Development of an EORTC quality of life phase III module measuring cancer‐related fatigue (EORTC QLQ‐FA13)
Bibliographic record
Abstract
BACKGROUND: European Organisation for Research and Treatment of Cancer (EORTC) has developed a new multidimensional instrument measuring cancer-related fatigue that can be used in conjunction with the quality of life core questionnaire, EORTC QLQ-C30. The paper focuses on the development of the phase III module, collaborating with seven European countries, including a patient sample of 318 patients. METHODS: The methodology followed the EORTC guidelines for developing phase III modules. Patients were assessed by questionnaires (EORTC QLQ-C30 with the EORTC Fatigue Module FA15) followed by an interview, asking for their opinions on the difficulty in understanding, on annoyance and on intrusiveness. RESULTS: The phase II FA15 was revised on the basis of qualitative analyses (comments of the patients), quantitative results (descriptive statistics) as well as the multi-item response theory analyses. The three dimensions (physical, emotional and cognitive) of the scale could be confirmed. CONCLUSIONS: As a result, EORTC QLQ-FA13 is now available as a valid phase III module measuring cancer-related fatigue in clinical trials and will be psychometrically improved in the upcoming phase IV.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".