Assessment of a new system for primary site assignment in high‐grade serous carcinoma of the fallopian tube, ovary, and peritoneum
Bibliographic record
Abstract
AIMS: The available evidence indicates that most non-uterine high-grade serous carcinomas (HGSCs) arise from the fallopian tube (FT), but approaches to primary site assignment have not evolved to reflect this. The aim of this study was to assess the application of recently proposed criteria for site assignment. METHODS AND RESULTS: One hundred and fifty-one HGSCs from four centres were reviewed retrospectively. Sixty-three of 80 (79%) chemonaive (CN) and 45 of 71 (68%) post-neoadjuvant chemotherapy (NACT) cases were assigned as FT primaries with the new criteria, whereas 58 of 80 (73%) and 45 of 71 (63%) were assigned as ovarian primaries with traditional criteria (P < 0.0001). Of 111 prospectively collected HGSCs, with consistent detailed fimbrial examination, 44 of 53 (83%) CN and 44 of 58 (76%) NACT cases were assigned as FT primaries. The reproducibility of site assignment was tested in a subset of 50 cases: all four reviewing pathologists agreed on the primary site in 48 of 50 (96%) cases, and three of four agreed in 49 of 50 (98%) cases. Of the 53 prospectively studied CN cases, bilateral ovarian involvement (62%) was significantly more frequent than bilateral tubal involvement (12%, P < 0.0001), further supporting a tubal origin and ovarian metastasis in most cases. CONCLUSIONS: With currently accepted protocols, the proposed guidelines are easy to apply and result in consistent site assignment in non-uterine HGSCs. Most cases of non-uterine HGSC were considered to be primary FT neoplasms.
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 | 0.027 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".