Multiple treatment comparisons in a series of anti-malarial trials with an ordinal primary outcome and repeated treatment evaluations

Methodological approaches for analysing data from therapeutic efficacy studies

Several anti-malarial drugs have been evaluated in randomized clinical trials to treat acute uncomplicated Plasmodium falciparum malaria. The outcome of anti-malarial drug efficacy studies is classified into one of four possible outcomes defined by the World Health Organization: adequate clinical and parasitological response, late parasitological failure, late clinical failure, early treatment failure. These four ordered categories are ordinal data, which are reduced to either a binary outcome (i.e., treatment success and treatment failure) to calculate the proportions of treatment failure or to time-to-event outcome for KaplanMeier survival analysis. The arbitrary transition from 4-level ordered categories to 2-level type categories results in a loss of statistical power. In the opinion of the authors, this outcome can be considered as ordinal at a fixed endpoint or at longitudinal endpoints. Alternative statistical methods can be applied to 4-level ordinal categories of therapeutic response to optimize data exploitation. Furthermore, network meta-analysis is useful not only for direct comparison of drugs which were evaluated together in a randomized design, but also for indirect comparison of different artemisinin-based combinations across different clinical studies using a common drug comparator, with the aim to determine the ranking order of drug efficacy. Previous works conducted in Cameroonian children served as data source to illustrate the feasibility of these novel statistical approaches. Data analysis based on ordinal end-point may be helpful to gain further insight into anti-malarial drug efficacy.

Efficacy and safety of artemisinin-based combination therapies for the treatment of uncomplicated malaria in pediatrics: a systematic review and meta-analysis

BACKGROUND

Malaria is a major cause of morbidity and mortality in pediatrics in malaria endemic areas. Artemisinin-based combination therapies (ACTs) are the drugs of choice for malaria management particularly across malaria-endemic countries. This systematic review and meta-analysis was performed to assess efficacy and safety of ACTs for uncomplicated malaria in pediatric populations.

METHODS

A body of evidence was searched for published ACT trials until March 06, 2020. The search was focused on efficacy and safety studies of ACTs for uncomplicated malaria in pediatrics. PubMed library was searched using best adapted search terms after multiple trials. References were exported to the endnote library and then to Covidence for screening. Data was extracted using the Covidence platform. The per-protocol analysis report for the efficacy and the intention-to-treat analysis for the safety were synthesized. Met-analysis was carried using Open Meta-Analyst software. Random effects model was applied and the heterogeneity of studies was evaluated using I2 statistic.

RESULTS

Nineteen studies were included in the final analysis. Overall, crude, PCR-corrected P. falciparum malaria treatment success rate was 96.3 and 93.9% for day 28 and 42, respectively. In the subgroup analysis, PCR-corrected adequate clinical and parasitological response (ACPR) of dihydroartemisinin-piperaquine (DP) was 99.6% (95% CI: 99.1 to 100%, I2 = 0%; 4 studies) at day 28 and 99.6% (95% CI of 99 to 100%, I2 = 0%; 3 studies) at day 42. Nine studies reported ACT related adverse drug reactions (ADR) (8.3%, 356/4304). The reported drug related adverse reactions ranged from 1.8% in DP (two studies) to 23.3% in artesunate-pyronaridine (AP). Gastrointestinal symptoms were the most common ACT related adverse effects, and all ADRs were reported to resolve spontaneously.

CONCLUSION

ACTs demonstrated a high crude efficacy and tolerability against P. falciparum. The high treatment success and tolerability with low heterogeneity conferred by DP has implication for policy makers who plan the use of ACTs for uncomplicated falciparum malaria treatment in pediatrics.

Response-adaptive treatment allocation for clinical studies with ordinal responses

Ordinal responses are common in clinical studies. Although the proportional odds model is a popular option for analyzing ordered-categorical data, it cannot control the type I error rate when the proportional odds assumption fails to hold. The latent Weibull model was recently shown to be a superior candidate for modeling ordinal data, with remarkably better performance than the latent normal model when the data are highly skewed. In clinical trials with ordinal responses, a balanced design is common, with equal sample allocation for each treatment. However, a more ethical approach is to adopt a response-adaptive allocation scheme in which more patients receive the better treatment. In this paper, we propose the use of the doubly adaptive biased coin design to generate treatment allocations that benefit the trial participants. The proposed treatment allocation scheme not only allows more patients to receive the better treatment, it also maintains compatible test power for the comparison of treatment efficiencies. A clinical example is used to illustrate the proposed procedure.

Comparison of anti-malarial drugs efficacy in the treatment of uncomplicated malaria in African children and adults using network meta-analysis

Background

Artemisinin-based combination therapy (ACT) and novel drug combinations are available and used in African countries to treat uncomplicated malaria. Network meta-analysis methods are rarely and poorly applied for the comparison of their efficacies. This method was applied on a set of randomized controlled trials to illustrate its usefulness.

Methods

A literature review available in Pubmed was conducted in July 2016. Eligible studies, conducted in sub-Saharan Africa, published between 2002 and 2016, focused on randomized controlled trials of at least two artemisinin-based combinations to treat uncomplicated malaria in children and adults. Agglomerate data were: the number of PCR-corrected adequate clinical and parasitological response (ACPR) on day 28, used as the primary endpoint in all interventions, the number of participants and the list of treatments. A Bayesian random effect meta-analysis using a binary outcome was the method to compare the efficacy. Ranking measure was used to obtain a hierarchy of the competing interventions.

Results

In total, 76 articles were included; 13 treatment regimens were involved and tested in 36,001 patients. Using artemether–lumefantrine (AL) as the common comparator for the entire network, 12 relative treatment effects were estimated and indirect comparisons were obtained. Dihydroartemisinin–piperaquine (DHAP) was shown to be more effective than AL (odds ratio [OR] = 1.92; 95% CI 1.30–2.82; 19,163 patients), ASAQ (OR = 1.70; 95% CI 1.10–2.64; 14,433 patients), and amodiaquine–sulfadoxine–pyrimethamine (AQSP): OR = 2.20; 95% CI 1.21–3.96; 8863 patients. Artesunate–amodiaquine (ASAQ) was comparable to AL (OR = 1.11; 95% CI 0.84–1.45; 21,235 patients). No significant difference was found between artesunate and mefloquine (ASMQ) and AL (OR = 1.20; 95% CI = 0.52-2.8; 13,824 participants). According to treatment ranking, among the WHO-recommended ACT medicines, DHAP was shown to be the most efficacious.

Conclusions

Based on the available evidence, this study demonstrated the superiority of DHAP among currently recommended artemisinin-based combinations. The application of the methods described here may be helpful to gain better understanding of treatment efficacy and improve future decisions. However, more data are needed to allow robust conclusions about the results in comparison with novel drugs. Further surveillance of the efficacy of anti-malarial drugs and clinical trials are needed to closely follow the evolution of the epidemiology of drug-resistant malaria in Africa.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-017-1963-0) contains supplementary material, which is available to authorized users.

A scoping review of indirect comparison methods and applications using individual patient data

BACKGROUND

Several indirect comparison methods, including network meta-analyses (NMAs), using individual patient data (IPD) have been developed to synthesize evidence from a network of trials. Although IPD indirect comparisons are published with increasing frequency in health care literature, there is no guidance on selecting the appropriate methodology and on reporting the methods and results.

METHODS

In this paper we examine the methods and reporting of indirect comparison methods using IPD. We searched MEDLINE, Embase, the Cochrane Library, and CINAHL from inception until October 2014. We included published and unpublished studies reporting a method, application, or review of indirect comparisons using IPD and at least three interventions.

RESULTS

We identified 37 papers, including a total of 33 empirical networks. Of these, only 9 (27 %) IPD-NMAs reported the existence of a study protocol, whereas 3 (9 %) studies mentioned that protocols existed without providing a reference. The 33 empirical networks included 24 (73 %) IPD-NMAs and 9 (27 %) matching adjusted indirect comparisons (MAICs). Of the 21 (64 %) networks with at least one closed loop, 19 (90 %) were IPD-NMAs, 13 (68 %) of which evaluated the prerequisite consistency assumption, and only 5 (38 %) of the 13 IPD-NMAs used statistical approaches. The median number of trials included per network was 10 (IQR 4-19) (IPD-NMA: 15 [IQR 8-20]; MAIC: 2 [IQR 3-5]), and the median number of IPD trials included in a network was 3 (IQR 1-9) (IPD-NMA: 6 [IQR 2-11]; MAIC: 2 [IQR 1-2]). Half of the networks (17; 52 %) applied Bayesian hierarchical models (14 one-stage, 1 two-stage, 1 used IPD as an informative prior, 1 unclear-stage), including either IPD alone or with aggregated data (AD). Models for dichotomous and continuous outcomes were available (IPD alone or combined with AD), as were models for time-to-event data (IPD combined with AD).

CONCLUSIONS

One in three indirect comparison methods modeling IPD adjusted results from different trials to estimate effects as if they had come from the same, randomized, population. Key methodological and reporting elements (e.g., evaluation of consistency, existence of study protocol) were often missing from an indirect comparison paper.

Multiple comparisons with two controls for ordered categorical responses

In clinical studies, ordered categorical responses are common. To compare the efficacy of several treatments with a control for ordinal responses, the normal latent variable model has recently been proposed. This approach conceptualizes the responses as manifestations of an underlying continuous normal variable. In this article, we extend this idea to develop the multiple comparison method for use when there are two controls in the clinical trial. The proposed method is constructed such that the familywise type I error rate is controlled at a prespecified level. In addition, for a given level of test power, the procedure to evaluate the required sample size is provided. The proposed testing procedure is also illustrated by an example from a clinical study.

Comparison of two treatments with skewed ordinal responses

In clinical studies, the proportional odds model is widely used to compare treatment efficacies when the responses are categorically ordered. However, this model has been shown to be inappropriate when the proportional odds assumption is invalid, mainly because it is unable to control the type I error rate in such circumstances. To remedy this problem, the latent normal model was recently promoted and has been demonstrated to be superior to the proportional odds model. However, the application of the latent normal model is limited to compare treatments with similar underlying distributions except possibly their means and variances. When the underlying distributions are very different in skewness, both of the aforementioned procedures suffer from the undesirable inflation of the type I error rate. To solve the problem for clinical studies with ordinal responses, we provide a viable solution that relies on the use of the latent Weibull distribution, which is a member of the log-location-scale family. The proposed model is able to control the type I error rate regardless of the degree of skewness of the treatment responses. In addition, the power of the test also outperforms that of the latent normal model. The testing procedure draws on newly developed theoretical results related to latent distributions from the location-scale family. The testing procedure is illustrated with two clinical examples.

Malaria: an update on current chemotherapy

INTRODUCTION

Chemotherapy of malaria has become a rapidly changing field. Less than two decades ago, treatment regimens were increasingly bound to fail due to emerging drug resistance against 4-aminoquinolines and sulfa compounds. By now, artemisinin-based combination therapies (ACTs) constitute the standard of care for uncomplicated falciparum malaria and are increasingly also taken into consideration for the treatment of non-falciparum malaria.

AREAS COVERED

This narrative review provides an overview of the state-of-art antimalarial drug therapy, highlights the global portfolio of current Phase III/IV clinical trials and summarizes current developments.

EXPERT OPINION

Malaria chemotherapy remains a dynamic field, with novel drugs and drug combinations continuing to emerge in order to outpace the development of large-scale drug resistance against the currently most important drug class, the artemisinin derivatives. More randomized controlled studies are urgently needed especially for the treatment of malaria in first trimester pregnant women. ACTs should be used for the treatment of imported malaria more consequently. Gaining sufficient efficacy and safety information on ACT use for non-falciparum species including Plasmodium ovale and malariae should be a research priority. Continuous investment into malaria drug development is a vital factor to combat artemisinin resistance and successfully improve malaria control toward the ultimate goal of elimination.