Development and Validation of a Pre-Chemotherapy Nomogram for Colorectal Cancer Toxicity

A dataset of 306 patients with stage II/III colorectal cancer receiving oxaliplatin-based adjuvant chemotherapy, used to develop a predictive nomogram for severe chemotherapy-induced toxicity. The data includes baseline Systemic Immune-Inflammation Index (SII) and Prognostic Nutritional Index (PNI) values, patient age, and outcomes including grade 3–4 adverse events and therapy duration. The dataset was created by Wenjing Li and last updated on May 11, 2026.

Use Cases

• Validating predictive models for chemotherapy-induced toxicity based on SII and PNI biomarkers.
• Training machine learning classifiers to identify high-risk patients for severe adverse events.
• Conducting retrospective clinical research on the relationship between immune-nutritional indices and chemotherapy tolerance.
• Benchmarking new risk assessment tools against the published nomogram's performance metrics.

Strengths

• Dataset is based on a cohort of 306 patients, providing a foundation for model development.
• The derived nomogram demonstrated strong predictive performance with an optimism-corrected AUC of 0.867.
• Analysis identified statistically significant independent risk factors: high SII (adjusted OR=8.56) and low PNI (adjusted OR=4.69).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain modeling tasks.
• The dataset is small (10.5 KB), indicating limited scope and feature set.

Provenance

Source

figshare

Collection Method

Retrospective analysis of patient records.

Freshness

Last updated 2026-05-11 04:21:52; freshness should be verified.