Probability modeling and statistical inference in cancer screening
"Cancer screening has been carried out for six decades, however, there are many unsolved problems: how to estimate key parameters involved in screenings, such as sensitivity, time duration in the preclinical state (i.e., sojourn time), and time duration in the disease-free state, how to estimat...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Boca Raton, London, New York
CRC Press
2024
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| Ausgabe: | First edition |
| Schriftenreihe: | Chapman & Hall/CRC biostatistics series
A Chapman & Hall Book |
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Tag hinzufügen | Zusammenfassung: | "Cancer screening has been carried out for six decades, however, there are many unsolved problems: how to estimate key parameters involved in screenings, such as sensitivity, time duration in the preclinical state (i.e., sojourn time), and time duration in the disease-free state, how to estimate the distribution of lead time, the diagnosis time advanced by screening; how to evaluate the long-term outcomes of screening, including the probability of overdiagnosis among the screen-detected, when to schedule the first exam based on one's current age and risk tolerance; and when to schedule the upcoming exam based on one's screening history, age, and risk tolerance. These problems need proper probability models and statistical methods to deal with. Highlights: Gives a concise account of the analysis of cancer screening data using probability models and statistical methods. Real data sets are provided, so that cancer researchers and statisticians can apply the methods in the learning process. Develops statistical methods in the commonly used disease progressive model Provides solutions to practical problems and introduces open problems. Provides a framework for the most recent development based on the author's research. The book is primarily aimed at researchers and practitioners from biostatistics and cancer research. Readers should have prerequisite knowledge of calculus, probability, and statistical inference. The book could be used as a one-semester textbook on the topic of cancer screening methodology for a graduate-level course"-- Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- List of Figures -- List of Tables -- Symbols -- 1. A Brief Review of Probability and Examples of Screening Data -- 1.1. Sample space, event, and probability -- 1.2. Random variable and distribution function -- 1.3. Expectation, moments, and correlation -- 1.4. Frequentist statistics and Bayes inference -- 1.5. Markov Chain Monte Carlo algorithms -- 1.6. Screening data format -- 1.7. The Minnesota Colorectal Cancer Study -- 1.8. The Mayo Lung Project -- 1.9. The Health Insurance Plan (HIP) of Greater New York -- 1.10. The National Lung Screening Trial (NLST) study -- 2. Estimating the Three Key Parameters -- 2.1. Introduction -- 2.2. The three key parameters and other terminology -- 2.3. Probability calculation -- 2.3.1. Probability of incidence and lifetime risk -- 2.3.2. Probability of screen-detected cases -- 2.3.3. Probability of interval incidence cases -- 2.4. Sensitivity as a function of age -- 2.4.1. Probability formulation and the likelihood -- 2.4.2. Simulation: Checking model reliability -- 2.4.3. Application: The HIP for breast cancer -- 2.4.4. Application: The Minnesota Colorectal Cancer study -- 2.4.5. Application: The Mayo Lung Project -- 2.4.6. Application: The National Lung Screening Trial -- 2.5. Sensitivity as a function of time in the Sp and sojourn time -- 2.5.1. Probability formulation and likelihood -- 2.5.2. Application: The NLST-CT for heavy smokers -- 2.6. An open problem -- 2.7. Bibliographic notes -- 2.8. Solution for some exercises -- 3. Testing Dependency of Two Screening Modalities -- 3.1. Introduction -- 3.2. Data format for two screening modalities -- 3.3. Testing dependency under the stable disease model -- 3.3.1. The likelihood function. |
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| Beschreibung: | Literaturverzeichnis: Seite 251-258 |
| Beschreibung: | xxiii, 261 Seiten Diagramme |
| ISBN: | 9781032513300 978-1-032-51330-0 9781032518312 978-1-032-51831-2 |