Literature DB >> 7061168

Evaluation of some mathematical models for tumor growth.

V G Vaidya, F J Alexandro.   

Abstract

A number of mathematical models for tumor growth have been proposed in the past to increase the understanding of the tumor growth process. This study evaluates the exponential, the Gompertz, the Bertalanffy and the logistic models. The data used for the evaluation of the models consists of: the untreated primary carcinoma of the human lung, and induced sarcoma in mice. The non-linear regression method was used for the analysis of the data. The logistic equation gave the best fit in the cases of all seven patients. However, the Bertalanffy equation was the best in seven out of 10 cases of mice. The models were also judged by comparing the percentage error in predicting the volume of a tumor.

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Year:  1982        PMID: 7061168     DOI: 10.1016/0020-7101(82)90048-4

Source DB:  PubMed          Journal:  Int J Biomed Comput        ISSN: 0020-7101


  26 in total

1.  Gompertzian growth pattern correlated with phenotypic organization of colon carcinoma, malignant glioma and non-small cell lung carcinoma cell lines.

Authors:  M A A Castro; F Klamt; V A Grieneisen; I Grivicich; J C F Moreira
Journal:  Cell Prolif       Date:  2003-04       Impact factor: 6.831

2.  Mathematical Models for Tumor Growth and the Reduction of Overtreatment.

Authors:  Berdine L Heesterman; John-Melle Bokhorst; Lisa M H de Pont; Berit M Verbist; Jean-Pierre Bayley; Andel G L van der Mey; Eleonora P M Corssmit; Frederik J Hes; Peter Paul G van Benthem; Jeroen C Jansen
Journal:  J Neurol Surg B Skull Base       Date:  2018-07-23

3.  Cellular interactions constrain tumor growth.

Authors:  Jeffrey West; Paul K Newton
Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-23       Impact factor: 11.205

4.  Cancer chemotherapy: optimal control using the Verhulst-Pearl equation.

Authors:  G W Swan
Journal:  Bull Math Biol       Date:  1986       Impact factor: 1.758

5.  Tumor growth in vivo and as multicellular spheroids compared by mathematical models.

Authors:  M Marusić; Z Bajzer; S Vuk-Pavlović; J P Freyer
Journal:  Bull Math Biol       Date:  1994-07       Impact factor: 1.758

6.  Association of Tumor Size With Prognosis in Patients With Resectable Endometrial Cancer: A SEER Database Analysis.

Authors:  Xuefei Hou; Suru Yue; Jie Liu; Zhiqing Qiu; Liming Xie; Xueying Huang; Shasha Li; Liren Hu; Jiayuan Wu
Journal:  Front Oncol       Date:  2022-06-23       Impact factor: 5.738

Review 7.  In silico cancer modeling: is it ready for prime time?

Authors:  Thomas S Deisboeck; Le Zhang; Jeongah Yoon; Jose Costa
Journal:  Nat Clin Pract Oncol       Date:  2008-10-14

8.  Modelling of chronic wound healing dynamics.

Authors:  D Cukjati; S Rebersek; R Karba; D Miklavcic
Journal:  Med Biol Eng Comput       Date:  2000-05       Impact factor: 3.079

9.  Characterization and quantification of necrotic tissues and morphology in multicellular ovarian cancer tumor spheroids using optical coherence tomography.

Authors:  Feng Yan; Gokhan Gunay; Trisha I Valerio; Chen Wang; Jayla A Wilson; Majood S Haddad; Maegan Watson; Michael O Connell; Noah Davidson; Kar-Ming Fung; Handan Acar; Qinggong Tang
Journal:  Biomed Opt Express       Date:  2021-05-13       Impact factor: 3.732

10.  Modified Gompertz equation for electrotherapy murine tumor growth kinetics: predictions and new hypotheses.

Authors:  Luis E Bergues Cabrales; Juan J Godina Nava; Andrés Ramírez Aguilera; Javier A González Joa; Héctor M Camué Ciria; Maraelys Morales González; Miriam Fariñas Salas; Manuel Verdecia Jarque; Tamara Rubio González; Miguel A O'Farril Mateus; Soraida C Acosta Brooks; Fabiola Suárez Palencia; Lisset Ortiz Zamora; María C Céspedes Quevedo; Sarah Edward Seringe; Vladimir Crombet Cuitié; Idelisa Bergues Cabrales; Gustavo Sierra González
Journal:  BMC Cancer       Date:  2010-10-28       Impact factor: 4.430

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