Assigning site of origin in non-uterine high-grade serous cancers: Bridging the gap between research and clinical practice
Bibliographic record
Abstract
Background and aims: In research studies it is now evident that the majority of high-grade serous ovarian cancers (HGSC) starts in the fallopian tube. However, this is not reflected in clinical practice. The criteria for assigning tubal origin used in research studies rely on identifying serous tubal intraepithelial carcinoma (STIC), or tubal mucosa involvement (TMI) in fallopian tubes examined in toto (examined in 2-mm section). The clinical criteria currently used recommended by the FIGO (International Federation of Gynecology and Obstetrics) and WHO (World Heath Organization) are based on the location of the dominant tumour mass. Recently, a consensus proposal based on research criteria has been put forward by a group of academic pathologists for adoption in clinical practice. However, there are concrete difficulties in applying research criteria to clinical practice. The reason for this is that routinely examining the fallopian tubes in toto is perceived as difficult to implement, STIC is difficult to standardize, and TMI has been challenged as a reliable criterion. This study aims to bridge the gap between research studies and clinical practice by evaluating what is currently done in clinical practice in comparison to the new recommendations relating to correct assignment of fallopian tube primary. This is done by examining all consecutive cases reported as ovarian, primary peritoneal, tubal cancer in a tertiary care gynecologic oncology center over a seven-year period. Therefore, the specific aim of this study is to evaluate which of the criteria proposed is already in use at our institution, and which is not and should be implemented. Methods: Retrospective analysis of all surgical pathology reports signed out as cancer of the ovary, peritoneum or fallopian tubes at a publically funded cancer centre relating to cytoreductive surgeries performed between January 2007 and December 2013. Surgical pathology reports were examined to identify pragmatic criteria for clinical adoption. Results: During the study period of 277 cases, 215 (125 HGSC and 90 non-HGSCs) had fallopian tubes examined in toto, which represents 91% of the cases. The primary was assigned as ovary, peritoneum, fallopian tube, tubo-ovarian and uncertain in 48%, 17.6%, 19.2%, 8.8%, and 6.4% respectively of HGSC cases vs. 95.6%, 1.1%, 3.3%, 0%, and 0% respectively of non-HGSCs. (STIC) was seen only in 12.8% of HGSC and TMI in 56%. If TMI was used systematically as a criterion to assign tubal origin, the assigned primaries would be: 29.6% primary ovarian cancers, 11.2% primary peritoneal, 56 % tubal and 3.2% uncertain. We then compared the frequency of TMI in HGSC vs non-HGSCs and we found that only five cases of non-HGSCs had TMI. Discussion: These results suggest that all components of the proposed criteria, examination of the tubes in toto, identification of STIC and TMI, is already being done. However, it was not used to assign site of origin. Therefore, the proposed criteria appear to be implementable. Conclusion: Examination of the fallopian tubes in toto and meticulous reporting of TMI appear feasible in clinical practice and may help bridge the gap between research and clinical practice. Increasing the proportion of HGSC cases attributed to tubal primary and correctly assigning site of origin of HGSC is of clinical importance because it has implications for screening and early detection.Key words: fallopian tube cancer, STIC, tubal mucosa, origin of HGSC
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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 | 0.044 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 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".