Bibliographic record
Abstract
In Reply: We thank the author for their valuable comments and engagement with our research. Our study assessed the characteristics, management, and incidence of high-grade serous carcinoma in 107 patients across Canada diagnosed with an isolated serous tubal intraepithelial carcinoma lesion.1 The cumulative incidence of high-grade serous carcinoma was 1.1% (95% CI, 0.1–5.3%) at 2 years, 5.7% (95% CI, 1.8–13.1%) at 5 years, and 19.7% (95% CI, 8.9–33.5%) at 7 years, consistent with recent literature.2,3 These estimates were derived from a pan-Canadian cohort with heterogenous genetic and ethnic backgrounds. Ethnicity data were not available due to the retrospective study design. A univariate Cox proportional hazards model including age, germline BRCA1/2 status, initial procedure, surgery indication, and treatment groups revealed no significant predictive factor. Small sample size and few events limit analyses in rare diseases, which we attempted to mitigate through a national consortium. This underscores the need for an international prospective registry for isolated serous tubal intraepithelial carcinoma. Among the 45 patients with confirmed serous tubal intraepithelial carcinoma, cumulative incidence of high-grade serous carcinoma was 2.6% at 2 and 5 years (95% CI, 0.2–11.7%). Three patients developed high-grade serous carcinoma at 17.2, 69.7, and 73.1 months, respectively. The last case was not captured in the 2-year and 5-year cutoffs and therefore was not shown in the figure. No competing events of death occurred; 43 cases were censored. Patients initially included but later found to have a serous tubal intraepithelial lesion or no serous tubal intraepithelial carcinoma on pathology review may still be at risk of high-grade serous carcinoma and should be assessed separately, but this was beyond our study's scope. Finally, we agree that opportunistic salpingectomy is an essential risk-reducing strategy for high-grade serous carcinoma in the general population.4 In addition, our findings highlight the importance of SEEFIM protocol and expert gynecologic pathology review for serous tubal intraepithelial carcinoma lesions until standardized algorithms are validated to ensure that no serous tubal intraepithelial carcinoma or early high-grade serous carcinoma lesion is missed, which is critical for patient management and outcome.
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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 | 0.005 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.021 | 0.027 |
| Insufficient payload (model declined to judge) | 0.038 | 0.028 |
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".