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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 李文宗 | |
dc.contributor.author | Tzu-Hsuan Huang | en |
dc.contributor.author | 黃紫渲 | zh_TW |
dc.date.accessioned | 2021-06-17T09:07:39Z | - |
dc.date.available | 2025-03-13 | |
dc.date.copyright | 2020-03-13 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-11-28 | |
dc.identifier.citation | 1. Taiwan Cancer Registry Unit. Cancer Registry Annual Report 2016. Taiwan: Health Promotion Administration Ministry of Health and Welfare Taiwan.
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Mariotto AB, Noone AM, Howlader N, et al. Cancer survival: anoverview of measures, uses, and interpretation. J Natl Cancer Inst Monogr. 2014;2014(49):145–186. 15. 25. Estève J, Benhamou E, Croasdale M, Raymond L. Relative survival and the estimation of net survival: elements for further discussion. Stat Med. 1990;9(5):529–538. 16. Belot A, Ndiaye A, Luque-Fernandez MA, Kipourou DK, Maringe C, Rubio FJ, Rachet B. Summarizing and communicating on survival data according to the audience: a tutorial on different measures illustrated with population-based cancer registry data. Clinical Epidemiology 2019;11:53–65. 17. P.C. Lambert, P.W. Dickman, C.P. Nelson, P. Royston, Estimating the crude prob- ability of death due to cancer and other causes using relative survival models, Stat. Med. 2010; 29:885–895. 18. Bouvier AM, Remontet L, Hedelin G, et al. Conditional relative survival of cancer patients and conditional probability of death: A French National Database analysis. 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Surg Endosc. 2005;19(5):687–692. 35. Anderson O, Ni Z, Møller H, et al. Hospital volume and survival in oesophagectomy and gastrectomy for cancer. Eur J Cancer. 2011;47(16):2408-2414. 36. Hannan EL, Radzyner M, Rubin D, Dougherty J, et al. The influence of hospital and surgeon volume on in-hospital mortality for colectomy, gastrectomy, and lung lobectomy in patients with cancer. Surgery. 2002;131(1), 6-15. 37. de Angelis R, Sant M, Coleman MP, et al. Cancer survival in Europe 1999-2007 by country and age: results of EUROCARE-5-a population-based study. Lancet Oncol. 2014;15(1):23–34. 38. Allemani C, Weir HK, Carreira H, et al. Global surveillance of cancer survival 1995–2009: analysis of individual data for 25, 676, 887 patients from 279 population-based registries in 67 countries (CONCORD-2). Lancet. 2015;385(9972):977–1010. 39. Wang Y, Chiang CJ, Lee WC. Age-standardized expected years of life lost: quantification of cancer severity. BMC Public Health. 2019; 19: 486. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74791 | - |
dc.description.abstract | 截至2018年,癌症已連續36年蟬聯台灣十大死因第一位。隨著高齡化的趨勢,癌症所造成的社會負擔,已是台灣群體健康的重要議題。受限於死亡登記檔死因錯誤分類(Misclassification)以及垃圾死因碼(Garbage Code)的問題,目前進行的存活分析大多都是使用全死因死亡為終點事件的存活分析(Overall Survival)。然而,近期在全人口的癌症存活分析中,相對存活分析(Relative Survival)的概念已經越來越被討論。相較於傳統的存活分析方式,相對存活分析納入了競爭風險(Competing Risks)的概念,利用癌症造成的額外死亡風險率(Excess Mortality Hazard),將癌症病患的死亡分解成因癌症而死亡以及因其他非癌症因素而死亡兩部分。進而在假設癌症病患只會死於癌症,而不會死於其他競爭死因的假想情境中,推算出可用在不同族群、國家之間比較的兩個指標:淨存活率(NS)與設限平均淨存活時間(RMNST); 以及真實情境中計算出來的兩個存活機率指標和兩個存活時間指標,分別為:癌症病患死於癌症的粗死亡機率(CPDcancer)、癌症病患死於非癌症因素的粗死亡機率(CPDother)、因癌症所造成的設限平均生命損失(NLYLcancer)以及因其他非癌症因素所造成的設限平均生命損失(NLYLother)。這四個指標提供了比以往更精確的癌症存活狀況,同時也進一步地描繪出因罹患癌症所造成的疾病預後狀況與生命損失。本研究藉由台灣癌症登記資料與死亡登記資料,納入1997年1月1日至2007年12月31日被診斷成癌症的病患,並追蹤至2017年12月31日。本研究藉由相對存活分析的各個指標,以性別、年齡、居住地都市化程度、收治醫療院所規模以及癌症期別作為分層變項,完整的描述台灣18種癌症的癌症病患因癌症與其他非癌症因素所造成的預後狀況與生命損失。 | zh_TW |
dc.description.abstract | Cancer has been the leading cause of death for 37 years since 1982 in Taiwan. For evaluating the prognosis of cancer patients, population-based cancer survival analysis plays an important role. However, researchers are unable to distinguish the deaths due to cancer and others because the cause of death is unreliable, such as misclassified and garbage code. In contract to conventional survival analysis, relative survival analysis allows researchers to disentangle the impact on survival of the cancer from other causes of death by estimating excess mortality hazard of cancer even when the cause of death is unavailable or unreliable.
In relative survival setting, net survival probability (NS) and restricted mean net survival time (RMNST) estimates the survival that cancer patients would experience if they could only die from the cancer under study. They are useful for comparing the prognosis of cancer between different populations or countries because both two measures do not depend on mortality from other causes. Crude probability of death (CPD) and number of life year lost (NLYL) are both calculate in the real situation and disentangle into two parts: Crude probability of death due to cancer (CPDcancer), crude probability of death due to other causes (CPDother), number of life year lost due to cancer (NLYLcancer) and number of life year lost due to other causes (NLYLother). These measures together present the whole picture about the death with probabilities and life lost after diagnose the cancer. We recruit patients diagnosed between 1997 and 2007 and followed up to December 31, 2017 from Taiwan population-based cancer registry. Include total 18 cancers. Estimation are stratified by age, sex, calendar year, development level of city, level of hospital volume and cancer stage. We finally provide eight measurements from both survival analysis and relative survival analysis. Each of them contributing differently to provide more comprehensive and detailed information to patients, clinicians, health policy makers. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T09:07:39Z (GMT). No. of bitstreams: 1 ntu-108-F98842019-1.pdf: 31303742 bytes, checksum: c151a89653b9271d212248ffbdd3947b (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 目錄
中文摘要 i 英文摘要 ii 圖目錄 vii 表目錄 xiii 第一章 前言 1 第二章 重要名詞解釋 4 第一節 全人口癌症登記資料的存活分析 4 第二節 全人口癌症登記資料的相對存活分析 6 第一項 相對存活比率 6 第二項 淨存活率 7 第三項 條件淨存活率 7 第四項 設限平均淨存活時間 7 第五項 癌症病患粗死亡機率 8 第六項 癌症造成的淨生命損失 9 第三章 研究目的與動機 11 第四章 研究方法 12 第一節 資料來源 13 第二節 居住地都市化程度 14 第三節 收治醫療院所規模 15 第四節 癌症別與癌症期別 15 第五節 相對存活分析 17 第一項 個人風險計算 17 第二項 平均淨存活率與10年設限平均淨存活時間 17 第三項 癌症病患粗死亡機率與存活機率 17 第四項 設限平均淨生命損失與設限平均存活時間 18 第五章 研究結果 20 第一節 台灣18大癌症整體分析結果 20 第一項 平均淨存活率以及設限平均淨存活時間 20 第二項 粗死亡機率與存活機率 37 第三項 設限平均存活時間與設限平均生命損失 50 第二節 14種癌症分析結果 64 口腔癌 64 第一項 平均淨存活率以及設限平均淨存活時間 64 第二項 粗死亡機率與存活機率 68 第三項 設限平均存活時間與設限平均生命損失 69 鼻咽癌 73 第一項 平均淨存活率以及設限平均淨存活時間 74 第二項 粗死亡機率與存活機率 77 第三項 設限平均存活時間與設限平均生命損失 79 食道癌 82 第一項 平均淨存活率以及設限平均淨存活時間 82 第二項 粗死亡機率與存活機率 85 第三項 設限平均存活時間與設限平均生命損失 88 胃癌 91 第一項 平均淨存活率以及設限平均淨存活時間 92 第二項 粗死亡機率與存活機率 95 第三項 設限平均存活時間與設限平均生命損失 98 結腸癌 100 第一項 平均淨存活率以及設限平均淨存活時間 101 第二項 粗死亡機率與存活機率 103 第三項 設限平均存活時間與設限平均生命損失 107 直腸癌 110 第一項 平均淨存活率以及設限平均淨存活時間 111 第二項 粗死亡機率與存活機率 114 第三項 設限平均存活時間與設限平均生命損失 117 肝癌 120 第一項 平均淨存活率以及設限平均淨存活時間 121 第二項 粗死亡機率與存活機率 124 第三項 設限平均存活時間與設限平均生命損失 125 胰臟癌 129 第一項 平均淨存活率以及設限平均淨存活時間 130 第二項 粗死亡機率與存活機率 131 第三項 設限平均存活時間與設限平均生命損失 134 肺癌 136 第一項 平均淨存活率以及設限平均淨存活時間 137 第二項 粗死亡機率與存活機率 140 第三項 設限平均存活時間與設限平均生命損失 143 女性乳癌 146 第一項 平均淨存活率以及設限平均淨存活時間 147 第二項 粗死亡機率與存活機率 149 第三項 設限平均存活時間與設限平均生命損失 152 子宮頸癌 155 第一項 平均淨存活率以及設限平均淨存活時間 156 第二項 粗死亡機率與存活機率 158 第三項 設限平均存活時間與設限平均生命損失 160 卵巢癌 163 第一項 平均淨存活率以及設限平均淨存活時間 164 第二項 粗死亡機率與存活機率 166 第三項 設限平均存活時間與設限平均生命損失 168 攝護腺癌 171 第一項 平均淨存活率以及設限平均淨存活時間 172 第二項 粗死亡機率與存活機率 174 第三項 設限平均存活時間與設限平均生命損失 177 膀胱癌 180 第一項 平均淨存活率以及設限平均淨存活時間 181 第二項 粗死亡機率與存活機率 183 第三項 設限平均存活時間與設限平均生命損失 185 第六章 結論與討論 188 參考文獻 191 附錄圖表 194 | |
dc.language.iso | zh-TW | |
dc.title | 台灣癌症相對存活分析與生命損失 | zh_TW |
dc.title | Cancer Relative Survival and Life Lost in Taiwan | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-1 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 林先和,方啟泰,蕭朱杏,廖勇柏 | |
dc.subject.keyword | 存活分析,競爭風險,相對存活分析,存活率,設限平均存活時間,淨存活率,設限平均淨存活時間,癌症粗死亡機率,設限平均生命損失, | zh_TW |
dc.subject.keyword | Survival Analysis,Competing Risk,Relative Survival Analysis,Survival Probability,Restricted Mean Survival Time,Net Survival Probability,Restricted Mean Net Survival Time,Crude Probability of Death due to Cancer,Number of Life Year Lost, | en |
dc.relation.page | 296 | |
dc.identifier.doi | 10.6342/NTU201904337 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-11-28 | |
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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