Machine Learning Analysis of Lipid and Metabolic Profiles in Adults with Adenoid Hyperplasia

TL;DR

This study used machine learning to find differences in blood lipid and metabolic profiles between adults with adenoid hyperplasia and healthy individuals.

Contribution

The study identifies HDL, HbA1C, and ALT as potential biomarkers for adenoid hyperplasia using XGBoost and SHAP analysis.

Findings

HDL levels were significantly lower in the adenoid hyperplasia group compared to the control group.

ALT levels showed a trend toward being higher in the adenoid hyperplasia group.

XGBoost and SHAP analysis provided insights into biomarker associations despite dataset limitations.

Abstract

Background and Objectives: The nasopharynx, unlike other pharyngeal regions, includes an important part of the immune system, called the adenoid (nasopharyngeal tonsil); its posterior wall contains lymphoid tissue belonging to Waldeyer’s ring. Nasopharyngeal posterior wall thickness is often associated with adenoid hyperplasia in adults. The current study aimed to compare the blood lipid and metabolic profiles of adult patients with increased nasopharyngeal posterior wall thickness to those of the healthy population. Materials and Methods: This study included a cohort of 98 patients, 52 in the control group and 46 diagnosed with increased nasopharyngeal posterior wall thickness due to adenoid hyperplasia. Clinical and biochemical data were collected from medical records at Sivas Cumhuriyet University and Erbaa State Hospital between January 2024 and March 2025. The dataset consisted of the following 11 features: age, sex, total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, fasting blood glucose, glycated hemoglobin (HbA1C), C-reactive protein (CRP), alanine aminotransferase (ALT), and aspartate aminotransferase (AST). Results: HDL was significantly lower in the adenoid hyperplasia group (mean = 48.68, SD = 21.87) compared to the control group (mean = 51.31, SD = 11.80; Kruskal–Wallis H = 4.750, p = 0.029), with a small effect size (Cohen’s d = −0.156). ALT was higher in the adenoid hyperplasia group (mean = 26.35, SD = 16.93 vs. 20.88, SD = 11.42; permutation test p = 0.082), suggesting a trend toward significance. HbA1C had a higher mean in the adenoid hyperplasia group (7.88, SD = 9.82 vs. 6.18, SD = 1.18; p = 0.852), with high variability. Conclusions: In conclusion, this study identified HDL, HbA1C, and ALT as potential biomarkers for nasopharyngeal adenoid hyperplasia, with XGBoost and SHAP providing valuable insights despite dataset constraints.

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