Gastric Cancer Tumor Regression Patterns and Nodal Risk After Therapy, 195 Patients

195 patients with advanced gastric cancer were analyzed for tumor regression patterns after neoadjuvant or conversion therapy. The dataset, authored by Na Li and last updated in April 2026, contains clinical and pathological characteristics used to model the relationship between regression patterns and lymph node metastasis (ypN positivity).

Use Cases

• Predicting residual lymph node metastasis (ypN positivity) based on tumor regression patterns (centripetal, diffuse/mixed, centrifugal).
• Stratifying postoperative nodal risk for patients after neoadjuvant or conversion therapy.
• Building logistic regression models for clinical decision support using features like Becker tumor regression grade (TRG) and ypT stage.
• Validating predictive models for individualized lymphadenectomy research using internal validation methods like cross-validation.

Strengths

• Includes data from 195 patients, providing a foundation for statistical analysis.
• Model performance metrics are reported, including an AUC of 0.875 and a Brier score of 0.137 for the full-cohort model.
• Internal validation was performed using a 7:3 split-sample analysis and 10-fold cross-validation.
• Released under a CC-BY-4.0 license, allowing for reuse and modification.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 56.9 KB file size suggests a limited scope, likely containing summary statistics or a supplementary document rather than raw patient-level data.

Provenance

Source

figshare, author Na Li.

Collection Method

Clinical and pathological data from patients with advanced gastric cancer treated with neoadjuvant or conversion therapy.

Time Range

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Freshness

Last updated 2026-04-13 05:45:57

Geography

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