Key Risk Factors, Sex Differences, and the Influence of High-Intensity Exercise on Colorectal Carcinogenesis: A 10-Year Cohort Study Based on 1,120,377 Individuals from the NHISS Data
Bibliographic record
Abstract
Colorectal cancer (CRC) is the third most common cancer globally. Therefore, this study aims to examine data from the National Health Insurance Sharing Service (NHISS) to investigate factors influencing colon cancer incidence, focusing on key variables and optimal cutoff points. The patient cohort from the NHISS database included 1,120,377 individuals aged 1–85 years. CRC data were retrieved using diagnostic codes from the Korean Standard Classification of Diseases and Causes of Death. Analyses included logistic regression and receiver operating characteristic curve assessments. In this retrospective cohort study, 1,120,377 patients were analyzed for over 10 years, including 2802 with CRC via propensity score matching (PSM). Key risk factors were blood pressure, fasting blood sugar, liver somatic index, alcohol consumption, smoking duration, and hemoglobin levels. Patients with CRC showed sex differences in gamma-glutamyl transpeptidase (GGT). High-intensity exercise (3 days/week) reduced CRC risk by 26% (p < 0.05). Optimal threshold points for GGT and Charlson Comorbidity Index (CCI) were 23.50 U/L (AUC, 0.52) and 1.50 (AUC, 0.58), respectively. CCI scores were higher in patients with cancer, especially men with peptic ulcers and both sexes with metastatic cancer (p < 0.01). Our findings reveal new risk factors and interventions, including tailored exercise programs for CRC management, highlighting the importance of enhanced preventive strategies and personalized care.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".