Malaria is a sickness caused by a germ that can get into a person's body when a mosquito bites them. It can cause fever, headache, body aches and weakness. It can even cause death, especially in children. When malaria is treated with the appropriate medicine(s), it can be cured completely. The purpose of this study is to find out if it is better to use chloroquine alone or in combination with another drug to most effectively treat malaria. About 640 children with malaria, aged 6 months to 5 years of age, from the Blantyre Malaria Project Research Clinic at the Ndirande Health Center in Malawi will be in the study. They will be treated with either chloroquine alone or a combination of chloroquine plus another medication (azithromycin or artesunate or atovaquone-proguanil) every time they get malaria for a year. Blood samples will be collected and tested at least every 4 weeks. Participants will be involved in the study for 1 year.
Combination therapy is becoming the mainstay of malaria treatment. In general, the goal of combination therapy is to treat resistant infections successfully and to prevent the emergence and spread of resistance. The antimalarial combination therapies currently in use were not designed based on optimal pairing of drugs to deter the development and spread of parasite resistance to the individual partner drugs in settings of high malaria transmission. Careful studies are needed to identify the pharmacokinetic and pharmacodynamic properties of drug combinations that will deter resistance and prolong the useful therapeutic life of the next generation of antimalarial drug combinations. Current in vivo methods for measuring antimalarial drug efficacy in high-transmission areas use a 14 or 28-day follow-up period, but a single episode study misses several critical factors in assessing the efficacy and impact of antimalarial treatment. When follow-up is extended beyond 28 days, more cases of apparent resistance or treatment failure are found. Single-episode studies cannot assess the impact of therapy on the incidence of malaria over time. These limitations of standard in vivo studies have led the investigators to advocate longitudinal studies of drug efficacy. In addition to measuring efficacy of individual treatments, longitudinal studies measure sustained efficacy with repeated use of the same regimen over time, a scenario that more accurately reflects the real-life use of anti-malarial medication. The primary outcome of interest is the incidence of malaria episodes, as well as the secondary outcomes of anemia and severe malaria, are all highly relevant to public health policy-makers, as they reflect not only the burden of disease but also the utilization of health resources. Longitudinal studies also permit assessment of how pharmacokinetic properties of drugs affect the incidence of treatment episodes. This is a randomized, open-label, longitudinal drug efficacy trial. Participants will include 640 children, aged 6 months to 5 years, who are found to have uncomplicated malaria at the Blantyre Malaria Project Research Clinic at the Ndirande Health Centre in Blantyre, Malawi. After enrollment, participants will be randomized to one of four treatment arms: chloroquine alone or chloroquine in combination with artesunate, atovaquone-proguanil (AP), or azithromycin. The treatment outcome will be assessed through a standard 28-day efficacy study. Participants will subsequently be evaluated every 4 weeks and encouraged to return to the study clinic any time they are ill during the course of one year. If a new episode of uncomplicated malaria is diagnosed, the participant will receive the same therapy as assigned on enrollment. Polymerase chain reaction-corrected 28-day efficacy will be evaluated for each treatment episode. The primary study objective is to compare annual incidence of malaria clinical episodes. Secondary objectives are to: assess anti-malarial drug efficacy at first administration, by treatment arm; assess anti-malarial drug efficacy during subsequent episodes of malaria, by treatment arm; measure prevalence of chloroquine resistant parasites during the trial, by treatment arm; assess effect of each treatment arm on anemia at the end of study participation; assess safety of these drugs with repeated use; determine the chloroquine blood levels at which chloroquine sensitive and resistant parasites are able to cause infection; assess the effect of population movements on the risk of malaria infection; and assess the spatial patterns and the environmental determinants of malaria infection. Participants will be involved in study rela
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
640
Atovaquone-proguanil: once a day for 3 days, Pediatric tablet: 62.5 mg/25 mg, Full strength tablet: 250 mg/100 mg
Artesunate: 4mg/kg once a day for 3 days, 50 mg tablet
Azithromycin 30 mg/kg once a day for 3 days, 200 mg/5cc suspension
Chloroquine: 10 mg/kg on days 0 and 1, 5 mg/kg/day on day 2, 100 mg tablet.
Blantyre Malaria Project - Ndirande Health Centre
Blantyre, Blantyre, Malawi
Number of Clinical Malaria Episodes Per Year of Follow-up
Clinical malaria episode was defined as at least one symptom of malaria and a positive malaria smear. The number of clinical malaria episodes (not including the initial malaria episode) reported by participants during follow up is presented as the number per Person Years at Risk (PYAR).
Time frame: 1 year
Number of Participants With Day 28 Adequate Clinical and Parasitologic Response in Each Treatment Arm
Adequate clinical and parasitologic response (ACPR) was defined as the absence of parasitemia at Day 28 and without previously meeting any of the criteria of early treatment or late clinical failure.
Time frame: Day 28 of initial malaria episode (Episode 0)
Number of Participants With Day 28 Adequate Clinical and Parasitologic Response in Each Treatment Arm
Adequate clinical and parasitologic response (ACPR) was defined as the absence of parasitemia at Day 28 and without previously meeting any of the criteria of early treatment or late clinical failure.
Time frame: Day 28 of first subsequent malaria episode (Episode 1)
Number of Participants With Day 28 Adequate Clinical and Parasitologic Response in Each Treatment Arm
Adequate clinical and parasitologic response (ACPR) was defined as the absence of parasitemia at Day 28 and without previously meeting any of the criteria of early treatment or late clinical failure.
Time frame: Day 28 of second subsequent malaria episode (Episode 2)
Number of Participants With Day 28 Adequate Clinical and Parasitologic Response in Each Treatment Arm
Adequate clinical and parasitologic response (ACPR) was defined as the absence of parasitemia at Day 28 and without previously meeting any of the criteria of early treatment or late clinical failure.
Time frame: Day 28 of third subsequent malaria episode (Episode 3)
Number of Participants With Day 28 Adequate Clinical and Parasitologic Response in Each Treatment Arm
Adequate clinical and parasitologic response (ACPR) was defined as the absence of parasitemia at Day 28 and without previously meeting any of the criteria of early treatment or late clinical failure.
Time frame: Day 28 of fourth subsequent malaria episode (Episode 4)
Number of Cases of Severe Malaria in Each Treatment Arm
A case of severe malaria included one or more of the following: Hemoglobin ≤5 g/dL; prostration; respiratory distress; bleeding; recent seizures, coma or obtundation (Blantyre coma score \< 5); inability to drink, or persistent vomiting. All cases were then adjudicated by a panel of investigators prior to analysis.
Time frame: 1 Year
Mean Hemoglobin at the Last Study Visit in Each Treatment Arm for the Age Group of Participants 3 Years of Age or Younger.
Hemoglobin values were assessed from blood collected at the last study visit at one year after enrollment. Group means are stratified by participants 3 years of age and under, and over 3 to 5 years of age.
Time frame: 1 year
Mean Hemoglobin at the Last Study Visit in Each Treatment Arm for the Age Group of Participants Greater Than 3 Years to 5 Years of Age.
Hemoglobin values were assessed from blood collected at the last study visit at one year after enrollment. Group means are stratified by participants 3 years of age and under, and over 3 to 5 years of age.
Time frame: 1 year
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 0 of initial malaria episode (Episode 0)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 14 of initial malaria episode (Episode 0)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 0 of first subsequent malaria episode (Episode 1)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 14 of first subsequent malaria episode (Episode 1)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 0 of second subsequent malaria episode (Episode 2)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 14 of second subsequent malaria episode (Episode 2)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 0 of third subsequent malaria episode (Episode 3)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 14 of third subsequent malaria episode (Episode 3)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 0 of fourth subsequent malaria episode (Episode 4)
Mean Creatinine in Each Treatment Arm (Renal Function)
Creatine values were assessed from blood draws at Day 0 and Day 14 of each malaria episode. Samples that were below the limit of detection were reported as 44.2 micromoles/liter, equivalent to the lower limit of detection.
Time frame: Day 14 of fourth subsequent malaria episode (Episode 4)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 0 of initial malaria episode (Episode 0)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 14 of initial malaria episode (Episode 0)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 0 of first subsequent malaria episode (Episode 1)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 14 of first subsequent malaria episode (Episode 1)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 0 of second subsequent malaria episode (Episode 2)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 14 of second subsequent malaria episode (Episode 2)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 0 of third subsequent malaria episode (Episode 3)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 14 of third subsequent malaria episode (Episode 3)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 0 of fourth subsequent malaria episode (Episode 4)
Mean Alanine Transaminase (ALT) in Each Treatment Arm (Hepatic Function)
ALT values were assessed from blood draws at Day 0 and Day 14 of each malaria episode.
Time frame: Day 14 of fourth subsequent malaria episode (Episode 4)
Number of Participants in Each Treatment Arm Who Change From "Normal" to "Abnormal" on Any Questions of the Neurological Examination
A basic age-appropriate neurological examination was conducted on Day 28 of each malaria illness episode and also at Days 112 and 224, and at 1 year. Subjects were were counted as a "change from 'normal' to 'abnormal' " if they had the 'normal' (or not-applicable) response for the initial day 28 exam and an 'abnormal' response at their last exam. If a subject did not have an exam at 1 year then the last available exam that was not associated with an illness episode (either Day 112 or 224) was used.
Time frame: 1 Year
Number of Participants Infected With Parasites With the Mutation Pfcrt 76T on Day 0 of the Initial Episode of Malaria
The presence of parasites with the mutation pfCRT 76T was measured with filter paper specimens collected at the time of enrollment and with successful parasite DNA amplification using pyrosequencing.
Time frame: Day 0 of initial episode of malaria
Number of Participants Infected With Parasites With the Mutation Pfcrt 76T at Recrudescent Episodes of Malaria
Participants were enrolled in the study at the time of the initial episode of malaria. If the participant presented with a subsequent episode of malaria at any time during the one year of follow-up, the presence of parasites with the mutation pfCRT 76T was measured with filter paper specimens collected at the time of enrollment and with successful parasite DNA amplification using pyrosequencing.
Time frame: Recrudescent episodes of malaria within one year of enrollment
Number of Participants With New and Recrudescent Malaria Infections After Initial Treatment
Participants were enrolled at the time of initial malaria episode and treated. Subsequent to treatment, subjects were monitored for the occurrence of new and recrudescent malaria infections, which were distinguished by analysis of the infecting parasites using merozoite surface protein-2 polymorphic gene length variation.
Time frame: 28 days to 1 year
Number of Participants With New and Recrudescent Infections After Subsequent New Episodes
Participants were enrolled at the time of initial malaria episode and treated. Subsequent to treatment, participants who subsequently suffered new malaria episodes were monitored for the additional occurrence of new and recrudescent malaria infections, which were distinguished by analysis of the infecting parasites using merozoite surface protein-2 polymorphic gene length variation.
Time frame: Day 28 to 1 year
Time to First Malaria Episode in Participants Who Travelled and Slept Outside the City Versus Those Who Did Not Travel and Sleep Outside the City.
The cumulative hazard of having a malaria attack within one year for those participants who travelled and slept in rural areas (outside the city) versus those who did not was calculated and is presented as a life table to display the number of subjects at risk, the number with first clinical episode and the number censored at each time point. Participants are right-censored at the time of first malaria episode. Participants who did not develop malaria during follow-up or were lost to follow-up were censored at the time of their last visit.
Time frame: Days 0 - 420
Nearest Neighbor Index as a Measure of Spatial Pattern of the Distribution of Malaria Cases in Ndirande
The Global Positioning System (GPS) was used to establish the coordinates of participants' homes. The distribution of these coordinates was analyzed for evidence of clustering, or occurring closer together than would be expected on the basis of chance. Nearest Neighbor Index is a ratio of the observed mean distance over the expected mean distance. If the index is less than 1, the pattern exhibits clustering. If the index is greater than 1, the trend is toward dispersion.
Time frame: 1 year
Pharmacokinetics of Chloroquine Represented by Time of Maximal Concentration (Tmax) and Chloroquine Half-life
1727 non-zero concentration measurements from 479 participants were pooled and used for population pharmacokinetic modeling in Monolix413s. Compartmental population pharmacokinetic modeling was used due to highly sparse data. The model was parameterized in terms of absorption rate constant for chloroquine (Ka), apparent clearance for chloroquine (CL/F, with F as the unknown oral bioavailability), apparent volume of distribution of the central and peripheral compartments for chloroquine (Vd/F), and the inter-compartmental clearance for chloroquine (Q/F). Only these primary population pharmacokinetic parameters could be estimated using the type of data collected. The best-fit population PK model was then used to estimate individual parameter estimates to derive Tmax and half-life.
Time frame: Day 0 - Day 28
Pharmacokinetics of Chloroquine Represented by Maximum Concentration (Cmax)
1727 non-zero concentration measurements from 479 participants were pooled and used for population pharmacokinetic modeling in Monolix413s. Compartmental population pharmacokinetic modeling was used due to highly sparse data. The model was parameterized in terms of absorption rate constant for chloroquine (Ka), apparent clearance for chloroquine (CL/F, with F as the unknown oral bioavailability), apparent volume of distribution of the central and peripheral compartments for chloroquine (Vd/F), and the inter-compartmental clearance for chloroquine (Q/F). Only these primary population pharmacokinetic parameters could be estimated using the type of data collected. The best-fit population PK model was then used to estimate individual parameter estimates to derive Cmax in nanograms per milliliter (ng/mL).
Time frame: Day 0 - Day 28
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