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Distinct Clinical Phenotypes in Gastric Pathologies: A Cluster Analysis of Demographic and Biomarker Profiles in a Diverse Patient Population Publisher Pubmed



Gorjizadeh N1 ; Arani AS2 ; Yazdi SAM3, 4 ; Biglari M5 ; Bahar M6
Authors
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Authors Affiliations
  1. 1. Department of Internal Medicine, Sina University Hospital, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Internal Medicine, Shahid Beheshti University Hospital, Kashan University of Medical Sciences, Kashan, Iran
  3. 3. Department of Surgery, Sina University Hospital, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Research Institute for Oncology, Hematology and Cell Therapy, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Department of Medical Genetics, Familial and Hereditary Cancers Institute, Tehran, Iran

Source: Journal of Gastrointestinal Surgery Published:2025


Abstract

Background: Understanding the heterogeneity of a population at risk is an important step in the early detection of gastric cancer. This study aimed to cluster demographic, hematologic, and biochemical markers of gastric cancer in a heterogeneous sample of patients. Methods: Data of 695 adult patients (50.0% women) who were diagnosed with histologically confirmed gastric cancer or benign gastric disease or identified as healthy individuals (December 2018 to August 2019; Hangzhou, China) were analyzed. A hierarchical clustering was performed using a factorial analysis of mixed data. To assess the clustering scheme, a machine-learning classification model was developed using the Extreme Gradient Boosting algorithm and subsequently ranked the variables for differentiating patient phenotypes. Results: Of note, 3 clusters were identified using patient characteristics. The classification model demonstrated high performance (multiclass area under the curve = 0.921) in recognizing the clusters. The top 5 important variables in differentiating the clusters were sex (male/female), hemoglobin, albumin, creatinine, and high-density lipoprotein (all analysis of variance P <.001) in decreasing order of importance. The prevalence rates of gastric cancer in clusters I, II, and III were 95.8%, 53.8%, and 34%, respectively (χ2(2) = 164.050; P <.001). Cluster I (n = 167) predominantly had an inflammatory profile, cluster II (n = 240) had metabolic disturbances, and cluster III (n = 288) had a relatively favorable metabolic and inflammatory profile. Conclusion: There were distinct clinical phenotypes in the population, each with varying prevalence of gastric cancer. A combination of routine clinical data outperformed carbohydrate or carcinoembryonic antigens in capturing the heterogeneity of the population regarding gastric pathologies. © 2025 Society for Surgery of the Alimentary Tract
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