Prevalence of hematological malignancies in Africa: A systematic review and meta-analysis
Bibliographic record
Abstract
Hematological malignancies are a class of neoplasms that include a variety of diverse diseases that all develop from and change into lymphatic and bone marrow cells. Hematological malignancies significantly contribute to illness and mortality in African nations. The prevalence of these malignancies has not been evaluated in this continent. The purpose of this systematic review and meta-analysis was to assess the pooled prevalence of hematological malignancies in Africa. From October to November 2023, the electronic databases PubMed, Google Scholar, Web of Science, Research Gate, Embase, and Scopus were extensively searched to identify pertinent research. The Newcastle‒Ottawa Quality Scale for cross-sectional studies was used to assess the quality of the included studies. The analysis tool used was STATA-14. To calculate the pooled prevalence of hematological malignancies, a random effects model was used. Heterogeneity was measured by using the I 2 value. Subgroup analysis was conducted for country, age of study subjects, population type, study design, and publication year. We evaluated publication bias through the implementation of a funnel plot and Egger’s test and conducted a sensitivity analysis. A total of 34 published articles including 43,099 study participants were included. The pooled prevalence of hematological malignancies was 27.30%. There was high heterogeneity, with an I 2 value of 99.2%. Leukemia had the highest pooled prevalence (53.69%) among the hematological malignancy types, followed by lymphoma (38.36%). According to subgroup analysis conducted in African countries, Kenya had the highest pooled prevalence (44.69%). On the other hand, the lowest pooled prevalence reported in Nigeria (20.52%). Furthermore, the age-based subgroup analysis of the study participants revealed that children had a greater pooled prevalence of hematological malignancies than adults (60.92% vs. 17.02%), respectively. In African populations, the pooled prevalence of hematological malignancies was 27.30%. This suggests that there is a significant prevalence of hematological malignancy, necessitating regular monitoring and accurate diagnosis. Trial registration PROSPERO CRD42023427152.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.041 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".