Background

In areas of high malaria transmission, individuals are repeatedly inoculated with malaria parasites. At any one time, most infected individuals control their infection and are asymptomatic, but some develop severe life-threatening diseases. Since malaria parasitaemia is so common, it is difficult to diagnose whether malaria is the cause of illness or whether the parasites are coincidental. In clinical studies of severe malaria, misdiagnosis leads to the false inclusion of patients who do not have severe malaria, impacting the accuracy of results.

This study will develop a biomarker-based diagnostic model of severe malaria, using easily measured biomarkers such as platelet counts and white blood counts. This model will improve our understanding of the genetic susceptibility to malaria, the impact of blood transfusion in severe malaria, and how to better design clinical trials in endemic areas. These three research questions rely on a precise definition of severe malaria.

Research Questions

Severe falciparum malaria remains a major cause of preventable childhood death in sub-Saharan Africa despite the availability of highly effective therapies.

The most significant disease burden is in areas with intense mosquito-borne transmission where children are repeatedly inoculated. In these areas of high transmission, effective interventions have the greatest public health benefit. It is logistically feasible to do large clinical studies of severe malaria that test new interventions (sufficient patient numbers).

However, in high transmission areas, severe malaria is largely confined to young children, and it is difficult to assess causality in severe disease, especially distinguishing between invasive bacterial sepsis and severe malaria. Many apparently healthy children have microscopy detectable P. falciparum parasites in their blood, resulting in a low positive predictive value for blood stage parasitaemia in severe disease.

In the absence of predictive biomarkers, the diagnosis of severe malaria in young children and the distinction from bacterial sepsis is therefore imprecise. This critical difficulty in clinical diagnosis affects all quantitative analyses and research that relies on a precise clinical phenotype of severe malaria: clinical therapeutic studies, vaccine studies, epidemiological studies of the burden of disease, and human genetic association studies. Most studies of severe malaria will include some patients who have malaria parasites in their blood but whose primary cause of the severe disease is non-malarial. This phenotypic heterogeneity can obscure important results.

This issue can potentially be resolved using predictive biomarkers in a probabilistic framework. This study will develop and validate the methodological framework underlying the use of biomarkers to adjust for population heterogeneity in clinically defined severe malaria and then apply this framework to answer three important research questions:

1. Which severely ill patients benefit from a blood transfusion?
2. What are the protective effect and protective mechanisms of glucose-6 phosphate dehydrogenase (G6PD) deficiency in severe malaria?
3. How can we design phase 2 evaluations of new therapies that take into account baseline patient heterogeneity?

The aims of this research project are both methodological (development of statistical methods and development of a causal inference framework with which to validate the methods) and applied (individual patient data meta-analysis and clinical trial guidelines).

Aims

1. Develop and then validate a probabilistic definition (phenotype) for severe malaria based on known biomarkers which can be easily measured in low-resource settings.
2. Re-analyse all available data on the relationship between G6PD deficiency and severe malaria, specifically testing the hypothesis that G6PD deficiency protects against an increased risk of death in severe malaria.
3. Carry out a systematic review and individual patient data meta-analysis looking at the effect of blood transfusion in severe malaria, using the developed probabilistic definition for accounting for phenotypic variability and uncertainty. This will specifically test the hypothesis that blood transfusion may be harmful in moderately anaemic severe malaria patients.
4. Develop new statistical methods to account for phenotypic heterogeneity in genetic case-control studies.
5. Develop guidelines for the design and analysis of phase 2 evaluations of new antimalarial drugs in areas of high transmission, notably cipargamin.