Financial distress in patients with advanced cancer
Bibliographic record
Abstract
PURPOSE: We examined the frequency and severity of financial distress (FD) and its association with quality of life (QOL) and symptoms among patients with advanced cancer in France. DESIGN: In this cross-sectional study, 143 patients with advanced cancer were enrolled. QOL was assessed using the Functional Assessment of Cancer General (FACT-G) and symptoms assessed using Edmonton Assessment System (ESAS) and Hospital Anxiety and Depression Scale (HADS). FD was assessed using a self-rated numeric scale from 0 to 10. RESULTS: Seventy-three (51%) patients reported having FD. Patients reported having FD were most likely to be younger (53.8 (16,7SD) versus 62 (10.5SD), p<0.001), single (33 (62%) versus 40(44%), p = 0.03) and had a breast cancer (26 (36%), p = 0.024). Patients with FD had a lower FACT-G score (59 versus 70, p = 0.005). FD decreased physical (14 versus 18, p = 0.008), emotional (14 versus 16, p = 0.008), social wellbeing (17 versus 19, p = 0.04). Patients with FD had higher HADS-D (8 versus 6 p = 0.007) and HADS-A (9 versus 7, p = 0.009) scores. FD was linked to increased ESAS score (59 (18SD) versus 67 (18SD), p = 0.005) and spiritual suffering (22(29SD) versus 13(23SD), p = 0.045). CONCLUSION: The high rate of patient-reported FD was unexpected in our studied population, as the French National Health Insurance covers specific cancer treatments. The FD was associated with a poorer quality of life. Having a systematic assessment, with a simple tool, should lead to future research on interventions that will increase patients' QOL.
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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 | 0.001 | 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 | 0.000 |
| 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".