Hope, Quality of Life, and Benefit From Treatment in Women Having Chemotherapy for Platinum-Resistant/Refractory Recurrent Ovarian Cancer: The Gynecologic Cancer Intergroup Symptom Benefit Study
Bibliographic record
Abstract
Chemotherapy for platinum-resistant/refractory ovarian cancer is motivated by the hope of benefit. We sought to determine the relationships between: (a) trait hope, expectation of symptom benefit from chemotherapy, and anxiety and depression; (b) hope and perceived efficacy of chemotherapy; and (c) unfulfilled hope (where expectations for benefit are not fulfilled) and depression. Methods. Adult patients enrolled within stage 1 of the Gynecologic Cancer Intergroup Symptom Benefit Study were included. Patient. Reported outcomes were collected from 126 women with predominantly platinum-resistant ovarian cancer at baseline, prior to the first four treatment cycles (12-16 weeks), and four weeks after completing chemotherapy or at disease progression, whichever came first. Associations were assessed with Spearman rank correlation coefficient (r) and odds ratio. Results. Trait hope and expectation of symptom benefit from chemotherapy were weakly correlated with each other (r = 0.25). Trait hope, but not expectation of symptom benefit, was negatively correlated with anxiety (r = -0.43) and depression (r = -0.50). The smaller the discrepancy between perceived and expected symptom benefit, the less likely the patient was to have scores indicative of depression (odds ratio: 0.68; 95% confidence interval: 0.49-0.96; p = .026). Conclusion. Trait hope and expectation of symptom benefit from chemotherapy appear to be distinct and independent of the aspects of quality of life and scores for depression. Hope did not appear to affect perceived efficacy of chemotherapy in alleviating symptoms, but women whose expectation of symptom benefit from chemotherapy was not fulfilled were more likely to have scores indicative of depression. It may be preferable to encourage hope toward achievable goals rather than toward benefits from chemotherapy.
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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 | 0.003 |
| 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 | 0.001 |
| 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".