Philippe Guerin was a clinician before working with Médecins Sans Frontières across Asia and Africa. He is now Professor of Epidemiology and Global Health at the University of Oxford, with a special interest in malaria. His work has provided evidence to support changes in the World Health Organization’s treatment guidelines for malaria.
'Malaria treatment guidelines are developed for the general population, but are rarely tailored for vulnerable subpopulations such as babies, pregnant women, and patients with comorbidities such as malnutrition, or HIV co-infections,' says Professor Guerin.
'It is imperative to develop optimised approaches for these groups too, to give them the best treatment for them. This is what is called precision public health.'
This is not because health authorities do not recognise the vulnerabilities these groups face - it is because there just wasn’t enough data to make clear recommendations. Vulnerable groups such as young children, pregnant women, or patients suffering from concomitant comorbidities are rarely included in clinical studies for a number of reasons, including ethical or safety concerns, costs, and recruitment challenges.
The problem is compounded by the fact that they are far fewer clinical studies of health conditions that affect the global south, compared to diseases that affect economically richer countries.
Answering new research questions from existing data
'When it comes to diseases in resource limited settings, data are scarce and scattered: the number of scientific publications for something like diabetes is about 10 times that for malaria,' points out Professor Guerin.
One way to get around to this problem is to club together clinical data from individual patients into a larger, single dataset. Doing so can produce policy-changing scientific evidence from existing data, essentially allowing researchers to answer new scientific questions from old data.
The power of this approach was illustrated by a recent study led by Professor Guerin, which found that antimalarial treatments are more likely to fail in children with acute malnutrition.
'Malaria and malnutrition both affect poorer communities with limited research resources, so there just aren’t enough studies on the efficacy of antimalarial drugs in malnourished children, and past studies have contradictory results,' says Professor Philippe Guerin. 'So we used a different strategy to answer this question.'
The research team pooled individual patient data from 36 different antimalarial efficacy studies from 24 countries, that included body measurements (including height and weight) for the study participants. Using this information about weight versus height and age, the researchers could infer which children were likely to be malnourished (acute and chronic), and track outcomes specifically for this group.
'No one individual study included a large enough sample of malnourished children to uncover a clear relationship, but by combining information across many different studies, which each included few malnourished children, we were able to spot a clear pattern,' said Guerin.
'Clinical trial data have potentially bigger value than a single use'
This approach of combining data from many studies and then reusing it to answer new research questions, was pioneered by the WorldWide Antimalarial Resistance Network (WWARN), which brought together hundreds of scientists from more than three hundred institutes to pool their knowledge – and to identify gaps in this knowledge.
Established in 2009, Professor Guerin was WWARN’s first Director, and led a group of scientists attempting to bypass some of the unique challenges of malaria clinical research: 'Security concerns and pollical instability can often make it difficult or impossible to carry out a clinical trial in many countries affected by malaria. Limited resources in health systems can also make it difficult to enrol a representative sample of patients, as many patients aren’t able to access healthcare, making them invisible to clinicians,' says Professor Guerin.
'All of this means that clinical research in diseases of poverty often has relatively small sample sizes. This makes it harder to identify risk factors for patients, as these risk factors are relatively rare: if you’re only looking at a few patients, you might not have one of these rare patients, or you might not have enough of these patients to spot a pattern' says Professor Guerin. 'It was only be assembling lots of data together, under the aegis of WWARN, that we were able to understand what was happening in populations at risk for malaria.'
WWARN’s work identified that the standard dose of an otherwise effective antimalarial treatment, was actually too low for children under five for the combination dihydroartemsinin-piperaquine. This finding led the WHO to revise its official treatment guidelines.
Similarly, WWARN’s work on malaria in pregnancy has provided strong evidence to support WHO’s guidelines for malaria treatment for pregnant women, which were initially based on a much weaker evidence base.
This approach of clubbing together existing data also gets around the much more limited funding for studying diseases that largely affect people in the global south.
'Running a clinical trial can be 20 times more expensive if not more than clubbing together existing data and analysing it to answer the same research question,' says Professor Guerin. 'Clinical data here is scarce and precious – when the primary analysis is completed, there is an opportunity for maximising the added value of existing data.'
Equity in research
WWARN’s success showed that it was possible to produce policy-changing scientific evidence from existing data, and in 2016, the Infectious Diseases Data Observatory (IDDO) extended the same approach to other tropical infectious diseases.
Headed by Professor Philippe Guerin, IDDO’s main staff headquarters is in Oxford University’s Old Road Campus. IDDO promotes the reuse of individual patient data across the global infectious disease community, especially for malaria.
With over 15 people in the data management team alone, IDDO curates data that scientists across the world submit, harmonises them and connects them up with other datasets, and then makes the data available for free to any researcher, enabling scientists to answer new research questions from existing data.
It is particularly keen that research is led and informed by scientists and communities that are actually affected by the diseases: more than half of the IDDO curated data are used for individual patient data meta-analyses led by researchers from low and middle income countries, across Africa, Asia and Latin America.
IDDO also hosts TDR fellows, as part of a WHO career development programme which places researchers from disease-endemic countries with research organisations, to develop clinical research skills – IDDO will be welcoming two new TDR fellows this year. It also works with a number of institutions based in endemic regions including the Wellcome programmes in Asia and Africa, the EDCTP network of excellence (which brings together 15 European and 25 African countries), and the Indian Council of Medical Research to provide training.
'Tackling a disease like malaria needs many different kinds of expertise from many different places, and it is great to be working on a platform that brings many different kinds of scientists, from many different places, together', Professor Guerin says.
Find out more about IDDO’s resources to support malaria research on the IDDO/WWARN website
The full story is available on the University of Oxford website.