Threshold models of tumor recurrence

The main advantage of threshold models of tumor recurrence is that they closely parallel the real observation process in cancer post-treatment surveillance. Such models are typically based on the assumption that a recurrent tumor becomes detectable when its size attains some threshold value which ma...

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Bibliographic Details
Published inMathematical and computer modelling Vol. 23; no. 6; pp. 153 - 164
Main Author Yakovlev, A.Yu
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.03.1996
Subjects
Censored observations
Detectable size
Stochastic models
Time-to-tumor distributions
Tumor recurrence
Stochastic models
Tumor recurrence
Detectable size
Time-to-tumor distributions
Censored observations
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Summary:The main advantage of threshold models of tumor recurrence is that they closely parallel the real observation process in cancer post-treatment surveillance. Such models are typically based on the assumption that a recurrent tumor becomes detectable when its size attains some threshold value which may be treated as a random variable. This paper discusses various stochastic models that have been proposed for the analysis of data on tumor latency subject to censoring effects. A new model allowing for surviving clonogenic cells is presented.
ISSN:0895-7177
1872-9479
DOI:10.1016/0895-7177(96)00024-6