IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v387y2008i13p3162-3172.html
   My bibliography  Save this article

A superstatistical model of metastasis and cancer survival

Author

Listed:
  • Leon Chen, L.
  • Beck, Christian

Abstract

We introduce a superstatistical model for the progression statistics of malignant cancer cells. The metastatic cascade is modeled as a complex nonequilibrium system with several macroscopic pathways and inverse-chi-square distributed parameters of the underlying Poisson processes. The predictions of the model are in excellent agreement with observed survival-time probability distributions of breast cancer patients.

Suggested Citation

  • Leon Chen, L. & Beck, Christian, 2008. "A superstatistical model of metastasis and cancer survival," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3162-3172.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:13:p:3162-3172
    DOI: 10.1016/j.physa.2008.01.116
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437108001398
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2008.01.116?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. P. Royston, 2001. "The Lognormal Distribution as a Model for Survival Time in Cancer, With an Emphasis on Prognostic Factors," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 55(1), pages 89-104, March.
    2. Thurner, Stefan & Wick, Nikolaus & Hanel, Rudolf & Sedivy, Roland & Huber, Lukas, 2003. "Anomalous diffusion on dynamical networks: a model for interacting epithelial cell migration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 475-484.
    3. R. S. Mendes & L. C. Malacarne & C. Anteneodo, 2007. "Statistics of football dynamics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(3), pages 357-363, June.
    4. Sumiyoshi Abe & Stefan Thurner, 2006. "Hierarchical And Mixing Properties Of Static Complex Networks Emerging From Fluctuating Classical Random Graphs," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 17(09), pages 1303-1311.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ewin Sánchez & Manuel González-Navarrete & Christian Caamaño-Carrillo, 2021. "Bivariate superstatistics: an application to statistical plasma physics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(2), pages 1-7, February.
    2. Sánchez, Ewin, 2019. "Burr type-XII as a superstatistical stationary distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 443-446.
    3. Kosun, Caglar & Ozdemir, Serhan, 2016. "A superstatistical model of vehicular traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 466-475.
    4. Lubashevsky, Ihor & Friedrich, Rudolf & Heuer, Andreas & Ushakov, Andrey, 2009. "Generalized superstatistics of nonequilibrium Markovian systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(21), pages 4535-4550.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carlota Torrents & Angel Ric & Robert Hristovski & Lorena Torres-Ronda & Emili Vicente & Jaime Sampaio, 2016. "Emergence of Exploratory, Technical and Tactical Behavior in Small-Sided Soccer Games when Manipulating the Number of Teammates and Opponents," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-15, December.
    2. dos Santos, M.A.F. & Colombo, E.H. & Anteneodo, C., 2021. "Random diffusivity scenarios behind anomalous non-Gaussian diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    3. Patrick Royston, 2007. "Multiple imputation of missing values: further update of ice, with an emphasis on interval censoring," Stata Journal, StataCorp LP, vol. 7(4), pages 445-464, December.
    4. Sun Eric & Jena Anupam B & Lakdawalla Darius & Reyes Carolina & Philipson Tomas J & Goldman Dana, 2010. "The Contributions of Improved Therapy and Earlier Detection to Cancer Survival Gains, 1988-2000," Forum for Health Economics & Policy, De Gruyter, vol. 13(2), pages 1-22, February.
    5. Shirin Moghaddam & John Newell & John Hinde, 2022. "A Bayesian Approach for Imputation of Censored Survival Data," Stats, MDPI, vol. 5(1), pages 1-19, January.
    6. Nath, Debraj, 2023. "Superstatistics of anisotropic oscillator in a noncommutative plane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    7. Selamawit Endale Gurmu, 2018. "Assessing Survival Time of Women with Cervical Cancer Using Various Parametric Frailty Models: A Case Study at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia," Annals of Data Science, Springer, vol. 5(4), pages 513-527, December.
    8. Narizuka, Takuma & Yamamoto, Ken & Yamazaki, Yoshihiro, 2014. "Statistical properties of position-dependent ball-passing networks in football games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 157-168.
    9. Warisa Thangjai & Suparat Niwitpong, 2020. "Comparing particulate matter dispersion in Thailand using the Bayesian Confidence Intervals for ratio of coefficients of variation," Statistics in Transition New Series, Polish Statistical Association, vol. 21(5), pages 41-60, December.
    10. Chrys Caroni, 2022. "Regression Models for Lifetime Data: An Overview," Stats, MDPI, vol. 5(4), pages 1-11, December.
    11. Nicholas Longford, 2008. "Inference with the lognormal distribution," Economics Working Papers 1104, Department of Economics and Business, Universitat Pompeu Fabra.
    12. Zamora, Dario Javier & Tsallis, Constantino, 2022. "Probabilistic models with nonlocal correlations: Numerical evidence of q-Large Deviation Theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:387:y:2008:i:13:p:3162-3172. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.