Osteosarcoma Limb Salvage Surgery Outcomes with Tumor Size and Margin Data

A clinical dataset of 196 cases from a single institution between 2010 and 2015, focusing on 88 high-grade extremity osteosarcoma patients with potentially inadequate surgical margins. The data was used to build a decision tree model analyzing the interaction between tumor size and close surgical margins on local recurrence, metastasis, and overall survival. The dataset was created by Yingying Shi and is licensed under CC-BY-4.0.

Use Cases

• Training prognostic models for local recurrence based on surgical margin width and tumor size.
• Analyzing interaction effects between tumor size and surgical margin status on metastasis and overall survival.
• Validating machine learning algorithms like decision trees for clinical outcome prediction in oncology.
• Studying risk stratification for patients undergoing limb salvage surgery for high-grade osteosarcoma.

Strengths

• Includes data from 196 cases over a 5-year period (2010-2015), providing a defined clinical cohort.
• Contains specific, measured variables such as peri-neurovascular margin width and tumor size as a percentage of limb length.
• Analysis employed multivariate Cox regression and machine learning with cross-validation, suggesting a structured analytical approach.

Limitations

• Row count for the primary analytical subset is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is from a single institution, which may reflect specific treatment protocols and limit generalizability.

Provenance

Source

figshare, author Yingying Shi.

Collection Method

Retrospective review of medical records from a single institution.

Time Range

January 2010 to December 2015.

Freshness

Last updated 2026-04-24 05:40:37; freshness should be verified.