A Case-Control Study of Alcohol Consumption and Esophageal Cancer in the Northeast State of Mizoram, India
Bibliographic record
Abstract
Summary: Esophageal cancer is one of the main health issues in Mizoram. The risk factors of the disease are related to consumption of alcohol. There have not been any epidemiological studies on this subject in the state. The aim of the study is to assess the relationship between esophageal cancer and consumption of alcohol. Materials and Methods: A hospital based matched case-control study was conducted comprising of 138 cases with histologically confirmed diagnosis of esophageal cancer and 276 controls that were cancer and esophageal cancer disease free. Cases and controls matched by gender and age (± 5 years). Ratio of cases and controls were 1:2. A questionnaire was used to collect information on possible risk factors of esophageal cancer. The odds ratios (OR) and 95% confidence intervals (CI) for gastric cancer were calculated by a conditional logistic regression. Results: Cases had significantly lower education level. Most of the cases are from middle income class. After adjustment for consumption of betel quid, tobacco, smoking, body mass index (BMI), family history of cancer, education level and income level, higher risk of esophageal cancer was found for those who have the habit of consuming alcohol in the morning. After controlling for consumption of betel quid, tobacco, smoking, body mass index (BMI), family history of cancer, education level, income level, dietary habits, physical activity, consumption of Zu(locally brewed alcohol) and both Zu(locally brewed alcohol) and commercial alcohol(rum, whisky, vodka and beer, etc) are also associated with higher risk of esophageal cancer (O.R = 9.820, 95% CI = 2.029-47.523).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".