Designing clinical and genetic guidelines of colorectal cancer screening as an effective roadmap for risk management.
Bibliographic record
Abstract
AIM: We aimed to present clinical and genetic guidelines of colorectal cancer screening for risk assessment of populations at risk. BACKGROUND: National guidelines can be used as a guide for choosing the method of screening for each individual. These guidelines facilitate decision making and support the delivery of cancer screening service. METHODS: In the first step, a comparative study was performed by using secondary data extracted from the literature review. Three countries (Canada, Australia and United States) were selected from 25 countries that are member in the International Cancer Screening Network (ICSN). The second step of study was qualitative survey. The study was based on the grounded theory approach. Study tool was semi-structured interview. Interviewing involves asking questions and getting answers from participants. 22 expert's perspectives about guidelines of colorectal cancer screening were surveyed. RESULTS: Screening program of selected countries was compared. Countries were surveyed by number of risk groups and subgroups, criteria for risk assessment, beginning age, recommendations, screening approaches and intervals. Australia and United States have three risk groups and Canada has two risk groups. Four risk groups were defined in the national guideline, including high risk, increased risk, average and low risk group. The high risk group comprises of 8 subgroups, increased risk group comprises of 3 subgroups and average risk group contain 4 subgroups. Approved clinical criteria for hereditary syndromes and the roadmap of genetic and pathologic survey were designed. CONCLUSIONS: Guidelines and pathways have a vital role in the quality improvement of CRC screening program. National guidelines were refined according to the environmental and genetic criteria of colorectal cancer in Iran. These guidelines provide evidence-based recommendations by risk groups. National pathways as a risk assessment tool can evaluate and improve the processes and outcomes of cancer screening in practice. One of the suggestions for future research is the designing expert system for real-time decision making during a clinical interaction.
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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 | 0.032 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".