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Advances in Bioinformatics
Volume 2011 (2011), Article ID 172615, 8 pages
Neutropenia Prediction Based on First-Cycle Blood Counts Using a FOS-3NN Classifier
1Department of Electrical and Computer Engineering, Queen's University, Kingston, ON, K7L 3N6, Canada
2Division of Signaling Biology, IBM Life Sciences Discovery Centre, Toronto Medical Discovery Tower, 9-305, 101 College Street, Toronto, Ontario, M5G 1L7, Canada
3Departments of Oncology, Medicine, Pharmacology and Toxicology, Queen's University, Kingston, ON, K7L 5P9, Canada
Received 21 September 2011; Revised 16 December 2011; Accepted 31 December 2011
Academic Editor: Shandar Ahmad
Copyright © 2011 Elize A. Shirdel et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- D. R. Budman, D. A. Berry, C. T. Cirrincione et al., “Dose and dose intensity as determinants of outcome in the adjuvant treatment of breast cancer,” Journal of the National Cancer Institute, vol. 90, no. 16, pp. 1205–1211, 1998.
- W. Hryniuk and H. Bush, “The importance of dose intensity in chemotherapy of metastatic breast cancer,” Journal of Clinical Oncology, vol. 2, no. 11, pp. 1281–1288, 1984.
- G. Bonadonna, P. Valagussa, A. Moliterni, M. Zambetti, and C. Brambilla, “Adjuvant cyclophosphamide, methotrexate, and fluorouracil in node-positive breast cancer: the results of 20 years of follow-up,” The New England Journal of Medicine, vol. 332, no. 14, pp. 901–906, 1995.
- G. H. Lyman, N. Kuderer, J. Greene, and L. Balducci, “The economics of febrile neutropenia: implications for the use of golony-stimulating factors,” European Journal of Cancer, vol. 34, no. 12, pp. 1857–1864, 1998.
- J. Chang, “Chemotherapy dose reduction and delay in clinical practice. evaluating the risk to patient outcome in adjuvant chemotherapy for breast cancer,” European Journal of Cancer, vol. 36, supplement 1, pp. S11–S14, 2000.
- J. H. Silber, M. Fridman, R. S. DiPaola, M. H. Erder, M. V. Pauly, and K. R. Fox, “First-cycle blood counts and subsequent neutropenia, dose reduction, or delay in early-stage breast cancer therapy,” Journal of Clinical Oncology, vol. 16, no. 7, pp. 2392–2400, 1998.
- C. A. Uyl-de Groot, E. Vellenga, and F. F. H. Rutten, “An economic Model to assess the savings from a clinical application of haematopoietic growth factors,” European Journal of Cancer A, vol. 32, no. 1, pp. 57–62, 1996.
- P. Jenkins and S. Freeman, “Pretreatment haematological laboratory values predict for excessive myelosuppression in patients receiving adjuvant FEC chemotherapy for breast cancer,” Annals of Oncology, vol. 20, no. 1, pp. 34–40, 2009.
- G. Dranitsaris, D. Rayson, M. Vincent et al., “Identifying patients at high risk for neutropenic complications during chemotherapy for metastatic breast cancer with doxorubicin or pegylated liposomal doxorubicin: the development of a prediction model,” American Journal of Clinical Oncology, vol. 31, no. 4, pp. 369–374, 2008.
- E. Rivera, M. Haim Erder, M. Fridman, D. Frye, and G. N. Hortobagyi, “First-cycle absolute neutrophil count can be used to improve chemotherapy-dose delivery and reduce the risk of febrile neutropenia in patients receiving adjuvant therapy: a validation study,” Breast Cancer Research, vol. 5, no. 5, pp. R114–R120, 2003.
- J. Matsubara, M. Ono, A. Negishi et al., “Identification of a predictive biomarker for hematologic toxicities of gemcitabine,” Journal of Clinical Oncology, vol. 27, no. 13, pp. 2261–2268, 2009.
- A. Uys, B. L. Rapoport, H. Fickl, P. W. A. Meyer, and R. Anderson, “Prediction of outcome in cancer patients with febrile neutropenia: comparison of the multinational association of supportive care in cancer risk-index score with procalcitonin, C-reactive protein, serum amyloid A, and interleukins-1β, -6, -8 and -10,” European Journal of Cancer Care, vol. 16, no. 6, pp. 475–483, 2007.
- M. E. Straver, A. M. Glas, J. Hannemann et al., “The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer,” Breast Cancer Research and Treatment, vol. 119, no. 3, pp. 551–558, 2010.
- A. Ramon-Lopez, R. Nalda-Molina, B. Valenzuela, and J. J. Perez-Ruixo, “Semi-mechanistic model for neutropenia after high dose of chemotherapy in breast cancer patients,” Pharmaceutical Research, vol. 26, no. 8, pp. 1952–1962, 2009.
- M. Moreau, J. Klastersky, A. Schwarzbold et al., “A general chemotherapy myelotoxicity score to predict febrile neutropenia in hematological malignancies,” Annals of Oncology, vol. 20, no. 3, pp. 513–519, 2009.
- R. R. Weichselbaum, H. Ishwaran, T. Yoon et al., “An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer,” Proceedings of the National Academy of Sciences of the United States of America, vol. 105, no. 47, pp. 18490–18495, 2008.
- G. H. Lyman, D. C. Dale, and J. Crawford, “Incidence and predictors of low dose-intensity in adjuvant breast cancer chemotherapy: a nationwide study of community practices,” Journal of Clinical Oncology, vol. 21, no. 24, pp. 4524–4531, 2003.
- J. M. Bueno-de-Mesquita, S. C. Linn, R. Keijzer et al., “Validation of 70-gene prognosis signature in node-negative breast cancer,” Breast Cancer Research and Treatment, vol. 117, no. 3, pp. 483–495, 2009.
- D. Jiang and N. Zhao, “A clinical prognostic prediction of lymph node-negative breast cancer by gene expression profiles,” Journal of Cancer Research and Clinical Oncology, vol. 132, no. 9, pp. 579–587, 2006.
- X. J. Ma, Z. Wang, P. D. Ryan et al., “A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen,” Cancer Cell, vol. 5, no. 6, pp. 607–616, 2004.
- K. V. I. Rolston, “Prediction of neutropenia,” International Journal of Antimicrobial Agents, vol. 16, no. 2, pp. 113–115, 2000.
- M. J. Korenberg, “A robust orthogonal algorithm for system identification and time-series analysis,” Biological Cybernetics, vol. 60, no. 4, pp. 267–276, 1989.
- M. M. Atia, M. J. Korenberg, and A. Noureldin, “Fast features reduction of radio maps for real-time fingerprint-based wireless positioning systems,” Electronics Letters, vol. 47, no. 20, pp. 1151–1153, 2011.
- A. G. Perry, M. J. Korenberg, G. G. Hall, and K. M. Moore, “Modeling and syndromic surveillance for estimating weather-induced heat-related illness,” Journal of Environmental and Public Health, vol. 2011, Article ID 750236, 10 pages, 2011.
- E. Fix and J. L. Hodges, “Discriminatory analysis, non parametric discrimination: consistency problems,” Tech. Rep., USAF School of Aviation Medicine, Randolph Field, Tex, USA, 1951.
- T. R. Golub, D. K. Slonim, P. Tamayo et al., “Molecular classification of cancer: class discovery and class prediction by gene expression monitoring,” Science, vol. 286, no. 5439, pp. 531–527, 1999.
- V. Vapnik, Ed., The Nature of Statistical Learning Theory, Springer, New York, NY, USA, 2000.
- S. L. Pomeroy, P. Tamayo, M. Gaasenbeek et al., “Prediction of central nervous system embryonal tumour outcome based on gene expression,” Nature, vol. 415, no. 6870, pp. 436–442, 2002.
- E. L. Kaplan and P. Meier, “Nonparametric estimation from incomplete observations,” Journal of the American Statistical Association, vol. 53, pp. 457–481, 1958.