The Design of a Patient-Centered Hierarchal Composite Outcome for a Multi-Center Randomized Controlled Trial in Metastatic Bone Disease
Bibliographic record
Abstract
The proximal femur represents the most frequent site in the appendicular skeleton for metastatic bone disease (MBD) to occur, with a high risk for pathologic fracture. While surgical stabilization is typically used to manage fractures, reconstruction approaches are gaining popularity due to improved survival. Previous studies have focused on clinical outcomes, but patient-centered outcomes remain underexplored. This study aims to develop a patient-centered primary outcome for the Proximal FEmur Reconstruction or Internal Fixation fOR Metastases (PERFORM) Randomized Controlled Trial, employing a mixed-methods approach. First, a focus group with advanced cancer patients and caregivers identified relevant outcomes. Next, a discrete choice experiment (DCE) assessed the importance of these outcomes among stakeholders, including surgeons, patients and caregivers. The most important components for the primary outcome were identified: mortality within twelve months, physical function assessed at four months using the PROMIS® Global Physical Function score, and the number of days at home within twelve months. The DCE further confirmed that survival and physical function were most prioritized. The PERFORM trial’s primary outcome, developed through extensive stakeholder engagement, will guide the evaluation of surgical approaches for MBD of the proximal femur and has the potential to influence patient-centered practice.
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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 | 0.059 | 0.065 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".