Serum Cytokine and Tumor Marker Profiles for Gastric Cancer Diagnosis

165 participants, including healthy controls and patients with gastric cancer or precancerous lesions, provide serum levels for nine cytokines and five conventional tumor markers. This case-control study by Qiuyan Zhang, last updated in 2026, explores combined biomarker models for early noninvasive detection. The research demonstrates that integrated models can achieve area under the curve (AUC) values up to 0.97 for discriminating gastric cancer from healthy controls.

Use Cases

• Building diagnostic classification models based on combined serum cytokine and tumor marker profiles.
• Analyzing the relationship between inflammatory cytokines (e.g., IL-6, IL-16) and gastric carcinogenesis stages.
• Evaluating feature importance for biomarker panels using methods like SHAP analysis as mentioned in the description.
• Comparing the diagnostic performance of individual biomarkers versus multimarker combinations using ROC analysis.

Strengths

• Includes data from 165 participants across three distinct clinical groups: healthy controls, precancerous lesions, and gastric cancer.
• Quantifies 14 specific serum analytes: nine cytokines (IL-1ra, IL-6, IL-7, IL-8, IL-10, IL-16, IL-17, IL-21, TNF-α) and five tumor markers (CEA, CA19-9, CA125, CA72-4, AFP).
• Reported diagnostic models show high performance, with an integrated model achieving an AUC of 0.97 for discriminating gastric cancer from healthy controls.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The study is described as a single-center, cross-sectional case-control study, which may limit generalizability.

Provenance

Source

Qiuyan Zhang via figshare.

Collection Method

Single-center, cross-sectional case-control study with serum samples analyzed by ELISA.

Time Range

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Freshness

Last updated 2026-04-28 04:29:07; freshness should be verified.

Geography

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