Evidence map›Paper›PMID 42448305›Full record

ReviewBlood advances2026

Burkitt lymphoma: current understanding, unmet needs, and research directions.

Adiba Khan, Cristina López, Suzanne D Turner, Sam M Mbulaiteye

Abstract readReview
In one paragraph

Review in Blood advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Adiba KhanDepartment of Pathology, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-3171-7771
Cristina LópezHematopathology Section, Pathology Department, Hospital Clínic de Barcelona, Barcelona, Spain.ORCID 0000-0001-6644-1659
Suzanne D TurnerDepartment of Pathology, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-8439-4507
Sam M MbulaiteyeInfections and Immunoepidemiology Branch, National Cancer Institute, Bethesda, MD.ORCID 0000-0002-8273-9831

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractBurkitt lymphoma (BL) is an aggressive B-cell lymphoma historically classified into endemic, sporadic, or immunodeficiency-associated BL based on clinical and epidemiological features. Recent genomic and epigenomic studies have refined this framework, distinguishing Epstein-Barr virus (EBV)-positive and EBV-negative BL molecular subtypes that cut across traditional clinical and epidemiological categories and exhibit distinct biological profiles. In high-income countries (HICs), BL is highly curable with intensive multiagent chemotherapy and antibody-based therapy. In contrast, survival in sub-Saharan Africa rarely exceeds 50%, reflecting diagnostic delays, limited access to effective treatment, and challenges in supportive care. This review summarizes the advances in BL epidemiology, molecular biology, diagnosis, and treatment, highlighting how genomic insights have identified novel biomarkers for earlier detection and monitoring, as well as potential targeted therapies with reduced toxicity. These advances present opportunities to develop scalable diagnostic tools and tailored therapeutic strategies to narrow survival disparities, particularly in resource-limited settings, where most patients occur, and among adults and patients with relapsed or refractory BL in HICs. We also outline key unanswered questions in BL epidemiology and pathogenesis, discuss opportunities for translational research, and emphasize the need for improved model systems to study therapeutic resistance to close the survival gap.

Indexed as

Burkitt LymphomaBiomarkers, TumorHerpesvirus 4, HumanHumansBiomarkers, Tumor

Identifiers

PMID42448305
PMCPMC13672841

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.