title: An original approach was used to better evaluate the capacity of a prognostic marker using published survival curves.
abstract: OBJECTIVE
  Predicting chronic disease evolution from a prognostic marker is a key field of research in clinical epidemiology. However, the prognostic capacity of a marker is not systematically evaluated using the appropriate methodology. We proposed the use of simple equations to calculate time-dependent sensitivity and specificity based on published survival curves and other time-dependent indicators as predictive values, likelihood ratios, and posttest probability ratios to reappraise prognostic marker accuracy.
  
  
  METHODS
  The methodology is illustrated by back calculating time-dependent indicators from published articles presenting a marker as highly correlated with the time to event, concluding on the high prognostic capacity of the marker, and presenting the Kaplan-Meier survival curves. The tools necessary to run these direct and simple computations are available online at http://www.divat.fr/en/online-calculators/evalbiom.
  
  
  RESULTS
  Our examples illustrate that published conclusions about prognostic marker accuracy may be overoptimistic, thus giving potential for major mistakes in therapeutic decisions.
  
  
  CONCLUSIONS
  Our approach should help readers better evaluate clinical articles reporting on prognostic markers. Time-dependent sensitivity and specificity inform on the inherent prognostic capacity of a marker for a defined prognostic time. Time-dependent predictive values, likelihood ratios, and posttest probability ratios may additionally contribute to interpret the marker's prognostic capacity.
authors.affiliation: Department of Biostatistics, Pharmacoepidemiology and Subjective Measures in Health Sciences, EA 4275, Nantes University, 1 rue Gaston Veil, 44035 Nantes, France. Electronic address: Etienne.Dantan@univ-nantes.fr.
authors.forename: Etienne
authors.initials: E
authors.lastname: Dantan
authors.affiliation: CRC & Division of Clinical Epidemiology, Department of Health and Community Medicine, University of Geneva and University Hospitals of Geneva, rue Gabrielle Perret-Gentil 4, 1211 Geneva, Switzerland.
authors.forename: Christophe
authors.initials: C
authors.lastname: Combescure
authors.affiliation: Department of Biostatistics, Pharmacoepidemiology and Subjective Measures in Health Sciences, EA 4275, Nantes University, 1 rue Gaston Veil, 44035 Nantes, France.
authors.forename: Marine
authors.initials: M
authors.lastname: Lorent
authors.affiliation: TcLand Expression, 21 rue Lanoue Bras de Fer, 44200 Nantes, France.
authors.forename: Joanna
authors.initials: J
authors.lastname: Ashton-Chess
authors.affiliation: Institute of Transplantation, Urology and Nephrology (ITUN), CHU Nantes and INSERM U1064, 30 bd Jean-Monnet, 44093 Nantes, France.
authors.forename: Pascal
authors.initials: P
authors.lastname: Daguin
authors.affiliation: Department of Surgical Oncology, Institut de Cancérologie de l'Ouest-Cancer Center René Gauducheau, Boulevard Jacques Monod, 44805 Saint-Herblain, France.
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Classe
authors.affiliation: Institute of Transplantation, Urology and Nephrology (ITUN), CHU Nantes and INSERM U1064, 30 bd Jean-Monnet, 44093 Nantes, France; CIC Biotherapy, CHU Nantes, 30 bd Jean-Monnet, 44093 Nantes, France.
authors.forename: Magali
authors.initials: M
authors.lastname: Giral
authors.affiliation: Department of Biostatistics, Pharmacoepidemiology and Subjective Measures in Health Sciences, EA 4275, Nantes University, 1 rue Gaston Veil, 44035 Nantes, France.
authors.forename: Yohann
authors.initials: Y
authors.lastname: Foucher
mesh_terms: D015415:Biomarkers; D002908:Chronic Disease; D006801:Humans; D053208:Kaplan-Meier Estimate; D016013:Likelihood Functions; D011237:Predictive Value of Tests; D011379:Prognosis; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers
keywords: Likelihood ratios; Predictive values; Prognostic factor; Sensitivity; Specificity; Survival analysis