A Structural Equation Model for early screening of cholangiocarcinoma among Thai population in Northeast Thailand - Jetnapis Rayubkul; Sathirakorn Pongpanich; Bandit Thinkhamrop; Wongsa Laohasiriwong; Roshan Kumar Mahato (International Journal of Public Health Asia Pacific, 2026)
Background: Cholangiocarcinoma (CCA) represents a critical public health challenge in Northeast Thailand, with the world's highest incidence rates. Early detection remains crucial for improving patient outcomes, yet comprehensive screening models integrating multiple risk factors are lacking. Objectives: This study developed and validated a structural equation model (SEM) to identify factors influencing early screening diagnosis of cholangiocarcinoma among Thai populations in Northeast Thailand. Methods: A retrospective analysis was conducted using data from the Cholangiocarcinoma Screening and Care Program (CASCAP) involving 1,196,685 participants aged 40-100 years across 20 northeastern provinces. The SEM incorporated seven latent constructs: personnel factors, behavioural factors, family history, liver fluke infection, disease factors, ultrasound findings, and confirmatory diagnosis. Model fit was evaluated using established indices (CFI, RMSEA, TLI). Results: Overall suspected CCA prevalence was 2.61% (95% CI: 2.56-2.65), with significantly higher rates among males (3.01%) versus females (2.36%). The final SEM demonstrated acceptable fit (χ²/df=2.10, CFI=0.928, RMSEA=0.054, TLI=0.910). Key predictive pathways emerged: behavioural and family history factors → liver fluke infection → ultrasound screening → diagnosis → suspected pathology. Personnel factors (β=0.555), behavioural factors (β=0.544), and liver fluke infection (β=0.172) showed significant direct effects on suspected CCA diagnosis. Conclusion: The validated SEM provides a comprehensive framework for early CCA screening, emphasizing the critical roles of behavioural modification, familial risk assessment, and ultrasound-based detection. These findings support targeted intervention strategies and evidence-based screening protocols for high-risk populations in endemic regions.