Modification of Homologous Recombination Deficiency Score Threshold and Association with Long-Term Survival in Epithelial Ovarian Cancer
Bibliographic record
Abstract
New therapies, such as poly-ADP ribose polymerase inhibitors (PARPi), and immunotherapy treatments have generated great interest in enhancing individualized molecular profiling of epithelial ovarian cancer (EOC) to improve management of the disease. In EOC patients, putative biomarkers for homologous recombination deficiency (HRD), microsatellite instability (MSI), and tumor mutational burden (TMB) were characterized and correlated with survival outcomes. A series of 300 consecutive EOC patients were enrolled. Patients underwent neoadjuvant chemotherapy (n = 172) or primary cytoreductive surgery (n = 128). Molecular profiling and survival analyses were restricted to the primary cytoreductive surgery cohort due to tissue availability. All patients underwent germline testing for HRD- and MSI-related gene mutations. When sufficient tissue was available, screening for somatic BRCA1/2 mutations, BRCA1 promoter methylation, HRD score (a measure of genomic instability), MSI, and TMB testing were performed. HRD score ≥33 was associated with improved overall survival on multivariable analysis. In the era of biomarker-driven clinical care, HRD score ≥33 may be a useful adjunctive prognostic tool and should be evaluated in future studies to predict PARPi benefits.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".