Development of an EORTC module to improve quality of life assessment in patients with gastric cancer
Bibliographic record
Abstract
AIMS: A valid measure of quality of life (QL) that is sensitive to clinically significant changes in health is important for the assessment of patients with gastric cancer. The aims of this study were to examine whether the EORTC (European Organisation for Research and Treatment of Cancer) QLQ-C30 core questionnaire alone could distinguish between two clinically different groups of patients and to design a module, which included relevant patient-defined gastric cancer-specific variables. METHODS: The QLQ-C30 was completed by patients with potentially curable disease and those undergoing palliative treatment, and the results were compared between the two groups. A disease-specific module was then developed in four distinct phases according to EORTC guidelines. Relevant issues were identified from a literature search and structured interviews with patients and healthcare professionals, and worded into a provisional questionnaire which was pretested to determine any problems in its content, before formal validation. RESULTS: All of the subscales and single items within the QLQ-C30 were scored similarly by 144 patients, 86 with operable disease and 58 having palliative treatment, except constipation (P = 0.001). On the basis of interviews with 58 patients and 24 professionals, from the UK, France, Germany and Spain, 43 issues were reduced to produce a provisional questionnaire consisting of 24 items and pretested in 114 patients undergoing radical gastrectomy, palliative resection or other supportive measures. The resulting questionnaire, containing 22 items divided into five scales (dysphagia, pain, reflux, dietary restrictions and specific emotional problems related to gastric cancer and its treatment) and four single items, is undergoing validation. CONCLUSIONS: The EORTC QLQ-C30 is a valid generic instrument, but does not address all factors constituting QL in patients with gastric cancer. A specific module has been developed, which includes issues volunteered by patients to increase sensitivity and improve the evaluation of treatments for a disease where QL is important.
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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 | 0.006 | 0.012 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".