Background: Several artemisinin-based combination therapies (ACT) are available to treat uncomplicated malaria in Africa. The present study aimed to assess the ranking of their efficacy and tolerance.
Methods: A database of randomized controlled trials was retrieved from published papers. Network meta-analysis was used to compare efficacy on day 28 and day 42 after initiation of treatment. Age covariate effect on treatment outcome was assessed, and a modeling approach to reduce heterogeneity among trials was evaluated under the hypothesis of consistency in a meta-regression. Safety and adverse events were compared among different ACTs. A Bayesian analysis was performed to implement the consistency models using WinBUGS software. The results were compared to those of the frequentist approach using the R software.
Results: Eighty-one articles, in which a total of 15 different ACTs were tested in more than 36,000 patients, were included. On day 28, dihydroartemisinin-piperaquine (DHPP) was more effective than artemether-lumefantrine (AL) before (odds ratio [OR], 1.83; 95% confidence interval [CI], 1.31 - 2.56) and after age-covariate adjustment (OR, 1.70; 95% CI, 1.20 - 2.43). The result was similar on day 42. DHPP occupied the top rank. The risk of having cough, diarrhoea or headache post-treatment was significantly lower with DHPP than AL. Artesunate-mefloquine (ASMQ) was associated with a significantly lower prevalence of vomiting or nausea (OR, 0.80; 95% CI, 0.48 - 1.30) and headache (OR, 0.53; 95% CI, 0.40 - 0.68) compared to AL. On the contrary, vomiting and nausea occurred more frequently after fixed-dose artesunate-amodiaquine formulation (ASAQf) than with AL (OR, 1.45; 95% CI, 1.18 - 1.78). The risk of anaemia was higher with ASAQf and co-blistered artesunate-amodiaquine (ASAQc) than with AL. There was no significant difference in risk of anaemia (
P > 0.05) between AL and different formulations of ASAQ.
Conclusions: Based on the available evidence, this study demonstrated the superiority of DHPP, followed by AL, among currently recommended ACTs in terms of efficacy and tolerance. Network meta-analysis could be an alternative analytical tool but needs more data input from therapeutic efficacy studies. The determination of the best available therapy requires data triangulation and data science.
Since the World Health Organization (WHO) recommended artemisinin-based combination therapy (ACT) as the first-line treatment of uncomplicated Plasmodium falciparum malaria, there has been a growing interest in field-based randomized controlled trials. Most African countries adopted this drug policy during the 2000s, resulting in a large amount of published evidence-based data on the efficacy, tolerability, and safety of these antimalarial drugs. Antimalarial drug efficacy is usually assessed in therapeutic efficacy studies based on the standardized WHO protocol, initially published in 1994 and updated in 1996, 2003, and 2009 [1] [2] [3] [4]. The amount of data being generated in the field is ever-increasing, and the results of many, but not all studies, have been published. Because of this growth of evidence-based data, novel methods to collect, analyze, and summarize clinical data to identify the best available therapy have become indispensable.
Systematic reviews and meta-analyses have become a common approach to extracting relevant information from therapeutic efficacy studies based on either individual patient data or study level data (i.e., aggregate data) [5] [6] [7] [8]. However, analysis requires an identification of the event of interest and study of effect modifiers. The event of interest can be both a good or poor outcome (i.e., treatment success or treatment failure) and a time-fixed or time-dependent variable. The use of network meta-analysis (NMA), a meta-regression analysis with dummy variables for treatments that can be used to analyze effect within covariate levels, is advocated by some authors [6] [7].
WHO-recommended ACTs include the following drug combinations: artesunate-amodiaquine (ASAQ), artesunate-sulfadoxine-pyrimethamine (ASSP), artemether-lumefantrine (AL), dihydroartemisinin-piperaquine (DHPP), and artesunate-mefloquine (ASMQ) [9]. The sixth combination, artesunate-pyronaridine (ASPY), has undergone field evaluation, and it was recently added to this list of WHO-approved ACTs [9] [10] [11]. There are also several non-WHO-recommended ACTs, including artesunate-sulfamethoxypyrazine-pyrimethamine (ASSMP), dihydroartemisinin-piperaquine-trimethoprim triple combination (DHPPT), artesunate-atovaquone-proguanil (ASATPG), artemisinin-naphtoquine (ASNAPH), artesunate-amodiaquine-chlorpheniramine (ASAQCPH), and arterolane maleate-piperaquine phosphate (AMPP), that are used in some countries to treat P. falciparum malaria [12] [13] [14]. In addition, a non-ACT combination, amodiaquine-sulfadoxine-pyrimethamine (AQSP), had been deployed during the transition period in the 2000s before the full adoption of ACTs in many African countries, and its efficacy had been compared to that of ACTs in randomized clinical studies [15] [16] [17].
The doses of ACT are variable, and for ASAQ, several different doses and formulations have been used. Most ACTs are administered as a single daily dose for three days. The fixed-dose AL is an outstanding exception, requiring twice daily doses for three days (a total of six doses administered over three days, with an 8-hr interval between the first and second dose). ASAQ is administered as a once daily fixed-dose combination (FDC) or twice daily doses for three days [18] [19]. ASAQ dose varies due to the availability of three formulations: non-fixed dose combinations (NFDC), which may be either loose NFDC (ASAQl) or co-blistered NFDC (ASAQc), and fixed-dose combinations (ASAQf) [20]. The dose effect should be taken into consideration in the comparison of antimalarial drugs.
AL, ASAQ, and DHPP have been found to be safe for use in children, but a non-negligible number of adverse events have been associated with the intake of ACT [5]. In an earlier work [21], DHPP was identified as the best available ACT to treat uncomplicated falciparum malaria in terms of efficacy and safety. At the point where the public health community needs a comprehensive, reliable and timely information to slow the emergence of antimalarial drug resistance and maintain the efficacy of antimalarial treatments, there is a need for an update on the efficacy, safety, and tolerability of available ACTs and a strategy to reduce heterogeneity in the evaluation of treatment by considering baseline characteristics of the study. Given an increasing number of ACTs and published studies on their safety profile in children, the aim of the present study was to investigate the modifiers of treatment effect by analyzing treatment by covariate interactions and adverse events associated with each ACT.
2. Methods2.1. Data Collection and Extraction of Effect Modifiers
Data were extracted from a recent database of randomized clinical trials involving children and adults (excluding pregnant women) with uncomplicated falciparum malaria [21]. In that previous work, several articles were selected, involving 13 ACT drug regimens to treat approximately 36,000 patients in children and adults in sub-Saharan African countries. Indeed, a new search using the same criteria as the previous work [21] was performed between August 2017 (the month of the publication of the previous work) and December 2017, and more recent studies published between 2017 and December 2020 were added. For the present study, the completed database was re-assessed, and studies that evaluated adverse events and polymerase chain reaction (PCR)-corrected efficacy on days 28 and 42 were retrieved. The primary outcome considered in the present study was the PCR-corrected rate of adequate clinical and parasitological response (ACPR). Secondary outcomes were fever clearance, parasite clearance, gametocyte carriage on days 0, 7, or 14, and change in haemoglobin from baseline values on day 0 (minimum 28-day follow-up). Adverse events that were assessed (any time after drug administration) included headache, dizziness, palpitation, anorexia, abdominal pain, vomiting, nausea, diarrhoea, fatigue or weakness, anaemia, drowsiness, asthenia, cough, pruritus, and rash. Serious drug-related adverse effects were also included.
The intention-to-treat approach (ITT) was used to extract the number of participants randomized and assigned to each treatment group with the aim of restoring the integrity of the randomization process. For the dichotomous outcome of both efficacy (i.e., treatment success or treatment failure) and safety (the presence or absence of adverse events), the number of participants who experienced the event on each follow-up day up to 28 days was evaluated. Covariates were age, parasite density, weight, and baseline body temperature. Age was standardized, and parasite density was transformed to logarithmic values to derive normally distributed covariate values. The effects of different doses and formulations of ASAQ and adverse events for each treatment were also evaluated. Randomized clinical trials analyzed in this work reported the study type (multi-centre, randomized, open-label), with details and outcome of all randomized participants (complete follow-up, withdrawal, lost-to-follow-up, and exclusion).
2.2. Antimalarial Drugs
Drugs were assigned numbers from 1 to 13 as in our previous study [21]. With two additional formulations of ASAQ found in the database, the numbering for drug combinations was extended to 15, i.e., AL was assigned treatment number 1, which represents the common comparator drug, 2 = AQSP, 3 = ASAQc, 4 = ASAQf, 5 = ASAQl, 6 = ASAQCPH, 7 = ASATPG, 8 = ASCD, 9 = ASMQ, 10 = ASNAPH, 11 = ASPY, 12 = ASSMP, 13 = ASSP, 14 = DHPP, and 15 = DHPPT.
2.3. Measures of Treatment Effect and Statistical Analysis
The primary outcome, i.e., the proportion of ACPR, was combined and presented using the OR in the ITT population. Direct and indirect comparisons were extracted. The global statistical modeling based on a randomly mixed effect model was presented in some research works [21] [22]. In addition to that model, a meta-regression analysis was developed using the existing code, with age covariate to assess the change in efficacy of the different interventions. All analyses were based on a random effect model to account for different end-point evaluations. Heterogeneity was explored using I2 statistics and test of inconsistency. To account for heterogeneity in the patient populations, a dummy random variable was defined as 1 if the patient was a child less than 15 years and 0 for other patient populations. In addition, meta-regression was used to assess the changes in treatment effect with the same heterogeneity variance assumed for every comparison and the effect of covariates on treatment effect. The age covariate was used to fit an NMA-regression model. Studies with missing covariates were excluded. AL was the main comparator drug.
2.4. Choice of Prior Probability Distribution
All treatment effect was given uniform priors between −10 and 10. This strategy avoids numerical “traps” encountered when running the model with a uniform prior between 0 and 20 [23]. Prior age covariate effect distribution was given a flat normal distribution N (0, 10−5). Vague prior between-trial standard deviation was a uniform distribution between 0 and 20.
2.5. Treatment Ranking
To measure how the treatment was comparatively better than another treatment, P-scores were used and averaged over different treatments [24]. The method was found to be comparable with the surface under the cumulative ranking curve (SUCRA) [25]. All analysis was carried out using WinBUGS and the R package net meta [26].
3. Results3.1. Description of Included Studies
Table 1 presents the number of studies for each treatment arm and the number of comparisons between different ACTs and the comparator drug AL on days 28, 42, and 63. Of 85 studies, 81 assessed the efficacy on day 28 (Supplementary Table 1), 2 studies on day 35 [14] [15] (Supplementary Table 1), 4 studies on day 42 only (Supplementary Table 1), 2 studies on day 28 and 63 (Supplementary Table 1), and 20 studies on day 28 and day 42 (Supplementary Table 1). Among these studies, the efficacy of different doses of ASAQ was assessed in 17 studies. A total of 71 studies had an age covariate available with a 28-day endpoint. The studies that reported adverse events (n = 43) are summarized for each treatment in Supplementary Table 2 and Supplementary Table 3.
Description of the number of studies for each treatment arm and adverse events
Treatments
No. of studies with adverse events*
Total randomized sample
No. of studies with adverse events at each time point
No. of studies with PCR-corrected ACPR**
No. studies/No. of patients with PCR corrected ACPR (total assessed)
Day 28
Day 42
Total randomized participants with ACPR on Day 28
Day 28
Total randomized participants on Day 42
Day 42
AQSP
5
793
4
5
10
2623
10/1684
1/439
AL
41
8979
38
12
63
13,435
63/11,546
20/3420
ASAQc
5
1226
3
2
5
1441
3/1185
2/282
ASAQCPH
1
54
1
1
1
54
1/47
ASAQf
10
2478
9
4
17
4225
17/3832
1085
6/856
ASAQl
9
929
8
1
22
2857
22/2407
238
2/199
ASATPG
1
100
1
0
1
70
1/60
0
0
ASCD
3
1505
2
0
3
677
1/521
359
1/302
ASMQ
3
552
2
1
5
683
5/646
302
2/204
ASPY
1
355
1
0
1
673
628
565
673
ASSMP
3
837
3
0
4
1087
4/1022
ASSP
2
750
2
0
14
1976
13/1790
135
1/112
DHPP
15
4938
14
7
24
6972
24/5655
2400
9/2111
DHPPT
1
212
1
0
1
212
204
Zero or empty cells means that there were no studies evaluated at that time point. *43 studies reported adverse events. **81 studies assessed the efficacy of day 28.
Multiple comparison of therapeutic efficacy among various ACTs and a non-ACT combination on day 28
WinBUGS
R
With age covariate n = 71 studies
AL as the comparator
Without age covariate; n = 81 studies
ASAQf as the comparator
Without age covariate; n = 81 studies
ASAQl as the comparator
OR; 95% credibility intervals
OR; 95% credibility intervals
OR; 95% credibility intervals
AQSP
0.9 [0.5; 1.6]
AQSP
0.64 [0.34; 1.21]
AQSP
0.99 [0.54; 1.80]
ASAQc
1.03 [0.48; 2.23]
AQASc
0.66 [0.26; 1.64]
AQASc
1.02 [0.41; 2.50]
ASAQf
1.37 [0.9; 2.08]
AQASl
0.65 [0.37; 1.12]
AQASf
1.53 [0.88; 2.67]
ASAQl
0.96 [0.64; 1.44]
AL
0.77 [0.51; 1.16]
AL
1.18 [0.80; 1.76]
ASAQCPH
1.51 [0.33; 6.81]
ASAQCPH
1.01 [0.20; 5.33]
ASAQCPH
1.56 [0.31; 7.79]
ASATPG
3.24 [0.54; 19.38]
ASATPG
2.04 [0.30; 14.05]
ASATPG
3.15 [0.49; 19.95]
ASCD
0.7 [0.36; 1.36]
ASCD
0.61 [0.27; 1.37]
ASCD
0.94 [0.41; 2.11]
ASMQ
1.25 [0.52; 2.98]
ASMQ
0.90 [0.37; 2.14]
ASMQ
1.37 [0.57; 3.27]
ASNAPH
0.01 [2 × 10−5; 1.38]
ASNAPH
0.01 [0.004; 2.32]
ASNAPH
0.14 [0.0061; 3.57]
ASPY
1.9 [0.66; 5.45]
ASPY
1.30 [0.42; 3.93]
ASPY
1.98 [0.65; 6.03]
ASSMP
1.4 [0.55; 3.57]
ASSMP
0.96 [0.41; 2.24]
ASSMP
1.48 [0.60; 3.66]
ASSP
1.03 [0.61; 1.74]
ASSP
0.69 [0.36; 1.30]
ASSP
1.06 [0.63; 1.78]
DHPP
1.88 [1.27; 2.78]
DHPP
1.25 [0.75; 2.06]
DHPP
1.92 [1.16; 3.17]
DHPPT
1.99 [0.35; 11.37]
DHPPT
1.10 [0.18; 6.74]
DHPPT
1.70 [0.28; 10.34]
81 studies met the criterion of 28-day PCR-corrected ACPR. The comparator was varied to enable comparison with different ASAQ doses.
Assessment of the efficacy of WHO-recommended ACTs on day 42
ACT
Estimate of therapeutic efficacy
Odds ratio
95% confidence interval
P-value
AL
1.00
[0.34; 3.41]
(comparator drug)
AQSP*
0.78
[0.36; 1.70]
0.53
ASAQ
0.94
[0.587; 1.489]
0.77
ASMQ
1.07
[0.34; 3.41]
0.90
ASPY
1.42
[0.64; 3.12]
0.39
ASSP
1.78
[0.49; 6.48]
0.38
DHPP
1.65
[1.06; 2.56]
0.02**
Twenty studies were combined, and comparison was made with other treatments, using AL as the comparator drug. *AQSP, a non-WHO-recommended, non-ACT combination, was included for comparison since several African countries have adopted it during the transition period in the 2000s before full implementation of ACT-based antimalarial drug policy. Quantifying heterogeneity/inconsistency: tau2 = 0.2940; tau = 0.5422; I2 = 76.3% [62.3%; 85.1%]. **Statistically significant (P < 0.05).
3.2. Analysis of the Efficacy Trials on Day 28
The updated malaria network evidence illustrated in Figure 1 shows different drug combinations, including ASAQ with different dosages, which were compared with each other. The comparison between different ACTs and AL in the presence of age covariate, as well as the comparison of different doses of ASAQ in the absence of age covariate, is summarized in Table 2. DHPP was more effective than AL in the presence of age covariate (OR = 1.88, 95% confidence interval [CI], 1.27 - 2.78). In the absence of age covariate with ASAQl as the comparator, DHPP was also more effective (OR = 1.92, 95% CI, 1.16 - 3.17). On the other hand, given either ASAQl or ASAQf as the comparator, a non-statistical difference (P > 0.05) was found between different ACTs.
3.3. Clinical Efficacy on Day 42
A total of 20 studies assessed clinical efficacy on day 42 with two or more of the following combinations: AQSP, ASAQ, AL, ASMQ, ASPY, ASSP, and DHPP (Table 3). ASCD was excluded from analysis because this ACT is not recommended, and its production had ceased due to serious adverse effects associated with dapsone in African patients with glucose-6-phosphate dehydrogenase deficiency. By setting AL as the comparator, DHPP was 1.6-fold more efficacious than AL (OR = 1.65; 95% CI, 1.06 - 2.56; P < 0.05) (Table 3). On day 42, the difference in therapeutic efficacy between AL and ACTs other than DHPP was not statistically significant (P > 0.05).
3.4. Secondary Outcome Results
The safety of AL, as compared with other ACTs, was assessed. Adverse events were extracted from 43 studies. Thirty-eight of 81 studies did not report drug tolerance. The frequency of adverse effects and studies in which they were assessed are presented in Supplementary Table 3. The adverse events reported in different studies are summarized in Table 4 and Table 5. Adverse events were heterogeneous among studies. The common adverse events (≥1/100 and <1/10) among patients receiving AL included the following: anorexia, vomiting, anaemia, diarrhoea, vomiting, and abdominal pain (Table 4). Cough was the only very commonly reported adverse events (≥1/10) of AL and DHPP. The respiratory and gastrointestinal tracts were the most commonly affected organs, constituting 35% and 33% of all reported adverse events in AL-treated children, respectively. The number of events was very low with new alternative drugs (Table 4), while adverse events were more prevalent with ASSMP (Table 5).
Organ system classification and frequency of adverse events during follow-up for WHO-recommended therapies from 43 studies
Organ system
AL
DHPP
ASAQc
ASAQf
ASAQl
AQSP†
ASMQ
ASSP
Cardiovascular
Palpitation
6 (0.7)*
3 (2.5)*
Central nervous system
Headache
429 (47.8)
270 (54.7)
70 (57.1)
2 (2.2)
66 (8.3)
67 (121.4)
5 (6.66)
Dizziness
67 (7.5)
23 (4.6)
33 (29.9)
32 (12.9)
57 (61.4)
18 (32.6)
6 (8)
Gastrointestinal
Anorexia
380 (42.3)
344 (69.7)
43 (35.1)
116 (46.8)
56 (60.3)
90 (11.3)
2 (2.66)
Abdominal pain
425 (65.9)
367 (74.3)
106 (86.5)
23 (9.3)
84 (90.4)
113 (14.2)
24 (43.5)
9 (12)
Vomiting, nausea
592 (65.9)
360 (72.9)
134 (109.3)
197 (79.5)
131 (141.0)
105 (13.2)
60 (108.7)
69 (92)
Diarrhoea
445 (49.6)
424 (85.9)
16 (13.0)
136 (54.9)
27 (29.1)
47 (5.9)
3 (5.4)
General
Weakness
256 (47.3)
54 (10.9)
5 (4.1)
4 (1.6)
43 (46.3)
75 (9.4)
145 (262.7)
Haematological
Anaemia D7
513 (57.1)
112 (22.7)
107 (87.3)
125 (50.4)
11 (11.8)
57 (7.2)
191 (346.0)
Haematological
Anaemia > D7
141 (15.7)
158 (32.0)
143 (57.7)
93 (100.1)
Others
Drug_related_AE
23 (2.6)*
4 (0.8)*
36 (14.5)
Drowsiness
12 (1.3)
5 (4.1)
14 (5.6)
13 (14.)
2 (0.2)
Asthenia
177 (19.7)
153 (31.0)
107 (87.3)
39 (15.7)
Respiratory
Cough
1087 (121.1)
1155 (233.9)
40 (32.6)
346 (139.6)
78 (84.0)
162 (20.4)
16 (21.33)
Skin and appendages
Pruritus
51 (5.7)
34 (6.9)
16 (13.0)
49 (19.8)
8 (8.6)
48 (6.0)
5 (9.0)
Rash
42 (4.7)
86 (17.4)
1 (0.8)
18 (7.26)
8 (8.6)
Total studies with treatment arm
41
15
5
10
9
5
3
2
Studies with/without AL and the treatment group
5
4
3
1
Total sample size
8979
4938
1226
2478
929
793
552
750
*Risk per 1000 patients; D: day; AE: adverse event. †AQSP, a non-WHO-recommended, non-ACT combination, was included for comparison.
Organ system classification and number of adverse events reported for new alternative ACTs from 43 studies
Organ system
Adverse events
Sample size*
ASAQCPH
ASATPG
ASPY
ASSMP
DHPPT
54
100
355
837
212
Gastrointestinal
vomit_nausea
29
30
52
21
Haematological
Anaemia D7
49
Haematological
Anaemia
Gastrointestinal
Abdominal pain
37
55
5
Gastrointestinal
Diarrhoea
10
2
Skin and appendages
Pruritus
3
6
General
Weakness
11
Respiratory
Cough
44
1
Gastrointestinal
Anorexia
19
Central nervous system
Headache
24
Skin and appendages
Rash
1
Cardiovascular
Palpitation
Others
Drowsiness
7
Others
Asthenia
2
Central nervous system
Dizziness
14
1
*Randomized sample size for each combination. D: day; AE: adverse event.
For studies comparing AL with other ACTs, the risk of adverse event was compared (Table 6). Descriptive statistics for all studies involved in this comparison can be found in Supplementary Table 2. Comparisons showed that the risk of having a headache (relative risk [RR], 0.80; 95% CI, 0.67 - 0.96), diarrhoea (RR 0.85; 95% CI, 0.74 - 0.97), and cough (RR, 0.91; 95% CI, 0.85 - 0.98) was significantly lower (P < 0.05) with DHPP than with AL. However, treatment with DHPP resulted in an increased risk of anaemia than with AL (raw RR, 2.23; 95% CI, 1.64 - 3.02). On the other hand, ASMQ was associated with less vomiting and nausea (OR, 0.80; 95% CI, 0.48 - 1.30), anaemia (OR 0.8; 95% CI, 0.74 - 0.99), and headache (OR 0.53; 95% CI, 0.40 - 0.68), compared to AL (Table 6).
4. Discussion
The efficacy and tolerance of ACTs were updated using the existing database. The primary outcome, i.e., the rate of ACPR, was extended beyond 28 days and the mixed effect model was used to account for the variability of children’s responses to different ACTs. Different doses of ASAQ were also accounted for. For instance, in the selected studies, the efficacy of ASAQ FDC was assessed as it was found that this combination ensures optimal dosing and provides higher treatment efficacy.
Difference in crude risk of adverse events between each treatment and AL
Adverse events
Raw relative risk (95% confidence interval)
DHPP
ASAQc
ASAQf
ASAQl
AQSP*
ASMQ
ASSP
Vomiting/nausea
1.00 (0.85 - 1.18)
-
1.45 (1.18 - 1.78)
1.24 (0.98 - 1.58)
1.12 (0.82 - 1.53)
0.80 (0.48 - 1.30)
2.54 (1.63 - 3.98)
Anaemia
2.23 (1.64 - 3.02)
1.70 (1.26 - 2.30)
4.18 (2.93 - 5.95)
1.53 (1.26 - 1.86)
0.91 (0.61 - 1.32)
0.85 (0.74 - 0.99)
-
Abdominal pain
1.10 (0.93 - 1.28)
1.63 (1.21 - 2.20)
2.02 (0.97 - 4.21)
1.25 (0.88 - 1.81)
1.10 (0.80 - 1.49)
-
1.07 (0.41 - 2.76)
Diarrhoea
0.85 (0.74 - 0.97)
0.74 (0.39 - 1.40)
0.94 (0.75 - 1.18)
0.71 (0.44 - 1.14)
0.93 (0.60 - 1.44)
-
-
Pruritus
0.77 (0.43 - 1.38)
1.63 (0.74 - 3.58)
10.67 (4.25 - 26.76)
5.94 (0.7 - 50.81)
3.56 (1.85 - 6.83)
-
-
Cough
0.91 (0.85 - 0.98)
1.27 (0.80 - 2.01)
0.91 (0.80 - 1.04)
0.62 (0.48 - 0.77)
-
-
-
Anorexia
0.89 (0.76 - 1.03)
2.19 (1.29 - 3.70)
0.98 (0.76 - 1.25)
1.55 (1.05 - 2.28)
1.95 (1.37 - 2.76)
-
-
Headache
0.80 (0.67 - 0.96)
1.09 (0.79 - 1.52)
-
-
0.60 (0.31 - 1.12)
0.53 (0.40 - 0.68)
2.38 (0.46 - 12.26)
Number of studies with AL
14
5
8
8
4
3
1
Number of children in AL
4740
1250
2471
909
540
711
634
Number of children in trt arm
3681
1226
2222
763
593
552
664
Each treatment was taken as the reference and compared to AL in the same trials that compared both treatments. Data on adverse events occurring at any time during the follow-up period from 43 published studies. *AQSP, a non-WHO-recommended, non-ACT combination, was included for comparison since several African countries have adopted its use during the transition period in the 2000s before full implementation of ACT-based antimalarial drug policy.
Age covariate was used in a meta-regression analysis to assess the benefit of each drug compared to AL while accounting for variation among trials in terms of protocol, patients, and follow-up period. The rate of adverse events was compared between ACTs to assess the safety and tolerability of different pairs of treatment arms.
The inclusion of age covariate did not modify the differences between treatments, as found in previous works [21] [27]. Compared to AL, treatment with DHPP and ASMQ resulted in a statistically significant increase (P < 0.05) in the chance of recovery, i.e. ACPR, as well as a lower probability (P < 0.05) of encountering adverse events in African children. The present analysis showed similar conclusions to a recent study that compared three combinations, DHPP, AL, and ASMQ, in which it was found that the treatment success rate was higher with DHPP compared to AL [28]. In addition, children who received one of these two combinations (DHPP or ASMQ) experienced a lower prevalence (P < 0.05) of cough, weakness, abdominal pain, or loss of appetite compared with those who were treated with AL. In another recent study conducted in Cameroon, there were no major adverse reactions in the DHPP group, further supporting the observation that DHPP is more efficacious, safer, and more tolerated than ASMQ and AL in African children [28] [29]. However, AL efficacy is still very high, with the rate of ACPR above 95% in most clinical studies conducted in Africa [30]. Indeed, despite the observed mild to moderate adverse events reported in the eligible studies, AL has a good tolerability [31] [32].
In this work, ASSMP and ASPY were the less studied novel ACTs. Adverse events were reported more frequently with ASSMP than with other ACTs. There is another novel non-WHO-approved ACT, such as AMPP, which, compared to AL, showed high cure rates in the ITT-analysis on day 28 (96.6% vs. 95.0%) and day 42 (94.4% vs. 93.1%), respectively [33]. However, more evidence-based data on the new alternative ACT are required in sub-Saharan Africa to evaluate their efficacy and safety in comparison to the currently WHO-recommended ACTs.
This study has several limitations. First, the study did not re-assess the selection bias for the evidence since this procedure was performed in our previous work [21]. Secondly, the performance of NMA proved to be difficult for one study reporting the outcome on day 42 due to inconsistency in treatment effect and inconsistent variances in a multi-arm study [34]. This methodological problem related to the difficulty in performing estimation with meta-regression analysis of a small number of studies led to an unreliable ranking of treatment efficacy. To overcome this problem, different treatments were ranked using a frequentist approach. Thirdly, because only a small number of studies were available, the rates of adverse events were compared using a fixed effect model. Moreover, a limited amount of evidence with new alternative ACTs did not allow a more precise estimate of treatment effect.
5. Conclusion
This study suggests that continued use of ACTs for treating uncomplicated malaria in Africa is warranted, but more attention should be paid to mild to moderate adverse events that have been reported frequently in different clinical studies and to potential ACT resistance. Indeed, it is essential to understand the mechanisms involved in the acquisition of artemisinin resistance by P. falciparum to adapt malaria treatment policies and propose new therapeutic strategies. Understanding the mechanisms of artemisinin resistance, regular updates on the epidemiology of drug-resistant malaria, and surveillance are critical components of the overall strategy to prevent the expansion of artemisinin-resistant P. falciparum. Country-specific meta-analyses are also needed to ensure that ACTs remain effective in Africa.
Acknowledgements
We are grateful to Dr. Djam Alain (University of Dschang, Faculty of Medicine and Pharmaceutical Sciences) for his critical reading of the manuscript.
Availability of Data and Materials
All studies reviewed and involved in the analysis are found in Supplementary Tables 1-3. The subset of data included in the analysis of adverse events is in Supplementary Table 2.
Conflicts of Interest
The authors declare that they have no competing interests.
Funding
The authors did not receive funding for this study.
Authors’ Contributions
SWY reviewed the existing database, added additional studies, performed data analysis, and drafted the manuscript; LKB assisted in the interpretation of results and improved the manuscript. All authors read and approved the final manuscript.
Cite this paper
WhegangYoudom, S., Tchouenkou, R.S., Ndong-Nguéma, E.-P. and Basco, L.K. (2022) Comparison of Efficacy and Safety of Artemisinin-Based Combination Therapies for Treating Uncomplicated Falciparum Malaria in Sub-Saharan African Countries: An Update on the Changes in Efficacy Using Network Meta-Analysis. Advances in Infectious Diseases, 12, 405-421. https://doi.org/10.4236/aid.2022.123032
ReferencesWorld Health Organization (1994) Antimalarial Drug Policies: Data Requirements, Treatment of Uncomplicated Malaria and Management of Malaria in Pregnancy. WHO/MAL/94.1070, World Health Organization, Geneva.World Health Organization (1996) Assessment of Therapeutic Efficacy to Antimalarial Drugs for Uncomplicated Falciparum Malaria in Areas with Intense Transmission. WHO/MAL/96.1007, World Health Organization, Geneva.World Health Organization (2003) Assessment and Monitoring of Antimalarial Drug Efficacy for the Treatment of Uncomplicated Falciparum Malaria. World Health Organization, Geneva.World Health Organization (2009) Methods for Surveillance of Antimalarial Drug Efficacy. World Health Organization, Geneva.Egunsola, O. and Oshikoya, K.A. (2013) Comparative Safety of Artemether-Lumefantrine and Other Artemisinin-Based Combinations in Children: A Systematic Review. Malaria Journal, 12, Article No. 385. https://doi.org/10.1186/1475-2875-12-385Jansen, J.P. and Cope, S. (2012) Meta-Regression Models to Address Heterogeneity and Inconsistency in Network Meta-Analysis of Survival Outcomes. BMC Medical Research Methodology, 12, Article No. 152. https://doi.org/10.1186/1471-2288-12-152Dias, S., Sutton, A.J., Ades, A.E. and Welton, N.J. (2013) Evidence Synthesis for Decision Making 2: A Generalized Linear Modeling Framework for Pairwise and Network Meta-Analysis of Randomized Controlled Trials. Medical Decision Making, 33, 60-617. https://doi.org/10.1177/0272989X12458724Maiga, F.O., Wele, M., Toure, S.M., Keita, M., Tangara, C.O., Refeld, R.R., et al. (2021) Artemisinin-Based Combination Therapy for Uncomplicated Plasmodium falciparum Malaria in Mali: A Systematic Review and Meta-Analysis. Malaria Journal, 20, Article No. 356. https://doi.org/10.1186/s12936-021-03890-0World Health Organization (2015) Guidelines for the Treatment of Malaria. 3rd Edition, World Health Organization, Geneva.Tshefu, A.K., Gaye, O., Kayentao, K., Thompson, R., Bhatt, K.M., Sesay, S.S., et al. (2010) Efficacy and Safety of a Fixed-Dose Oral Combination of Pyronaridine-Artesunate Compared with Artemether-Lumefantrine in Children and Adults with Uncomplicated Plasmodium falciparum Malaria: A Randomised Non-Inferiority Trial. Lancet, 375, 1457-1467. https://doi.org/10.1016/S0140-6736(10)60322-4Bukirwa, H., Unnikrishnan, B., Kramer, C.V., Sinclair, D., Nair, S. and Tharyan, P. (2014) Artesunate Plus Pyronaridine for Treating Uncomplicated Plasmodium falciparum Malaria. Cochrane Database of Systematic Reviews, No. 3, Article No. CD006404. Update In: Cochrane Database of Systematic Reviews, 2019, No. 1, Article No. CD006404. https://doi.org/10.1002/14651858.CD006404.pub2Toure, O.A., Mwapasa, V., Sagara, I., Gaye, O., Thompson, R., Maheshwar, A.V., et al. (2017) Assessment of Efficacy and Safety of Arterolane Maleate-Piperaquine Phosphate Dispersible Tablets in Comparison with Artemether-Lumefantrine Dispersible Tablets in Pediatric Patients with Acute Uncomplicated Plasmodium falciparum Malaria: A Phase 3, Randomized, Multicenter Trial in India and Africa. Clinical Infectious Diseases, 65, 1711-1720.Thanh, N.X., Trung, T.N., Phong, N.C., Quang, H.H., Dai, B., Shanks, G.D., et al. (2012) The Efficacy and Tolerability of Artemisinin-Piperaquine (Artequick<sup>®</sup>) Versus Artesunate-Amodiaquine (Coarsucam<sup>TM</sup>) for the Treatment of Uncomplicated Plasmodium falciparum Malaria in South-Central Vietnam. Malaria Journal, 11, Article No. 217. https://doi.org/10.1186/1475-2875-11-217Isba, R., Zani, B., Gathu, M. and Sinclair, D. (2015) Artemisinin-Naphthoquine for Treating Uncomplicated Plasmodium falciparum Malaria. Cochrane Database of Systematic Reviews, No. 2, Article No. CD011547. https://doi.org/10.1002/14651858.CD011547Sinclair, D., Zani, B., Donegan, S., Olliaro, P. and Garner, P. (2009) Artemisinin-Based Combination Therapy for Treating Uncomplicated Malaria. Cochrane Database of Systematic Reviews, No. 3, Article No. CD007483. https://doi.org/10.1002/14651858.CD007483.pub2Kayentao, K., Maiga, H., Newman, R.D., McMorrow, M.L., Hoppe, A., Yattara, O., et al. (2009) Artemisinin-Based Combinations Versus Amodiaquine Plus Sulphadoxine-Pyrimethamine for the Treatment of Uncomplicated Malaria in Faladje, Mali. Malaria Journal, 8, Article No. 5. https://doi.org/10.1186/1475-2875-8-5Maiga, H., Djimde, A.A., Beavogui, A.H., Toure, O., Tekete, M., Sangare, C.P., et al. (2015) Efficacy of Sulphadoxine-Pyrimethamine + Artesunate, Sulphadoxine Pyrimethamine + Amodiaquine, and Sulphadoxine-Pyrimethamine Alone in Uncomplicated Falciparum Malaria in Mali. Malaria Journal, 14, Article No. 64. https://doi.org/10.1186/s12936-015-0557-yAssi, S.B., Aba, Y.T., Yavo, J.C., Nguessan, A.F., Tchiekoi, N.B., San, K.M., et al. (2017) Safety of a Fixed-Dose Combination of Artesunate and Amodiaquine for the Treatment of Uncomplicated Plasmodium falciparum Malaria in Real-Life Conditions of Use in Côte d’Ivoire. Malaria Journal, 16, Article No. 8. https://doi.org/10.1186/s12936-016-1655-1Ndiaye, J.L., Faye, B., Gueye, A., Tine, R., Ndiaye, D., Tchania, C., et al. (2011) Repeated Treatment of Recurrent Uncomplicated Plasmodium falciparum Malaria in Senegal with Fixed-Dose Artesunate plus Amodiaquine versus Fixed-Dose Artemether Plus Lumefantrine: A Randomized, Open-Label Trial. Malaria Journal, 10, Article No. 237. https://doi.org/10.1186/1475-2875-10-237WWARN Artemisinin-Based Combination Therapy (ACT) Africa Baseline Study Group (2016) Gametocyte Carriage in Uncomplicated Plasmodium falciparum Malaria Following Treatment with Artemisinin Combination Therapy: A Systematic Review and Meta-Analysis of Individual Patient Data. BMC Medicine, 14, Article No. 79. https://doi.org/10.1186/s12916-016-0621-7Whegang Youdom, S., Tahar, R. and Basco, L.K. (2017) Comparison of Antimalarial Drug Efficacy in the Treatment of Uncomplicated Malaria in African Children and Adults Using Network Meta-Analysis. Malaria Journal, 16, Article No. 311. https://doi.org/10.1186/s12936-017-1963-0Salanti, G. (2012) Indirect and Mixed-Treatment Comparison, Network, or Multiple-Treatments Meta-Analysis: Many Names, Many Benefts, Many Concerns for the Next Generation Evidence Synthesis Tool. Research Synthesis Methods, 3, 80-97. https://doi.org/10.1002/jrsm.1037Röver, C., Bender, R., Dias, S., Schmid, C.H., Schmidli, H., Sturtz, S., et al. (2021) On Weakly Informative Prior Distributions for the Heterogeneity Parameter in Bayesian Random-Eff4cts Meta-Analysis. Research Synthesis Methods, 12, 448-474. https://doi.org/10.1002/jrsm.1475Rücker, G. and Schwarzer, G. (2017) Resolve Conflicting Rankings of Outcomes in Network Meta-Analysis: Partial Ordering of Treatments. Research Synthesis Methods, 8, 526-536. https://doi.org/10.1002/jrsm.1270Salanti, G., Ades, A.E. and Ioannidis, J.P. (2011) Graphical Methods and Numerical Summaries for Presenting Results from Multiple-Treatment Meta-Analysis: An Overview and Tutorial. Journal of Clinical Epidemiology, 64, 163-171. https://doi.org/10.1016/j.jclinepi.2010.03.016R Core Team (2020) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. https://www.R-Project.org/Whegang Youdom, S., Chiabi, A. and Basco, L.K. (2019) Monitoring the Efficacy and Safety of Artemisinin-Based Combination Therapies: A Review of Anti-Malarial Therapeutic Efficacy Trials in Cameroon. Drugs in R&D, 19, 1-14. https://doi.org/10.1007/s40268-018-0259-3Metoh, T.N., Somo-Moyou, R., Fon, P.G., Tambo, E., Chen, J.H. and Zhou, X.N. (2021) Efficacy and Safety Assessment of Three Artemisinin-Based Combination Therapy (ACTs) in the Treatment of P. falciparum Malaria in Cameroon. Journal of Infectious Diseases and Epidemiology, 7, Article No. 242.Sevene, E., Banda, C.G., Mukaka, M., Maculuve, S., Macuacua, S., Vala, A., et al. (2019) Efficacy and Safety of Dihydroartemisinin-Piperaquine for Treatment of Plasmodium falciparum Uncomplicated Malaria in Adult Patients on Antiretroviral Therapy in Malawi and Mozambique: An Open Label Non-Randomized Interventional Trial. Malaria Journal, 18, Article No. 277. https://doi.org/10.1186/s12936-019-2909-5World Health Organization (2020) Report on Antimalarial Drug Efficacy, Resistance and Response: 10 Years of Surveillance (2010-2019). World Health Organization, Geneva.Abamecha, A., Yilma, D., Addisu, W., El-Abid, H., Ibenthal, A., Noedl, H., et al. (2020) Therapeutic Efficacy of Artemether-Lumefantrine in the Treatment of Uncomplicated Plasmodium falciparum Malaria in Chewaka District, Ethiopia. Malaria Journal, 19, Article No. 240. https://doi.org/10.1186/s12936-020-03307-4Toure, O.A., Penali, L.K., Yapi, J.D., Ako, B.A., Toure, W., Djerea, K., et al. (2009) A Comparative, Randomized Clinical Trial of Artemisinin/Naphtoquine Twice Daily One Day versus Artemether/Lumefantrine Six Doses Regimen in Children and Adults with Uncomplicated Falciparum Malaria in Côte d’Ivoire. Malaria Journal, 8, Article No. 148. https://doi.org/10.1186/1475-2875-8-148Toure, O.A., Valecha, N., Tshefu, A.K., Thompson, R., Krudsood, S., Gaye, O., et al. (2016) A Phase 3, Double-Blind, Randomized Study of Arterolane Maleate-Piperaquine Phosphate Vs Artemether-Lumefantrine for Falciparum Malaria in Adolescent and Adult Patients in Asia and Africa. Clinical Infectious Diseases, 62, 964-971. https://doi.org/10.1093/cid/ciw029Faye, B., Ndiaye, J.L., Ndiaye, D., Dieng, Y., Faye, O. and Gaye, O. (2007) Efficacy and Tolerability of Four Antimalarial Combinations in the Treatment of Uncomplicated Plasmodium falciparum Malaria in Senegal. Malaria Journal, 6, Article No. 80. https://doi.org/10.1186/1475-2875-6-80