (Neuberger 2016). Further, this review stated that folic acid may interfere with the efficacy of SP; however, the efficacy and safety of folic acid supplementation on these outcomes has not been established. This review will provide evidence on the effectiveness of daily folic acid supplementation in healthy and malaria-infected individuals living in malaria-endemic areas. Additionally, it will contribute to achieving both the WHO Global Technical Strategy for Malaria 2016-2030 (WHO 2015d), and United Nations Sustainable Development Goal 3 (to ensure healthy lives and to promote well-being for all of all ages) (United Nations 2021), and evaluating whether the potential effects of folic acid supplementation, at different doses (e.g. 0.4 mg, 1 mg, 5 mg daily), interferes with the effect of drugs used for prevention or treatment of malaria. To examine the effects of folic acid supplementation, at various doses, on malaria susceptibility (risk of infection) and severity among people living in areas with various degrees of malaria endemicity. We will examine the interaction between folic acid supplements and antifolate antimalarial drugs. Specifically, we will aim to answer the following. Among uninfected people living in malaria endemic areas, who are taking or not taking antifolate antimalarials for malaria prophylaxis, does taking a folic acid-containing supplement increase susceptibility to or severity of malaria infection? Among people with malaria infection who are being treated with antifolate antimalarials, does folic acid supplementation increase the risk of treatment failure? Criteria for considering studies for this review Types of studies Inclusion criteria Randomized controlled trials (RCTs) Quasi-RCTs with randomization at the individual or cluster level conducted in malaria-endemic areas (areas with ongoing, local malaria transmission, including areas approaching elimination, as listed in the World Malaria Report 2020) (WHO 2020) Exclusion criteria Ecological studies Observational studies In vivo/in vitro studies Economic studies Systematic literature reviews and meta-analyses (relevant systematic literature reviews and meta-analyses will be excluded but flagged for grey literature screening) Types of participants Inclusion criteria Individuals of any age or gender, living in a malaria endemic area, who are taking antifolate antimalarial medications (including but not limited to sulfadoxine/pyrimethamine (SP), pyrimethamine-dapsone, pyrimethamine, chloroquine and proguanil, cotrimoxazole) for the prevention or treatment of malaria (studies will be included if more than 70% of the participants live in malaria-endemic regions) Studies assessing participants with or without anaemia and with or without malaria parasitaemia at baseline will be included Exclusion criteria Individuals not taking antifolate antimalarial medications for prevention or treatment of malaria Individuals living in non-malaria endemic areas Types of interventions Inclusion criteria Folic acid supplementation Form: in tablet, capsule, dispersible tablet at any dose, during administration, or periodically Timing: during, before, or after (within a period of four to six weeks) administration of antifolate antimalarials Iron-folic acid supplementation Folic acid supplementation in combination with co-interventions that are identical between the intervention and control groups. Co-interventions include: anthelminthic treatment; multivitamin or multiple micronutrient supplementation; 5-methyltetrahydrofolate supplementation. Exclusion criteria Folate through folate-fortified water Folic acid administered through large-scale fortification of rice, wheat, or maize Comparators Placebo No treatment No folic acid/different doses of folic acid Iron Types of outcome measures Primary outcomes Uncomplicated malaria (defined as a history of fever with parasitological confirmation; acceptable parasitological confirmation will include rapid diagnostic tests (RDTs), malaria smears, or nucleic acid detection (i.e. polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), etc.)) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Severe malaria (defined as any case with cerebral malaria or acute P. falciparum malaria, with signs of severity or evidence of vital organ dysfunction, or both) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Parasite clearance (any Plasmodium species), defined as the time it takes for a patient who tests positive at enrolment and is treated to become smear-negative or PCR negative. This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Treatment failure (defined as the inability to clear malaria parasitaemia or prevent recrudescence after administration of antimalarial medicine, regardless of whether clinical symptoms are resolved) (WHO 2019). This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Secondary outcomes Duration of parasitaemia Parasite density Haemoglobin (Hb) concentrations (g/L) Anaemia: severe anaemia (defined as Hb less than 70 g/L in pregnant women and children aged six to 59 months; and Hb less than 80 g/L in other populations); moderate anaemia (defined as Hb less than 100 g/L in pregnant women and children aged six to 59 months; and less than 110 g/L in others) Death from any cause Among pregnant women: stillbirth (at less than 28 weeks gestation); low birthweight (less than 2500 g); active placental malaria (defined as Plasmodium detected in placental blood by smear or PCR, or by Plasmodium detected on impression smear or placental histology). Search methods for identification of studies A search will be conducted to identify completed and ongoing studies, without date or language restrictions. Electronic searches A search strategy will be designed to include the appropriate subject headings and text word terms related to each intervention of interest and study design of interest (see Appendix 1). Searches will be broken down by these two criteria (intervention of interest and study design of interest) to allow for ease of prioritization, if necessary. The study design filters recommended by the Scottish Intercollegiate Guidelines Network (SIGN), and those designed by Cochrane for identifying clinical trials for MEDLINE and Embase, will be used (SIGN 2020). There will be no date or language restrictions. Non-English articles identified for inclusion will be translated into English. If translations are not possible, advice will be requested from the Cochrane Infectious Diseases Group and the record will be stored in the "Awaiting assessment" section of the review until a translation is available. The following electronic databases will be searched for primary studies. Cochrane Central Register of Controlled Trials. Cumulative Index to Nursing and Allied Health Literature (CINAHL). Embase. MEDLINE. Scopus. Web of Science (both the Social Science Citation Index and the Science Citation Index). We will conduct manual searches of ClinicalTrials.gov, the International Clinical Trials Registry Platform (ICTRP), and the United Nations Children's Fund (UNICEF) Evaluation and Research Database (ERD), in order to identify relevant ongoing or planned trials, abstracts, and full-text reports of evaluations, studies, and surveys related to programmes on folic acid supplementation in malaria-endemic areas. Additionally, manual searches of grey literature to identify RCTs that have not yet been published but are potentially eligible for inclusion will be conducted in the following sources. Global Index Medicus (GIM). African Index Medicus (AIM). Index Medicus for the Eastern Mediterranean Region (IMEMR). Latin American & Caribbean Health Sciences Literature (LILACS). Pan American Health Organization (PAHO). Western Pacific Region Index Medicus (WPRO). Index Medicus for the South-East Asian Region (IMSEAR). The Spanish Bibliographic Index in Health Sciences (IBECS) (ibecs.isciii.es/). Indian Journal of Medical Research (IJMR) (journals.lww.com/ijmr/pages/default.aspx). Native Health Database (nativehealthdatabase.net/). Scielo (www.scielo.br/). Searching other resources Handsearches of the five journals with the highest number of included studies in the last 12 months will be conducted to capture any relevant articles that may not have been indexed in the databases at the time of the search. We will contact the authors of included studies and will check reference lists of included papers for the identification of additional records. For assistance in identifying ongoing or unpublished studies, we will contact the Division of Nutrition, Physical Activity, and Obesity (DNPAO) and the Division of Parasitic Diseases and Malaria (DPDM) of the CDC, the United Nations World Food Programme (WFP), Nutrition International (NI), Global Alliance for Improved Nutrition (GAIN), and Hellen Keller International (HKI). Data collection and analysis Selection of studies Two review authors will independently screen the titles and abstracts of articles retrieved by each search to assess eligibility, as determined by the inclusion and exclusion criteria. Studies deemed eligible for inclusion by both review authors in the abstract screening phase will advance to the full-text screening phase, and full-text copies of all eligible papers will be retrieved. If full articles cannot be obtained, we will attempt to contact the authors to obtain further details of the studies. If such information is not obtained, we will classify the study as "awaiting assessment" until further information is published or made available to us. The same two review authors will independently assess the eligibility of full-text articles for inclusion in the systematic review. If any discrepancies occur between the studies selected by the two review authors, a third review author will provide arbitration. Each trial will be scrutinized to identify multiple publications from the same data set, and the justification for excluded trials will be documented. A PRISMA flow diagram of the study selection process will be presented to provide information on the number of records identified in the literature searches, the number of studies included and excluded, and the reasons for exclusion (Moher 2009). The list of excluded studies, along with their reasons for exclusion at the full-text screening phase, will also be created. Data extraction and management Two review authors will independently extract data for the final list of included studies using a standardized data specification form. Discrepancies observed between the data extracted by the two authors will be resolved by involving a third review author and reaching a consensus. Information will be extracted on study design components, baseline participant characteristics, intervention characteristics, and outcomes. For individually randomized trials, we will record the number of participants experiencing the event and the number analyzed in each treatment group or the effect estimate reported (e.g. risk ratio (RR)) for dichotomous outcome measures. For count data, we will record the number of events and the number of person-months of follow-up in each group. If the number of person-months is not reported, the product of the duration of follow-up and the number of children evaluated will be used to estimate this figure. We will calculate the rate ratio and standard error (SE) for each study. Zero events will be replaced by 0.5. We will extract both adjusted and unadjusted covariate incidence rate ratios if they are reported in the original studies. For continuous data, we will extract means (arithmetic or geometric) and a measure of variance (standard deviation (SD), SE, or confidence interval (CI)), percentage or mean change from baseline, and the numbers analyzed in each group. SDs will be computed from SEs or 95% CIs, assuming a normal distribution of the values. Haemoglobin values in g/dL will be calculated by multiplying haematocrit or packed cell volume values by 0.34, and studies reporting haemoglobin values in g/dL will be converted to g/L. In cluster-randomized trials, we will record the unit of randomization (e.g. household, compound, sector, or village), the number of clusters in the trial, and the average cluster size. The statistical methods used to analyze the trials will be documented, along with details describing whether these methods adjusted for clustering or other covariates. We plan to extract estimates of the intra-cluster correlation coefficient (ICC) for each outcome. Where results are adjusted for clustering, we will extract the treatment effect estimate and the SD or CI. If the results are not adjusted for clustering, we will extract the data reported. Assessment of risk of bias in included studies Two review authors (KSC, LFY) will independently assess the risk of bias for each included trial using the Cochrane 'Risk of bias 2' tool (RoB 2) for randomized studies (Sterne 2019). Judgements about the risk of bias of included studies will be made according to the recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). Disagreements will be resolved by discussion, or by involving a third review author. The interest of our review will be to assess the effect of assignment to the interventions at baseline. We will evaluate each primary outcome using the RoB2 tool. The five domains of the Cochrane RoB2 tool include the following. Bias arising from the randomization process. Bias due to deviations from intended interventions. Bias due to missing outcome data. Bias in measurement of the outcome. Bias in selection of the reported result. Each domain of the RoB2 tool comprises the following. A series of 'signalling' questions. A judgement about the risk of bias for the domain, facilitated by an algorithm that maps responses to the signalling questions to a proposed judgement. Free-text boxes to justify responses to the signalling questions and 'Risk of bias' judgements. An option to predict (and explain) the likely direction of bias. Responses to signalling questions elicit information relevant to an assessment of the risk of bias. These response options are as follows. Yes (may indicate either low or high risk of bias, depending on the most natural way to ask the question). Probably yes. Probably no. No. No information (may indicate no evidence of that problem or an absence of information leading to concerns about there being a problem). Based on the answer to the signalling question, a 'Risk of bias' judgement is assigned to each domain. These judgements include one of the following. High risk of bias Low risk of bias Some concerns To generate the risk of bias judgement for each domain in the randomized studies, we will use the Excel template, available at www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2. This file will be stored on a scientific data website, available to readers. Risk of bias in cluster randomized controlled trials For the cluster randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 1b (bias arising from the timing of identification or recruitment of participants) and its related signalling questions. To generate the risk of bias judgement for each domain in the cluster RCTs, we will use the Excel template available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-cluster-randomized-trials. This file will be stored on a scientific data website, available to readers. Risk of bias in cross-over randomized controlled trials For cross-over randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 2 (bias due to deviations from intended interventions), and Domain 3 (bias due to missing outcome data), and their respective signalling questions. To generate the risk of bias judgement for each domain in the cross-over RCTs, we will use the Excel template, available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-crossover-trials, for each risk of bias judgement of cross-over randomized studies. This file will be stored on a scientific data website, available to readers. Overall risk of bias The overall 'Risk of bias' judgement for each specific trial being assessed will be based on each domain-level judgement. The overall judgements include the following. Low risk of bias (the trial is judged to be at low risk of bias for all domains). Some concerns (the trial is judged to raise some concerns in at least one domain but is not judged to be at high risk of bias for any domain). High risk of bias (the trial is judged to be at high risk of bias in at least one domain, or is judged to have some concerns for multiple domains in a way that substantially lowers confidence in the result). The 'risk of bias' assessments will inform our GRADE evaluations of the certainty of evidence for our primary outcomes presented in the 'Summary of findings' tables and will also be used to inform the sensitivity analyses; (see Sensitivity analysis). If there is insufficient information in study reports to enable an assessment of the risk of bias, studies will be classified as "awaiting assessment" until further information is published or made available to us. Measures of treatment effect Dichotomous data For dichotomous data, we will present proportions and, for two-group comparisons, results as average RR or odds ratio (OR) with 95% CIs. Ordered categorical data Continuous data We will report results for continuous outcomes as the mean difference (MD) with 95% CIs, if outcomes are measured in the same way between trials. Where some studies have reported endpoint data and others have reported change-from-baseline data (with errors), we will combine these in the meta-analysis, if the outcomes were reported using the same scale. We will use the standardized mean difference (SMD), with 95% CIs, to combine trials that measured the same outcome but used different methods. If we do not find three or more studies for a pooled analysis, we will summarize the results in a narrative form. Unit of analysis issues Cluster-randomized trials We plan to combine results from both cluster-randomized and individually randomized studies, providing there is little heterogeneity between the studies. If the authors of cluster-randomized trials conducted their analyses at a different level from that of allocation, and they have not appropriately accounted for the cluster design in their analyses, we will calculate the trials' effective sample sizes to account for the effect of clustering in data. When one or more cluster-RCT reports RRs adjusted for clustering, we will compute cluster-adjusted SEs for the other trials. When none of the cluster-RCTs provide cluster-adjusted RRs, we will adjust the sample size for clustering. We will divide, by the estimated design effects (DE), the number of events and number evaluated for dichotomous outcomes and the number evaluated for continuous outcomes, where DE = 1 + ((average cluster size 1) * ICC). The derivation of the estimated ICCs and DEs will be reported. We will utilize the intra-cluster correlation coefficient (ICC), derived from the trial (if available), or from another source (e.g., using the ICCs derived from other, similar trials) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). If this approach is used, we will report it and undertake sensitivity analysis to investigate the effect of variations in ICC. Studies with more than two treatment groups If we identify studies with more than two intervention groups (multi-arm studies), where possible we will combine groups to create a single pair-wise comparison or use the methods set out in the Cochrane Handbook to avoid double counting study participants (Higgins 2021). For the subgroup analyses, when the control group was shared by two or more study arms, we will divide the control group (events and total population) over the number of relevant subgroups to avoid double counting the participants. Trials with several study arms can be included more than once for different comparisons. Cross-over trials From cross-over trials, we will consider the first period of measurement only and will analyze the results together with parallel-group studies. Multiple outcome events In several outcomes, a participant might experience more than one outcome event during the trial period. For all outcomes, we will extract the number of participants with at least one event. Dealing with missing data We will contact the trial authors if the available data are unclear, missing, or reported in a format that is different from the format needed. We aim to perform a 'per protocol' or 'as observed' analysis; otherwise, we will perform a complete case analysis. This means that for treatment failure, we will base the analyses on the participants who received treatment and the number of participants for which there was an inability to clear malarial parasitaemia or prevent recrudescence after administration of an antimalarial medicine reported in the studies. Assessment of heterogeneity Heterogeneity in the results of the trials will be assessed by visually examining the forest plot to detect non-overlapping CIs, using the Chi2 test of heterogeneity (where a P value of less than 0.1 indicates statistical significance) and the I2 statistic of inconsistency (with a value of greater than 50% denoting moderate levels of heterogeneity). When statistical heterogeneity is present, we will investigate the reasons for it, using subgroup analysis. Assessment of reporting biases We will construct a funnel plot to assess the effect of small studies for the main outcome (when including more than 10 trials). Data synthesis The primary analysis will include all eligible studies that provide data regardless of the overall risk of bias as assessed by the RoB2 tool. Analyses will be conducted using Review Manager 5.4 (Review Manager 2020). Cluster-RCTs will be included in the main analysis after adjustment for clustering (see the previous section on cluster-RCTs). The meta-analysis will be performed using the Mantel-Haenszel random-effects model or the generic inverse variance method (when adjustment for clustering is performed by adjusting SEs), as appropriate. Subgroup analysis and investigation of heterogeneity The overall risk of bias will not be used as the basis in conducting our subgroup analyses. However, where data are available, we plan to conduct the following subgroup analyses, independent of heterogeneity. Dose of folic acid supplementation: higher doses (4 mg or more, daily) versus lower doses (less than 4 mg, daily). Moderate-severe anaemia at baseline (mean haemoglobin of participants in a trial at baseline below 100 g/L for pregnant women and children aged six to 59 months, and below 110 g/L for other populations) versus normal at baseline (mean haemoglobin above 100 g/L for pregnant women and children aged six to 59 months, and above 110 g/L for other populations). Antimalarial drug resistance to parasite: known resistance versus no resistance versus unknown/mixed/unreported parasite resistance. Folate status at baseline: Deficient (e.g. RBC folate concentration of less than 305 nmol/L, or serum folate concentration of less than 7nmol/L) and Insufficient (e.g. RBC folate concentration from 305 to less than 906 nmol/L, or serum folate concentration from 7 to less than 25 nmol/L) versus Sufficient (e.g. RBC folate concentration above 906 nmol/L, or serum folate concentration above 25 nmol/L). Presence of anaemia at baseline: yes versus no. Mandatory fortification status: yes, versus no (voluntary or none). We will only use the primary outcomes in any subgroup analyses, and we will limit subgroup analyses to those outcomes for which three or more trials contributed data. Comparisons between subgroups will be performed using Review Manager 5.4 (Review Manager 2020). Sensitivity analysis We will perform a sensitivity analysis, using the risk of bias as a variable to explore the robustness of the findings in our primary outcomes. We will verify the behaviour of our estimators by adding and removing studies with a high risk of bias overall from the analysis. That is, studies with a low risk of bias versus studies with a high risk of bias. Summary of findings and assessment of the certainty of the evidence For the assessment across studies, we will use the GRADE approach, as outlined in (Schünemann 2021). We will use the five GRADE considerations (study limitations based on RoB2 judgements, consistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence as it relates to the studies which contribute data to the meta-analyses for the primary outcomes. The GRADEpro Guideline Development Tool (GRADEpro) will be used to import data from Review Manager 5.4 (Review Manager 2020) to create 'Summary of Findings' tables. The primary outcomes for the main comparison will be listed with estimates of relative effects, along with the number of participants and studies contributing data for those outcomes. These tables will provide outcome-specific information concerning the overall certainty of evidence from studies included in the comparison, the magnitude of the effect of the interventions examined, and the sum of available data on the outcomes we considered. We will include only primary outcomes in the summary of findings tables. For each individual outcome, two review authors (KSC, LFY) will independently assess the certainty of the evidence using the GRADE approach (Balshem 2011). For assessments of the overall certainty of evidence for each outcome that includes pooled data from included trials, we will downgrade the evidence from 'high certainty' by one level for serious (or by two for very serious) study limitations (risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates, or potential publication bias).

Crider K ，Williams J ，Qi YP ，Gutman J ，Yeung L ，Mai C ，Finkelstain J ，Mehta S ，Pons-Duran C ，Menéndez C ，Moraleda C ，Rogers L ，Daniels K ，Green P ... -  《Cochrane Database of Systematic Reviews》

Triple artemisinin-based combination therapies versus artemisinin-based combination therapies for uncomplicated Plasmodium falciparum malaria: a multicentre, open-label, randomised clinical trial.

Artemisinin and partner-drug resistance in Plasmodium falciparum are major threats to malaria control and elimination. Triple artemisinin-based combination therapies (TACTs), which combine existing co-formulated ACTs with a second partner drug that is slowly eliminated, might provide effective treatment and delay emergence of antimalarial drug resistance. In this multicentre, open-label, randomised trial, we recruited patients with uncomplicated P falciparum malaria at 18 hospitals and health clinics in eight countries. Eligible patients were aged 2-65 years, with acute, uncomplicated P falciparum malaria alone or mixed with non-falciparum species, and a temperature of 37·5°C or higher, or a history of fever in the past 24 h. Patients were randomly assigned (1:1) to one of two treatments using block randomisation, depending on their location: in Thailand, Cambodia, Vietnam, and Myanmar patients were assigned to either dihydroartemisinin-piperaquine or dihydroartemisinin-piperaquine plus mefloquine; at three sites in Cambodia they were assigned to either artesunate-mefloquine or dihydroartemisinin-piperaquine plus mefloquine; and in Laos, Myanmar, Bangladesh, India, and the Democratic Republic of the Congo they were assigned to either artemether-lumefantrine or artemether-lumefantrine plus amodiaquine. All drugs were administered orally and doses varied by drug combination and site. Patients were followed-up weekly for 42 days. The primary endpoint was efficacy, defined by 42-day PCR-corrected adequate clinical and parasitological response. Primary analysis was by intention to treat. A detailed assessment of safety and tolerability of the study drugs was done in all patients randomly assigned to treatment. This study is registered at ClinicalTrials.gov, NCT02453308, and is complete. Between Aug 7, 2015, and Feb 8, 2018, 1100 patients were given either dihydroartemisinin-piperaquine (183 [17%]), dihydroartemisinin-piperaquine plus mefloquine (269 [24%]), artesunate-mefloquine (73 [7%]), artemether-lumefantrine (289 [26%]), or artemether-lumefantrine plus amodiaquine (286 [26%]). The median age was 23 years (IQR 13 to 34) and 854 (78%) of 1100 patients were male. In Cambodia, Thailand, and Vietnam the 42-day PCR-corrected efficacy after dihydroartemisinin-piperaquine plus mefloquine was 98% (149 of 152; 95% CI 94 to 100) and after dihydroartemisinin-piperaquine was 48% (67 of 141; 95% CI 39 to 56; risk difference 51%, 95% CI 42 to 59; p<0·0001). Efficacy of dihydroartemisinin-piperaquine plus mefloquine in the three sites in Myanmar was 91% (42 of 46; 95% CI 79 to 98) versus 100% (42 of 42; 95% CI 92 to 100) after dihydroartemisinin-piperaquine (risk difference 9%, 95% CI 1 to 17; p=0·12). The 42-day PCR corrected efficacy of dihydroartemisinin-piperaquine plus mefloquine (96% [68 of 71; 95% CI 88 to 99]) was non-inferior to that of artesunate-mefloquine (95% [69 of 73; 95% CI 87 to 99]) in three sites in Cambodia (risk difference 1%; 95% CI -6 to 8; p=1·00). The overall 42-day PCR-corrected efficacy of artemether-lumefantrine plus amodiaquine (98% [281 of 286; 95% CI 97 to 99]) was similar to that of artemether-lumefantrine (97% [279 of 289; 95% CI 94 to 98]; risk difference 2%, 95% CI -1 to 4; p=0·30). Both TACTs were well tolerated, although early vomiting (within 1 h) was more frequent after dihydroartemisinin-piperaquine plus mefloquine (30 [3·8%] of 794) than after dihydroartemisinin-piperaquine (eight [1·5%] of 543; p=0·012). Vomiting after artemether-lumefantrine plus amodiaquine (22 [1·3%] of 1703) and artemether-lumefantrine (11 [0·6%] of 1721) was infrequent. Adding amodiaquine to artemether-lumefantrine extended the electrocardiogram corrected QT interval (mean increase at 52 h compared with baseline of 8·8 ms [SD 18·6] vs 0·9 ms [16·1]; p<0·01) but adding mefloquine to dihydroartemisinin-piperaquine did not (mean increase of 22·1 ms [SD 19·2] for dihydroartemisinin-piperaquine vs 20·8 ms [SD 17·8] for dihydroartemisinin-piperaquine plus mefloquine; p=0·50). Dihydroartemisinin-piperaquine plus mefloquine and artemether-lumefantrine plus amodiaquine TACTs are efficacious, well tolerated, and safe treatments of uncomplicated P falciparum malaria, including in areas with artemisinin and ACT partner-drug resistance. UK Department for International Development, Wellcome Trust, Bill & Melinda Gates Foundation, UK Medical Research Council, and US National Institutes of Health.

van der Pluijm RW ，Tripura R ，Hoglund RM ，Pyae Phyo A ，Lek D ，Ul Islam A ，Anvikar AR ，Satpathi P ，Satpathi S ，Behera PK ，Tripura A ，Baidya S ，Onyamboko M ，Chau NH ，Sovann Y ，Suon S ，Sreng S ，Mao S ，Oun S ，Yen S ，Amaratunga C ，Chutasmit K ，Saelow C ，Runcharern R ，Kaewmok W ，Hoa NT ，Thanh NV ，Hanboonkunupakarn B ，Callery JJ ，Mohanty AK ，Heaton J ，Thant M ，Gantait K ，Ghosh T ，Amato R ，Pearson RD ，Jacob CG ，Gonçalves S ，Mukaka M ，Waithira N ，Woodrow CJ ，Grobusch MP ，van Vugt M ，Fairhurst RM ，Cheah PY ，Peto TJ ，von Seidlein L ，Dhorda M ，Maude RJ ，Winterberg M ，Thuy-Nhien NT ，Kwiatkowski DP ，Imwong M ，Jittamala P ，Lin K ，Hlaing TM ，Chotivanich K ，Huy R ，Fanello C ，Ashley E ，Mayxay M ，Newton PN ，Hien TT ，Valecha N ，Smithuis F ，Pukrittayakamee S ，Faiz A ，Miotto O ，Tarning J ，Day NPJ ，White NJ ，Dondorp AM ，Tracking Resistance to Artemisinin Collaboration ... -  《-》

Intermittent preventive treatment with dihydroartemisinin-piperaquine and risk of malaria following cessation in young Ugandan children: a double-blind, randomised, controlled trial.

Intermittent preventive treatment (IPT) of malaria with dihydroartemisinin-piperaquine is a promising strategy for malaria prevention in young African children. However, the optimal dosing strategy is unclear and conflicting evidence exists regarding the risk of malaria after cessation of chemoprevention. We aimed to compare two dosing strategies of IPT with dihydroartemisinin-piperaquine in young Ugandan children, and to evaluate the risk of malaria after cessation of IPT. In this double-blind, randomised controlled phase 2 trial, women and their unborn children were recruited at Tororo District Hospital (Tororo, Uganda). Eligible participants were HIV-negative women aged 16 years or older with a viable pregnancy (gestational age 12-20 weeks). Women and their unborn children were randomly assigned (1:1:1:1) to one of four treatment groups, all receiving dihydroartemisinin-piperaquine, on the basis of the IPT intervention received by the woman during pregnancy: women every 8 weeks, children every 4 weeks; women every 4 weeks, children every 4 weeks; women every 8 weeks, children every 12 weeks; and women every 4 weeks, children every 12 weeks. Block randomisation was done by an independent investigator using a computer-generated randomisation list (permuted block sizes of six and 12). We analysed children on the basis of their random assignment to receive dihydroartemisinin-piperaquine (20 mg/160 mg tablets) once daily for 3 consecutive days every 4 weeks or 12 weeks. Children received study drugs from age 8 weeks to 24 months and were followed-up to age 36 months. Participants and investigators were masked to treatment allocation. The primary outcome was the incidence of symptomatic malaria during the intervention and following cessation of the intervention, adjusted for potential confounders. The primary outcome and safety were assessed in the modified intention-to-treat population, which included all children who reached 8 weeks of age and received at least one dose of study drug. This trial is registered with ClinicalTrials.gov, number NCT02163447. Between Oct 21, 2014, and May 18, 2015, 191 children were born, of whom 183 reached 8 weeks of age and received at least one dose of study drug and thus were included in the primary analysis (96 children in the 4-week group and 87 in the 12-week group). During the intervention, the incidence of symptomatic malaria was significantly lower among children treated every 4 weeks than children treated every 12 weeks; three episodes occurred among children treated every 4 weeks (incidence 0·018 episodes per person-year) compared with 61 episodes among children treated every 12 weeks (incidence 0·39 episodes per person-year; adjusted incidence rate ratio [aIRR] 0·041, 95% CI 0·012-0·150, p<0·0001). After cessation of IPT, children who had previously received dihydroartemisinin-piperaquine every 4 weeks had a lower incidence of symptomatic malaria than children who were treated every 12 weeks; 62 episodes occurred among children previously treated every 4 weeks (incidence 0·73 episodes per person-year) compared with 83 episodes among children treated every 12 weeks (incidence 1·1 episodes per person-year; aIRR 0·62, 0·40-0·95, p=0·028). In the 4-week group, 94 (98%) of 96 children had adverse events versus 87 (100%) of 87 children in the 12-week group. The most commonly reported adverse event was cough in both treatment groups (94 [98%] in the 4-week group vs 87 [100%] in the 12-week group). 16 children had severe adverse events (seven [7%] children in the 4-week group vs nine [10%] children in the 12-week group). No severe adverse events were thought to be related to study drug administration. One death occurred during the intervention (age 8 weeks to 24 months), which was due to respiratory failure unrelated to malaria. IPT with dihydroartemisinin-piperaquine given every 4 weeks was superior to treatment every 12 weeks for the prevention of malaria during childhood, and this protection was extended for up to 1 year after cessation of IPT. Eunice Kennedy Shriver National Institute of Child Health and Human Development.

Muhindo MK ，Jagannathan P ，Kakuru A ，Opira B ，Olwoch P ，Okiring J ，Nalugo N ，Clark TD ，Ruel T ，Charlebois E ，Feeney ME ，Havlir DV ，Dorsey G ，Kamya MR ... -  《-》

Pyronaridine-artesunate or dihydroartemisinin-piperaquine versus current first-line therapies for repeated treatment of uncomplicated malaria: a randomised, multicentre, open-label, longitudinal, controlled, phase 3b/4 trial.

Artemether-lumefantrine and artesunate-amodiaquine are used as first-line artemisinin-based combination therapies (ACTs) in west Africa. Pyronaridine-artesunate and dihydroartemisinin-piperaquine are potentially useful for diversification of ACTs in this region, but further safety and efficacy data are required on malaria retreatment. We did a randomised, multicentre, open-label, longitudinal, controlled phase 3b/4 clinical trial at seven tertiary centres in Burkina Faso, Guinea, and Mali. Eligible participants for first malaria episode and all retreatment episodes were adults and children aged 6 months and older with microscopically confirmed Plasmodium spp malaria (>0 to <200 000 parasites per μL of blood) and fever or history of fever in the previous 24 h. Individuals with severe or complicated malaria, an alanine aminotransferase concentration of more than twice the upper limit of normal, or a QTc greater than 450 ms were excluded. Using a randomisation list for each site, masked using sealed envelopes, participants were assigned to either pyronaridine-artesunate or dihydroartemisinin-piperaquine versus either artesunate-amodiaquine or artemether-lumefantrine. Block sizes were two or four if two treatments were allocated, and three or six if three treatments were allocated. Microscopists doing the parasitological assessments were masked to treatment allocation. All treatments were once-daily or twice-daily tablets or granules given orally and dosed by bodyweight over 3 days at the study centre. Patients were followed up as outpatients up to day 42, receiving clinical assessments on days 0, 1, 2, 3, 7, 14, 21, 28, 35, and 42. Two primary outcomes were compared for non-inferiority: the 2-year incidence rate of all microscopically confirmed, complicated and uncomplicated malaria episodes in patients in the intention-to-treat population (ITT; non-inferiority margin 20%); and adequate clinical and parasitological response (ACPR) in uncomplicated malaria across all episodes (unadjusted and PCR-adjusted for Plasmodium falciparum and unadjusted for other Plasmodium spp) in the per-protocol population on days 28 and 42 (non-inferiority margin 5%). Safety was assessed in all participants who received one dose of study drug. This study is registered at the Pan African Clinical Trials Registry (PACTR201105000286876). Between Oct 24, 2011, and Feb 1, 2016, we assigned 4710 eligible participants to the different treatment strategies: 1342 to pyronaridine-artesunate, 967 to artemether-lumefantrine, 1061 to artesunate-amodiaquine, and 1340 to dihydroartemisinin-piperaquine. The 2-year malaria incidence rate in the ITT population was non-inferior for pyronaridine-artesunate versus artemether-lumefantrine (1·77, 95% CI 1·63-1·93 vs 1·87, 1·72-2·03; rate ratio [RR] 1·05, 95% CI 0·94-1·17); and versus artesunate-amodiaquine (1·39, 95% CI 1·22-1·59 vs 1·35, 1·18-1·54; RR 0·97, 0·87-1·07). Similarly, this endpoint was non-inferior for dihydroartemisinin-piperaquine versus artemether-lumefantrine (1·16, 95% CI 1·01-1·34 vs 1·42 1·25-1·62; RR 1·22, 95% CI 1·06-1·41) and versus artesunate-amodiaquine (1·35, 1·21-1·51 vs 1·68, 1·51-1·88; RR 1·25, 1·02-1·50). For uncomplicated P falciparum malaria, PCR-adjusted ACPR was greater than 99·5% at day 28 and greater than 98·6% at day 42 for all ACTs; unadjusted ACPR was higher for pyronaridine-artesunate versus comparators at day 28 (96·9% vs 82·3% for artemether-lumefantrine and 95·6% vs 89·0% for artesunate-amodiaquine) and for dihydroartemisinin-piperaquine versus comparators (99·5% vs 81·6% for artemether-lumefantrine and 99·0% vs 89·0% for artesunate-amodiaquine). For non-falciparum species, unadjusted ACPR was greater than 98% for all study drugs at day 28 and at day 42 was greater than 83% except for artemether-lumefantrine against Plasmodium ovale (in ten [62·5%] of 16 patients) and against Plasmodium malariae (in nine [75·0%] of 12 patients). Nine deaths occurred during the study, none of which were related to the study treatment. Mostly mild transient elevations in transaminases occurred with pyronaridine-artesunate versus comparators, and mild QTcF prolongation with dihydroartemisinin-piperaquine versus comparators. Pyronaridine-artesunate and dihydroartemisinin-piperaquine treatment and retreatment of malaria were well tolerated with efficacy that was non-inferior to first-line ACTs. Greater access to these efficacious treatments in west Africa is justified. The European and Developing Countries Clinical Trial Partnership, Medicines for Malaria Venture (Geneva, Switzerland), the UK Medical Research Council, the Swedish International Development Cooperation Agency, German Ministry for Education and Research, University Claude Bernard (Lyon, France), University of Science, Techniques and Technologies of Bamako (Bamako, Mali), the Centre National de Recherche et de Formation sur le Paludisme (Burkina Faso), Institut de Recherche en Sciences de la Santé (Bobo-Dioulasso, Burkina Faso), and Centre National de Formation et de Recherche en Santé Rurale (Republic of Guinea).

West African Network for Clinical Trials of Antimalarial Drugs (WANECAM) 《-》