Colorectal cancer screening guidelines for average-risk and high-risk individuals: A systematic review
Bibliographic record
Abstract
AIMS: This review aims to summarize the different colorectal cancer guidelines for average-risk and high-risk individuals from various countries. METHODS: August 2022), was performed at EBSCOhost, JSTOR, PubMed, ProQuest, SAGE, and ScienceDirect. RESULTS: A total of 18 guidelines were included in this review. Most guidelines recommended screening between 45 and 75 years for average-risk individuals. Recommendations regarding colorectal cancer screening in high-risk individuals were more varied and depended on the risk factor. For high-risk individuals with a positive family history of colorectal cancer or advanced colorectal polyp, screening should begin at age 40. Some frequently suggested screening modalities in order of frequency are colonoscopy, FIT, and CTC. Furthermore, several screening intervals were suggested, including colonoscopy every 10 years for average-risk and every 5-10 years for high-risk individuals, FIT annually in average-risk and every 1-2 years in high-risk individuals, and CTC every five years for all individuals. CONCLUSION: All individuals with average-risk should undergo colorectal cancer screening between 45 and 75. Meanwhile, individuals with higher risks, such as those with a positive family history, should begin screening at age 40. Several recommended screening modalities were suggested, including colonoscopy every 10 years in average-risk and every 5-10 years in high-risk, FIT annually in average-risk and every 1-2 years in high-risk, and CTC every five years.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".