Are more complicated tumour control probability models better?

Abstract

Mathematical models for the tumour control probability (TCP) are used to estimate the expected success of radiation treatment protocols of cancer. There are several TCP models in the literature, from the simplest (Poissonian TCP) to the well-advanced stochastic birth-death processes. Simple and complex models often make the same predictions. Hence, here, we present a systematic study where we compare six of these TCP models: the Poisson TCP, the Zaider-Minerbo TCP, a Monte Carlo TCP and their corresponding cell cycle (two-compartment) models. Several clinical non-uniform treatment protocols for prostate cancer are employed to evaluate these models. These include fractionated external beam radiotherapies, and high and low dose rate brachytherapies. We find that in realistic treatment scenarios, all one-compartment models and all two-compartment models give basically the same results. A difference occurs between one-compartment and two-compartment models due to reduced radiosensitivity of quiescent cells.We find that care must be taken for the right choice of parameters, such as the radiosensitivities α and β and the hazard function h. Typically, different hazard functions are used for fractionated treatment (fractionated survival fraction) and for brachytherapies (Lea-Catcheside protraction factor). We were able to combine these two approaches into one 'effective' hazard function. Based on our results, we can recommend the use of the Poissonian TCP for everyday treatment planning. More complicated models should only be used when absolutely necessary.

A non-local model for cancer stem cells and the tumour growth paradox

“…We are aware of detailed radiation treatment models involving the linear quadratic model and tumour control probabilities, but a detailed discussion of this framework does not add to the argument we want to make here. For details on radiation treatment modelling, we refer the reader to Gong et al (2011) and Dawson & Hillen (2006). Here, at the treatment time t * , we choose new initial data as…”

ROC Analysis in Radiotherapy: A TCP Model-Based Test

“…We obtain sampled data from Monte Carlo simulations of the two-compartment Dawson-Hillen (DH) model [1,6]. We add a gaussian noise into the radiation dose in order to simulate the uncertainty on its deposition.…”

“…Gong et al [6] compared different TCP models regarding to clinical treatment protocols for prostate cancer. In this study, the Monte Carlo method was used as a valid approach to determine the tumour survival for one and twocompartment models.…”

“…Some of these models have properties derived from multi-cellular biological systems approach and are analyzed either by continuum or cell-based models [5]. It has been shown recently that for the case of prostate cancer-and low proliferating tumours in general-diferent TCP models for radiotherapy lead practically to the same predictions regarding the TCP evolution in time [6], suggesting the use of simpler and more computationally feasible models in the clinic. However these simpler models tend to neglect the peculiar biological differences between tumours.…”

Sobre mecanismos mesoscópicos do crescimento de tumores

“…Comparando rDMC com a solução exata, estimamos desvios de 0,5% nas primeiras 150 horas, contra 15% com sDMC; e aproximadamente 3% para 7900 horas (rDMC) contra 5% (sDMC). [88], i.e., para cada simulação, e para cada passo de tempo, define-se um indicador do sucesso do tratamento, S l (t), como uma função delta de Kronecker S l (t) = δ…”