S2303 Temporal Trends in the Mortality of Gastric Malignancies in Canada Over the Past 3 Decades
Bibliographic record
Abstract
Introduction: Gastric malignancies impose paramount global health burden due to the resultant morbidity and mortality. Therefore, thorough evaluation of the temporal trends in the mortality of gastric malignancies in Canada over the past 3 decades is mandated to effectively introduce effective measures at therapeutic and preventative level. Methods: The temporal trends in gastric cancer-related mortality in Canada over the past 30 years was initially evaluated by accessing data from the Global Burden of Disease 2019 database. Subsequently, Joinpoint Analysis software (v 5.2.0, National Cancer Institute) was utilized to calculate the annual percentage change (APC) and the average annual percentage change (AAPC), stratified by gender and age. Results: Over a span of 3 decades, a total of 81,492 gastric cancer-related deaths were reported in Canada with a male predominance of 59.5%. Stratification by age revealed a statistically significant decline in gastric cancer-related mortality across all age groups, with individuals aged 75 years and older witnessing the highest decline (AAPC -0.78; 95% confidence interval [CI] -0.93 to -0.65; P< 0.001). A similar decline in gastric cancer-related deaths, but to a lesser extent, was noted in the 50-74-years-old age group with an AAPC of -0.68 (95%CI -0.81 to -0.58; P< 0.001). Whereas the lowest decline in gastric cancer-related mortality was observed in individuals aged 15-49 years old with an AAPC of -0.47 (95%CI -0.62 to -0.31; P< 0.001) (Figure 1). Gender stratification demonstrated a statistically significant decline in gastric cancer-related deaths with females having higher decrease than males (AAPC -1.18; 95%CI -1.23 to -1.09; P< 0.001 in females and AAPC -0.37; 95%CI -0.56 to -0.21; P< 0.001). Conclusion: Over the period 1990-2019, gastric cancer-related mortality in Canada witnessed a significant decline across all age groups and in both men and women. Such decline in Canada is similar to observed trends in other developed countries and can be largely attributed to advanced treatment modalities in terms of endoscopic interventions, surgical approaches, and chemotherapeutics.Figure 1.: The annual percentage change of gastric cancer-related deaths stratified by age in Canada during the period 1990-2019.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".