2016 IANS International Guidelines for Practice Standards in the Detection of Anal Cancer Precursors
Bibliographic record
Abstract
OBJECTIVES: To define minimum standards for provision of services and clinical practice in the investigation of anal cancer precursors. METHODS: After initial face to face meetings of experts at the International Papillomavirus meeting in Lisbon, September 17 to 21, 2015, a first version was drafted and sent to key stakeholders. A complete draft was reviewed by the Board of the International Anal Neoplasia Society (IANS) and uploaded to the IANS Web site for all members to provide comments. The final draft was ratified by the IANS Board on June 22, 2016. RESULTS: The essential components of a satisfactory high-resolution anoscopy (HRA) were defined. Minimum standards of service provision, basic competencies for clinicians, and standardized descriptors were established. Quality assurance metrics proposed for practitioners included a minimum of 50 HRAs per year and identifying 20 cases or more of anal high-grade squamous intraepithelial lesions (HSILs). Technically unsatisfactory anal cytological samples at first attempt in high-risk populations should occur in less than 5% of cases. Where cytological HSIL has been found, histological HSIL should be identified in ≥ 90% of cases. Duration of HRA should be less than 15 minutes in greater than 90% of cases. Problematic pain or bleeding should be systematically collected and reported by 10% or lesser of patients. CONCLUSIONS: These guidelines propose initial minimum competencies for the clinical practice of HRA, against which professionals can judge themselves and providers can evaluate the effectiveness of training. Once standards have been agreed upon and validated, it may be possible to develop certification methods for individual practitioners and accreditation of sites.
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 | 0.166 | 0.286 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.015 | 0.013 |
| Research integrity | 0.019 | 0.018 |
| Insufficient payload (model declined to judge) | 0.009 | 0.011 |
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".