Cancer and Metastasis Reviews

, Volume 30, Issue 2, pp 153–159 | Cite as

External validation of a model to predict the survival of patients presenting with a spinal epidural metastasis

  • Ronald H. M. A. BartelsEmail author
  • Ton Feuth
  • Dirk Rades
  • Rune Hedlund
  • Carlos Villas
  • Yvette van der Linden
  • Wolgang Börm
  • Arnoud Kappelle
  • Richard W. M. van der Maazen
  • J. André Grotenhuis
  • André L. M. Verbeek


The surgical treatment of spinal metastases is evolving. The major problem is the selection of patients who may benefit from surgical treatment. One of the criteria is an expected survival of at least 3 months. A prediction model has been previously developed. The present study has been performed in order to validate externally the model and to demonstrate that this model can be generalized to other institutions and other countries than the Netherlands. Data of 356 patients from five centers in Germany, Spain, Sweden, and the Netherlands who were treated for metastatic epidural spinal cord compression were collected. Hazard ratios in the test population corresponded with those of the developmental population. However, the observed and the expected survival were different. Analysis revealed that the baseline hazard function was significantly different. This tempted us to combine the data and develop a new prediction model. Estimating iteratively, a baseline hazard was composed. An adapted prediction model is presented. External validation of a prediction model revealed a difference in expected survival, although the relative contribution of the specific hazard ratios was the same as in the developmental population. This study emphasized the need to check the baseline hazard function in external validation. A new model has been developed using an estimated baseline hazard.


Spinal metastases Epidural compression Surgical treatment Prediction model 





  1. 1.
    Bartels, R. H. M. A., van der Linden, Y. M., & van der Graaf, W. T. A. (2008). Spinal extradural metastasis: review of current treatment options. CA: A Cancer Journal for Clinicians, 58, 245–259.CrossRefGoogle Scholar
  2. 2.
    Bartels, R. H. M. A., Feuth, T., van der Maazen, R., et al. (2007). A model to predict the life expectancy of patients with spinal epidural metastasis. Cancer, 110, 2042–2049.PubMedCrossRefGoogle Scholar
  3. 3.
    Moons, K. G. M., Royston, P., Vergouwe, Y., Grobbee, D. E., & Altman, D. G. (2009). Research methods & reporting. Prognosis and prognostic research: what, why, and how? BMJ, 338, b375.PubMedCrossRefGoogle Scholar
  4. 4.
    Altman, D. G., & Royston, P. (2000). What do we mean by validating a prognostic model? Statistics in Medicine, 19, 453–473.PubMedCrossRefGoogle Scholar
  5. 5.
    Steyerberg, E. W. (2009). Validation of prediction models. 1, 299–311.Google Scholar
  6. 6.
    Steyerberg, E. W., Vickers, A. J., Cook, N. R., et al. (2010). Assessing the performance of prediction models. A framework for traditional and novel measures. Epidemiology, 21, 128–138.PubMedCrossRefGoogle Scholar
  7. 7.
    van Houwelingen, H. C. (2010). Validation, calibration, revision and combination of prognostic survival models. Statistics in Medicine, 19, 3401–3415.CrossRefGoogle Scholar
  8. 8.
    van Houwelingen, H. C., & Thorogood, J. (1995). Construction, validation and updating of a prognostic model for kidney graft survival. Statistics in Medicine, 14, 1999–2008.PubMedCrossRefGoogle Scholar
  9. 9.
    White, I. R., & Royston, P. (2009). Imputing missing covariate values for the Cox model. Statistics in Medicine, 28, 1982–1998.PubMedCrossRefGoogle Scholar
  10. 10.
    Harrell Jr, F. E. (2001). Regression modeling strategies. With applications to linear models, logistic regression, and survival analysis. 1,Google Scholar
  11. 11.
    Chow, E., Davis, L., Panzarella, T., et al. (2005). Accuracy of survival prediction by palliative radiation oncologists. International Journal of Radiation Oncology, Biology, Physics, 61, 870–873.PubMedCrossRefGoogle Scholar
  12. 12.
    Chow, E., Harth, T., Hruby, G., Finkelstein, J., Wu, J., & Danjoux, C. (2001). How accurate are physicians’ clinical prediction of survival and the available prognostic tools in estimating survival times in terminally ill cancer patients? A systematic review. Clinical Oncology, 13, 209–218.PubMedGoogle Scholar
  13. 13.
    Amdur, R. J., Bennett, J., Olivier, K., et al. (2009). A prospective, phase II study demonstrating the potential value and limitation of radiosurgery for spine metastases. American Journal of Clinical Oncology, 32, 515–520.CrossRefGoogle Scholar
  14. 14.
    Rades, D., Dunst, J., & Schild, S. E. (2008). The first score predicting overall survival in patients with metastatic spinal cord compression. Cancer, 112, 157–161.PubMedCrossRefGoogle Scholar
  15. 15.
    van Houwelingen, H. C. (2000). Validation, calibration, revision and combination of prognostic survival models. Statistics in Medicine, 19, 3401–3415.PubMedCrossRefGoogle Scholar
  16. 16.
    Patchell, R. A., Tibbs, P. A., Regine, W. F., et al. (2005). Direct decompressive surgical resection in the treatment of spinal cord compression caused by metastatic cancer: a randomised trial. Lancet, 366, 643–648.PubMedCrossRefGoogle Scholar
  17. 17.
    Steyerberg, E. W., Mushkudiani, N., Perel, P., et al. (2008). Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Medicine, 5, e165. doi: 10.1371/journal.pmed.0050165-.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Ronald H. M. A. Bartels
    • 1
    Email author
  • Ton Feuth
    • 2
  • Dirk Rades
    • 3
  • Rune Hedlund
    • 4
  • Carlos Villas
    • 5
  • Yvette van der Linden
    • 6
  • Wolgang Börm
    • 7
  • Arnoud Kappelle
    • 8
  • Richard W. M. van der Maazen
    • 9
  • J. André Grotenhuis
    • 1
  • André L. M. Verbeek
    • 2
  1. 1.Department of NeurosurgeryRadboud University Nijmegen Medical CentreNijmegenThe Netherlands
  2. 2.Department of Epidemiology, Biostatistics, and Health Technology AssessmentRadboud University Nijmegen Medical CentreNijmegenThe Netherlands
  3. 3.Department of Radiation OncologyUniversity of LuebeckLuebeckGermany
  4. 4.Department of OrthopedicsSahlgrenska University HospitalGothenburgSweden
  5. 5.Department of Orthopaedic Surgery and TraumatologyUniversity of NavarraPamplonaSpain
  6. 6.Radiotherapeutic Institute FrieslandLeeuwardenThe Netherlands
  7. 7.Diakonissenanstalt, Neurosurgical CIinicFlensburgGermany
  8. 8.Department of NeurologyRadboud University Nijmegen Medical CentreNijmegenThe Netherlands
  9. 9.Department of Radiation OncologyRadboud University Nijmegen Medical CentreNijmegenThe Netherlands

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