Literature DB >> 9348741

A mathematical model of breast and ovarian cancer treated with paclitaxel.

J C Panetta1.   

Abstract

A mathematical model that describes the effects of cell-cycle-specific drugs on cancer and normal tissue is developed. The model takes into account the proliferating cells, which are sensitive to the treatment, and the quiescent cells, which are resistant to the treatment. With the use of information from the medical literature, model parameters are estimated for breast and ovarian cancer as well as for bone marrow. Then, with the use of the model and the estimated parameters, some acceptable treatment strategies are discussed in terms of treatment period, drug-infusion time, and proliferative fraction of cancer mass. Finally, these results are compared with current clinical practices for treatment with Taxol, and possible improvements on current treatment strategies are suggested.

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Year:  1997        PMID: 9348741     DOI: 10.1016/s0025-5564(97)00077-1

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  16 in total

1.  A spatial model of tumor-host interaction: application of chemotherapy.

Authors:  Peter Hinow; Philip Gerlee; Lisa J McCawley; Vito Quaranta; Madalina Ciobanu; Shizhen Wang; Jason M Graham; Bruce P Ayati; Jonathan Claridge; Kristin R Swanson; Mary Loveless; Alexander R A Anderson
Journal:  Math Biosci Eng       Date:  2009-07       Impact factor: 2.080

Review 2.  Dissecting cancer through mathematics: from the cell to the animal model.

Authors:  Helen M Byrne
Journal:  Nat Rev Cancer       Date:  2010-03       Impact factor: 60.716

Review 3.  The dynamics of drug resistance: a mathematical perspective.

Authors:  Orit Lavi; Michael M Gottesman; Doron Levy
Journal:  Drug Resist Updat       Date:  2012-03-03       Impact factor: 18.500

4.  Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies.

Authors:  Rajul K Jain; David S Hong; Aung Naing; Jennifer Wheler; Thorunn Helgason; Nai-Yi Shi; Yash Gad; Razelle Kurzrock
Journal:  Cell Cycle       Date:  2015       Impact factor: 4.534

5.  Modeling the efficacy of trastuzumab-DM1, an antibody drug conjugate, in mice.

Authors:  Nelson L Jumbe; Yan Xin; Douglas D Leipold; Lisa Crocker; Debra Dugger; Elaine Mai; Mark X Sliwkowski; Paul J Fielder; Jay Tibbitts
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-04-28       Impact factor: 2.745

6.  Chemotherapy in conjoint aging-tumor systems: some simple models for addressing coupled aging-cancer dynamics.

Authors:  Mitra S Feizabadi; Tarynn M Witten
Journal:  Theor Biol Med Model       Date:  2010-06-15       Impact factor: 2.432

7.  Integrating cell-cycle progression, drug penetration and energy metabolism to identify improved cancer therapeutic strategies.

Authors:  Raja Venkatasubramanian; Michael A Henson; Neil S Forbes
Journal:  J Theor Biol       Date:  2008-02-21       Impact factor: 2.691

Review 8.  Mathematical models of breast and ovarian cancers.

Authors:  Dana-Adriana Botesteanu; Stanley Lipkowitz; Jung-Min Lee; Doron Levy
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2016-06-03

9.  Conceptualizing a tool to optimize therapy based on dynamic heterogeneity.

Authors:  David Liao; Luis Estévez-Salmerón; Thea D Tlsty
Journal:  Phys Biol       Date:  2012-11-29       Impact factor: 2.583

10.  Generalized principles of stochasticity can be used to control dynamic heterogeneity.

Authors:  David Liao; Luis Estévez-Salmerón; Thea D Tlsty
Journal:  Phys Biol       Date:  2012-11-29       Impact factor: 2.583

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