HIV infection and esophageal cancer in Sub-Saharan Africa: a comprehensive meta-analysis
Bibliographic record
Abstract
Africa hosts the highest burden of esophageal cancer (49%) and HIV (60%) worldwide. It is imperative to investigate the synergistic impact of these two diseases on African populations. This study conducted an exhaustive computerized search of databases, including Medline/PubMed, Embase, Web of Science, Scopus, Cochrane library, and African Journals Online, to identify eligible studies up to October 2023. HIV infection was the exposure, esophageal cancer risk was the outcome, and healthy subjects with no cancer history served as comparators. Study quality was assessed using the Newcastle-Ottawa scale, and potential publication bias was evaluated through funnel plots and the Egger test. Meta-analyses were conducted using Stata 17.0 software and involved a thorough examination of 98,397 studies. Out of these, eight studies originating from Eastern and Southern Africa, recognized as esophageal cancer hotspots on the continent, met the eligibility criteria. The analysis revealed a non-significant association between HIV infection and esophageal cancer risk (odds ratio = 1.34 [95% confidence interval, 0.85-2.12]; with 0.26 as p-value of overall effects). The Egger test yielded a p-value of 0.2413, suggesting the absence of publication bias. In summary, this systematic review and meta-analysis indicate that there is no established causal link between HIV infection and esophageal cancer risk. However, further research is essential to delve into the potential mechanisms underlying this relationship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".