CT-Based Radiomics Nomogram for Predicting Survival in Primary Tracheal Malignancy

Shuchao Wang's study on figshare presents a prognostic model for primary tracheal malignancy (PTM) patients. The dataset, last updated in April 2026, is derived from a retrospective review of 115 patients. It includes a radiomics score (Radscore) based on seven CT features and the clinical factor of longitudinal length, combined into a nomogram for survival prediction.

Use Cases

• Training survival prediction models based on the seven selected radiomics features.
• Validating the performance of radiomics scores (Radscore) against clinical factors like longitudinal length.
• Building clinical decision support tools using the combined radiomics nomogram described in the study.
• Benchmarking new prognostic models for tracheal cancer against the reported C-index performance metrics.

Strengths

• Includes validation on a separate cohort of 30 patients.
• Model performance is quantified with C-index values (e.g., 0.79 for the nomogram) and decision curve analysis.
• The prognostic model combines seven radiomics features with a key clinical factor (longitudinal length).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Dataset is very small at 13.3 KB, indicating limited scope.

Provenance

Source

Shuchao Wang via figshare.

Collection Method

Retrospective review of patient data.

Time Range

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Freshness

Last updated 2026-04-15 04:37:06; freshness should be verified.

Geography

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