Amputation Versus Limb-Salvage Surgery as Treatments for Pediatric Bone Sarcoma: A Comparative Study of Survival, Function, and Quality of Life
Bibliographic record
Abstract
BACKGROUND: Pediatric appendicular bone sarcomas, including osteosarcoma and Ewing's sarcoma, are rare but aggressive malignancies that have a profound impact on survival, physical function, and quality of life (QoL). Treatment options usually involve either limb-salvage surgery (LSS) or amputation (AMP), although evidence about outcomes among these approaches is still limited. METHODS: A retrospective cohort study was conducted involving pediatric cases treated for appendicular bone sarcomas between 2000 and 2021 at the Instituto Português de Oncologia de Lisboa (IPOL), a Portuguese oncology center in Lisbon. It evaluated functional and QoL outcomes and survival. Patients were stratified by surgical approach (LSS vs. AMP) and evaluated by validated outcome tools, including the Toronto Extremity Salvage Score (TESS) and the Medical Outcomes Study Short-Form 36 version 2 (MOS SF-36v2) QoL questionnaire. P-values <0.05 were considered significant. RESULTS: A total of 62 patients were included, with an overall five-year survival rate of 38%. Poorer survival outcomes were recorded among those presenting with metastatic disease, larger tumor sizes (>8 cm), and those who underwent AMP. Limb-salvage surgery was performed in 59.7% of cases and presented higher mean functional scores (88.4%) compared with AMP (79%). The QoL scores varied, with LSS patients reporting better outcomes in physical and emotional domains. Patients from Portuguese-speaking African countries (PSAC) had poorer survival rates, a finding that reflects disparities that could be related to advanced disease presentation and limited health resources. CONCLUSION: Limb-salvage surgery had better functional outcomes and QoL compared to AMP. However, survival of these patients remains a challenge, especially for those from resource-limited settings. These results highlight the need for early diagnosis, improvement in access to healthcare, and further research to improve 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".