In this narrative review we present the natural evolution of predictive models to their presentation in the nomogram format.
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We show their clinical usefulness and the objective parameters that contribute to their clinical use: calibration, discrimination, decision curves and probability density functions. We continue detailing the various existing predictive models/nomograms in relation to prostate cancer aggressiveness before and after biopsy, before and after primary treatment, recurrence and castration resistance. Finally we include future markers in advanced stage of implementation in the context of nomograms and related to the aggressiveness of prostate cancer: PCA3, PHI coefficient, 4Kscore, cell cycle progression (Prolaris®) and single nucleotid polymorphisms.
Borque Á, Esteban LM, Sanz G, Rubio-Briones J, Gil Sanz MJ. Are you the author?
Servicio de Urología, Hospital Universitario Miguel Servet, Zaragoza, España; Escuela Universitaria Politécnica Superior, Universidad de Zaragoza, Zaragoza, España; Departamento de Métodos Estadísticos, Facultad de Ciencias, Universidad de Zaragoza, Zaragoza, España; Servicio de Urología, Instituto Valenciano de Oncología, Valencia, España.
Reference: Arch Esp Urol. 2015 Apr;68(3):267-81.
Article in Spanish.