Reducing Uncertainty: Predictors of Stopping Chemotherapy Early and Shortened Survival Time in Platinum Resistant/Refractory Ovarian Cancer—The GCIG Symptom Benefit Study
Bibliographic record
Abstract
BACKGROUND: Clinicians and patients often overestimate the benefits of chemotherapy, and overall survival (OS), in platinum resistant/refractory ovarian cancer (PRROC). This study sought to determine aspects of health-related quality of life and clinicopathological characteristics before starting chemotherapy that were associated with stopping chemotherapy early, shortened survival, and death within 30 days of chemotherapy. MATERIALS AND METHODS: This study enrolled women with PRROC before starting palliative chemotherapy. Health-related quality of life was measured with EORTC QLQ-C30/QLQ-OV28. Chemotherapy stopped within 8 weeks of starting was defined as stopping early. Logistic regression was used to assess univariable and multivariable associations with stopping chemotherapy early and death within 30 days of chemotherapy; Cox proportional hazards regression was used to assess associations with progression-free and OS. RESULTS: < .012). CONCLUSION: Women with low GHS, RF, or PF before starting chemotherapy were more likely to stop chemotherapy early, with short OS. Self-ratings of GHS, RF, and PF could improve patient-clinician communication regarding prognosis and help decision-making in women considering chemotherapy for PRROC. IMPLICATIONS FOR PRACTICE: Measuring aspects of health-related quality of life when considering further chemotherapy in platinum resistant/refractory ovarian cancer (PRROC) could help identify women with a particularly poor prognosis who are unlikely to benefit from chemotherapy and could therefore be spared unnecessary treatment and toxicity in their last months of life. Self-ratings of global health status, role function, and physical function could improve patient-clinician communication regarding prognosis and help decision-making in women considering chemotherapy for PRROC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".