Computational design of improved standardized chemotherapy protocols for grade II oligodendrogliomas

Víctor M Pérez-García, Luis E Ayala-Hernández, Juan Belmonte-Beitia, Philippe Schucht, Michael Murek, Andreas Raabe and Juan Sepúlveda

PLOS Computational Biology, 2019, vol. 15, issue 7, 1-17

Abstract: Here we put forward a mathematical model describing the response of low-grade (WHO grade II) oligodendrogliomas (LGO) to temozolomide (TMZ). The model describes the longitudinal volumetric dynamics of tumor response to TMZ of a cohort of 11 LGO patients treated with TMZ. After finding patient-specific parameters, different therapeutic strategies were tried computationally on the ‘in-silico twins’ of those patients. Chemotherapy schedules with larger-than-standard rest periods between consecutive cycles had either the same or better long-term efficacy than the standard 28-day cycles. The results were confirmed in a large trial of 2000 virtual patients. These long-cycle schemes would also have reduced toxicity and defer the appearance of resistances. On the basis of those results, a combination scheme consisting of five induction TMZ cycles given monthly plus 12 maintenance cycles given every three months was found to provide substantial survival benefits for the in-silico twins of the 11 LGO patients (median 5.69 years, range: 0.67 to 68.45 years) and in a large virtual trial including 2000 patients. We used 220 sets of experiments in-silico to show that a clinical trial incorporating 100 patients per arm (standard intensive treatment versus 5 + 12 scheme) could demonstrate the superiority of the novel scheme after a follow-up period of 10 years. Thus, the proposed treatment plan could be the basis for a standardized TMZ treatment for LGO patients with survival benefits.Author summary: We developed a mathematical model describing the longitudinal volumetric growth data of grade II oligodendroglioma patients and their response to temozolomide. The model was used to explore alternative therapeutic protocols for the in-silico twins of the patients and in virtual clinical trials. The simulations show that enlarging the time interval between chemotherapy cycles would maintain the therapeutic efficacy, while limiting toxicity and deferring the development of resistance. This may allow for improved drug-exposure by administering a larger number of cycles for longer treatment periods. A scheme based on this idea consisting of an induction phase (5 consecutive cycles, 1 per month) and a maintenance phase (12 cycles given in three-months intervals) led to substantial survival benefits in-silico. The computational results suggest that a clinical trial enrolling 100 patients per arm (standard intensive therapy versus 5+12 novel scheme) could prove the effectiveness of the proposed approach after a follow-up period of 10 years.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1006778

DOI: 10.1371/journal.pcbi.1006778

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