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  3. Optimal Combinations of Chemotherapy and Radiotherapy in Low-Grade Gliomas: A Mathematical Approach.
 

Optimal Combinations of Chemotherapy and Radiotherapy in Low-Grade Gliomas: A Mathematical Approach.

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BORIS DOI
10.48350/162698
Publisher DOI
10.3390/jpm11101036
PubMed ID
34683177
Description
Low-grade gliomas (LGGs) are brain tumors characterized by their slow growth and infiltrative nature. Treatment options for these tumors are surgery, radiation therapy and chemotherapy. The optimal use of radiation therapy and chemotherapy is still under study. In this paper, we construct a mathematical model of LGG response to combinations of chemotherapy, specifically to the alkylating agent temozolomide and radiation therapy. Patient-specific parameters were obtained from longitudinal imaging data of the response of real LGG patients. Computer simulations showed that concurrent cycles of radiation therapy and temozolomide could provide the best therapeutic efficacy in-silico for the patients included in the study. The patient cohort was extended computationally to a set of 3000 virtual patients. This virtual cohort was subject to an in-silico trial in which matching the doses of radiotherapy to those of temozolomide in the first five days of each cycle improved overall survival over concomitant radio-chemotherapy according to RTOG 0424. Thus, the proposed treatment schedule could be investigated in a clinical setting to improve combination treatments in LGGs with substantial survival benefits.
Date of Publication
2021-10-16
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Keyword(s)
low-grade gliomas mathematical modeling mathematical oncology radiation therapy temozolomide
Language(s)
en
Contributor(s)
Ayala-Hernández, Luis E
Gallegos, Armando
Schucht, Philippe
Universitätsklinik für Neurochirurgie
Murek, Michael Konradorcid-logo
Universitätsklinik für Neurochirurgie
Universitätsklinik für Neurochirurgie
Pérez-Romasanta, Luis
Belmonte-Beitia, Juan
Pérez-García, Víctor M
Additional Credits
Universitätsklinik für Neurochirurgie
Series
Journal of personalized medicine
Publisher
MDPI
ISSN
2075-4426
Access(Rights)
open.access
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