Published in PLOS One on 2026-08-03, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Solomon Gedfie, Melese Abate Reta, Muluken Gashaw, Alembante Bazezew, Abdu Jemal, Nigatu Getu, Mengistu Tesfa Alula, Bewuketu Belete Alemu, Marye Nigatie, Getinet Kumie, Zewdu Tefera, Brhanu Kassanew, Ermias Getachew, Assefa Sisay, Yalewayker Gashaw, Mesfine Desale, Ephrem Tamrat, Zelalem Dejazmach, Wagaw Abebe, Agenagnew Ashagre, Tadesse Misganaw, Woldeteklehaymanot Kassahun, Mehmet Baysal
Source: PLOS One • DOI 10.1371/journal.pone.0354814
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
Leukemia is a group of diverse and biologically distinct blood cancers. While progress has been made in combating infectious diseases, chronic diseases like leukemia are increasingly prevalent. Current data on leukemia’s prevalence in Africa are inconsistent, necessitating a comprehensive systematic review. This study aims to determine the pooled prevalence and associated risk factors of leukemia across Africa through a systematic review and meta-analysis.
This systematic review and meta-analysis were conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted across multiple databases, including PubMed/MEDLINE, Scopus, and Science Direct, supplemented by searches using the Google Scholar and manual searches to identify eligible studies. Statistical analysis was performed using STATA version 11, with a random-effects model employed to compute pooled estimates. Higgen’s I2 test statistics and meta-regression was conducted to explore potential sources of heterogeneity. Publication bias was assessed visually by Funnel plots and statistically using Egger’s weighted regression test, a p-value of less than 0.05 indicates the presence of significant publication bias.
A total of 17,546 articles were retrieved, of which fifteen studies, which recruited 42,884 individuals, were included in the meta-analysis. The pooled prevalence of leukemia was 5.09% (95% CI: 4.02, 6.17) with I2 of 97.1%. Due to the heterogeneity, subgroup analyses by country showed that the highest prevalence was 10.58% in Nigeria, and the lowest was 0.58% in Zambia. Subgroup analysis based on publication year revealed 4.16% among studies conducted before 2015 and 6.67% among studies conducted after 2016. Additionally subgroup by sample size showed: smaller sample sizes (<384 participants) yielded a higher pooled estimate of 7.99%, conversely, studies with larger sample sizes (≥385 participants) showed 3.61%. Whereas subgroup analysis by population showed that 3.38% in children and 7.15% in the general population. Among the factors identified, rural residency (OR: 56.98, 95% CI: 9.97–326.70) and older age (OR: 3.90, 95% CI: 1.39–10.98) were significant predictors of leukemia in Africa.
This review reveals a pooled prevalence of 5.09%, with rural residency and older age identified as significant predictors of leukemia in Africa, underscoring a public health concern.
Introduction
Leukemia is a diverse group of blood cancers that originate in the bone marrow and other blood-forming tissues [1]. These cancers involve the unchecked growth of immature blood cells, interfering with normal blood cell production and potentially spreading to other organs [2]. Leukemia is classified according to both cell lineage and how quickly the disease progresses. The cell lineage determines whether it is lymphoid or myeloid leukemia, while the progression rate categorizes it as either acute or chronic [2,3]. This essential classification system informs how clinicians diagnose, treat, and predict outcomes for patients. When categorized clinically by disease progression (acute or chronic) and cell lineage (myeloid or lymphoid), this blood cancer exhibits unique biological characteristics across its various subtypes [4].
Reading this evidence
Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.
This briefing makes the source accessible within the wider public health desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2026 Solomon Gedfie, Melese Abate Reta, Muluken Gashaw, Alembante Bazezew, Abdu Jemal, Nigatu Getu, Mengistu Tesfa Alula, Bewuketu Belete Alemu, Marye Nigatie, Getinet Kumie, Zewdu Tefera, Brhanu Kassanew, Ermias Getachew, Assefa Sisay, Yalewayker Gashaw, Mesfine Desale, Ephrem Tamrat, Zelalem Dejazmach, Wagaw Abebe, Agenagnew Ashagre, Tadesse Misganaw, Woldeteklehaymanot Kassahun, Mehmet Baysal. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.
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