Enhanced Functional and Surgical Outcomes With 3D Printing in Orthopedic Oncology: A Comparative Meta‐Analysis Against Conventional Techniques
Bibliographic record
Abstract
INTRODUCTION: Three-dimensional printing (3DP) technology has increasingly gained attention in orthopedic oncology, where complex tumor resections and reconstructions demand high precision. 3DP enables the creation of patient-specific models and prostheses, which can improve postoperative quality of life for patients while assisting surgeons in preoperative planning, enhancing surgical accuracy, and improving outcomes in complex oncologic cases. Despite its potential, comprehensive data on the effectiveness and applications of 3DP in orthopedic oncology are limited. This paper assesses whether using 3DP compared to conventional techniques results in better outcomes in orthopedic oncology. METHODS: A comprehensive search of Ovid MEDLINE, Embase, Scopus, and Web of Science was conducted until November 2024. Studies comparing 3D printing to conventional methods in orthopedic oncology and reporting outcomes such as operative time, blood loss, recurrence rates, or functional scores were included. Weighted means and meta-analyses were conducted to compare these outcomes. Statistical heterogeneity was adjusted by using a random-effects model. RESULTS: Fourteen studies comprising 478 patients met the inclusion criteria. Our primary findings were improved MSTS scores (mean difference [MD]: 2.17, p = 0.00) and decreased blood loss (MD: -69.8 mL, p = 0.00) in the 3D printing groups. There was no significant difference in operative time between 3D printing and conventional techniques (MD: -12.2 min, p = 0.32). Tumor recurrence rates did not differ significantly between groups (relative risk: 0.88, p = 0.50). Subgroup analyses indicated that 3D-printed implants showed the greatest benefit in reducing OR time and blood loss, with the other subgroups showing no significant difference in OR time, blood loss, or recurrence rate. CONCLUSION: The findings suggest that 3D printing in orthopedic oncology may enhance surgical precision by reducing OR time, intraoperative blood loss, and improving postoperative function, without affecting recurrence rates. Substantial heterogeneity limits confidence in these findings. LEVEL OF EVIDENCE: Level III.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".