The Multivariate Statistical Assessment of Metal Exposure in Fingernails of Women with Cervical Cancer

Purpose: This study aimed to evaluate the association between trace metal exposure and the risk of cervical cancer in Vietnamese women using fingernail elemental profiling and multivariate statistical methods. Methods: Fingernail samples were collected from 61 women diagnosed with cervical cancer and 43 healthy controls. Concentrations of eight metals—including Cr, Mn, Fe, Cu, Zn, As, Se, and Pb— were quantified using total reflection X-ray fluorescence (TXRF) spectrometry. Multivariable logistic regression was applied to estimate the odds ratios (ORs) for predicting increased risks of cervical cancer. In addition, Spearman correlation analysis and principal component analysis (PCA) were used to explore the associations among metals, demographic factors, and geographic regions. Results: The concentrations of Cr, Mn, Cu, As, and Pb in fingernails were significant predictors of an increased risk of cervical cancer. As and Pb showed the strongest associations, with ORs of7.11 and 5.89, respectively (p < 0.001). In contrast, Zn demonstrated a protective effect (OR < 1; p = 0.0011). The model showed excellent discriminative power (AUC = 0.963), with high sensitivity (0.814) and specificity (0.984). Correlation analyses revealed distinct patterns of metal accumulation across age groups and regions and suggested complex inter-element interactions. PCA confirmed that age and region of residence influenced the metal profiles, supporting their utility in exposure assessments. Conclusion: Fingernail analysis combined with multivariate statistics provides a practical approach for evaluating chronic metal exposure and its association with an increased risk of cervical cancer. This method may contribute to biomonitoring efforts and risk stratification in environmental health studies.