title: Survival analysis in hematologic malignancies: recommendations for clinicians.
abstract: The widespread availability of statistical packages has undoubtedly helped hematologists worldwide in the analysis of their data, but has also led to the inappropriate use of statistical methods. In this article, we review some basic concepts of survival analysis and also make recommendations about how and when to perform each particular test using SPSS, Stata and R. In particular, we describe a simple way of defining cut-off points for continuous variables and the appropriate and inappropriate uses of the Kaplan-Meier method and Cox proportional hazard regression models. We also provide practical advice on how to check the proportional hazards assumption and briefly review the role of relative survival and multiple imputation.
authors.affiliation: Department of Hematology, Hospital Clínic, IDIBAPS, Barcelona jdelgado@clinic.ub.es.
authors.forename: Julio
authors.initials: J
authors.lastname: Delgado
authors.affiliation: Hematopathology Unit, Hospital Clínic, IDIBAPS, Barcelona.
authors.forename: Arturo
authors.initials: A
authors.lastname: Pereira
authors.affiliation: Deparment of Hemostasis and Hemotherapy, Hospital Clínic, IDIBAPS, Barcelona.
authors.forename: Neus
authors.initials: N
authors.lastname: Villamor
authors.affiliation: Department of Hematology, Hospital Clínic, IDIBAPS, Barcelona.
authors.forename: Armando
authors.initials: A
authors.lastname: López-Guillermo
authors.affiliation: Josep Carreras Leukemia Research Institute, Hospital Clínic, Barcelona, Spain.
authors.forename: Ciril
authors.initials: C
authors.lastname: Rozman
mesh_terms: D000368:Aged; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000401:mortality* / Q000473:pathology; D008297:Male; D017410:Practice Guidelines as Topic; D016016:Proportional Hazards Models; D012372:ROC Curve; D012984:Software