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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳秀熙 | |
dc.contributor.author | Chiung-Jung Wen | en |
dc.contributor.author | 温瓊容 | zh_TW |
dc.date.accessioned | 2021-05-14T17:47:16Z | - |
dc.date.available | 2016-03-12 | |
dc.date.available | 2021-05-14T17:47:16Z | - |
dc.date.copyright | 2015-03-12 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-02-15 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/4790 | - |
dc.description.abstract | 研究背景 巴金森氏症是第二常見的退化性疾病,最終會導致身體功能下降以及減少壽命。及早治療可以延緩疾病的進展以及延長存活時間,故及早診斷及治療益發顯得重要。但根據巴金森氏症的異質性建構其疾病自然史並探討早期診斷巴金森氏症的效益的研究仍很少見。因此,本篇論文的研究目的主要有三: 1.利用一個以社區為基礎的族群,比較主動偵測與被動偵測巴金森氏症的效益 2.建立以Hoehn-Yahr 分類疾病階段(簡稱H-Y stage)為基礎的巴金森氏症疾病自然史,並且將可能影響疾病自然史轉移速率的因子加入模式中 3.進行早期偵測巴金森氏症的成本效益分析。
材料與方法 本研究資料來源為2001年基隆社區巴金森氏症篩檢的資料。第一部分研究先比較兩種偵測巴金森氏症的方式(主動偵測與被動偵測)的累積偵測率及H-Y stage的分布。第二部分研究則利用非標準化的病例-世代設計於以H-Y stage為基礎的巴金森氏症疾病自然史。我們利用三階段及五階段的馬可夫模式去建構以H-Y stage為基礎的巴金森氏症疾病自然史。我們將可能影響疾病自然史的因子如基本資料、生活習慣以及飲食習慣也考慮於疾病自然史中。最後,我們利用所建構五階段的馬可夫模式,模擬60歲以上的研究世代 ,在追蹤20年後在不同篩檢策略下所得之巴金森氏症篩檢的成本效益及成本效用分析。疾病進展的參數得自第二部分得自實證資料所估計的自然病史,成本及效益均折現3%,在模擬1000個樣本大小為10000人的世代族群所得在不同篩檢策略下的累積成本效益/效用後,分別依每多增加一年及每多增加一生活品質校正年所需增加的成本、在不同的付費意願下的成本效益/效用接受曲線、及成本-效益/效用散佈圖進行比較。 結果 主動偵測和被動偵測分別偵測出192個以及89個巴金森氏症病人。主動偵測比被動偵測約可找出1.8倍多(95%CI: 1.4-2.3)的巴金森氏症病人,並且在主動偵測組中早期(H-Y stage I,II)的個案所佔的比例顯著多於被動偵測組(80.4% vs. 61.5%, p=0.04) 。 結果顯示疾病自然史在三階段的馬可夫模式中,一個60歲以上的人發生巴金森氏症的年發生率為千分之8.2。從可偵測前期至臨床期的轉移率0.5935 (95% CI: 0.4330-0.7541),即其平均滯留期為1.68年。在五階段的馬可夫模式中,發生巴金森氏症的年發生率為千分之7.8。從可偵測前期的早期到晚期(H-Y stage III+)的年轉移速率為0.2498 (95% CI:0.1420-0.3576);從可偵測的早期到臨床早期的年轉移速率為0.3982(95% CI: 0.2564-0.5399)。從可偵測晚期到臨床晚期的年轉移速率2.1227(95% CI: 0.5109-3.7346)。考量不同的特性對五階段模式中各狀態間轉移速率的影響,結果顯示每增加10歲,發生巴金森氏症的相對危險性為1.79倍 (95% CI: 1.32-2.44) 且加速篩檢可偵測早期進展到可偵測晩期的速率,其相對危險性為5.08倍(95% CI: 1.94-13.29)。低尿酸濃度同樣為巴金森氏症的危險因子,其相對危險性為1.54倍(95% CI: 1.04-2.28)。教育程度較高者其自篩檢可偵測早期到晚期的速率亦較高 (RR=14.65, 95% CI: 2.94-54.53)。 根據模擬的資料所得到不同篩檢間隔的結果來評估篩檢的效益中,每年篩檢可以降低71% (95%CI: 65-80%)進展至晚期巴金森氏症的百分比,若篩檢間隔分別為兩年、三年、四年或六年,則可以降低進展至晚期巴金森氏症的百分比分別為54% (95% CI: 45-62%)、43% (95%CI: 32-52%)、35% (95%CI: 23-45%)、以及25% (95% CI:12-36%)。 由決定性模式所得成本效益及成本效用分析的結果分別為每增加一人年需多花$1169到$1804;每增加一生活品質校正年需多花$1715到$2606。在每增加一人年之付費意願$20,000下,每年篩檢可得到最大的淨效益($280,687),其次為每二年一次($280,511)及每三年一次($280,416)和無篩檢($280,113),相同的趨勢亦反映在以生活品質校正年的淨效益結果。 機率性成本效益分析的結果顯示付費意願$20,000下,在參與率為100%及60%下具成本效益的機率為69-79%及64-74%;相對條件下具成本效用的機率分別為62.6%-70.2%和58.2%-62.6%。 結論 主動偵測比被動偵測的方式可偵測出幾乎兩倍的個案,並且可以減少49%的晚期巴金森氏的病人。結果顯示,一個60歲以上的人平均從篩檢可偵測期進展到臨床期的時間約為兩年。篩檢的間隔越密集,可以減少進展至H-Y stage晚期的比率越大。依H-Y疾病狀態去建構病人是屬於篩檢可偵測的早期進展到臨床期或由篩檢可偵測的晚期進展到臨床期的疾病自然史模式,可提供巴金森氏症早期偵測的探討空間。應用這些狀態轉移的參數,本論文說明了愈密集的篩檢間隔可降低晚期巴金森氏症的比例愈大,具成本效益的機率也愈大。 | zh_TW |
dc.description.abstract | Background Parkinson’s disease (PD) is the second most common degenerative disorder which will eventually cause functional decline and reduce lifespan. The development of therapies that slow disease progression and improve survival makes early detection and treatment of PD especially important. Besides, the characteristics of heterogeneity in natural history and the uncertainty in the decision analysis of early detection of PD prevention have not been fully investigated. The aims of this thesis consist of three parts: (1) the first was to to use a community-based cohort to compare the detection methods for active detecting PD. (2) the second was to elucidate the temporal natural history of Hoehn-Yahr-stage-based PD with a Markov process with and without the incorporation of covariates into different transitions corresponding to the natural history model and the third part was to evaluate the cost-effectiveness analysis.
Material and Method First part of data were derived from a community-based screening survey for PD in 2001. Cumulative detection rate and Hoehn-Yahr (H-Y) stage distribution of both the active and passive detection groups were estimated and compared. In the second part, we use a non-standard case-cohort design for modelling the natural history of H- Y stage-base PD. We built a three-state and a five-state Markov models for the H-Y stage-based natural history. Variables such as baseline characteristic, life style and dietary habit were collected and were incorporated into the model to assess the effect of each covariate on respective transitions. In the final part, the Markov decision analysis was envisaged to estimate the cost-effectiveness and cost-utility of active screening for PD in the community setting for residents aged 60 years or older over a 20-year period. We used a five-state Markov model to simulate the progression of PD and the sequel afterwards. The cumulative cost under different strategies was also collected. Parameters of disease progression followed the empirical estimates of the temporal natural history in the second Part. The main outcome measure was cost per life-year gain and per quality-adjusted life-year (QALY) gained with a 3% annual discount rate. The scattered cost-effectiveness plane (CE plane) and acceptability curve was presented given a 1000 Monte Carlo simulated samples for running 10,000 trials. Results One hundred and ninty-two IPD cases and 89 IPD were detected by the active and passive detection methods, respectively. The active method detected approximately 1.8-fold (95% confidence interval: 1.4-2.3) the IPD cases of the passive method. Early H-Y stage (stage I and II) IPD cases were statistically significantly higher in the active method than in the passive method (80.4% vs. 61.5%, p=0.04). Base on a three-state homogeneous Markov model, annual incidence rate of being susceptible to PD for subjects aged 60 years or older was 8.2 per 1000 person-years. Annual transition rate from screening detectable (SD) phase to clinical detectable (CD) phase was 0.5935 (95% CI: 0.4330-0.7541), which yielded 1.68 years of mean sojourn time staying in the SD phase. In a five-state homogeneous Markov model, the estimate incidence of SD phase PD was similar to that estimated from the three-state model, 7.8 per 1000. The transition rate from H-Y I/II to H-Y III+ in the SD phase was 0.2498 (95% CI: 0.1420-0.3576). The transition rates from SD to CD for early stage (H-Y I/II) and late stage (H-Y III+) were 0.3982 (95% CI: 0.2564-0.5399) and 2.1227 (95% CI: 0.5109-3.7346), respectively. Considering the effects of patient specific covariate on the transitions in the five-state model, the results of multivariable analysis on multiple transition shows that advancing age led to an increased 10 years risk of developing PD (aRR=1.79, 95% CI: 1.32-2.44) and faster transition from HY I/II to HY III+ before surfacing to CD phase (RR=5.08, 95% CI: 1.94-13.29). Low level of uric acid also played the role of risk factor in the incidence of PD (RR=1.54, 95% CI: 1.04-2.28). High level of education strongly affected the transition from HY I/II to HY III+ before surfacing to CD phase (RR=14.65, 95% CI: 2.94-54.53). In the simulated results for effectiveness of different screening interval, annual screening reduced 71% (95% CI: 64-77%) reduction of advanced stage (H-Y stage III+) cases compared to no screen. When the inter-screening intervals were 2-yearly, 3-yearly, 4-year, or 6-yearly, reduction of advanced H-Y stage cases was 54% (95% CI: 45-62%), 43% (95% CI: 32-52%), 35% (95% CI: 23-45%), and 25% (95% CI: 12-36%), respectively. The results from deterministic Markov decision analysis of the cost-effectiveness and cost-utility analysis shows that the incremental cost-effectiveness ratios (ICER) of PD screening with different inter-screening intervals compared to no screen ranged from $1169 to $1804 per life-year gained. The incremental cost-utility ratio ranged from $1715 to $2606 per quality-adjusted life-year gained. The annual screen had the greatest net monetary benefit (NMB) ($280,687) in terms of life-year gained, followed by biennial ($280,511), triennial ($280,416) screen, and no screen ($280,113). The same trend was observed for the NMB in terms of QALY gained. The results of the probabilistic Markov decision models shows that the probability of screening programs being cost-effective at $20,000 of willingness-to-pay (WTP) was 69-79% and 64-74% given 100% and 60% of attendance rates, respectively. The corresponding figures in the cost-utility analyses were 62.6%-70.2% and 58.2-62.6% given 100% and 60% of attendance rates, respectively. Conclusion The active method detected almost two times the PD cases as the passive method and also reduced 49 % (95% CI: 4%-73%) the IPD cases classed in H-Y stage III or greater. Our results reveal that an individual aged 60 year or older who is susceptible to PD and entered the SD phase would progress to CD, on average around 1.5 years. The progression from the SD to the CD by H-Y stage had been quantified with detectable window for the identification of early H-Y stage before the transition to late H-Y stage which form the bases of the best-case estimates for the disease progression of PD in the absence of screening. With the application of these transition parameters, this thesis demonstrates that if the intensive screening for PD is offered, the large the reduction in late H-Y PD would be achieved and the probability of being cost-effective could be high. | en |
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dc.description.tableofcontents | 誌謝………………………………………………………………i
中文摘要 ………………………………………………………..ii ABSTRACT………………………………………………………vi. Chapter 1 Introduction....................................18 1.1 Impact of Parkinson’s Disease.................. ..18 1.2 Temporal Natural History Based on Hoehn and Yahr stage ..................................................19 1.3 The Importance of Active Detective Method for Parkinson’s Disease Classified by Hoehn and Yahr Stage...19 1.4 Effectiveness of Early Detection and Treatment for Parkinson’s Disease......................................20 1.5 Cost-effectiveness Analysis of Early Detection for Parkinson’ Disease..................................... 21 1.6 Motivation and Aims of the Study.................22 Chapter 2 Literature Review..............................24 2.1 Burden of Parkinson’s Disease...................24 2.1.1 Clinical characteristics of Parkinson’s Disease 24 2.1.2 Incidence........................................24 2.1.3 Prevalence.......................................24 2.2 Natural History of Parkinson’s Disease with Hoehn-Yahr Stage...............................................26 2.3 Stochastic Models for Disease Natural History....28 2.3.1 Introduction of Markov Model.....................28 2.3.2 Three-state Homogeneous Markov Model for Disease Natural History..........................................30 2.3.3 Three-state Model with Weibull Distribution.......31 2.3.4 Incorporation of patient specific covariates......33 2.3.5 Bayesian inversion for a non-standard case-cohort design....................................................33 2.3.6 Five-state non-homogeneous stochastic model.......35 2.3.7 Semi-Markov Model.................................37 2.4 Covariates associated with the progression of Parkinson’s Disease......................................39 2.4.1 Risk Factors......................................39 2.4.2 Protective Factors..................................42 2.5 Quality of Life by Hoehn-Yahr Stage...............45 2.6 Cost-effectiveness Analysis in Parkinson’s Disease ..................................................47 2.6.1 Cost Analysis of Parkinson’s Disease.............47 2.6.2 Cost Effectiveness Analysis of Parkinson’s Disease ..................................................48 Chapter 3 Study Design and Data Source....................50 3.1 Study Cohort......................................50 3.2 Study design......................................51 3.2.1 Cross-sectional survey............................51 3.2.2 Natural History of Parkinson’s Disease with Hoehn-Yahr Stage with Stochastic Process Based on Case-cohort Design....................................................53 3.2.3 Data Collection.....................................54 3.2.4 Homogeneous Markov model incorporated with covariates associated with the transition rates...........56 3.2.5 Cost-effectiveness analysis for early detection of Parkinson’s disease......................................56 Chapter 4 Hoehn-Yahr stage-based natural history of PD with Stochastic Process........................................58 4.1 Homogeneous Markov model..........................58 4.1.1 Model Specification.................................58 4.1.2 Likelihood..........................................61 4.1.3 Estimation of parameter.............................70 4.2 Incorporation of patient specific covariates..........70 4.3 Simulation for the effect of screening policy.........71 4.4 Cost-effectiveness Analysis...........................73 Chapter 5 Results.........................................79 5.1 Part I: Compare the two detection methods for detecting Parkinson’s disease......................................79 5.2 Part II: To Elucidate the temporal natural history of Hoehn-Yahr- stage-based Parkinson’s disease with stochastic process........................................81 5.2.1 Three-state Markov model............................81 5.2.2 Five-state Markov model.............................84 5.2.3 Incorporation of patient specific covariates for the five-state Markov model...................................85 5.3 Part III: Cost-effectiveness of Population-based Screening for PD..........................................89 5.3.1 Simulation for the effect of screening policy.......89 5.3.2 Results of deterministic cost-effectiveness and cost-utility analysis..........................................90 5.3.3 Results of probabilistic cost-effectiveness and cost-utility analysis..........................................91 Chapter 6 Discussion......................................94 6.1 Part I: Compare the two detection methods for active detecting Parkinson’s disease............................94 6.2 Part II: Natural History of Parkinson’s Disease by Hoehn-Yahr Stage..........................................97 6.3 Part III Cost-effectiveness Analysis of screening of PD .................................................102 Chapter 7 Conclusion.....................................107 FIGURES..................................................108 TABLES..................................................134 ABBREVIATION NOTE........................................165 REFERENCE................................................166 | |
dc.language.iso | en | |
dc.title | 隨機過程應用於預防巴金森氏症Hoehn-Yahr 分類疾病進展之實證評估 | zh_TW |
dc.title | Evidence-based Evaluation of Preventing Progression of Hoehn-Yahr-stage-based Parkinson’s Disease with Stochastic Process | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-1 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 劉宏輝,黃國晉,程蘊菁,嚴明芳,潘信良 | |
dc.subject.keyword | 巴金森氏症,早期篩檢,成本效益,Hoehn-Yahr分類, | zh_TW |
dc.subject.keyword | Parkinson's disease,Early Screening,Cost-Effectiveness,Hoehn-Yahr Stage, | en |
dc.relation.page | 173 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2015-02-15 | |
dc.contributor.author-college | 公共衛生學院 | zh_TW |
dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
顯示於系所單位: | 流行病學與預防醫學研究所 |
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