Mucinous appendiceal neoplasms with or without pseudomyxoma peritonei: a review
Bibliographic record
Abstract
Mucinous appendiceal neoplasms (MANs) are rare tumours and the primary cause of pseudomyxoma peritonei. These tumours have a much more benign course than typical colorectal cancers, generally growing for many years before giving any clinical signs. The spectrum of presentations, tumour stages and the underlying cytology is very wide, warranting from the simplest operation like an appendicectomy to the most complicated operation like a complete cytoreduction surgery and hyperthermic intraperitoneal chemotherapy. Fortunately, most patients can be offered a curative treatment, but limiting operative morbidity without compromising oncologic outcomes is the biggest challenge in managing these patients. Histopathology is the cornerstone of decision making for MANs, but is also subject to ongoing debate because of a lack of terminology consensus amongst pathologists. Combined with the rarity of this disease, the multiple histopathologic classification updates of MANs explain the ongoing confusion amongst clinicians in regard to individual optimal treatment. This review will cover the most recent histological classification of MANs and attempt to clarify optimal management of patients with different clinical presentation and histologic combinations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".