title: Modeling cancer detection: tumor size as a source of information on unobservable stages of carcinogenesis.
abstract: This paper is concerned with modern approaches to mechanistic modeling of the process of cancer detection. Measurements of tumor size at diagnosis represent a valuable source of information to enrich statistical inference on the processes underlying tumor latency. One possible way of utilizing this information is to model cancer detection as a quantal response variable. In doing so, one relates the chance of detecting a tumor to its current size. We present various theoretical results emerging from this approach and illustrate their usefulness with numerical examples and analyses of epidemiological data. An alternative approach based on a threshold type mechanism of tumor detection is briefly described.
authors.affiliation: Department of Statistics, 141 Cockins Hall, The Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA.
authors.forename: R
authors.initials: R
authors.lastname: Bartoszyński
authors.forename: L
authors.initials: L
authors.lastname: Edler
authors.forename: L
authors.initials: L
authors.lastname: Hanin
authors.forename: A
authors.initials: A
authors.lastname: Kopp-Schneider
authors.forename: L
authors.initials: L
authors.lastname: Pavlova
authors.forename: A
authors.initials: A
authors.lastname: Tsodikov
authors.forename: A
authors.initials: A
authors.lastname: Zorin
authors.forename: A Y
authors.initials: AY
authors.lastname: Yakovlev
mesh_terms: D003198:Computer Simulation; D006801:Humans; D008175:Lung Neoplasms / Q000473:pathology*; D008954:Models, Biological; D009367:Neoplasm Staging; D013269:Stochastic Processes