Risk Factors Related to Esophageal Cancer, a Case-Control Study in Herat Province of Afghanistan
Bibliographic record
Abstract
BACKGROUND: The Herat province of Afghanistan is located on the Asian Esophageal Cancer Belt (AECB), a wide area in Central and Eastern Asia where very high rates of esophageal cancer (EC) have been observed. Several risk factors have been reported in the AECB Region by previous studies. Considering lack of information in Afghanistan on this issue, a study was conducted to determine the major risk factors related to EC in order to guide protective measures. METHODS: A population-based case-control study was performed from July 2015 to August 2016 among 657 EC patients in the Herat Province and 180 histopathological confirmed cases and 189 controls were interviewed. A structured questionnaire was used and face-to-face interviews were conducted. RESULTS: Low body mass index (BMI), low socio-economic status, family history of EC, consumption of dark tea, very hot beverage and qulurtoroosh were found to be statistically significant for EC and esophageal squamous cell carcinoma (ESCC) in univariate analyses. According to multivariate analyses, sex (OR=2.268; 95% CI=1.238-4.153), very hot beverages (OR=2.253; 95% CI=1.271- 3.996), qulurtoroosh (OR=5.679; 95% CI=1.787-18.815), dark tea (OR=2.757; 95% CI=1.531-4.967), high previous BMI (OR=0.215; 95% CI=0.117-0.431) and low socio-economic status (OR=1.783; 95% CI=1.007-3.177) were associated with ESCC. Being male was found to increase the risk of ESCC with OR=2.268 (95% CI=1.238-4.153). CONCLUSION: Consuming very hot beverages dark tea and a local food, qulurtoroosh, were found as important risk factors for EC. Our findings warrant further studies and necessitate the implementation of protective measures for EC which is one of the leading cancers in the region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".