Spatial patterns, temporal trends, and age-period-cohort effects of colon cancer incidence in Kazakhstan, 2005–2024

Frontiers in Oncology, 2026

Полный текст Открытый доступ: Gold Метаданные (CSL-JSON)
DOI 10.3389/fonc.2026.1732883
Достоверность данных 70 средняя
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Аннотация

Background: Colon cancer incidence is increasing globally, yet its spatial and temporal dynamics in Central Asia remain insufficiently studied. This study aimed to assess regional disparities and temporal trends of colon cancer incidence in Kazakhstan from 2005 to 2024 using geospatial and age-period-cohort analyses. Methods: A nationwide population-based study was conducted using data from the Unified Nationwide Electronic Health System of Kazakhstan. Crude incidence rates (CR) and age-standardized incidence rates (ASR) were calculated per 100,000 population using the WHO world standard population. Spatial patterns were assessed based on the administrative division of 2005, and clustering was evaluated using the Getis-Ord Gi* statistic. Temporal trends were analyzed using Joinpoint regression and Age-Period-Cohort analysis modeling, including estimation of net drift, local drift, and period and cohort rate ratios. Results: The national CR was 9.64 per 100,000, and the ASR was 9.44 per 100,000. A persistent north-south gradient was observed, with higher incidence in northern and central regions (Pavlodar, Kostanay, Karaganda, North Kazakhstan, Astana) and lower rates in southern regions. Spatial clustering analysis identified significant hotspots in northern regions and coldspots in the south. Age-Period-Cohort analysis demonstrated a strong age effect across all models. The net drift was +0.57% per year (95% CI 0.23-0.91; p=0.001), with the highest increases observed in older age groups (65-84 years). Period and cohort effects were also significant, indicating the influence of demographic aging, healthcare changes, and generational risk factors. Conclusion: Colon cancer incidence in Kazakhstan is characterized by pronounced spatial disparities and is primarily driven by population aging. The combined geospatial and Age-Period-Cohort analysis approach provides a comprehensive framework for understanding disease dynamics and supports the development of targeted cancer control strategies.