Table of Contents
ISRN Oncology
Volume 2014 (2014), Article ID 912865, 5 pages
http://dx.doi.org/10.1155/2014/912865
Clinical Study

Survival Prediction Score: A Simple but Age-Dependent Method Predicting Prognosis in Patients Undergoing Palliative Radiotherapy

1Department of Oncology and Palliative Medicine, Nordland Hospital, 8092 Bodø, Norway
2Institute of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway

Received 17 December 2013; Accepted 13 February 2014; Published 19 March 2014

Academic Editors: P. Herst and G. Metro

Copyright © 2014 Kent Angelo 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.

Linked References

  1. P. Glare, K. Virik, M. Jones et al., “A systematic review of physicians' survival predictions in terminally ill cancer patients,” British Medical Journal, vol. 327, no. 7408, pp. 195–198, 2003. View at Google Scholar · View at Scopus
  2. F. Toscani, C. Brunelli, G. Miccinesi et al., “Predicting survival in terminal cancer patients: clinical observation or quality-of-life evaluation?” Palliative Medicine, vol. 19, no. 3, pp. 220–227, 2005. View at Publisher · View at Google Scholar · View at Scopus
  3. L. Gaspar, C. Scott, M. Rotman et al., “Recursive Partitioning Analysis (RPA) of prognostic factors in three Radiation Therapy Oncology Group (RTOG) brain metastases trials,” International Journal of Radiation Oncology Biology Physics, vol. 37, no. 4, pp. 745–751, 1997. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Pirovano, M. Maltoni, O. Nanni et al., “A new palliative prognostic score: a first step for the staging of terminally ill cancer patients,” Journal of Pain and Symptom Management, vol. 17, no. 4, pp. 231–239, 1999. View at Publisher · View at Google Scholar · View at Scopus
  5. E. Chow, K. Fung, T. Panzarella, A. Bezjak, C. Danjoux, and I. Tannock, “A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic,” International Journal of Radiation Oncology Biology Physics, vol. 53, no. 5, pp. 1291–1302, 2002. View at Publisher · View at Google Scholar · View at Scopus
  6. S. Gripp, S. Moeller, E. Bölke et al., “Survival prediction in terminally ill cancer patients by clinical estimates, laboratory tests, and self-rated anxiety and depression,” Journal of Clinical Oncology, vol. 25, no. 22, pp. 3313–3320, 2007. View at Publisher · View at Google Scholar · View at Scopus
  7. D. Rades, J. Dunst, and S. E. Schild, “The first score predicting overall survival in patients with metastatic spinal cord compression,” Cancer, vol. 112, no. 1, pp. 157–161, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. D. Rades, J. Dunst, and S. E. Schild, “A new scoring system to predicting the survival of patients treated with whole-brain radiotherapy for brain metastases,” Strahlentherapie und Onkologie, vol. 184, no. 5, pp. 251–255, 2008. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Nieder and M. P. Mehta, “Prognostic indices for brain metastases—usefulness and challenges,” Radiation Oncology, vol. 4, article 10, 2009. View at Publisher · View at Google Scholar · View at Scopus
  10. E. Chow, M. Abdolell, T. Panzarella et al., “Predictive model for survival in patients with advanced cancer,” Journal of Clinical Oncology, vol. 26, no. 36, pp. 5863–5869, 2008. View at Publisher · View at Google Scholar · View at Scopus
  11. E. R. Laws, I. F. Parney, W. Huang et al., “Survival following surgery and prognostic factors for recently diagnosed malignant glioma: data from the glioma outcomes project,” Journal of Neurosurgery, vol. 99, no. 3, pp. 467–473, 2003. View at Google Scholar · View at Scopus
  12. P. W. Sperduto, B. Berkey, L. E. Gaspar, M. Mehta, and W. Curran, “A new prognostic index and comparison to three other indices for patients with brain metastases: an analysis of 1,960 patients in the RTOG database,” International Journal of Radiation Oncology Biology Physics, vol. 70, no. 2, pp. 510–514, 2008. View at Publisher · View at Google Scholar · View at Scopus
  13. M. Federico, M. Bellei, L. Marcheselli et al., “Follicular lymphoma international prognostic index 2: a new prognostic index for follicular lymphoma developed by the international follicular lymphoma prognostic factor project,” Journal of Clinical Oncology, vol. 27, no. 27, pp. 4555–4562, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. C. Röllig, C. Thiede, M. Gramatzki et al., “A novel prognostic model in elderly patients with acute myeloid leukemia: results of 909 patients entered into the prospective AML96 trial,” Blood, vol. 116, no. 6, pp. 971–978, 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. J. N. Winter, S. Li, V. Aurora et al., “Expression of p21 protein predicts clinical outcome in DLBCL patients older than 60 years treated with R-CHOP but not CHOP: a prospective ECOG and Southwest Oncology Group correlative study on E4494,” Clinical Cancer Research, vol. 16, no. 8, pp. 2435–2442, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. D. Rades, N. D. Seibold, M. P. Gebhard, F. Noack, S. E. Schild, and C. Thorns, “Prognostic factors (including HPV status) for irradiation of locally advanced squamous cell carcinoma of the head and neck (SCCHN),” Strahlentherapie und Onkologie, vol. 187, no. 10, pp. 626–632, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. E. Chow, M. Abdolell, T. Panzarella et al., “Validation of a predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic,” International Journal of Radiation Oncology Biology Physics, vol. 73, no. 1, pp. 280–287, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. S. Gripp, S. Mjartan, E. Boelke, and R. Willers, “Palliative radiotherapy tailored to life expectancy in end-stage cancer patients: reality or myth?” Cancer, vol. 116, no. 13, pp. 3251–3256, 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. B. A. Guadagnolo, K. P. Liao, L. Elting et al., “Use of radiation therapy in the last 30 days of life among a large population-based cohort of elderly patients in the United States,” Journal of Clinical Oncology, vol. 31, pp. 80–87, 2013. View at Publisher · View at Google Scholar
  20. D. Rades, T. Veninga, A. Bajrovic et al., “A validated scoring system to identify long-term survivors after radiotherapy for metastatic spinal cord compression,” Strahlentherapie und Onkologie, vol. 189, no. 6, pp. 462–466, 2013. View at Publisher · View at Google Scholar
  21. D. Rades, M. Hueppe, and S. E. Schild, “A score to identify patients with metastatic spinal cord compression who may be candidates for best supportive care,” Cancer, vol. 119, no. 4, pp. 897–903, 2013. View at Publisher · View at Google Scholar
  22. P. W. Sperduto, S. T. Chao, P. K. Sneed et al., “Diagnosisspecific prognostic factors, indexes, and treatment outcomes for patients with newly diagnosed brain metastases: a multiinstitutional analysis of 4,259 patients,” International Journal of Radiation Oncology, Biology Physics, vol. 77, no. 3, pp. 655–661, 2010. View at Google Scholar
  23. C. Nieder, J. Norum, A. Dalhaug et al., “Best supportive care in patients with brain metastases and adverse prognostic factors: development of improved decision aids,” Support Care Cancer, vol. 21, no. 10, pp. 2671–2678, 2013. View at Publisher · View at Google Scholar
  24. A. T. Stopeck, U. Brown-Glaberman, H. Y. Wong et al., “The role of targeted therapy and biomarkers in breast cancer treatment,” Clinical & Experimental Metastasis, vol. 29, no. 7, pp. 807–819, 2012. View at Publisher · View at Google Scholar