Revisiting the FAITH Trial: A Secondary Analysis Yielding Novel Insights with the Win Ratio
Bibliographic record
Abstract
Background: Many orthopaedic trials use any unplanned reoperation as the primary outcome, but this overlooks how patients experience those outcomes. Using a high-quality hip fracture trial, we demonstrate how the relative importance of multiple patient-important outcomes can be effectively incorporated into data analysis, providing a more comprehensive understanding of treatment impact. Methods: This secondary analysis of the Fixation using Alternative Implants for the Treatment of Hip Fracture (FAITH) trial included 1,079 patients aged 50 years or older with a low-energy femoral neck fracture who were randomly assigned to treatment with a sliding hip screw or cancellous screws. The original trial used unplanned revision surgery as the primary outcome. Our primary analysis instead used a composite outcome of all-cause mortality at 4 months, ambulation status at 10 weeks (measured by the EuroQol-5 Dimension [EQ-5D] mobility dimension), and days at home within 4 months. We assessed outcomes hierarchically using the win ratio method, comparing each patient with every other patient in the alternative treatment group in a pairwise manner. We conducted sensitivity analyses at 6 and 12 months, and subgroup analyses to explore smoking status and fracture displacement as potential effect modifiers. Results: Of the 1,079 participants, 741 had EQ-5D data available for the primary analysis at 4 months, yielding 137,114 pairwise comparisons. A sliding hip screw was superior to cancellous screws in 65,158 (47.5%) comparisons, inferior to cancellous screws in 63,378 (46.2%) comparisons, and tied in 8,578 (6.3%), leading to a win ratio of 1.03 (95% confidence interval [CI] 0.86-1.23), but this difference was not statistically significant (p = 0.76). The sensitivity analysis results were similar at 6 and 12 months. In the subgroup analysis, a sliding hip screw was superior to cancellous screws in current smokers, with a win ratio of 1.65 (95% CI 1.02-2.65) at 6 months (p = 0.007). Conclusion: This analysis approach should be considered for future orthopaedic trials as it was consistent with the FAITH primary analysis findings but yielded a more nuanced interpretation of the patients' experience and offers deeper insights into intervention effectiveness. The bounds of the 95% CI for the primary outcome were within many standard definitions of equivalence, suggesting surgeons can assume similar patient-important outcomes with either treatment.
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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 | 0.158 | 0.352 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".