Survival and modelled cancer antigen-125 ELIMination rate constant K score in ovarian cancer patients in first-line before poly(ADP-ribose) polymerase inhibitor era: A Gynaecologic Cancer Intergroup meta-analysis
Bibliographic record
Abstract
BACKGROUND: In patients with advanced ovarian cancer, the modelled CA-125 ELIMination rate constant K (KELIM) is an early indicator of the tumour intrinsic chemosensitivity. We assessed the prognostic and surrogate values of KELIM with respect to those of surgery outcome (based on post-operative residual lesions) in the Gynaecologic Cancer Intergroup (GCIG) individual patient data meta-analysis MAOV (Meta-Analysis in OVarian cancer) built before the emergence of poly(ADP-ribose) polymerase (PARP) inhibitors. METHODS: The dataset was split into learning and validation cohorts (ratio 1:2). The individual modelled KELIM values were estimated, standardised by the median value, then scored as unfavourable (<1.0) or favourable (≥1.0). Overall survival (OS) and progression-free survival (PFS) analyses were performed with a two-step meta-analytic approach and surrogacy through a two-level meta-analytic model. RESULTS: KELIM was assessed in 5884 patients from eight first-line trials (learning, 1962; validation, 3922). A favourable KELIM score was significantly associated with longer OS (validation set, median, 78.8 versus 28.4 months, hazard-ratios [HR] 0.46, 95% confidence interval [CI], 0.41-0.50, C-index 0.68), and longer PFS (validation set, median 30.5 versus 9.8 months, HR 0.49, 95% CI, 0.45-0.54, C-index 0.68), as were International Federation of Gynaecology and Obstetrics (FIGO) stage and debulking surgery outcome. Three prognostic groups were identified based on the surgery outcome and KELIM score, with large differences in OS (105.1, ∼45.0, and 22.1 months) and PFS (58.1, ∼15.0, and 8.0 months). Surrogacy for OS and for PFS was not established. CONCLUSION: KELIM is an independent prognostic biomarker for survival, complementary to surgery outcome, representing a new determinant of first-line treatment success.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.030 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".