Abstract B017: Trends in early-onset colorectal, appendiceal, and anal tumour incidence by histological subtype in Australia from 1990 to 2020: A population-based time-series analysis
Bibliographic record
Abstract
Abstract Background: Early-onset bowel cancer incidence (age <50 years) has increased worldwide and is highest in Australia, but how trends vary across age, histology, and anatomical site remains unclear. We investigated appendiceal, proximal colon, distal colon, rectal, and anal cancer incidence trends by age and histology in Australia. Methods: Cancer incidence rate data were obtained from nation-wide cancer registries (1990–2020). Birth cohort-specific incidence rate ratios (IRRs) and annual percentage change were estimated using age-period-cohort modelling and joinpoint regression. Findings: Combining all malignant tumour histologies, early-onset incidence rose 5–9% annually, yielding 4,072 excess cases (1.5 per 100,000 person-years; 15% appendix, 28% colon, 48% rectum, 9% anus). Trends varied by site, period, and age: appendiceal cancer rose from 1990–2020 in 30–49-year-olds; colorectal cancers rose from around 1990–2010 in 20–29-year-olds and from 2010–2020 in 30–39-year-olds; anal cancer rose from 1990–2009 in 40–49-year-olds. Across sites, IRRs increased with successive birth cohorts since 1960. Adenocarcinoma incidence in the 1990s versus 1950s cohort was 2–3-fold for colorectum and 7-fold for appendix. The greatest subtype-specific increases occurred for appendiceal mucinous adenocarcinoma, colorectal non-mucinous adenocarcinoma, and anal squamous cell carcinoma. Colorectal neuroendocrine neoplasms, squamous cell carcinomas, and signet ring cell carcinomas rose across early-onset and later-onset strata. Interpretation: Appendiceal, colorectal, and anal cancer incidence is rising in Australia, with variation across age and histology. These generational shifts suggest evolving risk factor profiles and early-life exposures, highlighting the need to identify drivers of this growing burden. Citation Format: Aaron L. Meyers, James G. Dowty, Khalid Mahmood, Finlay A. Macrae, Christophe Rosty, Daniel D. Buchanan, Mark A. Jenkins. Trends in early-onset colorectal, appendiceal, and anal tumour incidence by histological subtype in Australia from 1990 to 2020: A population-based time-series analysis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr B017.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".