Mixed Ovarian Epithelial Carcinomas With Clear Cell and Serous Components are Variants of High-grade Serous Carcinoma
Bibliographic record
Abstract
There are conflicting data about chemoresistance and prognosis in ovarian clear cell carcinoma (CCC). This could be due to significant interobserver variation in the diagnosis of CCC and other ovarian surface epithelial tumors containing clear cells. Thirty-two cases previously diagnosed as CCC, high-grade ovarian serous carcinoma (SC), and mixed surface epithelial carcinoma (SEC) with clear cell and serous components were reviewed by 4 gynecologic pathologists blinded to the original diagnoses. Interobserver reproducibility was evaluated. Each case was also assessed using immunohistochemical markers Wilm tumor 1, estrogen receptor, and p53. The interobserver reproducibility was greatest for pure CCC (kappa of 0.82), and lowest for the mixed SEC (kappa of 0.32). Moderate agreement was seen in the pure SC category (kappa of 0.59). All pure SC and most mixed SEC presented as stage III or IV diseases. Most pure CCC presented as stage I or II diseases. Immunoreactivities of the mixed SECs were similar to those of pure SC, but significantly different from those of pure CCC for Wilm tumor 1 (P=0.0011 for both components), estrogen receptor (P=0.0003 for clear cell component, P=0.0001 for serous component), and p53 (P=0.0062 for both components). The serous and clear cell components of mixed SEC showed higher mitotic rates than pure CCC (P=0.004 and P=0.023, respectively), but the mitotic rate of pure SC was similar to the mixed SEC. We conclude that (1) pure CCC is reproducibly diagnosed. (2) The diagnosis of mixed ovarian SEC with clear cell component is not reproducible. (3) Mixed SEC with clear cell and serous components show similar stage, mitotic activities, and immunoreactivities to those of pure SC, and likely represent SC with clear cell changes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".