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- W1978072770 abstract "The evaluation of cancer treatment efficiency is often based on the risk of local recurrence. When applied to the statistical analysis of tumor recurrence data, a pertinent parametric method has the following distinct advantages: (1) it allows a natural interpretation in terms of parameters bearing clear biological meaning, (2) it provides a prediction of the recurrence risk forward in time beyond the follow-up period, (3) it offers a means of estimating survival fraction (probability of tumor cure) from the time-to-recurrence observations. This paper discusses a stochastic model of tumor recurrence based on the consideration of biological processes of tumor latency within the random minima framework. A parametric family of distributions is obtained that allows for a survival fraction, thereby providing an estimate of the probability of tumor cure. When applying the model to data on breast cancer, we estimate the expected number of clonogens which give rise to early and late recurrences and their progression rate parameters. The prime object of our concern is discrimination between true recurrence and spontaneuos carcinogenesis on the basis of the temporal characteristics of the tumor latency. As evidenced by the data analysis, such a discrimination is feasible and allows to conclude that the contralateral breast cancer may be interpreted as a preexisting subclinical tumor at the time of treatment." @default.
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- W1978072770 date "1996-09-01" @default.
- W1978072770 modified "2023-10-01" @default.
- W1978072770 title "A PARAMETRIC ANALYSIS OF TUMOR RECURRENCE DATA" @default.
- W1978072770 doi "https://doi.org/10.1142/s0218339096000260" @default.
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