Multiple sequential recurrences are one of the most important characteristics of superficial transitional cell carcinoma (TCC) of the bladder. Many investigations have been done to identify predictive factors for the first recurrence, but very few studies have investigated multiple recurrences of this cancer and its clinicopathologic factors associated. We consider counting process methods for analysing timeto-event data with recurrent outcomes using the models developed by Andersen and Gill and, Prentice, Williams, and Peterson. A postoperative nomogram is developed to predict recurrences based on those predictive factors.
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References
Greenlee, R.T., Hill-Harmon, M.B., Murray, T., Thun, M.: Cancer statistics. CA Cancer J Clin, 51, 15-36 (2001)
Hlmang, S., Hedelin, H., Anderstrm, C., Johansson, S.L.: The relationship among multiple recurrences, progression and prognosis of patients with Stage Ta and T1 transitional cell cancer of the bladder followed for at least 20 years. J Urol, 153, 1823-1827 (1995)
García, B., Rubio, G. Santamaría, C., Pontones, J.L., Vera, C.D., Jiménez, J.F.: A predictive mathematical model in the recurrence of bladder cancer. Math Comp Model, 42, 621-634 (2005)
Jaemal, A., Murray, T., Samuels, A., Ghafoor, A., Ward, E., Thun, M.: Cancer statistics 2002. CA Cancer J Clin, 53, 5-26 (2003)
Hermanek, P., Sobin, L.H.: TNM Classification of malignant tumours 4th ed. Springer-Verlag, Berlin (1998)
Andersen, P. K., Gill, R. D.: Cox’s regression model for counting processes: a large sample study. Ann Statis, 10, 1100-1120 (1982)
Prentice, R. L., Williams, B. J., Peterson, A. V.: On the regression analysis of multivariate failure time data. Biometrika, 68, 373-389 (1989)
Cox, D. R.: Partial likelihood. Biometrika, 62, 269-276 (1975)
Harrell, F.E.: Regression Modeling Strategies with Aplications to Linear Models, Logistic Regression and Survival Analysis. Springer, N.Y. (2002)
Harrell F. E., Lee, K.L., Mark, D. B.: Multivariate prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Statis Med, 15, 361-87 (1996)
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Santamaría, C., García-Mora, M.B., Rubio, G., Pontones, J.L. (2008). A Mathematical Model for Prediction of Recurrence in Bladder Cancer Patients. In: Bonilla, L.L., Moscoso, M., Platero, G., Vega, J.M. (eds) Progress in Industrial Mathematics at ECMI 2006. Mathematics in Industry, vol 12. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71992-2_151
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DOI: https://doi.org/10.1007/978-3-540-71992-2_151
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