A161 IMPACT OF EARLY-ONSET COLORECTAL CANCER ON DISABILITY-ADJUSTED LIFE YEARS IN CANADA: 1990 TO 2019
Bibliographic record
Abstract
Abstract Background Colorectal cancer is the third most common malignancy and remains a leading cause of potentially preventable morbidity and mortality. Early-onset colorectal cancer (EOCRC) is a growing public health focus, particularly in North America, where incidence rates have increased over time. Aims Recognizing that EOCRC affects patients in the prime of their life, we aimed to estimate the impact of EO-CRC on disability-adjusted life years (DALYs) lost in Canada between 1990 and 2019. Methods We used the Global Burden of Diseases (GBD) Study to assess temporal trends in incidence, mortality and DALYs for EOCRC (patients ampersand:003C50 years old) in Canada between 1990 and 2019. Point estimates are available from http://ghdx.healthdata. org/gbd-results-tool. Rates were estimated per 100 0000 individuals at risk and stratified by age and sex. Annual percentage changes (APC) were estimated using joinpoint regression with 95% confidence intervals (CIs). Results In 2019, the incidence, mortality and corresponding DALYs rates for EOCRC were 15.67 (95% CI 11.58, 20.81), 3.19 (95% CI 2.81, 3.61), and 161.88 (95% CI 142.50, 183.53) per 100,000 individuals, respectively. Overall incidence increased significantly during the study period by 1.12%/year (95% CI 0.91%, 1.62%). An analysis of the temporal trends demonstrates that the most significant increase in incidence in EOCRC occurred between 2000 - 2006 with an APC of 3.19% (95% CI 2.40%, 3.99%), which was primarily driven by an increased incidence in men. Mortality (APC 3.30%, 95% CI 2.41%, 4.19%) and DALYs (APC 3.28%, 95% CI 2.34%, 4.22%) for EOCRC also significantly increased for males between 2001 - 2006. Conclusions Our study reveals a substantial burden in early-onset colorectal cancer in Canada, with a significant increase in incidence over time and over 160 DALYs/100,000 population. Figure 1: Incidence (A), Mortality (B) and DALYs (C) for EOCRC in Canada between 1990 and 2019 with 95% CIs. Funding Agencies None
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| 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) | 0.004 | 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".