Hidden in plain sight – Survival consequences of baseline symptom burden in women with recurrent ovarian cancer
Bibliographic record
Abstract
OBJECTIVE: To describe the baseline symptom burden(SB) experienced by patients(pts) with recurrent ovarian cancer(ROC) prior and associations with progression free survival (PFS) and overall survival (OS). METHODS: We analysed baseline SB reported by pts. with platinum resistant/refractory ROC (PRR-ROC) or potentially‑platinum sensitive ROC receiving their third or greater line of chemotherapy (PPS-ROC≥3) enrolled in the Gynecologic Cancer InterGroup - Symptom Benefit Study (GCIG-SBS) using the Measure of Ovarian Symptoms and Treatment concerns (MOST). The severity of baseline symptoms was correlated with PFS and OS. RESULTS: The 948 pts. reported substantial baseline SB. Almost 80% reported mild to severe pain, and 75% abdominal symptoms. Shortness of breath was reported by 60% and 90% reported fatigue. About 50% reported moderate to severe anxiety, and 35% moderate to severe depression. Most (89%) reported 1 or more symptoms as moderate or severe, 59% scored 6 or more symptoms moderate or severe, and 46% scored 9 or more symptoms as moderate or severe. Higher SB was associated with significantly shortened PFS and OS; five symptoms had OS hazard ratios larger than 2 for both moderate and severe symptom cut-offs (trouble eating, vomiting, indigestion, loss of appetite, and nausea; p < 0.001). CONCLUSION: Pts with ROC reported high SB prior to starting palliative chemotherapy, similar among PRR-ROC and PPS-ROC≥3. High SB was strongly associated with early progression and death. SB should be actively managed and used to stratify patients in clinical trials. Clinical trials should measure and report symptom burden and the impact of treatment on symptom control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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".