Benjamin Ribba (1), Gentian Kaloshi (2), Mathieu Peyre (3), Damien Ricard (4), Vincent Calvez (1), Michel Tod (5,6), Branka Cajavec-Bernard (1), Ahmed Idbaih (2), Dimitri Psimaras (2), Linda Dainese (7), Johan Pallud (8), Stéphanie Cartalat-Carel (3), Jean-Yves Delattre (2), Jérôme Honnorat (3,6,9), Emmanuel Grenier (1), François Ducray (3,6,9)
(1) INRIA, Project-team NUMED, Ecole Normale Supérieure de Lyon, 46 allée d’Italie, 69007 Lyon Cedex 07, France. (2) AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Service de Neurologie Mazarin ; INSERM, U975, Centre de Recherche de l’Institut du Cerveau et de la Moelle ; Université Pierre & Marie Curie Paris VI, Faculté de médecine Pitié-Salpêtrière, CNRS UMR 7225 and UMR- S975, Paris, France. (3) Hospices Civils de Lyon, Hôpital Neurologique, Neuro-oncologie, Lyon, 69003 France. (4) Hôpital d’Instruction des Armées du Val-de-Grâce, Paris, 75005 France. (5) EA3738 CTO, Faculté de Médecine Lyon-Sud, Oullins, F-69600, France ; Pharmacie, Hôpital de la Croix Rousse, Hospices civils de Lyon, 69004 Lyon, France. (6) Université de Lyon, Claude Bernard Lyon 1, Lyon, F-69003, France. (7) Service de Neuropathologie, Hôpital de la Salpêtrière, 47 boulevard de l'Hôpital, Paris, France. (8) Service de Neurochirurgie, Centre Hospitalier Sainte-Anne, Paris, 75014 France, University Paris Descartes. (9) Lyon Neuroscience Research Center INSERM U1028/CNRS UMR 5292, Lyon, France.
Objectives: To develop a tumor growth inhibition model able to describe the evolution of diffuse low-grade gliomas (LGGs) growth dynamics in patients treated with chemotherapy or radiotherapy.
Methods: Model building was performed using longitudinal tumor size (mean tumor diameter) data assessed through imaging techniques in 21 patients treated with first-line PCV chemotherapy. The model was formulated under a population approach as a system of ordinary 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 chemotherapy and in 25 patients treated with first-line radiotherapy. Monolix was used to estimate the population and individual parameters.
Results: The model correctly predicted individual tumor response profiles before, during and after PCV chemotherapy. The same model structure was successfully applied to describe tumor size dynamics in patients treated with temozolomide chemotherapy or radiotherapy. Tumor-specific parameters were consistent across the three treatment modalities.
Conclusions: We developed a tumor growth inhibition model able to describe LGG tumor size evolution in patients treated with chemotherapy or radiotherapy. In the future, this model could constitute a rational tool to conceive more effective chemotherapy schedules.
Reference: PAGE 21 (2012) Abstr 2407 [www.page-meeting.org/?abstract=2407]
Poster: Oncology