Thyroid Cancer Prognostic Risk Model Based on Immune Gene Expression

Qi Qi's research dataset, last updated in April 2026, contains data for constructing a prognostic risk model for thyroid cancer. It is based on a retrospective study of 180 patients treated between May 2022 and April 2025, analyzing the expression of immune genes like CDK1, B3GNT7, S100A9, and MMP9. The dataset includes results from immune infiltration analysis and validation using the TCGA-THCA database.

Use Cases

• Building a prognostic risk model for thyroid cancer based on the expression levels of CDK1, B3GNT7, S100A9, and MMP9 genes.
• Analyzing correlations between specific immune genes and tumor immune cell infiltration abundance.
• Investigating the relationship between gene expression and clinical pathological features like lymph node metastasis (pN stage) and distant metastasis (pM stage).
• Validating prognostic models using external data sources like the TCGA-THCA database.

Strengths

• Includes data from 180 patient cases with defined good (126) and poor (54) prognosis groups.
• The constructed prognostic model achieved an average C-index of 0.919 and an AUC of 0.880.
• Analysis integrates patient data with external validation from the TCGA-THCA database.

Limitations

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

Provenance

Source

Retrospective study from a single hospital, with validation from the public TCGA-THCA database.

Collection Method

Clinical data collection, binary logistic regression, immune infiltration analysis via ssGSEA and GSEA algorithms, and Pearson correlation analysis.

Time Range

Patient treatment period from May 2022 to April 2025.

Freshness

Last updated 2026-04-22 22:01:10; freshness should be verified.

Geography

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