Data Sheet 1_Development of a prognostic model based on nutritional and inflammatory indic

Huike Wang's dataset contains clinical data from 660 esophageal cancer patients who underwent radical surgery between 2012 and 2018. The data was used to develop and validate a prognostic nomogram incorporating the inflammation–immunity–nutrition score (IINS) and red cell distribution width-to-lymphocyte ratio (RLR). The dataset was last updated on 2026-04-14.

Use Cases

• Training survival prediction models based on the IINS and RLR indicators.
• Validating prognostic tools for esophageal cancer using the provided training and validation cohorts.
• Analyzing the relationship between systemic inflammation, immunity, and nutritional status on patient outcomes.
• Benchmarking new models against the reported C-index, AUC, and risk reclassification metrics (IDI, NRI).

Strengths

• Includes data from 660 patients, split into training (n=459) and validation (n=201) cohorts.
• Model validation used multiple metrics including C-index, calibration, time-dependent AUC, DCA, IDI, and NRI.
• Data is associated with a published retrospective study methodology described in the description.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect temporal and institutional bias inherent to a single retrospective study.

Provenance

Source

Huike Wang via figshare

Collection Method

Retrospective analysis of clinical data from patients who underwent radical surgery.

Time Range

2012–2018

Freshness

Last updated 2026-04-14 04:19:52; freshness should be verified.