Increasing the Time Interval between PCV Chemotherapy Cycles as a Strategy to Improve Duration of Response in Low-Grade Gliomas: Results from a Model-Based Clinical Trial Simulation

Abstract

Background. We previously developed a mathematical model capturing tumor size dynamics of adult low-grade gliomas (LGGs) before and after treatment either with PCV (Procarbazine, CCNU, and Vincristine) chemotherapy alone or with radiotherapy (RT) alone. Objective. The aim of the present study was to present how the model could be used as a simulation tool to suggest more effective therapeutic strategies in LGGs. Simulations were performed to identify schedule modifications that might improve PCV chemotherapy efficacy. Methods. Virtual populations of LGG patients were generated on the basis of previously evaluated parameter distributions. Monte Carlo simulations were performed to compare treatment efficacy across in silico clinical trials. Results. Simulations predicted that RT plus PCV would be more effective in terms of duration of response than RT alone. Additional simulations suggested that, in patients treated with PCV chemotherapy, increasing the interval between treatment cycles up to 6 months from the standard 6 weeks can increase treatment efficacy. The predicted median duration of response was 4.3 years in LGGs treated with PCV cycles given every 6 months versus 3.1 years in patients treated with the classical regimen. Conclusion. The present study suggests that, in LGGs, mathematical modeling could facilitate clinical research by helping to identify, in silico, potentially more effective therapeutic strategies.

A mathematical model describes the malignant transformation of low grade gliomas: Prognostic implications

“…One can base the treatment decisions on the estimates of the tumour aggressiveness and potential time to malignant transformation which can be derived from imaging [ 29 ], taking into account also the levels of cytotoxicity induced. This is also in line with recent results that one may get a substantial therapeutical benefit by the use of protracted therapies instead of waiting for the malignant transformation to occur [ 30 , 31 ].…”

Computational design of improved standardized chemotherapy protocols for grade II oligodendrogliomas

“…[27]. Mazocco et al [31] found a similar result using in-silico simulations of the Ribba’s et al model [29].…”

“…Some previous models have explored different therapeutic regimens for low-grade gliomas [27, 28, 31, 34]. First, in Ref.…”

“…More sophisticate and realistic models such as E max models could have been used. We chose instead the simple linear relationship in line with other previous modeling works [29, 31] because of two reasons. The first one was that more complex and realistic models would imply fixing an additional parameter and making the model more sensitive to overfitting, an effect that we wanted to avoid.…”

Optimization of Cancer Treatment in the Frequency Domain

“…More specifically, a PKPD coupled tumor uptake model for immunocytokine-based cancer immunotherapy predicted that dose-dense administration schedules improve intratumoral drug uptake [59]. For brain tumors, however, it was found that lapatinib should be administered on a continuous daily schedule [60] while the time intervals between PCV (Procarbazine, CCNU, and Vincristine) chemotherapy cycles should be increased [61].…”