Abstract C027: Association of Binge Drinking with Early-Onset Colorectal Cancer: A Comparison to Late-Onset Cancers
Bibliographic record
Abstract
Abstract Objective: With increasing incidence, identifying modifiable risk factors contributing to early-onset colorectal cancer (EOCRC) is critically important. We examined if history of binge drinking was more associated with EOCRC than with late-onset colorectal cancer (LOCRC). Methods: Data from the Ohio Colorectal Cancer Prevention Initiavtive (OCCPI), a multi-center study conducted between 2013-2016, were used in this case-case comparison of EOCRC to LOCRC. Ohio residents with newly diagnosed primary colorectal cancers (CRC) were included in the OCCPI. Binge drinking was self-reported for the year before CRC diagnosis and during the decade in the particpants' life with the heaviest alcohol consumption. Binge drinking was defined as consuming >3 drinks within a two-hour period for both men and women. EOCRC cases were defined as those aged <50 at CRC diagnosis and LOCRC cases as those > age 49. The association between binge drinking and EOCRC was assessed with logistic regression, adjusting for sex, race, education, smoking status, and family history of CRC. Results: Included in the OCCPI were 323 EOCRC and 1,256 LOCRC cases. Engaging in binge drinking the year before one's CRC diagnosis was more associated with EOCRC than LOCRC (OR:3.15, 95%CI:2.31-4.30). Those with EOCRC were also more likely to report binge drinking during the time in their life with the heaviest alcohol consumption than LOCRC cases (OR:3.22, 95%CI:2.37-4.40). When we compared the youngest EOCRC ( age 59), the unadjusted associations observed were stronger with wider confidence intervals (OR: 6.65, 95%CI: 3.86-11.48; OR:4.44, 95%CI: 2.63-7.53 for the year before CRC diagnosis and the decade of most consumption, respectively). Conclusions: Compared to LOCRC, those with EOCRC were more likely to engage in binge drinking. Interventions to reduce binge drinking, particularly among younger adults, may have potential for EOCRC prevention. Citation Format: Electra D. Paskett, Samantha Rees, Rachel Pearlman, Peter Shields, Heather Hampel, Jo Freudenheim. Association of Binge Drinking with Early-Onset Colorectal Cancer: A Comparison to Late-Onset Cancers [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 C027.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".