Frequency of Serous Tubal Intraepithelial Carcinoma in Various Gynecologic Malignancies
Bibliographic record
Abstract
Serous tubal intraepithelial carcinoma (STIC) has been implicated in the pathogenesis of pelvic serous carcinoma. We hypothesized that, if this is the case, the frequency of STIC should be substantially lower in endometrial serous carcinomas, in nonserous gynecologic malignancies, and in benign gynecologic neoplasms than in ovarian or peritoneal serous carcinomas. From 2007 to 2009 the fallopian tubes of 342 consecutive gynecologic cases were entirely submitted for histology using the Sectioning and Extensively Examining the FIMbriated end protocol. This study included 300 of these cases (277 TAH-BSO, 23 BSO) after exclusion. The hematoxylin and eosin-stained slides from the fallopian tubes were independently reviewed by 2 gynecologic pathologists who were blinded to all other findings; disagreements were resolved by a third pathologist. Among 46 cases of ovarian malignancies, STIC was identified in 6 (18.8%) of 32 cases of serous carcinoma, but not in any other subtype. Similarly, STIC coexisted in 4 (14.3%) of 28 cases of endometrial serous carcinoma; however, no STIC was identified in any of the 74 cases of nonserous endometrial malignancies. STIC was identified in 2 (28.6%) of 7 cases of peritoneal serous carcinoma. No STIC was identified among 15 nongynecologic malignancies, 90 cases of benign conditions, and 27 cases of other conditions including 4 cases of cervical adenocarcinoma in situ and high-grade cervical intraepithelial lesions, 8 cases of endometrial atypical complex hyperplasias, and 15 cases of ovarian borderline tumors. In conclusion, the fallopian tube may be the origin of some pelvic serous carcinomas. Other possibilities that may explain the origin of pelvic high-grade serous carcinoma are discussed. Given that STIC coexisted with 14% of endometrial serous carcinomas, a more unifying theory may be that gynecologic serous carcinomas and STIC are multifocal lesions.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".