Early Detection and Age-Comparative Analysis of Colorectal Cancer Screening: Insights from the Turkish Population
Bibliographic record
Abstract
Background: This study aimed to evaluate the diagnostic yield of colonoscopy in asymptomatic individuals aged 45–49 years compared with those aged 50–54 years in a Turkish population, providing insights into region-specific screening strategies. Methods: This retrospective multicenter study was conducted across three tertiary endoscopy units in Turkey. Screening colonoscopy data from 3943 asymptomatic individuals aged 45–54 years between 2018 and 2023 were analyzed. The patients were stratified into two groups: 45–49 years (Group 1) and 50–54 years (Group 2). Demographic characteristics, polyp size, histological features, and prevalence of early-onset advanced colorectal neoplasia (EAO-aCRN) were assessed. Results: A total of 3943 patients were included, with 862 in Group 1 (45–49 years) and 3081 in Group 2 (50–54 years). The polyp detection rate was 16.6% in Group 1 and 22.9% in Group 2 (p < 0.001). The adenoma detection rates were 10.8% and 13.9% in Groups 1 and 2, respectively (p = 0.018). The advanced polyp detection rates were 3.2% and 7.3% in Groups 1 and 2, respectively (p < 0.001). Mean polyp size was 6.5 ± 5.1 mm in Group 1 and 8.8 ± 8.4 mm in Group 2 (p < 0.001). The mean number of polyps per patient was 1.5 ± 0.8 in Group 1 and 1.9 ± 1.6 in Group 2 (p = 0.023). Advanced neoplasia was detected in 16.6% of Group 1 patients compared with 22.9% of Group 2 patients (p < 0.001). Conclusions: While CRC screening at age 45 demonstrated lower detection rates of polyps and advanced neoplasia than at age 50, the higher prevalence of EAO-CRN among 45–49-year-olds in Turkey underscores the importance of early screening in high-risk populations. Tailored regional strategies incorporating individual risk factors are crucial for optimizing CRC prevention policies.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".