ArticleDigital health
Integrating machine learning and epidemiology to reveal trends in the disease burden of youth-onset rheumatoid arthritis and gout in East Asia: From 1990 to 2050.
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Abstract
Background: This study estimated the status of youth-onset rheumatoid arthritis (RA) and gout among adolescents and young adults (AYAs, aged 15-39 years) in East Asian five countries from 1990 to 2021, and analyzed disparities among these countries. Method: The numbers and age-standardized rates (ASRs) of prevalence, incidence, and disability-adjusted life years (DALYs) were calculated. Age-period-cohort (APC) analysis was employed to assess disease burden trends. Frontier analysis was applied to examine differences in health potential among countries. Eight machine learning time series models were employed to forecast the future burden trends. Results: China had the highest disease burden numbers among five countries in 2021 (e.g., gout prevalence cases: 1,434,359.2; incidence cases: 363,759.3; DALYs: 48,394.2). From 1990 to 2021, the Democratic People's Republic of Korea had the highest ASRs for gout (e.g., ASPR of 283.1 per 100,000 in 2021) and China had the highest ASRs for RA (e.g., ASDR of 20.9 per 100,000 in 2021). Male ASRs consistently exceeded female ASRs in gout, whereas the opposite pattern was observed in RA. APC analysis revealed that ASRs of both diseases increased with age and later birth cohorts. Machine learning forecasts indicated fluctuating upward trends by 2050. For instance, the Prophet model predicted that China's gout ASDR would rise to 9.3 per 100,000 (95% UI: 8.8-9.7) by 2050, while the ARIMA model suggested that China's RA ASPR would peak at 131.9 per 100,000 (95% UI: 128.1-135.8). The ARIMA model performed best for predicting ASPR in China and ASIR in Japan, whereas the Prophet was more appropriate for the remaining indicators. Conclusion: The burden of youth-onset RA and gout has become a major public health concern in East Asia. Therefore, East Asian countries should implement targeted screening strategies (such as early serum uric acid monitoring in young men) and formulate disease-specific interventions.
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