S222 Endoscopic Scoring Indices for Assessing Disease Severity in Familial Adenomatous
Bibliographic record
Abstract
Introduction: Several therapeutics are in development for familial adenomatous polyposis (FAP) to reduce polyp burden, the incidence of cancer and prevent or postpone surgery. However, there is limited consensus on the optimal method for measuring disease severity in FAP. We aimed to systematically review existing endoscopic severity indices for FAP. Methods: We searched MEDLINE, EMBASE and the Cochrane Library from inception to May 22, 2023 to identify studies that evaluated endoscopic disease severity and severity in children and adults with FAP. Results: A total of 94 studies were included. We evaluated component items of scoring indices, such as polyp count, polyp size and histology, and the scoring indices themselves (Table 1). Partial validation was observed for polyp count and size. The most common reported scoring index was the Spigelman classification system, which was used for assessing the severity of duodenal involvement. A single study reported almost perfect inter- and intra-observer agreement for this system. The InSIGHT polyposis staging system, which was used for assessing colorectal polyp burden has been partially validated. It showed substantial inter-observer reliability, however it lacked intra-observer reliability. Novel criteria for high-risk gastric polyps was developed and assessed for inter-observer reliability; however it showed a poor level of agreement. Another scoring index assessing the anal transition zone has not undergone validation. Conclusion: There are no fully validated endoscopic disease severity indices for FAP. Development and validation of reliable and responsive endoscopic disease severity instrument will be informative for clinical care, research and to assess the impact of pharmacological therapies on polyp burden in FAP. Table 1. - Characteristics of Included Studies Total studies (n = 94) Scoring items 57 (60.6%) Polyp count 52 (55.3%) Gastric 10 (10.6%) Duodenal and jejunal 11 (11.7%) Colorectal 33 (35.1%) Pouch 6 (6.4%) Polyp size 20 (21.3%) Gastric 5 (5.3%) Duodenal and jejunal 8 (8.5%) Colorectal 4 (4.3%) Pouch 4 (4.3%) Polyp histology 9 (9.6%) Gastric 2 (2.1%) Duodenal and jejunal 4 (4.3%) Colorectal 0 Pouch 3 (3.2%) Scoring indices 37 (39.4%) Spigelman classification 33 (35.1%) InSiGHT Polyposis Staging System (IPSS) 2 (2.1%) Grade severity of anal transition zone 1 (1.1%) Criteria to identify high risk gastric polyps 1 (1.1%)
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".