臺灣博碩士論文加值系統

前言
運用乳房攝影術以及其他工具進行乳癌檢在過去三十年間已發展得相當成熟並且廣泛運用於乳癌防治。雖然以族群方式運用乳房攝影作為篩檢工具可有效進行乳癌防治，對於運用個人化風險評估進行個人化的乳癌防治策略以在效率以及效用雙方面達成乳癌防治的目的近年來益發受到重視。對於BRCA第一型與第二型帶因者與非帶因者之乳癌防治措施有相當大的差異，如何區分族群中 BRCA第一型與第二型帶因者與非帶因者並分別提供適切的個人化乳癌防治策略做系統性的完整經濟評估在先前的研究中卻甚少被提及。
研究目標
本研究的主要目標在於
(1) 發展部分潛藏馬可夫模型在描述乳癌進展的同時將包含基因因子、傳統風險因子以及乳癌表現型等風險因子對於BRCA第一型與第二型帶因者與非帶因者在不同階段乳癌進程的影響納入模型考量中;
(2) 運用(1)之參數發展對於發生乳癌臨床症前期(preclinical detectable phase(PCDP)，即無症狀期)以及由臨床症前期進展成為臨床期(clinical phase, CP)之危險分數，藉以對目標族群進行危險分層；
(3) 架構於(1)與(2)之乳癌多階段疾病進程發展運用不同乳癌防治策略之馬可夫決策模型，藉以對各種防治策略進行評估；
(4) 對個人化乳癌防策略以及一致性乳癌防治策略分別以整體族群觀點以及BRCA第一型與第二型帶因者與非帶因者之觀點進行經濟評估。
材料與方法
本研究依BRCA第一型與第二型帶因者與非帶因者模擬一百萬名婦女，並發展三階段潛藏馬可夫模型描述無症狀乳癌存留於乳癌臨床症前期並成為篩檢偵測個案，以及其後續發展為具有症狀之臨床期乳癌成為篩檢間隔個案或拒絕個案之疾病進展過程。對於影響乳癌多階段進程之風險因子及其造成之疾病進展危險程度則由系統性文獻回顧獲得乳癌發生危險因子 (promotor) 以及乳癌進展危險因子(initiator)之影響。藉由不同危險因子的參數估計以及組合，可進一步得到乳癌由發生階段到進展階段之危險分數並據以對族群進行危險分層。對於不同乳癌疾病階段之防治策略，例如以預防性手術或以泰莫西芬(Tamoxifen)進行預防性投藥防止乳癌發生；或以不同篩檢間隔或篩檢工具進行乳癌篩檢偵測早期乳癌則以降低晚期乳癌以及乳癌死亡做為不同策略之效益評估指標。
本研究以所發展之部分潛藏馬可夫模型結合由實證資料中獲取之各乳癌疾病階段進程的危險因子模擬族群之乳癌進展過程。族群中之BRCA帶因狀態亦納入影響疾病演進之考量。 其他包含於模型之個人危險因子包含傳統風險因子(如身體質量指數、第一次足產年齡、使用荷爾蒙療法之病史)、基因因子如P53及單核苷酸多型性變異(SNPs)及乳癌病灶之免疫化學表徵(如ER、PR及Ki67)等不同類型之風險因子以建構多階段乳癌進展風險模型。這些個人化因子與對於不同階段之乳癌風險影響則進一步用以形成個人化危險分數據以進行族群危險分層。
基於上述之架構，本研究以馬可夫決策分析方法對個人化乳癌防策略以及一致性乳癌防治策略分別以整體族群觀點以及BRCA第一型與第二型帶因者與非帶因者之觀點進行經濟評估。
結果
對20到60 歲為起始年齡之BRCA帶因者估算之十年及終生乳癌發生危險分別介於6.5到 22% (十年乳癌危險)以及58 到 39% (終身罹癌危險)。對非BRCA帶因的50歲婦女，其十年及終生乳癌發生危險性在前10%高危險族群分別為3.36% 及 14.56% ，對最低10%危險性的婦女則分別為0.24%及1.1%。從無症狀至有症狀時期的時間間隔則隨著危險性增加而變短，介於3.74年至1.45年之間。
就均一乳癌防治策略而言，同樣利用乳房攝影術進行篩檢，族群採用的篩檢間隔愈短其效益愈大。一年一次的乳房攝影術篩檢相對於不篩檢在晚期乳癌及乳癌死亡的降低分別為13.9% (95% CI: 13.8-14.0%)及31% (95% CI: 30.9-31.1%)。若採風險分層建議篩檢間隔的個人化策略，則其效益介於統一每年篩檢與兩年一次篩檢之間，在晚期乳癌及乳癌死亡的降低分別為12.5% (95% CI: 12.4-12.6%)及28.4% (95% CI: 28.4-28.5%)，相似的結果可見於非BRCA帶因者之效益分析。對非BRCA帶因者而言，個人化篩檢間隔策略在風險較高者的效益較顯著，對具最高風險30%的婦女其晚期乳癌及乳癌死亡的降低分別為14.9% (95% CI: 14.8-15.1%) 及30.4 (95% CI: 30.3-30.5%)。針對個人化篩檢工具策略，其利用不同工具對於中度危險層(40-70百分位婦女)採乳房攝影術及乳房超音波之效益最大。
對BRCA帶因者結合初段與次段預防策略的效益整體說來不若非帶因者佳，主要是因為其疾病負擔較大。每年一次之篩檢所帶來之晚期乳癌風險降低介於16-18%之間，乳癌死亡降低則介於22-38%之間，此一效益之結果在合併預防性手術或預防性投藥作為介入策略之結果皆相近。若合併對以兩年於非BRCA帶因族群進行篩檢以及不同之BRCA帶因者介入策略以全族群角度進行效益評估結果顯示，對非BRCA帶因族群提供兩年一次乳房攝影以及對BRCA帶因族群中最高之20%婦女提供預防性手術結合對其餘80%風險之婦女進行每年乳房攝影可達成之效益最佳 (晚期乳癌風險降低：13.3%, 95信賴區間: 12.6-13.9%, 乳癌死亡風險降低：36.2%, 95CI: 25.3-26.6% )。
運用所發展之部分潛藏多階段馬可夫模型對以風險分層進行個人化篩檢間隔之乳癌防治策略進行經濟評估之結果顯示，此一篩檢策略之增量成本效益比(incremental cost-effectiveness ratio, ICER)為每人年美金34,585元 (95%信賴區間: 34,464-34,707元)，低於提供均一性每年乳房攝影篩檢(47,096元，95%信賴區間46946-47247元)以及每兩年乳房攝影篩檢(36,691元，95%信賴區間36,550-36,831元)。增量成本效益比在以風險分層提供個人化影像篩檢工具之策略則增為每人年115,838 元(95%信賴區間: 115,396-116,281)，此一結果主要是由於使用磁振掃描作為篩檢工具所需要之昂貴成本。對於非BRCA第一型與第二型帶因之族群進行個策略之經濟評估結果與此相似。綜合上述效益分析與經濟評估之結果顯示以風險分層為基礎之個人化篩檢間隔策略對於乳癌防治可用低於每兩年一次族群乳房攝影篩檢之增量成本效益比達到與對全族群提供每年一次乳房攝影篩檢相近之效益。此個人化篩檢間隔策略在付費意願(Willing-to-Pay, WTP)為2個平均國民所得標準下為一可接受之策略，而個人化篩檢工具策略即使在付費意願達3個平均國民所得標準仍未能達接受標準。
對於BRCA第一型與第二型帶因族群結合初段與次段預防策略之經濟評結果估計顯示，預防性手術結合乳房攝影之增量成本效益比為每人年2,722元，此一結果在增加磁振造影為篩檢工具之策略則增為49,884元。但若將對全族群進行基因檢測以獲取其BRCA帶因資訊所需花費之成本納入考量時，這些策略之增量成本效益比將大幅增加。對於BRCA帶因族群進行之策略在以2個平均國民所得作為付費意願標準多為可接受之策略。
結論
本研究為第一個運用系統化方式針對乳癌個人化防治策略進行經濟評估，並分別從BRCA帶因與非帶因者的角度進行詮釋。利用多階段個人風險預測模式的建構進行乳癌個人化防治不僅能有效降低乳癌的嚴重事件，且具成本效益。在個人化防治策略中，依個人危險提供不同篩檢間隔建議的策略最具成本效益，而個人化篩檢工具的使用能否具成本效益則被高危險族群所使用的影像工具之成本所決定。

誌謝 i
中文摘要 ii
Abstract vi
CONTENTS xii
LIST OF FIGURES xvi
LIST OF TABLES xviii
Chapter 1 Introduction 1
Chapter 2 Literature review 5
2.1 Literature review on breast cancer risk prediction 5
2.1.1 Risk prediction models for breast cancer using conventional factors 5
2.1.2 Risk prediction models for BRCA carrier status 9
2.1.3 Risk prediction models associated with SNPs 11
2.2 Literature review on multistate disease progression of breast cancer 12
2.2.1 Risk factors for the occurrence of breast cancer 12
2.2.2 Risk factors for the progression of breast cancer 14
2.3 Literature review on guidelines of breast cancer screening and diagnosis based on risk levels 15
2.4 Literature review on the cost-effectiveness analysis of breast cancer screening based on risk levels 17
Chapter 3 Risk-guided personalized preventive strategies for breast cancer 20
3.1 Systematic framework of risk-guided prevention of breast cancer 20
3.2 Personalized strategies for risk-score-based breast cancer screening 21
Chapter 4 Methodology of personalized partially-hidden multistate prediction model for breast cancer 23
4.1 Multi-state prediction model for asymptomatic and symptomatic BCs 23
4.2 Quantifying individual risk for the progression of breast cancer 24
4.3 Efficacy of intervention program 25
4.4 Cost-effectiveness analysis of personalized strategies for prevention of breast cancer 26
4.5 Markov decision framework for prevention of breast cancer 26
4.5.1 Markov decision model for the disease natural history of breast cancer 27
4.5.2 Markov decision model for the carrier of BRCA 29
4.5.3 Markov decision model for the non-BRCA carrier 30
4.6 Computer code for the cost-effectiveness analysis 30
4.6.1 Incorporating conventional risk factors and genetic factors in the progression of breast cancer 30
4.6.2 Define risk levels of breast cancer according the individualized risk score 44
4.6.3 Simulate the process of breast cancer evolution embedded in screening activity 46
4.6.4 Assessing efficacy of intervention 55
4.6.5 Assessing cost of interventions 58
Chapter 5 Results 66
5.1 Descriptive results of the simulated cohort 66
5.2 Estimated results of parameters on initiators and promoters 66
5.3 Multistate risk scores for initiators and promoters 66
5.4 Decile risk stratification of asymptomatic and symptomatic breast cancer 68
5.5 Efficacy and effectiveness of intervention 69
5.5.1 Efficacy of universal breast cancer screening 69
5.5.2 Efficacy of primary and secondary preventions for BRCA carriers 69
5.5.3 Efficacy of screening with various inter-screening interval by risk groups 70
5.5.4 Efficacy of multimodality approach 70
5.6 Results on cost-effectiveness analysis 70
5.6.1 Universal strategies for the overall group 70
5.6.2 Personalized strategies for the overall group 71
5.6.3 Screening strategies for non-BRCA carrier 71
5.6.4 Preventive strategies for BRCA carrier 72
Chapter 6 Discussion 74
6.1 Era of tailored prevention of breast cancer 74
6.2 Personalized risk stratification of the underlying population 75
6.3 Risk-guided personalized prevention of breast cancer 75
6.4 Methodological Considerations 77
6.5 Limitations 77
6.6 Conclusion 78
FIGURES 79
TABLES 119
REFERENCE 153

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