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C. H. Morrell, L. J. Brant, S. Sheng and E. J. Metter, “Screening for Prostate Cancer Using Multivariate Mixed Effects Models,” Journal of Applied Statistics, Vol. 39, No. 6, 2012, pp. 1151-1175. doi:10.1080/02664763.2011.644523

has been cited by the following article:

• TITLE: ROC Analysis in Radiotherapy: A TCP Model-Based Test

  AUTHORS: Mairon M. Santos, Ubiraci P. C. Neves

  KEYWORDS: Prostate Cancer; Radiotherapy; Tumour Control Probability; Hypothesis Test; ROC Curve; Dawson-Hillen Model; Monte Carlo Simulation

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.3 No.2, June 20, 2013

  ABSTRACT: Several mathematical models have been proposed to describe the dynamics of irradiated cancer cells and to evaluate the tumour control probability (TCP). In this article, we propose a TCP model-based statistical test for predicting the outcome of a radiation treatment. We determine the foresight capability of prostate tumour erradication (cure) from Monte Carlo simulations of the Dawson-Hillen TCP model. We construct the receiver operating characteristic (ROC) curves of the test from the probability distributions of the fraction of remaining tumour cells for simulated experiments that evolve either to cure or non-cure. Simulations show that a similar procedure may be applicable to clinical data. Results suggest that the evaluation of tumour sizes after the treatment has started may be used for short-term prognosis.