01 / SCREENING AND RISK FACTORS FOR MALNUTRITION IN OLDER PATIENTS WITH CANCER
Bibliographic record
Abstract
healthcare systems and financial distress inequalities among patients with advanced cancer.Co-authorstC. Barberet1, M. Filbet2, S. Sanchez3, M. Delgado4, E. Bruera5.1Centre Hospitalo-Universitaire de Grenoble, Department of Supportive and Palliative Care, Grenoble-, France.2service de soins palliaitfs pavillon1K CHLS CHU de Lyon, Palliative Medecine, Pierre Benite LYON, France.3Hu00f4pitaux Champagne Sud, Department of Medical Information Evaluation and Performance, Troyes, France.4The University of Texas MD Anderson Cancer Center, Department of Palliative- Rehabilitation- and Integrative Medicine-, Houston Texas, France.5University of Texas MD Anderson Cancer Center, Department of Palliative- Rehabilitation- and Integrative Medicine, Houston- TX, USA.Introduction:Financial distress (FD) is a common cause of suffering in patients with advanced cancer. There is limited data to compare the effects of FD of advanced cancer patient in two different health systems (US and France)ObjectivesTo compare the frequency and intensity of Financial Distress (FD) and its associations with symptom distress and quality of life (QOL) in patients with advanced cancer in France and US.MethodsWe conducted a secondary analysis of two cross-sectional studies with 292 patients enrolled in the USA (149 patients) and in France (143 patients). Self-rated FD (subjective experience of distress attributed to financial problems) numeric rating scale (0=best, 10=worst) and validated questionnaires assessed symptoms [Edmonton Symptom Assessment System (ESAS)], psychosocial-distress [Hospital Anxiety Depression Scale (HADS)], and QOL (FACT-G).ResultsThe average age was 59 (10SD),144 (49%) patients were female. In France FD was reported in 74 (52%) vs. 129 (88%) in the US (p<0.001). Severe FD (u22654/10) was reported in 100 US patients (68%) vs. 48 (34%) in France (p<0.001). QOL was better in the USA than in France (respectively 69 versus 63; p=0.003). French patients had more anxiety (8 versus 6; p=0.008) and depression (7 versus 6; p=0.004). FD was associated with the country USA, single status (0.907; p=0.023) and the presence of metastasis (1.538; p=0.036).Conclusions Even lower than US patients with advanced cancer , the FD is hight in French patients despite a free cancer care access. Further research focusing on indirect costs is needed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".