title: [Analysis of Survival Time and Other Event Times - What Does the Surgeon Need to Know?].
abstract: BACKGROUND
  Survival time is an important parameter to investigate therapeutic measures. It plays a crucial role in study concepts, data analyses as well as publications.
  
  
  OBJECTIVE
  The aim of this study was to emphasise essential points, which need to be taken into account to (i) gain resilient results of survival time analysis and (ii) appropriately evaluate scientific reports. Corner Points/Main Statements: (i) The main analytical methods are Kaplan-Meier procedure to estimate survival time curves, the log rank test to compare two or more survival curves from independent samples and Cox regression for comparisons under simultaneous consideration of several influencing factors. (ii) Dependent relationships between survival and censoring probabilities may falsify these statistical procedures. (iii) For several end points, which need to be differentiated (such as death, progression etc.), and for interdependent sample elements, extended statistical procedures such as competing risk analyses or extended Cox regression models are available.
  
  
  CONCLUSIONS
  Survival time analysis can be considered as being extraordinarily important for evaluation of data obtained in therapeutic studies. For the academic and publishing physician, in particular, for the clinical surgeon, a basic understanding of these methodological aspects in statistics is indispensable.
authors.affiliation: Institut für Biometrie und Medizinische Informatik, Medizinische Fakultät der Otto-von-Guericke-Universität Magdeburg, Deutschland.
authors.forename: S
authors.initials: S
authors.lastname: Kropf
authors.affiliation: Klinik für Allgemein-, Viszeral- & Gefäßchirurgie, Universitätsklinikum Magdeburg A. ö. R., Deutschland.
authors.forename: F
authors.initials: F
authors.lastname: Meyer
authors.affiliation: Institut für Biometrie und Medizinische Informatik, Medizinische Fakultät der Otto-von-Guericke-Universität Magdeburg, Deutschland.
authors.forename: E
authors.initials: E
authors.lastname: Glimm
mesh_terms: D018450:Disease Progression; D006801:Humans; D053208:Kaplan-Meier Estimate; D016016:Proportional Hazards Models; D011643:Publishing / Q000706:statistics & numerical data; D012307:Risk Factors; D013514:Surgical Procedures, Operative / Q000401:mortality*; D016019:Survival Analysis