Baseline predictors of early treatment failure in patients with platinum resistant/refractory (PRR) and potentially platinum sensitive (PPS ≥ 3) recurrent ovarian cancer (ROC) receiving ≥ 3 lines of chemotherapy: The Gynaecologic Cancer Intergroup (GCIG) Symptom Benefit Study (SBS).
Bibliographic record
Abstract
5564 Background: Women with PRR/PPS ≥ 3 ROC are a heterogeneous group with unpredictable response to palliative chemotherapy (PC). GCIG SBS recently completed recruitment of 949 patients treated with PC. Primary aim is to validate an instrument to measure symptom benefit; secondary aims include identifying factors that predict early progression. 25% of patients with PRR-ROC received < 8 weeks of PC. Methods: Physicians recorded baseline characteristics, symptoms (symptomatic ascites, cramping abdominal pain), site/extent of disease and prespecified lab values. Association between baseline characteristics and progression-free survival (PFS) was assessed using time-to-event methods. Median PFS was calculated according to clinically relevant categories and log-rank test applied to assess prognostic value. Cox regression was used to compute hazard ratios and 95% CI to assess the effect of variables on PFS. Results: Sufficient follow up for analysis of PFS was available in 791 patients. Median PFS and overall survival were 4.3 (95% CI: 3.9-4.9) and 12.9 months (95% CI: 11.4-14.0) respectively. In univariate analysis factors with statistically significant associations with PFS included: haemoglobin, PRR-ROC, ascites and abdominal cramps, nodal disease, thrombocytosis, CA125 > 1000, LDH > 600, ECOG status, and elevated c reactive protein. Non-significant factors included: visceral metastases, albumin < 25, lymphocytes < 0.5, tumour volume. Significant variables in multivariable analysis included: ECOG ≥ 2 (HR 1.61 95% CI 1.18-2.19 p = 0.003); nodal disease (HR 1.37 95%CI 1.13-1.67 p = 0.002); ascites (HR 1.54 95%CI 1.24-1.92 p = 0.0001); platinum resistant vs. sensitive (HR 1.39 95%CI 1.12-1.72 p = 0.002), CA125 > 1000 (HR 1.35 95%CI 1.09-1.67 p = 0.005); LDH > 600 (HR 1.88 95%CI 1.36-2.60 p = 0.0001). Conclusions: Several simple clinical variables help predict patients who progress rapidly and will be used to construct prognostic models to aid clinical decisions and trial stratification for clinical trials in PRR/PPS ≥ 3 ROC Clinical trial information: 12607000603415.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".