Validation of the French-Canadian version of the Expanded Prostate Cancer Index Composite (EPIC) in a French-Canadian population
Bibliographic record
Abstract
INTRODUCTION: This study aims to empirically validate the French-Canadian version of the Expanded Prostate Cancer Index Composite (EPIC), a measure of health-related quality of life for prostate cancer patients. METHODS: Two hundred fifty-one participants completed a battery of self-report scales, including the French-Canadian version of the EPIC, after having received radiation therapy or radical prostatectomy for prostate cancer. RESULTS: The internal consistency for the urinary incontinence, bowel, and sexual domains of the EPIC-26 was high (Cronbach's alpha coefficients from 0.80-0.92), while coefficients for the urinary irritation/obstruction (0.59) and hormonal (0.67) domains were lower. Item-total correlations (rs=0.15-0.85), and temporal stability (rs=0.72-0.93) generally supported the reliability of the instrument. The five-factor structure of the EPIC-26 was confirmed for the most part. The construct validity of the instrument was also supported by high correlations obtained between each domain and measures assessing similar constructs (rs=-0.56-0.83). The EPIC also showed an excellent sensitivity to change with significant differences obtained on EPIC scores (all p<0.05) between pre- and post-prostate cancer treatment. CONCLUSIONS: The psychometric qualities of the French-Canadian version of the EPIC are well-supported, thus providing a valid tool to assess health-related quality of life in prostate cancer patients.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".