While not exhaustive, this is so far the largest dataset of individual-patient tolerability data compiled on an ACT (ASAQ); it includes a sizeable number of patients (nearly 6,200, enrolled in randomized controlled trials, almost equally split between ASAQ and comparators groups) with tolerability outcomes (adverse events, AEs), and is representative of the spectrum composition of malaria patients (it comprises mostly children under five years of age (74%) from areas of moderate to high intensity of malaria transmission of nine sub-Saharan African countries). In more than half of these patients (over 3,300), events were recorded pre-treatment and graded in terms of intensity, which allowed identifying and analysing treatment emergent adverse events (TEAEs).
Both efficacy and tolerability information is essential to guide treatment policy. However, while millions of ACT treatments are given every year, and thousands of patients are enrolled in trials with ACT, little tolerability information is available. Tolerability data are often cursorily presented in papers and difficult to standardize and summarize. The availability of individual patient data and the use of standardized methods for analysis (including
]) made it possible both to draw generalizable conclusions and to identify site-specific differences.
Over 3,100 of these patients received ASAQ formulated as different products (of whom over 2,100 were treated with the loose or co-blistered and 1,000 with the fixed dose combination) by various manufacturers. Therefore, the conclusions reported here do not relate to an individual drug product, but rather the collective tolerability profile of ASAQ. Overall, the risk of experiencing an AE was not different in patients exposed to ASAQ or other forms of ACT and non-ACT, with some exceptions.
This analysis also provides important information on a number of safety-related issues.
Risks varied across the different trial sites; clinical safety appreciation differs from site to site and probably from investigator to investigator. Also, the type of data and the way they are collected varies. While standard criteria exist
], it would be useful to invest into harmonizing both the variables collected, the timing of assessment, and the grading of events, as well as the way data are reported and analysed.
One particular example is vomiting. Vomiting is a symptom of malaria, but can also be induced or made worse by treatment. In studies where treatment is given under direct observation it is possible to monitor the patients for the first hour post-dosing in case drug is vomited; this also allows re-administering the dose (in toto or in part) when so required, and distinguishing between early and late vomiting
]. Only one study provided for this
]; all other relied upon subjects or parent/guardians recall of episodes occurring in between visits.
Multivariate logistic regression analysis, as well as the comparison of TEAEs and AEs, pointed to the importance of looking to the considerable background noise generated by malaria itself (pretreatment and recurrence) as well as other diseases and conditions. For instance, the risk of GI events in general (and more specifically anorexia and diarrhoea) and other AEs (weakness) was higher in patients with recurrent malaria; cough (indicative of non-malaria infections) increased with follow-up time; older age was associated with a lower risk of most AEs.
It is important to distinguish the signs/symptoms of malaria from those that may be caused by the treatment. Assessing the drug-event relationship is highly subjective and prone to bias. Recording the occurrence and severity of (a defined set of) events before treatment is administered allows a better appreciation of the real contribution of a treatment to a patient’s status. When this is done (in this set of studies this involved ca. half of the patients enrolled), it is possible to report TEAE - ie the occurrence post-treatment of a sign/symptom that was not present before treatment, or its worsening with treatment. This applies also to RCTs, where randomization is expected to even out the risks of events at enrolment, as one is interested not only on the relative (between-treatment) but also the absolute risks for toxicity. These analyses showed that the risks, when considering AEs over TEAEs, ranged from no difference (rare events like jaundice, tinnitus) to double (vomiting), triple (abdominal pain), five-fold (nausea, headache, dizziness) differences. The relationship with prevalence of signs/symptom at enrolment was greater for AEs compared to TEAEs (meaning that the definition of AE is less independent of the sign/symptoms related to the disease itself).
Traditionally, the main concern in malaria has been efficacy, which has driven treatment recommendations (and a living databases of efficacy has been created
]). Safety and tolerability, instead, have been neglected. Now with generally efficacious, intensely used ACT, assessing safety risks has become as important as ever. Compared to pharmaco-vigilance, clinical trials offer the opportunity of closer, more detailed monitoring of events, but are unsuited for signal generation (rare events). Yet, monitoring and reporting on safety outcomes in clinical trials is more cumbersome and less standardized than for efficacy outcomes (and generally felt by trialists to be less appealing). Paradoxically, this has created situations whereby claims of toxicity based on dubious evidence can cause a treatment to be disliked, recommended against, or banned altogether.
In conclusion, this paper provides both (i) a comparative evaluation of the safety risks following various ACT on a large, representative sample of malaria patients; and (ii) a proposal for improved methods to assess safety risks.