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PRECiSE: PancREatic Cancer Prioritization and Screening Evaluation Tool
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | PRECiSE: PancREatic Cancer Prioritization and Screening Evaluation Tool. |
| 개인저자 | Abu-El-Haija, Lena A,. |
| 단체저자명 | North Carolina State University. |
| 발행사항 | [S.l.]: North Carolina State University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 129 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-03B. Dissertation Abstract International |
| ISBN | 9781085646093 |
| 학위논문주기 | Thesis (Ph.D.)--North Carolina State University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-03, Section: B.
Advisor: Hicklin, Karen |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | Pancreatic cancer (PC) is the fourth leading cause of death due to cancer in the US, and it is projected to be the second leading cause by 2030. While the incidence of PC is relatively low, it has been increasing in recent years. The mortality risk of PC is high with an 8% five-year survival rate. PC can be asymptomatic, which often leads to late diagnosis after the tumor has metastasized to other organs. The late diagnosis was initially perceived to be due to the tumor's rapid progression. However, recent findings have shown that there is an average of seven years from the start of the tumor until metastasis. This presents an opportunity for screening to detect PC patients earlier. Chapter 2 presents a discrete event simulation model of pancreatic cancer progression, where the discrete events are (i) tumor volume at symptomatic detection, (ii) tumor volume at transition from the local stage to the regional stage, and (iii) tumor volume at transition from the regional stage to the distant stage. The model is personalized to race, gender, and age. Surveillance, Epidemiology and End Results data were used to parameterize the model. Pancreatic cancer is resectable if the tumor can be surgically removed. Resection is the best option for improving survival rates. In Chapter 2, a resectability prediction tool is introduced. With resection being the only true cure for PC, there is a call for screening policies to catch the disease at an early stage. However, current screening policies remain nonspecific with undetermined screening start age, screening interval, and screening end age. The general population has a lifetime risk of 1.3%. However, some are at a much higher risk than others. There are calls for PC screening of high-risk patients only rather than a population wide screening. The International Cancer of the Pancreas Screening Consortium defines high-risk as genetic mutation or first-degree family members with PC. In Chapter 3, we present an extension to the progression model from Chapter 2, where the risk of a patient contributes to the incidence rate of PC. We overlay the progression model with different screening policies, where the screening start age is set at 50 years old, the screening end age is set at 100, and the screening interval was set at half a year, a year, two years, three years, four years, five years, and ten years. We created different homogeneous populations to study the effect of the screening policies and the effort associated with catching one pancreatic cancer by screening by race, gender, and patient PC risk. In Chapter 4, we expand the resectability prediction tool and integrate it with the screening model. We test screening policies with varying screening start age, screening end age, screening interval, and screening modality. We test the different policies on homogeneous and heterogeneous populations. We estimate the effort to screen and the average five-year survival of each policy. We create an effort to five-year survival frontier and identify the efficient policies. |
| 일반주제명 | Biomedical engineering. Oncology. Medical imaging. Systems science. |
| 언어 | 영어 |
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