Disparities in oesophageal cancer risk by age, sex, and nativity in Kuwait:1980–2019
Bibliographic record
Abstract
BACKGROUND: This cross-sectional cohort study assessed the inequalities in oesophageal carcinoma risk by age, sex and nativity in Kuwait: 1980-2019. METHODS: Using oesophageal cancer incidence data from the Kuwait National Cancer Registry, relevant Kuwaiti population data and World Standard Population as a reference, age-standardized incidence rates (ASIR) (per 100,000 person-years) overall and by subcohorts were computed. The incident oesophageal cancer cases count was overdispersed with excessive structural zeros, therefore, it was analyzed using multivariable zero-inflated negative binomial (ZINB) model. RESULTS: Overall ASIR of oesophageal cancer was 10.51 (95% CI: 6.62-14.41). The multivariable ZINB model showed that compared with the younger age category (< 30 years), the individuals in higher age groups showed a significant (p < 0.001) increasing tendency to develop the oesophageal cancer. Furthermore, compared with the non-Kuwaiti residents, the Kuwaiti nationals were significantly (p < 0.001) more likely to develop oesophageal cancer during the study period. Moreover, compared with 1980-84 period, ASIRs steadily and significantly (p < 0.005) declined in subsequent periods till 2015-19. CONCLUSIONS: A high incidence of oesophageal cancer was recorded in Kuwait, which consistently declined from 1980 to 2019. Older adults (aged ≥ 60 years) and, Kuwaiti nationals were at high risk of oesophageal cancer. Focused educational intervention may minimize oesophageal cancer incidence in high-risk groups in this and other similar settings. Future studies may contemplate to evaluate such an intervention.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".