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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 流行病學與預防醫學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90330
完整後設資料紀錄
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dc.contributor.advisor盧子彬zh_TW
dc.contributor.advisorTzu-Pin Luen
dc.contributor.author康詒婷zh_TW
dc.contributor.authorYi-Tyng Kangen
dc.date.accessioned2023-09-26T16:17:51Z-
dc.date.available2023-11-10-
dc.date.copyright2023-09-26-
dc.date.issued2023-
dc.date.submitted2023-07-25-
dc.identifier.citation1. World Health Organization, International Agency for Research on Cancer, https://gco.iarc.fr/today/fact-sheets-cancers
2. Moustafa M, Thomas J, et al,Epidemiological Trends of Head and Neck Cancer in the United States: A SEER Population Study,2017,75(12): 2562–2572
3. National Cancer Institute at national Institutes of Health, https://www.cancer.gov/types/head-and-neck
4. Liao C.T., Wallace C.G., et al, Clinical evidence of field cancerization in patients with oral cavity cancer in a betel quid chewing area, Oral Oncol, 2014,50(8), 721-731
5. Rebecca L. Siegel , Kimberly D. Miller , Cancer statistics, 2020,ACS journals,2020,70(1): p.7-30
6. Registry, T.T.C., Cancer Registry Annual Report, 2020 Taiwan. 2022.
7. Registry, T.T.C., Cancer Registry Annual Report, 2018 Taiwan. 2022.
8. Registry, T.T.C., Year cause of death statistical result, 2020 Taiwan. 2022.
9. Registry, T.T.C., Year cause of death statistical result, 2018 Taiwan. 2022.
10. 簡禎佑, 江豐裕, “頭頸癌之治療”, 高醫醫訊月刊,2009,第28卷第12期.
11. Aupérin A.:Epidemiology of head and neck cancers: an update, Curr Opin Oncol.2020,32(3):178-86
12. Wang Y., Wang S, , et al,Clinicopathological characteristics, treatment and prognosis of oral adenocarcinoma: a population-based study,2023,280(7):3365-3374
13. Nayeon Choi, Hack Jung, et al, Outcomes of Salvage Therapy for Oropharyngeal Cancer Recurrence Following Upfront Radiation Therapy and Prognostic Factors,2023
14. Zhong Liang, Meijuan Wu, et al, Updated racial disparities in incidence, clinicopathological features and prognosis of hypopharyngeal squamous carcinoma in the United States, 2023,18(3)
15. H Zhang , J Lu, et al,Construction and evaluation of an artificial intelligence-based risk prediction model for death in patients with nasopharyngeal cancer,2023, 43(2):271-279
16. Zhuo Song, Zewen Chen, et al, Competing risk models versus traditional Cox models for prognostic factors' prediction and care recommendation in patients with advanced laryngeal squamous carcinoma: a population-based study,2023
17. Marie W.N., Christian G., Epidemiology, outcomes, and prognostic factors in submandibular gland carcinomas: a national DAHANCA study,2023,280(7):3405-3413
18. Di Zhang, Lixi Li, Prognostic models for estimating survival of salivary duct carcinoma: a population-based study,2023,280:1939-1954
19. KAAS Warnakulasuriya, NW Johnson ,Epidemiology and risk factors for oral cancer: rising trends in Europe and possible effects of migration,Int Dent J, 1996, 46 (1): 245-250
20. C. Scully, R. Bedi,et al,Ethnicity and oral cancer, LancetOncol, ,2000,1(1):37-42
21. Liu Y., Lydia Zhong, et al, Neighborhood Socioeconomic Status and Racial and Ethnic Survival Disparities in Oral Cavity and Laryngeal Cancer,2023,32(5):642-652
22. Alice W Lee, Angela Sou, et al, Early onset of nasopharyngeal cancer in Asian/Pacific Islander Americans revealed by age-specific analysis,2023,80:25-29
23. Yao-Te Tsai, Chia-Hsuan Lai, et al,A Nomogram Incorporating Neutrophil-to-Lymphocyte Ratio and Squamous Cell Carcinoma Antigen Predicts the Prognosis of Oral Cancers,2023, 15(9):2492
24. Yueh-Feng Lu, Chia-Yun Wu, et al ,Postchemoradiotherapy systemic inflammation response index predicts treatment response and overall survival for patients with locally advanced nasopharyngeal cancer,2023
25. Ashley Diaz, Daniel Bujnowski, et al, Health Insurance Coverage and Survival Outcomes among Nasopharyngeal Carcinoma Patients: A SEER Retrospective Analysis,2022, 84(3):240-247.
26. Emily Z Yan, Benjamin M Wahle, et al,Race and socioeconomic status interact with HPV to influence survival disparities in oropharyngeal squamous cell carcinoma,2023, 12(8):9976-9987.
27. Mi Du, Dandara G., et al, Comparison of the Tree-Based Machine Learning Algorithms to Cox Regression in Predicting the Survival of Oral and Pharyngeal Cancers: Analyses Based on SEER Database,2020,12(10): 2802
28. Xia-Yan Luo, Ya-Min Zhang, et al, Development and validation of novel nomograms to predict survival of patients with tongue squamous cell carcinoma,2022,10(32): 11726-11742.
29. Cox, D.R., Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B (Methodological), 1972. 34(2): p. 187-202
30. Harrell, F.E., Jr., K.L. Lee, and D.B. Mark, Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med, 1996. 15(4): p. 361-87
31. Rades D., Inga Z., et al, Evaluation of the Impact of Smoking and Alcohol Consumption on Toxicity and Outcomes of Chemoradiation for Head and Neck Cancer,2023,43(2):823-830
32. A.D., Teemu H., et al, Exposure to alcohol and overall survival in head and neck cancer: A regional cohort study,2022,44(10):2109-2117
33. Priyanka Joshi, Sanjeev Waghmare, Molecular signaling in cancer stem cells of tongue squamous cell carcinoma: Therapeutic implications and challenges,2023,15(5):438-452
34. Huai-Pao Lee, Ching-Chih Lee, Prognostic stratification of oropharyngeal cancer patients in a betel nut chewing and low HPV area,2023, 52(1):27
35. Peter Kim Moon, Yifei Ma,Head and Neck Cancer Stage at Presentation and Survival Outcomes Among Native Hawaiian and Other Pacific Islander Patients Compared With Asian and White Patients,2022,148(7):636-645
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90330-
dc.description.abstract背景 :
頭頸癌是全球常見癌症排名第七大的癌症,發生率為14.24//100,000人,死亡率為6.87/100,000人。在台灣,頭頸癌的發生率為57.68/100,000人,死亡率則為22.34/100,000人,其中頭頸癌患者中更大多為口腔癌,發生率並為十大癌症的第五名且死亡率為十大癌症的第六名。因此,不論在世界又或是在台灣,頭頸癌都是排名前十的癌症,且台灣頭頸癌的發生率和死亡率數值又明顯較其他國家高。
在頭頸癌存活的研究中,頭頸癌的五年整體存活大約介於50%~65%之間,隨著癌症部位及種族的不同,頭頸癌的發病率、死亡率及存活時間都存在差異。因此本研究的目的是希望藉由台灣癌症登記中心的資料,建立屬於台灣人的預測模型,來預測頭頸癌患者的整體存活及腫瘤特定存活,並且使用美國癌症登記資料庫(The Surveillance, Epidemiology, and End Results ,SEER)中亞洲人的資料進行外部驗證,再進一步觀察亞洲和非亞洲患者的臨床結果是否存在差異。

方法 :
本研究主要蒐集由2013至2018年間在台灣癌症登記中心(The Taiwan Cancer Registry,TCR)被診斷為頭頸癌的患者資料,並分別針對有做手術的頭頸癌患者、有做手術的口腔癌患者和沒有做手術的頭頸癌患者建構三種Cox迴歸模型,最後會使用C-index及五年的每年存活預測,來判斷模型的預測能力和精確性。
在外部驗證方面,本研究使用2010至2015年的SEER資料,並針對兩種資料庫共有的變數進行建模,模型分別對非西班牙裔白人、非西班牙裔黑人及亞洲人進行C-index及五年的每年存活預測分析,來觀察亞洲與非亞洲之間的關係及模型的外推性。

結果 :
本研究總共建構了六個模型,其中針對有做手術頭頸癌患者的整體存活模型的解釋,為在控制了其他變數的情況下,年齡每增加一歲的死亡風險會是原來的1.02倍,女性發生死亡的風險是男性的0.74倍,腫瘤大小每增加一毫米的死亡風險會是原來的1.01倍,診斷年每增加一年的死亡風險會是原來的0.97倍,BMI每增加一單位的死亡風險會是原來的0.95倍,與口腔相比,口咽有較高的風險,其餘下咽、主唾腺、喉則都有較低的死亡風險(口咽, HR=1.24,P<0.001;下咽,HR=0.9,P=0.02;主唾腺,HR=0.72 ,P<0.001;喉,HR=0.92,P=0.16)等。
在模型的預測結果中,整體存活模型的C-index為0.7~0.74,腫瘤特定存活模型的C-index為0.76~0.78,兩者的C-index都大於0.7,代表模型有不錯的預測能力。五年的每年存活預測上,整體存活模型都沒有達到統計上的顯著差異,腫瘤特定存活模型則大多於前兩年沒有達到統計上顯著,且實際結果與預測結果的差異比例大多小於5%。在外部驗證方面,亞洲人之C-index明顯較其他種族高,但於五年的每年存活預測上,不論是非西班牙裔白人、非西班牙裔黑人及亞洲人均達到統計上的顯著差異。

結論 :
不論在整體存活模型又或者在腫瘤特定存活模型,本研究所建構的三種預測模型都有良好的預測能力,在台灣頭頸癌患者的存活預測上也有不錯的預測效果。在外部驗證方面,可以發現亞洲人相較於非亞洲人有較好的預測效果,但在每年的存活預測上,不論是亞洲又或者是非亞洲人,大多結果為實際的死亡人數與使用模型所預測的死亡人數有顯著差異,因此無法進行外推。最後,希望藉由本研究讓頭頸癌患者能夠進行自我評估,同時也提供患者與醫生對於是否接受治療在決策上得到更多資訊。
zh_TW
dc.description.abstractBackground:
Head and neck cancer is the seventh most common cancer in the world, with an incidence rate of 14.24/100,000 people and a mortality rate of 6.87/100,000 people. In Taiwan, the incidence rate of head and neck cancers is 57.68/100,000, and its mortality rate is 22.34/100,000. Among them, oral cancer ranks fifth in terms of incidence rate among the top ten cancers, and ranks sixth in terms of mortality rate among the top ten cancers. Whether worldwide or in Taiwan, head and neck cancer ranks among the top ten cancers, and the incidence and mortality rates of head and neck cancer in Taiwan are significantly higher than in other countries. The five-year overall survival rate ranges from 50% to 65%, however, the incidence, mortality, and survival time of head and neck cancer vary depending on cancer sites and race. Therefore, the purpose of this study is to develop prediction models specific to Taiwanese patients, using data from the Taiwan Cancer Registry, towards predicting overall survival and head and neck cancer-specific survival. The study will also include external validation using the American Cancer Registry Database (The Surveillance, Epidemiology, and End Results, SEER) to examine potential differences in clinical outcomes between Asian and non-Asian patients.
Method:
Patients diagnosed with head and neck cancer at the Taiwan Cancer Registry (TCR) between 2013 and 2018 were included in this study. Three Cox regression models were constructed for the following groups: head and neck cancer patients who underwent surgery, oral cancer patients who underwent surgery, and head and neck cancer patients who did not undergo surgery. The predictive ability and accuracy of the model were assessed using discrimination analysis via c-index and five-year annual survival prediction (calibration analysis). For external validation, head and neck cancer patients from the SEER data recruited between 2010 and 2015 were utilized for fitting models with variables that were common to both databases, as predictors. The models were evaluated using discrimination and calibration analyses to examine the relationship between Asian and non-Asian populations and assess the models’ generalizability.
Results:
A total of six models were constructed in this study. Among them, the overall survival model for patients with head and neck cancer who underwent surgery showed the following results: while controlling for covariates, the risk of death increased by 1.02 times for every one-year increase in age. The risk of death for females was 0.74 times to that of males. Additionally, the risk of death increased by 1.01 times for each millimeter increase in tumor size, while the risk of death decreased by 0.97 times for each year of diagnosis and increased with each unit increase in BMI. When compared to the oral cavity, the oropharynx had a higher risk of death, while the hypopharynx, main salivary gland, and larynx had lower mortality risks (oropharynx, HR=1.24, P<0.001; hypopharynx, HR=0.9, P=0.02; main salivary gland, HR=0.72, P<0.001; larynx, HR=0.92, P=0.16) and so on.The C-index of the overall survival model ranged from 0.7 to 0.74, and the cancer-specific survival model ranged from 0.76 to 0.78. Both c-index values exceeded 0.7, indicating that the models exhibited good predictive ability. The overall survival model did not show a statistically significant difference between observed and predicted survival via the calibration analysis. Most of the cancer-specific survival models also did not exhibit a statistically significant difference for the first two years, while the difference between the actual and predicted survival were < 5% for the latter years. In external validation, Asians exhibited a significantly higher c-index compared to other racial groups. However, in calibration analyses, statistically significant differences were observed between observed and predicted survival among non-Hispanic whites, non-Hispanic blacks, and Asians.
Conclusions:
Regardless whether it was the overall survival model or the cancer-specific survival model, the three prediction models developed in this study exhibit good predictive capabilities. The models demonstrate their effectiveness in predicting the survival of head and neck cancer patients in Taiwan. in the SEER data it was further observed that the Asians show better prediction performance compared to non-Asians. However, in in calibration analyses, both Asians and non-Asians experience significant difference between observed and predicted numbers of deaths, which makes extrapolation unreliable. Lastly, it is hoped that this study will enable patients with head and neck cancer to engage in self-assessment, thereby providing both patients and doctors with valuable information to make informed therapeutic decisions.
en
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dc.description.tableofcontents中文摘要 II
Abstract IV
目錄 VIII
第一章 導論 1
1.1. 研究背景 1
1.1.1. 頭頸癌介紹與其流行病學 1
1.1.2. 頭頸癌之治療手段及風險因子 2
1.1.3. 頭頸癌預後及影響因子 2
1.2. 研究動機 3
1.3. 研究目的 4
第二章 研究方法 4
2.1. 資料庫介紹 4
2.1.1 台灣癌症登記中心 4
2.1.2 Surveillance, Epidemiology, and End Results Program (SEER) 5
2.2. 資料篩選 5
2.3. 變數定義 6
2.4. 頭頸癌定義 7
2.5. Cox 比例風險模型(Cox proportional hazard model) 7
2.6. Harrell’s c-index (concordance index) 8
2.7. 模型建構流程 8
第三章 研究結果 10
3.1. 樣本資料篩選 10
3.2. 描述性統計分析 10
3.3. 影響台灣人頭頸癌存活預測的變項及模型預測表現 11
3.3.1. 整體存活模型 11
3.3.1.1 模型一 : 有做手術的頭頸癌患者 11
3.3.1.2 模型二 : 有做手術的口腔癌患者 12
3.3.1.3 模型三 : 沒有做手術的頭頸癌患者 13
3.3.2. 腫瘤特定存活模型 14
3.3.2.1. 模型一 : 有做手術的頭頸癌患者 14
3.3.2.2 模型二 : 有做作手術的口腔癌患者 15
3.3.2.3 模型三 : 沒有做手術的頭頸癌患者 16
3.4. 模型預測表現 17
3.5. 外部驗證結果 18
第四章 討論與結論 19
4.1 主要發現 19
4.2 研究限制 21
4.3 於公共衛生與臨床上的貢獻 21
第五章 圖說 22
參考資料 23
附錄 26
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dc.language.isozh_TW-
dc.title基於台灣癌登資料建構頭頸癌存活預測模型zh_TW
dc.titleDevelopment of a prediction model for head and neck cancer using the National Cancer Registry Data from Taiwanen
dc.typeThesis-
dc.date.schoolyear111-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee游宗憲;江濬如;王彥雯zh_TW
dc.contributor.oralexamcommitteeTsung-Hsien Yu;Chun-Ju Chiang;CHARLOTTE WANGen
dc.subject.keyword頭頸癌,台灣癌症登記系統,SEER,存活預測,種族差異,zh_TW
dc.subject.keywordhead and neck cancer,the Taiwan Cancer Registry (TCR),The Surveillance, Epidemiology, and End Results (SEER),Survival Prediction,racial differences,en
dc.relation.page62-
dc.identifier.doi10.6342/NTU202301904-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2023-07-25-
dc.contributor.author-college公共衛生學院-
dc.contributor.author-dept流行病學與預防醫學研究所-
dc.date.embargo-lift2028-07-21-
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