Skip to main content
Erschienen in: Journal of Medical Systems 7/2016

01.07.2016 | Mobile Systems

An Algorithm for Creating Prognostic Systems for Cancer

verfasst von: Dechang Chen, Huan Wang, Li Sheng, Matthew T. Hueman, Donald E. Henson, Arnold M. Schwartz, Jigar A. Patel

Erschienen in: Journal of Medical Systems | Ausgabe 7/2016

Einloggen, um Zugang zu erhalten

Abstract

The TNM staging system is universally used for classification of cancer. This system is limited since it uses only three factors (tumor size, extent of spread to lymph nodes, and status of distant metastasis) to generate stage groups. To provide a more accurate description of cancer and thus better patient care, additional factors or variables should be used to classify cancer. In this paper we propose a hierarchical clustering algorithm to develop prognostic systems that classify cancer according to multiple prognostic factors. This algorithm has many potential applications in augmenting the data currently obtained in a staging system by allowing more prognostic factors to be incorporated. The algorithm clusters combinations of prognostic factors that are formed using categories of factors. The dissimilarity between two combinations is determined by the area between two corresponding survival curves. Groups from cutting the dendrogram and survival curves of the individual groups define our prognostic systems that classify patients using survival outcomes. A demonstration of the proposed algorithm is given for patients with breast cancer from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute.
Literatur
1.
Zurück zum Zitat Siegel, R.L., Miller, K.D., Jemal, A., Cancer statistics. CA Cancer J. Clin. 65:5–29, 2015.CrossRefPubMed Siegel, R.L., Miller, K.D., Jemal, A., Cancer statistics. CA Cancer J. Clin. 65:5–29, 2015.CrossRefPubMed
2.
Zurück zum Zitat Edge, S.B., Byrd, D.R., Compton, C.C., Fritz, A.G., Green, F.L., AJCC Cancer staging manual. 7 ed. New York: Springer, 2010. Edge, S.B., Byrd, D.R., Compton, C.C., Fritz, A.G., Green, F.L., AJCC Cancer staging manual. 7 ed. New York: Springer, 2010.
3.
Zurück zum Zitat Andreu-Perez, J., Poon, C.C.Y., Merrifield, R.D., Wong, S.T.C., Yang, G.Z., Big data for health. IEEE J. Biomed. Health Inform. 19(4):1193–1208, 2015.CrossRefPubMed Andreu-Perez, J., Poon, C.C.Y., Merrifield, R.D., Wong, S.T.C., Yang, G.Z., Big data for health. IEEE J. Biomed. Health Inform. 19(4):1193–1208, 2015.CrossRefPubMed
4.
Zurück zum Zitat Klein, J.P., and Moeschberger, M.L., Survival Analysis: Techniques for Censored and Truncated Data. 2nd. New York: Springer, 2003. Klein, J.P., and Moeschberger, M.L., Survival Analysis: Techniques for Censored and Truncated Data. 2nd. New York: Springer, 2003.
5.
Zurück zum Zitat Gimotty, P.A., Guerry, D., Ming, M.E., et al., Thin Primary Cutaneous Malignant Melanoma: A Prognostic Tree for 10-Year Metastasis Is More Accurate Than American Joint Committee on Cancer Staging. J. Clin. Oncol. 22:3668–3676, 2004.CrossRefPubMed Gimotty, P.A., Guerry, D., Ming, M.E., et al., Thin Primary Cutaneous Malignant Melanoma: A Prognostic Tree for 10-Year Metastasis Is More Accurate Than American Joint Committee on Cancer Staging. J. Clin. Oncol. 22:3668–3676, 2004.CrossRefPubMed
6.
Zurück zum Zitat Chen, D., Xing, K., Henson, D., Sheng, L., Schwartz, A., Cheng, X.: Developing Prognostic Systems of Cancer Patients by Ensemble Clustering. doi:10.1155/2009/632786 (2009) Chen, D., Xing, K., Henson, D., Sheng, L., Schwartz, A., Cheng, X.: Developing Prognostic Systems of Cancer Patients by Ensemble Clustering. doi:10.​1155/​2009/​632786 (2009)
7.
Zurück zum Zitat Wu, D., Yang, C., Wong, S., Meyerle, J., Zhang, B., Chen, D., An examination of TNM staging of melanoma by a machine learning algorithm. Proceedings of 2012 International Conference on Computerized Healthcare, pp. 120–126, 2012. Wu, D., Yang, C., Wong, S., Meyerle, J., Zhang, B., Chen, D., An examination of TNM staging of melanoma by a machine learning algorithm. Proceedings of 2012 International Conference on Computerized Healthcare, pp. 120–126, 2012.
8.
Zurück zum Zitat Qi, R., Wu, D., Sheng, L., Henson, D., Schwartz, A., Xu, E., Xing, K., Chen, D., On an Ensemble algorithm for clustering cancer patient data. BMC Syst. Biol., 2013. doi:10.1186/1752-0509-7-S4-S9. Qi, R., Wu, D., Sheng, L., Henson, D., Schwartz, A., Xu, E., Xing, K., Chen, D., On an Ensemble algorithm for clustering cancer patient data. BMC Syst. Biol., 2013. doi:10.​1186/​1752-0509-7-S4-S9.
9.
Zurück zum Zitat Kaplan, E.L., and Meier, P., Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 53:457–481, 1958. Kaplan, E.L., and Meier, P., Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 53:457–481, 1958.
10.
Zurück zum Zitat Lin, X, and Xu, Q., A new method for the comparison of survival distributions. Pharmaceut. Statist. 9: 67–76, 2010.CrossRef Lin, X, and Xu, Q., A new method for the comparison of survival distributions. Pharmaceut. Statist. 9: 67–76, 2010.CrossRef
12.
Zurück zum Zitat Chen, D., Hueman, M.T., Henson, D.E., Schwartz, A.M., An algorithm for expanding the TNM staging system. Future Oncol. 12(8):1015–24, 2016.CrossRefPubMed Chen, D., Hueman, M.T., Henson, D.E., Schwartz, A.M., An algorithm for expanding the TNM staging system. Future Oncol. 12(8):1015–24, 2016.CrossRefPubMed
13.
Zurück zum Zitat Hastie, T., Tibshirani, R., Friedman, J., The elements of statistical learning: Data mining, inference, and prediction. 2nd Edn. New York: Springer, 2013. Hastie, T., Tibshirani, R., Friedman, J., The elements of statistical learning: Data mining, inference, and prediction. 2nd Edn. New York: Springer, 2013.
14.
Zurück zum Zitat Chen, D., Wang, H., Henson, D.E., Sheng, L., Hueman, M.T., Schwartz, A.M.: Clustering Cancer Data by Areas between Survival Curves. Submitted Chen, D., Wang, H., Henson, D.E., Sheng, L., Hueman, M.T., Schwartz, A.M.: Clustering Cancer Data by Areas between Survival Curves. Submitted
17.
Zurück zum Zitat Henson, D.E., Ries, L., Freedman, L.S., et al., Relationship among outcome, stage of disease, and histologic grade for 22,616 cases of breast cancer. Cancer 68:2142–2149, 1991.CrossRefPubMed Henson, D.E., Ries, L., Freedman, L.S., et al., Relationship among outcome, stage of disease, and histologic grade for 22,616 cases of breast cancer. Cancer 68:2142–2149, 1991.CrossRefPubMed
18.
Zurück zum Zitat Kaufman, L., and Rousseeuw, P., Finding Groups in Data: An introduction to cluster analysis. New York: Wiley, 1990. Kaufman, L., and Rousseeuw, P., Finding Groups in Data: An introduction to cluster analysis. New York: Wiley, 1990.
19.
Zurück zum Zitat Harrell, F.E., Lee, K.L., Mark D.B., Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat. Med. 15:361–387, 1996.CrossRefPubMed Harrell, F.E., Lee, K.L., Mark D.B., Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat. Med. 15:361–387, 1996.CrossRefPubMed
Metadaten
Titel
An Algorithm for Creating Prognostic Systems for Cancer
verfasst von
Dechang Chen
Huan Wang
Li Sheng
Matthew T. Hueman
Donald E. Henson
Arnold M. Schwartz
Jigar A. Patel
Publikationsdatum
01.07.2016
Verlag
Springer US
Erschienen in
Journal of Medical Systems / Ausgabe 7/2016
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-016-0518-1

Weitere Artikel der Ausgabe 7/2016

Journal of Medical Systems 7/2016 Zur Ausgabe