title: [Kaplan-Meier analysis in urological practice].
abstract: Kaplan-Meier curves and estimates of survival are the most common way to present survival data in medicine, especially for cohorts with different lengths of follow-up. Moreover, Kaplan-Meier curves present a frequently used general graphic approach to display time-to-event outcomes. A solid understanding of how Kaplan-Meier curves are generated and how they should be analyzed and interpreted is of great importance to appraise urological literature in daily clinical practice. This article describes the basic principles of Kaplan-Meier analysis, possible variants and pitfalls. Improved knowledge of Kaplan-Meier analysis can help to improve Evidence-based urology and its application in patient care.
authors.affiliation: Klinik und Poliklinik für Urologie, Universitätsklinikum Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Deutschland. mrink@uke.uni-hamburg.de
authors.forename: M
authors.initials: M
authors.lastname: Rink
authors.forename: L A
authors.initials: LA
authors.lastname: Kluth
authors.forename: S F
authors.initials: SF
authors.lastname: Shariat
authors.forename: M
authors.initials: M
authors.lastname: Fisch
authors.forename: R
authors.initials: R
authors.lastname: Dahlem
authors.forename: P
authors.initials: P
authors.lastname: Dahm
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D015577:Geriatric Assessment / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D018570:Risk Assessment / Q000379:methods* / Q000706:statistics & numerical data*; D014571:Urologic Neoplasms / Q000401:mortality*; D014572:Urology / Q000379:methods*