A concise review towards defining the exposome of oesophageal cancer in sub-Saharan Africa
Bibliographic record
Abstract
CONTEXT: Oesophageal cancer (EC) is among the common causes of illness and death among all cancers worldwide. Advanced EC has a poor prognosis, with worse outcomes observed in low-income settings. Oesophageal squamous cell carcinoma (ESCC) is the most common EC histology reported globally, with the highest ESCC incidence rates in the 'Asian Belt' and the African EC corridor. While the aetiology of ESCC is well-documented in the 'Asian belt', data for the African EC corridor and the entirety of sub-Saharan Africa (SSA) are fewer. OBJECTIVE: To help address gaps in ESCC aetiology in SSA, we critically evaluated evidence of lifestyle, environmental, and epigenetic factors associated with ESCC risk and discussed prospects of defining ESCC exposome. DATA INCLUSION: Unlimited English and non-English articles search were made on PubMed Central and Web of Science databases from January 1970 to August 2021. In total, we retrieved 999 articles and considered meta-analyses, case-control, and cohort studies. The quality of individual studies was assessed using the Newcastle-Ottawa scale. DATA EXTRACTION: Details extracted include the year of publication, country of origin, sample size, comparators, outcomes, study subjects, and designs. DATA ANALYSIS: Together, we assessed 13 case-control studies and two meta-analyses for the effect of lifestyle or environmental exposures on ESCC risk. Again, we evaluated seven case-control studies and one meta-analysis regarding the role of epigenetics in ESCC tumorigenesis. RESULTS: In general, evidence of ESCC aetiology points to essential contributions of alcohol, tobacco, hot beverages, biomass fuel, and poor oral health/hygiene, although more precise risk characterisation remains necessary. CONCLUSION: We conclude that ESCC in SSA is a multifactorial disease initiated by several external exposures that may induce aberrant epigenetic changes. The expanding aetiological research in this domain will be enhanced by evidence synthesis from classical and molecular epidemiological studies spanning the external and internal exposome.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".