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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳秀熙(Hsiu-Hsi Chen) | |
| dc.contributor.author | Fu-Jen Lee | en |
| dc.contributor.author | 李輔仁 | zh_TW |
| dc.date.accessioned | 2023-03-19T22:14:19Z | - |
| dc.date.copyright | 2022-10-13 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-09-23 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84522 | - |
| dc.description.abstract | 背景 由於糞便血紅蛋白濃度（f-Hb）已被證明是大腸直腸癌發生及死亡的預測因子。因此，如何利用 f-Hb 結合已開發的個人化基因資料來運用糞便免疫測試 (FIT)來發展個人化大腸直腸癌是值得研究的。 研究目的 鑑於有限的醫療資源和大腸鏡檢查的專業人力，我們的目標是開發精準的大腸直腸癌 FIT 篩檢，以優化 FIT 和大腸鏡檢查的使用。 研究方法 我們首先建立了一個具有特定狀態相關多因子多階段疾病進展模型，利用此模型發展一動態個人化風險預測模型，用於從小腺瘤到大腺瘤和臨床前可偵測大腸直腸癌( CRC )直至臨床期 CRC 的轉變。我們使用透過文獻回顧可獲得的資料來估計每個特定疾病狀態中相關因子的臨床比重。我們依照個人化風險預測模式使用數位雙胞胎方法創建兩個虛擬組別，分別為兩年篩檢與精準個人化篩檢。我們使用馬可夫指數回歸模式來估計臨床權重以建立多重疾病狀態風險分數。 結果 我們呈現多重疾病狀態風險分數並衍生動態個人化風險曲線。發展每十分位數分布的風險分數來預測大腸直腸癌的風險。更依據此風險分數將篩檢間隔分為1-6年形成個人化篩檢依據。在這一百萬人口中，我們所設計的個人化篩檢間隔結果發現精準大腸直腸癌FIT可減少12% FIT檢測量，在 7% 的陽性率下，產生840251次FIT 和 58818支大腸鏡檢查的減少。 結論 透過發展個人化不同間隔的篩檢(不管有無結合糞便DNA測試)，我們證實糞便血紅蛋白濃度合併基因訊息的最佳使用可以減少FIT測試及大腸鏡檢查。 | zh_TW |
| dc.description.abstract | Background As fecal hemoglobin concentration (f-Hb) has been demonstrated as a predictor for incident colorectal cancer and its mortality, it is of worthy of being investigated how to make use of f-Hb combined with the already developed personalized genetic profiles to develop personalized colorectal cancer screening with fecal immunological test (FIT). Objective We aimed to develop precision colorectal cancer FIT screening for the optimal use of FIT and colonoscopies given limited medical resources and professional manpower for colonoscopy. Methods We first built up a multistate disease progression model with the superimposition of state-specific correlates for dynamic personalized risk prediction model for each transition from small adenoma, through large adenoma and pre-clinical detectable CRC until clinical CRC. Each clinical weight corresponding to each state-specific correlate was estimated by using available empirical tabular data from literature review. A digital twin approach was used to create two virtual groups guided by the proposed individualized multistate risk prediction model including biennial screening regime versus precision screening regime. The Markov exponential regression model was applied to estimate clinical weights for building multistate risk scores. Results Multistate risk scores are presented for deriving dynamic personalized risk curves. The decile distribution of risk score was developed for predicting the risk of CRC. Various inter-screening intervals were further assigned for each decile of risk score ranging from 1 to 6 years. Given personalized inter-screening interval assigned for one million population, precision CRC FIT reduced 12% of FIT test, yielding the reduction of 840251 FIT and 58818 colonoscopies given 7% positive rate. Conclusions The optimal use of f-HB with or without combing genetic profiles for reducing FIT test and colonoscopies has been demonstrated by developing personalized inter-screening with and without stool DNA test. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T22:14:19Z (GMT). No. of bitstreams: 1 U0001-2209202212114100.pdf: 1639558 bytes, checksum: b257cfdd156c07d69038994301cd8901 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 目錄 謝辭 i 中文摘要 ii Abstract iii 目錄 iv 圖目錄 vi 表目錄 vii 第一章 導論 1 1.1 實習單位特色與簡介 (Practicum Unit Features and Brief Introduction) 1 1.2 大腸直腸癌疾病負擔與組織性篩檢策略 1 1.3 文獻回顧 3 1.3.1 大腸直腸癌之免疫糞便潛血篩檢 3 1.3.2 多標靶糞便DNA檢查(Multi-Target Stool DNA Test) 在大腸直腸癌篩檢的角色 4 1.3.3 大腸直腸癌的個人化篩檢策略 5 1.3.4 大腸直腸癌疾病進展 5 1.3.5 多階段進程與大腸癌疾病進展 7 1.4 研究目的與研究問題 (Research Purpose and Research Problems) 8 1.4.1 研究動機 8 1.4.2 研究目的 9 第二章 材料與方法 10 2.1 研究資料建構 10 2.2 大腸直腸癌多階段疾病進展 10 2.3 大腸直腸癌篩檢策略 11 2.4 篩檢策略效益評估指標 11 2.5 族群篩檢策略評估 12 第三章 結果 13 3.1 建構大腸直腸癌多階段和多因子模型 13 3.2 糞便血紅蛋白(f-Hb)濃度對大腸直腸癌風險的影響 16 3.3 風險分類 (Risk classification) 17 3.4 大型腺瘤至大腸直腸癌的停留時間(dwelling time) 17 3.5 個人化大腸結腸癌篩檢效益 18 3.6 從基因及糞便血紅蛋白(f-Hb)濃度評估大腸直腸癌風險 20 3.7 個人化大腸結腸癌篩檢優勢 21 第四章 討論 23 4.1 結合糞便血紅蛋白濃度及糞便DNA檢測之個人化篩檢的利益 23 4.2 結合糞便血紅蛋白及基因為導向的個人化多狀態風險評估模型 23 4.3 基因檢測的經濟考量 24 4.4 關於個人化風險電腦運算的臨床應用相關性 24 4.5 研究限制 24 4.6 結論 25 參考文獻 26 圖目錄 圖1 大腸直腸癌的自然病史圖 6 圖2 不同階段皆有影響因子大腸癌五階段自然病史馬可夫模型 13 圖3 誘發大腸腺瘤之危險因子的相對風險 14 圖4 馬可夫大腸癌自然病史模型中，第二階段至第五階段之基因危險因子之相對風險 15 圖5 基礎糞便血紅濃度與大腸直腸癌死亡率之風險比例 16 圖6 不同風險評分百分位數的大腸直腸癌累積風險 17 表目錄 表1 不同引發因子組合下，大腺瘤到浸潤癌的停留時間 18 表2 不同篩檢策略降低大腸直腸癌死亡率有效性的模擬結果（按風險百分位） 19 表3 依風險分層大腸癌罹病風險、陽性概似值及陰性概似值 20 表4 依風險分層個人化篩檢策略建議 21 表5 無篩檢、兩年一次免疫法篩檢及個人化篩檢模擬結果 22 | |
| dc.language.iso | zh-TW | |
| dc.title | 結合糞便血紅蛋白及基因模式的大腸直腸癌個人化篩檢 | zh_TW |
| dc.title | The Combination of Fecal Hemoglobin with Gene for Personalized Colorectal Cancer Screening | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 李宜家(Yi-Chia Lee),邱瀚模(Han-Mo Chiu),張吉仰(Chi-Yang Chang) | |
| dc.subject.keyword | 個人化篩檢,糞便血紅蛋白濃度,大腸直腸癌,風險分層,馬可夫模型, | zh_TW |
| dc.subject.keyword | Personalized screening,Fecal hemoglobin concentration,Colorectal cancer,Risk stratification,Markov model, | en |
| dc.relation.page | 35 | |
| dc.identifier.doi | 10.6342/NTU202203804 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-09-23 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 公共衛生碩士學位學程 | zh_TW |
| dc.date.embargo-lift | 2022-10-13 | - |
| 顯示於系所單位： | 公共衛生碩士學位學程 | |
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