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The AI-REAL programme led by Professor Anna Schuh and research teams in Tanzania and Uganda is improving the early detection and outcomes of childhood lymphoma in the region by increasing the speed and precision of diagnosis.

Over 90% of global childhood lymphoma cases are in sub-Saharan Africa, with these cancers caused by Epstein-Barr virus (EBV) infections, malaria and HIV. Despite effective treatments being available for lymphomas, outcomes are currently poor because many patients are either not diagnosed, are diagnosed late or are misdiagnosed and eventually die from late-stage cancer or the side-effects of wrong treatment. This is due to a huge lack of reliable diagnostic services in sub-Saharan Africa.

Funded by the National Institute for Health and Care Research (NIHR), AI-REAL (Aggressive Infection-Related East Africa Lymphoma) aims to increase the speed and precision of diagnosis in Uganda and Tanzania so that children with lymphomas are diagnosed much earlier. The programme is led by Professor Anna Schuh (Department of Oncology) with teams in Tanzania and Uganda led by Dr Clara Chamba and Dr Lulu Chirande (Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam), Dr Faraja Chiwanga and Dr Hadija Mwamtemi (Muhimbili National Hospital (MNH), Dar es Salaam), Dr Elifuraha Mkwizu (Kilimanjaro Christian Medical Centre (KCMC), Moshi), Dr Caroline Achola (Ministry of Health and Central Public Health Laboratory (CPHL), Kampala) and Dr Martin Ogwang and Ismail Legason (St Mary’s Hospital, Lacor).

In phase one of the AI-REAL programme, the international team established two new diagnostic technologies. Firstly, they enhanced local pathology services by installing automated immunostainers, training technicians in the quality control of specimen preparation and establishing independent digital review of pathology using digital whole slide imaging with mobile scanners as standard of care. Under guidance from senior clinical scientists and bio-informaticians based at the Oxford Molecular Diagnostics Centre, they then set up two local next-generation sequencing facilities for the genetic analysis of liquid biopsies (blood tests) to diagnose or exclude lymphoma in children presenting with lymph gland swellings. In parallel, they performed an extensive health-economic analysis of both pathology and liquid biopsy.

They have now started phase two of the programme, which is a head-to-head comparison between the best local pathology and liquid biopsy. Children and young adults with suspected lymphoma are recruited to the programme and undergo testing using both diagnostic technologies. Clinicians are informed of the results in the hospital tumour board meetings and use the information to reach a diagnosis.

As an example of the difference that this project is already making, the very first patient recruited by the team in Lacor was a 4-year-old child from a remote area in Northern Uganda. The child had been unwell for 2 months with kidney failure and abdominal swellings, and underwent an invasive tissue biopsy and a liquid biopsy. The liquid biopsy was shipped to CPHL in Kampala where a team of molecular scientists under leadership of Dr Achola performed rapid sequencing of viral and tumour DNA. These results were available just 5 days later and showed a type of lymphoma called Burkitt Lymphoma. When the pathology results from the invasive biopsy of the tumour came through, no clear diagnosis could be established because the sampled tissue was dead, and a re-biopsy was recommended. The doctors decided to use the liquid biopsy results to make a diagnosis and the child was started on Burkitt Lymphoma treatment. She is responding well to treatment and her kidney failure has already resolved.

Following this promising start, AI-REAL will prospectively recruit a total of 280 children and young adults to clinically validate the new technologies, and to test whether they speed up the diagnosis, increase the number of diagnosed children (especially among those too unwell to undergo invasive biopsy procedure), and if it improves survival.


Read more about the AI-REAL programme on the AI-REAL website.