What are the indications and survivorship of tumor endoprosthetic reconstructions for patients with extremity metastatic bone disease?
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Given advances in therapies, endoprosthetic reconstruction (EPR) in metastatic bone disease (MBD) may be increasingly indicated. The objectives were to review the indications, and implant and patient survivorship in patients undergoing EPR for MBD. METHODS: A review of patients undergoing EPR for extremity MBD between 1992 and 2022 at two centers was performed. Surgical data, implant survival, patient survival, and implant failure modes were examined. RESULTS: One hundred fifteen patients were included with a median follow-up of 14.9 months (95% confidence interval [CI]: 9.2-19.3) and survival of 19.4 months (95% CI: 13.6-26.1). The most common diagnosis was renal cell carcinoma (34/115, 29.6%) and the most common location was proximal femur (43/115, 37.4%). Indications included: actualized fracture (58/115, 50.4%), impending fracture (30/115, 26.1%), and failed fixation (27/115, 23.5%). Implant failure was uncommon (10/115, 8.7%). Patients undergoing EPR for failed fixation were more likely to have renal or lung cancer (p = 0.006). CONCLUSIONS: EPRs were performed most frequently for renal cell carcinoma and in patients with a relatively favorable survival. EPR was indicated for failed previous fixation in 23.5% of cases, emphasizing the importance of predictive survival modeling. EPR can be a reliable and durable surgical option for patients with MBD.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".