Statistics of Survival Prediction and Nomogram Development

  • Vincenzo Valentini
  • Andrea Damiani
  • Andre Dekker
  • Nicola Dinapoli
Part of the Medical Radiology book series (MEDRAD)


Survival statistics are fundamental in outcome evaluation of clinical studies for modern cancer science. The use of survival statistics allows to compare results and to predict the effect of therapies, by using different statistical approaches that can be also combined together. Definition of survival statistics can be performed mainly in three different ways (Non-parametric-Kaplan-Meier, Parametric and Semi-parametric), each one having its own computational methods and being implemented in different ways. Modern cancer publications strengthen the value of diagnostic tools that can be used for predicting outcome of newly diagnosed patients. The nomograms are examples of these tools: they are usually drawn to facilitate physicians in manually solving complex equations required to calculate outcomes predicted by using Cox’s proportional hazards models. The use of models to predict the outcome must follow adequate procedures for reliability evaluation and testing, in order to prevent the erroneous application on unsuitable patient populations.


Overall Survival Hazard Rate Receiver Operate Characteristic Curve Survival Statistic Receiver Operate Characteristic Curve Analysis 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Vincenzo Valentini
    • 1
  • Andrea Damiani
    • 2
  • Andre Dekker
    • 3
  • Nicola Dinapoli
    • 1
  1. 1.Department of RadiotherapyPol. A. Gemelli, Catholic University of Sacred HeartRomeItaly
  2. 2.External consultantCatholic University of Sacred HeartRomeItaly
  3. 3.Department of Radiation Oncology (MAASTRO), GROW–School for Oncology and Developmental BiologyMaastricht University Medical Center (MUMC+)MaastrichtThe Netherlands

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