Cross-cultural development of an EORTC questionnaire to assess health-related quality of life in patients with testicular cancer: the EORTC QLQ-TC26
Bibliographic record
Abstract
OBJECTIVE: Testicular cancer (TC) is the most common cancer in young men, and its incidence is increasing. The low mortality rate makes quality of life (QOL) an important issue in this patient group. This study aimed to develop a supplementary module of the EORTC QLQ-C30 questionnaire to assess TC-specific aspects of QOL. METHODS: Questionnaire development was conducted according to guidelines from the EORTC Quality of Life Group. Phase I comprised generation of QOL issues relevant to TC patients through a literature search and interviews with patients and experts. Phase II included operationalization and assessment of item relevance. In phase III, items were pre-tested in a cross-cultural sample to assess issues such as understandability and intrusiveness of items. RESULTS: In phase I and II, an initial list of 69 QOL issues possibly relevant to TC patients was refined through patient and expert interviews. The remaining 37 issues were operationalized into items and assessed for relevance and priority in an expert sample (n = 28) and a patient sample (n = 62) from Austria, Canada and the Netherlands. After revision of the item list, 26 items were considered eligible for pre-testing in phase III, in which 156 patients from Australia, Austria, Italy and Spain participated. All items passed criteria for pre-testing, thus forming the new EORTC QLQ-TC26. CONCLUSION: The newly developed EORTC QLQ-TC26 is now available in several languages to assess QOL in TC patients receiving treatment and in TC survivors. Phase IV of questionnaire development will comprise international field testing, including extensive analysis of psychometric characteristics of the EORTC QLQ-TC26.
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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 | 0.010 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".