رسالة جامعية
Bayesian Statistical Models for Assessing and Predicting Incidence, Case-fatality, and Mortality of Hepatocellular Carcinoma
| العنوان: | Bayesian Statistical Models for Assessing and Predicting Incidence, Case-fatality, and Mortality of Hepatocellular Carcinoma |
|---|---|
| العنوان البديل: | 貝氏統計模型應用於評估及預測肝癌發生率、致死率與死亡率 |
| المؤلفون: | Sih-Han Liao, 廖思涵 |
| مرشدي الرسالة: | Hsiu-Hsi Chen, Kuo-Liong Chien, 陳秀熙, 簡國龍 |
| سنة النشر: | 2019 |
| المجموعة: | National Digital Library of Theses and Dissertations in Taiwan |
| الوصف: | 107 Background After a series of prevention programs of hepatocellular carcinoma (HCC) over four decades, the overall incidence and mortality of HCC have started to decline between the late 1990s and the early 2000s in Taiwan. However, whether such declining trends of incidence and mortality have the same pattern by age groups and geographic areas is still elusive. Elucidating the time trends of both incidence and mortality in relation to these prevention programs play an important role in predicting the disease burden of HCC for decision-makers. Aims This thesis aimed to (1) report and assess the respective contributions of both time trends in incidence and case-fatality rate to the time trend of mortality by different age groups with empirical data and the modelling approach; (2) assess the effects of baseline (intercept), gradient (slope), and three change-point on time trends of incidence, case-fatality rate, and mortality; (3) predict three time trends of incidence, case-fatality rate, and mortality rate until 2025. Data Sources Empirical data used for estimating the parameters of the underlying model were derived from national vital statistics on incident cases of and deaths from HCC between 1979 and 2016 spanning three main interventions, mass vaccination, national health insurance, and antiviral therapy commencing from 1984, 1995, and 2004 (three change-points), respectively. Methods The empirical time trends of mortality were decomposed into both of incidence and case-fatality by age groups and geographic areas. We then developed a Bayesian mortality decomposition Poisson regression model to estimate the attributable proportion of incidence and case-fatality contributing to mortality due to three change-points of intervention programs. Bayesian hierarchical change-point models were proposed to model a cascade of the impacts from baseline values, gradients, and change-point on incidence, case-fatality, and mortality with respect to four age groups and 20 geographic areas. Results Based on Poisson regression underpinning, a statistical method was developed to decompose the trend change in mortality into the proportions attributable to incidence and case-fatality. The HCC mortality and incidence of individuals aged 30 to 84 years between 1979 to 2013 was extracted to evaluate the attributable proportion. Based on the time trends of HCC mortality and incidence incorporated with the time points for the implementation of interventions, the changing points were set in 1984, 1995 and 2004. 1979 to 1983, 1984 to 1994, 1995 to 2003 and 2004 to 2013 were defined as Period 1, 2, 3 and 4. The overall mortality reduction for Period 4 compared with Period 1 was -42.3% (95% CI: -46.0 to -38.3%) in the middle-aged group (30-49 years). When the mortality change was separated into the impact of incidence and survival, the results showed an increase in +51.3% (95% CI: 47.2 to 55.4%) attributable to incidence which was overwhelmed by a reduction in case-fatality rate (-71.9%, 95% CI: -74.8 to -68.8%). The overall mortality reduction for Period 4 compared with Period 3 was -22.8% (95% CI: -24.1 to -21.5%) in the middle-age group (50-69 years). This was separated into the proportion attributable to incidence and survival, which showed a reduction by -10.7% (95%CI: -12.1 to -9.3%) in HCC incidence during the period of national viral hepatitis therapy program. The change in HCC mortality for Period 4 compared with Period 2 was +41.0% (95% CI: 39.0 to 43.0%) in the old-age group. When further decomposing the mortality change for the elders into the proportion attributable to incidence and case-fatality, the results showed a reduction by -47.7% (95% CI: -50.0 to -45.3%) in HCC deaths due to improved survival after universal health care implementation. However, the efficacy was compromised by the increase in incidence rate (+69.2%, 95% CI: 68.2 to 70.1%) in the old age group. Using significant impacts of three intervention programs at individual and county level estimated by using Bayesian hierarchical change-point model, time trends of incidence until 2025 were predicted as 0.41 (95%CI: 0.29-0.54), 17.9 (95%CI: 16.1-20.0), 110.0 (95%CI: 99.8-120.8), and 314.9 (95%CI: 285.9, 346.8) per hundred thousand for < 30, 30-49,50-69, and ≥ 70 years for male and as 0.26 (95%CI: 0.16-0.39), 2.85 (95%CI: 2.36-3.40), 30.1 (95%CI: 26.7-34.0), and 183.7 (95%CI: 163.8-205.1) per hundred thousand for < 30, 30-49,50-69, and ≥ 70 years for female, respectively. For mortality, time trends until 2025 were predicted as 0.08 (95%CI: 0.05-0.11), 9.9 (95%CI: 9.1-10.8), 69.1 (95%CI: 65.0-73.4), and 274.1 (95%CI: 257.1-291.8) per hundred thousand for < 30, 30-49,50-69, and ≥ 70 years for male and as 0.09 (95%CI: 0.05-0.17), 1.5 (95%CI: 1.2-1.8), 17.9 (95%CI: 16.4-19.5), and 165.4 (95%CI: 153.2-178.2) per hundred thousand for < 30, 30-49,50-69, and ≥ 70 years for female, respectively. For overall fatality, time trends until 2025 were predicted as 0.60 (95%CI: 0.42-0.82). Conclusions Bayesian Poisson were developed here to assess the respective contributions of three main prevention program to incidence and case-fatality and Bayesian hierarchical change-point models were used to predict the disease burden of HCC until 2025. These findings have significant implication for providing a new insight into health care planning for prevention of HCC by different age groups and different counties. |
| Original Identifier: | 107NTU05544024 |
| نوع الوثيقة: | 學位論文 ; thesis |
| وصف الملف: | 120 |
| الإتاحة: | http://ndltd.ncl.edu.tw/handle/a794h3Test |
| رقم الانضمام: | edsndl.TW.107NTU05544024 |
| قاعدة البيانات: | Networked Digital Library of Theses & Dissertations |
| الوصف غير متاح. |