Literature DB >> 21476101

Tumor growth modeling from clinical trials reveals synergistic anticancer effect of the capecitabine and docetaxel combination in metastatic breast cancer.

N Frances1, L Claret, R Bruno, A Iliadis.   

Abstract

PURPOSE: Most of the cancer chemotherapy treatments employ drugs in combination. For combination treatments, it is relevant to assess interaction between two or more anticancer agents used in clinics. Based on clinical data and using modeling techniques, the work analyzes the pharmacodynamic interaction between capecitabine and docetaxel used in combination in metastatic breast cancer.
METHODS: We developed mathematical models to describe tumor growth inhibition profile under treatment based on Phase II and Phase III clinical data of capecitabine and docetaxel in metastatic breast cancer. Model parameters were estimated by population approach with NONMEM(®) on single-agent and combination data. Simulations were performed using MATLAB.
RESULTS: Capecitabine and docetaxel combination in metastatic breast cancer results in a synergistic effect as compared with the simple additive effects of single-agent treatments. Docetaxel is more efficient than capecitabine at the start of treatment but develops resistance faster. Modeling revealed no resistance of capecitabine for the combination data.
CONCLUSIONS: Modeling could be a powerful tool to design the most advantageous combination regimen for capecitabine and docetaxel in metastatic breast cancer in order to increase the time before regrowth and decrease the tumor size at regrowth.

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Year:  2011        PMID: 21476101     DOI: 10.1007/s00280-011-1628-6

Source DB:  PubMed          Journal:  Cancer Chemother Pharmacol        ISSN: 0344-5704            Impact factor:   3.333


  11 in total

1.  Assessing the impact of the addition of dendritic cell vaccination to neoadjuvant chemotherapy in breast cancer patients: A model-based characterization approach.

Authors:  Belén P Solans; Ascensión López-Díaz de Cerio; Arlette Elizalde; Luis Javier Pina; Susana Inogés; Jaime Espinós; Esteban Salgado; Luis Daniel Mejías; Iñaki F Trocóniz; Marta Santisteban
Journal:  Br J Clin Pharmacol       Date:  2019-06-14       Impact factor: 4.335

2.  Modeling the Relationship Between Exposure to Abiraterone and Prostate-Specific Antigen Dynamics in Patients with Metastatic Castration-Resistant Prostate Cancer.

Authors:  Xu Steven Xu; Charles J Ryan; Kim Stuyckens; Matthew R Smith; Fred Saad; Thomas W Griffin; Youn C Park; Margaret K Yu; Peter De Porre; An Vermeulen; Italo Poggesi; Partha Nandy
Journal:  Clin Pharmacokinet       Date:  2017-01       Impact factor: 6.447

Review 3.  Drug Exposure to Establish Pharmacokinetic-Response Relationships in Oncology.

Authors:  Belén P Solans; María Jesús Garrido; Iñaki F Trocóniz
Journal:  Clin Pharmacokinet       Date:  2020-02       Impact factor: 6.447

Review 4.  Pharmacokinetics, dynamics and toxicity of docetaxel: Why the Japanese dose differs from the Western dose.

Authors:  Hirotsugu Kenmotsu; Yusuke Tanigawara
Journal:  Cancer Sci       Date:  2015-03-25       Impact factor: 6.716

5.  Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma.

Authors:  A Ouerdani; H Struemper; A B Suttle; D Ouellet; B Ribba
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-11-03

Review 6.  A Review of Modeling Approaches to Predict Drug Response in Clinical Oncology.

Authors:  Kyungsoo Park
Journal:  Yonsei Med J       Date:  2017-01       Impact factor: 2.759

7.  Modeling Longitudinal Preclinical Tumor Size Data to Identify Transient Dynamics in Tumor Response to Antiangiogenic Drugs.

Authors:  L G Hutchinson; H-J Mueller; E A Gaffney; P K Maini; J Wagg; A Phipps; C Boetsch; H M Byrne; B Ribba
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-11-14

8.  Population Pharmacokinetic/Pharmacodynamic Modeling of Tumor Size Dynamics in Pembrolizumab-Treated Advanced Melanoma.

Authors:  M S Chatterjee; J Elassaiss-Schaap; A Lindauer; D C Turner; A Sostelly; T Freshwater; K Mayawala; M Ahamadi; J A Stone; R de Greef; A G Kondic; D P de Alwis
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-11-29

9.  A review of mixed-effects models of tumor growth and effects of anticancer drug treatment used in population analysis.

Authors:  B Ribba; N H Holford; P Magni; I Trocóniz; I Gueorguieva; P Girard; C Sarr; M Elishmereni; C Kloft; L E Friberg
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2014-05-07

Review 10.  Population pharmacokinetic-pharmacodynamic modelling in oncology: a tool for predicting clinical response.

Authors:  Brendan C Bender; Emilie Schindler; Lena E Friberg
Journal:  Br J Clin Pharmacol       Date:  2015-01       Impact factor: 4.335

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