Breast Cancer-Related Lymphedema Risk Prediction Model Data

A retrospective cohort of 234 patients undergoing breast cancer surgery, of whom 27 (11.5%) developed ipsilateral upper-limb lymphedema. The data was used to develop and internally validate a clinical prediction nomogram incorporating four variables. The dataset was authored by Yufei Fan and last updated on June 3, 2026.

Use Cases

• Developing a risk prediction model based on surgery type, pectoral nodes dissection, number of harvested lymph nodes, and N stage.
• Validating clinical prediction tools using bootstrap internal validation and decision curve analysis.
• Identifying high-risk patients for targeted preventive interventions based on the developed nomogram.

Strengths

• Model performance is quantitatively reported with an apparent AUC of 0.964 and a bootstrap optimism-corrected AUC of 0.954.
• The dataset includes 234 patient records with a clear outcome event rate of 11.5%.
• The model was developed using Firth penalized logistic regression to reduce sparse-data bias.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Retrospective cohort study.

Freshness

Last updated 2026-06-03 04:47:18; freshness should be verified.