MODELLING THE CANCER GROWTH PROCESS BY STOCHASTIC DELAY DIFFERENTIAL EQUATIONS UNDER VERHULTS AND GOMPERTZ’S LAW

Authors

  • Mazma Syahidatul Ayuni Mazlan Department Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang
  • Norhayati Rosli Department Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang
  • Nina Suhaity Azmi Department Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang

DOI:

https://doi.org/10.11113/jt.v78.7817

Keywords:

Verhults law, Gompertz law, deterministic model, stochastic delay differential equations

Abstract

In this paper, the uncontrolled environmental factors are perturbed into the intrinsic growth rate factor of deterministic equations of the growth process. The growth process under two different laws which are Verhults and Gompertz’s law are considered, thus leading to stochastic delay differential equations (SDDEs) of logistic and Gompertzian, respectively. Gompertzian deterministic model has been proved to fit well the clinical data of cancerous growth, however the performance of stochastic model towards clinical data is yet to be confirmed. The prediction quality of logistic and Gompertzian SDDEs are evaluating by comparing the simulated results with the clinical data of cervical cancer growth. The parameter estimation of stochastic models is computed by using simulated maximum likelihood method. We adopt 4-stage stochastic Runge-Kutta to simulate the solution of stochastic models. 

References

Bernard, W. S. and Christopher, P. W. 2014. World Cancer Report 2014. World Health Organization.

Omar, Z. A. and Tamin N. S. I. 2011. National Cancer Registry Report 2007. Malaysia Cancer Statistics-Data and Figure Peninsular Malaysia 2007. Ministry of Health Malaysia.

Chakrabarti, A., Verbridge, S., Stroock, A. D., Fischbach, C., and Varner, J. D. 2012. Multiscale Models of Breast Cancer Progression. Annals of Biomedical Engineering. 40(11): 2488-2500.

Hart, D., Shochat, E., and Agus, Z. 1998. The Growth Law of Primary Breast Cancer as Inferred from Mammography Screening Trials Data. British Journal of Cancer. 78: 382–387.

Elishmereni, M., Kheifetz, Y., Søndergaard, H., Overgaard, R. V., and Agur, Z. 2011. An Integrated Disease/Pharmacokinetic/Pharmacodynamic Model Suggests Improved Interleukin-21 Regimens Validated Prospectively for Mouse Solid Cancers. PLOS Computational Biology. 7(9): 1-10.

Zheng, Y., Moore, H., Piryatinska, A., Solis, T., and Sweet-Cordero, E. A. 2013. Mathematical Modeling of Tumor Cell Proliferation Kinetics and Label Retention in a Mouse Model of Lung Cancer. Cancer Research. 73(12): 3525-3533.

Sarapata, E. A. and de Pillis, L. G. 2014. A Comparison and Catalog of Intrinsic Tumor Growth Models. Bulletin Math Biology. 76: 2010-2024.

Benzekry, S., Lamont, C. Beheshti, A., Tracz, A., Ebos, J. M., Hlatky, L., and Hahnfeldt. P. 2014. Classical Mathematical Models for Description and Prediction of Experimental Tumor Growth. PLOS Computational Biology. 10(8): 1-19.

Laird, A.K. 1964. Dynamics of Tumour Growth. British Journal of Cancer. 13: 490–502.

Laird, A.K. 1965. Dynamics of Tumour Growth: Comparison of Growth Rates and Extrapolation of Growth Curve to One Cell. British Journal of Cancer. 19: 278–291.

Vaidya, V.G. and Alexandro, F.J. 1982. Evaluation of Some Mathematical Models for Tumor Growth. International Journal of Biomed Computation. 13: 19–36.

Michelson, S., Glicksman, A. S., and Leith, J. T. 1987. Growth in Solid Heterogeneous Human Colon Adenocarcinomas: Comparison of Simple Logistical Models. Cell Tissue Kinetics. 20: 343–355.

Norton, L., Simon, R., Brereton, H. D., and Bogden, A. E. 1976. Predicting the Course of Gompertzian Growth. Nature. 264: 542–544

Akanuma, A. 1978. Parameter Analysis of Gompertzian Function Growth Model in Clinical Tumors. European Journal of Cancer. 14: 681–688.

Mazma Syahidatul Ayuni Mazlan, and Norhayati Rosli. 2014. A Gompertzian Model with Random Effects to Cervical Cancer Growth. International Conference in Mathematics, Engineering and Industrial Applications (ICoMEIA 2014), Penang, Malaysia. 28-30 May 2014. 1660-1667.

Spratt, J. A., Von Fournier, D., Spratt, J. S., and Weber, E. E 1993. Decelerating Growth and Human Breast Cancer. Cancer Research. 71: 2013–2019.

MaruÅ¡ić, M., Bajzer, Z., Reyer, J. P., and Vukâ€Pavlović, S. 1994. Analysis of Growth of Multicellular Tumour Spheroids by Mathematical Models. Cell Proliferation. 27(2): 73-94.

Schuster, and Schuster, R. H. 1995. Reconstruction Models for the Ehrlich Ascites Tumor of the Mouse. Mathematical Population Dynamics. 2: 335-348.

ForyÅ›, U. and Marciniak-Czochra, A. 2003. Logistic Equations in Tumour Growth Modelling. International Journal of Applied Mathematics and Computer Science.13: 317-325.

Ditlevsen, S. and A. Samson. 2013. Introduction to Stochastic Models in Biology, in Stochastic Biomathematical Models. Springer Publishing.

Byrne, H. M. 1997. The Effect of Time Delays on the Dynamics of Avascular Tumor Growth. Mathematical Biosciences. 144: 83-117.

Gompertz, B. 1825. On the Nature of the Function Expressive of the Law of Human Mortality, and on a New Mode of Determining the Value of Life Contingencies. Philosophical Transactions of the Royal Society of London. 115: 513–583.

Ferrante, L., Bompadre, S., Possati, L., and Leone, L. 2000. Parameter Estimation in a Gompertzian Stochastic Model for Tumor Growth. Biometrics. 56: 1076-1081.

Lo, C. F. 2007. Stochastic Gompertz Model of Tumour Cell Growth. Journal of Theoretical Biology. 248: 317-321.

Weinberg, R. 2013. The Biology of Cancer. Garland Science Publishing.

Verhulst, P. F. 1838. Notice Sur la loi que la Population Suit Dans Son Accroissement. Corr. Math. Phys. 10: 113–121.

Norhayati Rosli. 2012. Stochastic Runge-Kutta Method for Stochastic Delay Differential Equations. PhD Thesis, Universiti Teknologi Malaysia.

Guillouzic, S. L’Heureux, I., and Longtin, A. (1999). Small Delay Approximation of Stochastic Delay Differential Equations. Physical Review E. 59: 3970-3982.

Friberg, S. and Mattson, S. 1997. On the Growth Rates of Human Malignant Tumors: Implications for Medical Decision Making. Journal of Surgical Oncology. 65(4): 284-297.

Downloads

Published

2016-03-09

How to Cite

MODELLING THE CANCER GROWTH PROCESS BY STOCHASTIC DELAY DIFFERENTIAL EQUATIONS UNDER VERHULTS AND GOMPERTZ’S LAW. (2016). Jurnal Teknologi (Sciences & Engineering), 78(3-2). https://doi.org/10.11113/jt.v78.7817