Aggressive Infection-Related East Africa Lymphoma (AI-REAL) project

Over 85% of childhood cancers occur in low‑ and middle‑income countries, and survival rates are low. Burkitt lymphoma (BL) is one of the most prevalent childhood malignancies in such countries, and is an aggressive cancer with around 50% survival at two years, compared to over 90% in high‑income countries. Reasons are multi‑faceted, and include late or inaccurate diagnosis and lower‑intensity treatments.

The primary aim of AI‑REAL was to validate the use of liquid biopsy (diagnosis based on DNA sequencing from a simple blood draw), performed locally, to diagnose BL. Liquid biopsy is non‑invasive and potentially faster and more sensitive than the current diagnosis by tissue biopsy and histopathology; BL is an ideal candidate for diagnosis by sequencing as it has a well‑understood genetic basis. The project developed and validated a targeted sequencing panel to detect BL, and established the first human diagnostic sequencing capability in East Africa.

In addition to effectiveness, it is also essential to demonstrate that the new diagnostic is cost‑effective, particularly in resource‑limited settings. The health economics team performed a microcosting of both the new diagnostic approach and current histopathology. These costings were then used in a cost‑effectiveness analysis, based on a delivery model where the blood sample could be taken directly in the community rather than at a specialist hospital. The basis of the model was a sub‑study performed within AI‑REAL to map the sources of delay for patients in accessing treatment. We found that the new diagnostic was plausibly cost‑effective, depending on the willingness‑to‑pay of decision‑makers, and projected how sequencing costs are expected to reduce in the future.

AI‑REAL was able to treat participating patients with rituximab, a high‑cost biological drug commonly used in BL in high‑income countries to achieve high survival rates. As some of our patients were unable to receive rituximab due to supply issues, we were able to perform an observational comparison, and found that patients who received rituximab had improved survival with little impact on safety. We performed an economic analysis and found that adding rituximab was highly likely to be cost‑effective, particularly for advanced‑stage patients.

AI‑REAL collected a wealth of data on not only features of the disease, but also patient characteristics, including social determinants of health, that is available to address questions of access and other drivers of outcome.

Funder: National Institute for Health Research RIGHT Programme 

PROJECT TEAM

Professor Sarah Wordsworth, Dr Liz Morrell, with the Department of Oncology and collaborating sites in Tanzania and Uganda