Impact of Referral Center Pathology Review on Diagnosis and Management of Patients With Appendiceal Neoplasms
Bibliographic record
Abstract
CONTEXT.—: Data regarding the clinical impact of subspecialist pathology review of appendiceal neoplasms are limited. OBJECTIVE.—: To determine whether pathology review by gastrointestinal pathologists at a tertiary-care referral center resulted in significant changes in the diagnosis and clinical management of appendiceal neoplastic lesions. DESIGN.—: We conducted a retrospective review of all patients with an initial diagnosis of appendiceal neoplasm referred to a tertiary-care referral center in Ontario, Canada, from 2010-2016. The discordance rate between original and review pathology reports, the nature of discordances, and the impact of any discordance on patient management were recorded. RESULTS.—: A total of 145 patients with appendiceal lesions were identified (low-grade mucinous appendiceal neoplasm [n = 79], invasive mucinous adenocarcinoma [n = 12], "colorectal type" adenocarcinoma [n = 12], goblet cell carcinoid and adenocarcinomas ex goblet cell carcinoid [n = 24], and other lesions/neoplasms [n = 20]). One or more changes in diagnoses were found in 36 of 145 cases (24.8%), with changes within the same category of interpretation (n = 10), stage (n = 7), grade (n = 6), and categoric interpretation (n = 5) being the most common. In 10 of 36 patients (28%), the diagnostic change led to a significant change in management, including recommendation for additional surveillance, systemic chemotherapy, additional surgery, or discontinuation of surveillance. CONCLUSIONS.—: Subspecialist pathology review of appendiceal neoplastic lesions led to a change in diagnosis in 36 of 145 cases (24.8%), of which nearly 30% (10 of 36 cases) led to a change in clinical management. The overall rate of clinically significant discordances was 7% (10 of 145). Our findings suggest that subspecialist pathology review of appendiceal neoplasms referred to specialized centers is justified.
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 | 0.006 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".