Osteosarcoma Patient Data for Prognostic Modeling of Limb Salvage Surgery

A retrospective review of 196 cases that underwent limb salvage surgery for high-grade osteosarcoma between January 2010 and December 2015. The dataset, authored by Yingying Shi, was used to study the interaction between tumor size and close surgical margins on local recurrence, metastasis, and overall survival.

Use Cases

• Training decision tree models to predict local recurrence based on tumor size and margin width.
• Analyzing the interaction effect between tumor size and peri-neurovascular margin on metastasis risk.
• Validating machine learning algorithms for survival analysis in cancer prognosis.
• Investigating heterogeneity in surgical outcomes for high-grade osteosarcoma patients.

Strengths

• Includes data from 196 patient cases, with a focused subset of 88 high-grade extremity osteosarcoma cases.
• Contains specific, clinically relevant variables such as tumor size (as a percentage of limb), surgical margin width, and oncological outcomes.
• Applies multiple analytical methods, including multivariate Cox regression and machine learning with cross-validation.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect temporal and institutional bias inherent to a single-center retrospective study.

Provenance

Source

figshare

Collection Method

Retrospective clinical review at a single institution.

Time Range

January 2010 to December 2015

Freshness

Last updated 2026-04-24 05:40:36; freshness should be verified.