Does Palliative Chemotherapy Palliate? Evaluation of Expectations, Outcomes, and Costs in Women Receiving Chemotherapy for Advanced Ovarian Cancer
Bibliographic record
Abstract
PURPOSE: The value of palliative chemotherapy in women with refractory and recurrent ovarian cancer is difficult to quantify, and little is known about patient expectations from these treatments. We evaluated in the current prospective study patient expectations, palliative outcomes of chemotherapy, and the inherent resource utilization in patients undergoing second- or third-line chemotherapy for recurrent or refractory advanced ovarian cancer. METHODS: The European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire C30 (EORTC QLQ C30) and Functional Assessment of Cancer Therapy-Ovarian (FACT-O) questionnaires were used to assess palliative benefit and an in-house questionnaire was used to gauge patient expectations. The minimal clinically important difference (MCID) was calculated by asking women to make a global rating of change and correlating this to the EORTC QLQ C30. Resource use was recorded and costs were calculated. RESULTS: Twenty-seven patients were accrued. Objective response was documented on seven of 27. The median survival was 11 months. Sixty-five percent of women expected that chemotherapy would make them live longer and 42% that it would cure them. After two cycles, quality-of-life (QL) improvement was seen particularly in global function (11 of 21) and emotional function (13 of 21) with EORTC QLQ C-30. Improvement was sustained for a median of 2 and 3 months, respectively, in these categories. The MCID was calculated to be 0.39 on a seven-point scale for physical function and 0.13 for global function. The mean total cost per patient for the study period was Can $12,500. CONCLUSION: Patient expectations from these treatments are often unrealistic. Although objective responses are low, active palliation with chemotherapy is associated with substantive improvement in patients' emotional function and global QL, with overall costs that seem relatively modest.
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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 | 0.002 | 0.010 |
| 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".