Abstract
To develop a tumor growth inhibition model for adult diffuse low-grade gliomas (LGG) able to describe tumor size evolution in patients treated with chemotherapy or radiotherapy. Using longitudinal mean tumor diameter (MTD) data from 21 patients treated with first-line procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-l-nitrosourea, and vincristine (PCV) chemotherapy, we formulated a model consisting of a system of differential equations, incorporating tumor-specific and treatment-related parameters that reflect the response of proliferative and quiescent tumor tissue to treatment. The model was then applied to the analysis of longitudinal tumor size data in 24 patients treated with first-line temozolomide (TMZ) chemotherapy and in 25 patients treated with first-line radiotherapy. The model successfully described the MTD dynamics of LGG before, during, and after PCV chemotherapy. Using the same model structure, we were also able to successfully describe the MTD dynamics in LGG patients treated with TMZ chemotherapy or radiotherapy. Tumor-specific parameters were found to be consistent across the three treatment modalities. The model is robust to sensitivity analysis, and preliminary results suggest that it can predict treatment response on the basis of pretreatment tumor size data. Using MTD data, we propose a tumor growth inhibition model able to describe LGG tumor size evolution in patients treated with chemotherapy or radiotherapy. In the future, this model might be used to predict treatment efficacy in LGG patients and could constitute a rational tool to conceive more effective chemotherapy schedules.
Highlights
We propose a model of tumor growth inhibition that successfully describes the time course of tumor size [measured as mean tumor diameter (MTD)] in patients with low-grade glioma (LGG)
We successfully use the model to analyze tumor size dynamics in patients treated with PCV chemotherapy and in patients treated with TMZ chemotherapy or radiotherapy, and we show that the nontreatmentrelated parameters of the model are consistent across the 3 therapeutic modalities
These treatment methods represent the main low-grade gliomas (LGG) treatment modalities used in various institutions
Summary
The use of existing clinical data to model tumors’ dynamic response to antitumor treatments is a promising approach toward improving treatment efficacy and accel-. Such strategies have been applied, for example, to predict and monitor chemotherapy-induced myelosuppresion [1]. Tumor growth inhibition (TGI) models have successfully been developed to assess tumor size dynamics following cytotoxic treatment in non–small cell lung cancer A TGI model was able to use data on tumor dynamics from a phase II study to predict overall survival in a subsequent phase III trial [4]. We rely on clinical data to develop a TGI model for adult diffuse low-grade gliomas (LGG). LGG treatment approaches include surgery, radiotherapy, and chemotherapy with procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-lnitrosourea (CCNU), and vincristine (PCV) or temozolomide (TMZ; ref. 6)
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