Application of Mathematical Modeling in Survival Time Prediction for Females with Advanced Cervical Cancer Treated Radio-chemotherapy

• Autorzy: Moczko J. , Roszak A.
• Języki publikacji: EN

Abstrakty

EN

Clinical investigations yield huge amount of experimental data which need appropriate processing. High degree of their variability decreases quality of prognostic and classification results. Frequently problem of strong redundancy of variables incorporated into model occurs, produces computational instabilities and in multifactorial models makes the appropriate interpretation of obtained results hindered. In this paper we present the set of mathematical procedures used in comparative analysis of two treatment methods for patients with advanced cervical cancer: radiotherapy and combined treatment of ionizing irradiation and chemotherapy.

Słowa kluczowe

EN

survival analysis; mathematical modeling; cervical cancer; radio-chemotherapy

• Wydawca: Institute of Bioorganic Chemistry Scientific Publishers OWN, Polish Academy of Sciences
• Czasopismo: Computational Methods in Science and Technology
• Rocznik: 2006
• Tom: Vol. 12, nr 2
• Strony: 143--147
• Opis fizyczny: Bibliogr. 7 poz., rys.

Twórcy

autor

Moczko J.

autor

Roszak A.

• Chair and Department of Computer Science and Statistics University of Medical Sciences in Poznań, Dąbrowskiego 79, 60-529 Poznań, Poland,

Bibliografia

• [1] A. Roszak, Badania nad skutecznością radiochemioterapii chorych na zaawansowanego raka szyjki macicy, Rep. Pract.Oncol. Radiother. 9 (S1), 131-162 (2004).
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• [3] Encyclopedia of Biostatistics, ed. P. Armitage, T. Colton,J. Wiley & Sons, Ltd. (2005).
• [4] E. A. Gehan, A generalized Wilcoxon test for comparing arbitrarily singly-censored samples, Biometrika, 52, 203-223 (1965a).
• [5] R. Peto and J. Peto, Asymptotically efficient rank invariant procedures, Journal of the Royal Statistical Society, 135,185-207 (1972).
• [6] D. R. Cox and D. Oakes, Analysis of survival data, New York: Chapman & Hall (1984).
• [7] T. Hastie, R. Tibshirani and J. Friedman, The elements of Statistical Learning. Data Mining, Inference and Prediction,Springer-Verlag NY (2001).