Methoden vergleichen
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| Prospektive Überlebenszeitanalyse× | Prospektive Kohortenstudie× | |
|---|---|---|
| Fachgebiet | Epidemiologie | Epidemiologie |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1958–1972 (foundational methods); prospective design emphasis formalized by 1980s | 1950s (systematic application); conceptual roots earlier |
| Urheber≠ | Kaplan & Meier (estimator, 1958); Cox (proportional hazards model, 1972); prospective design formalised in modern clinical epidemiology | Richard Doll and Austin Bradford Hill (landmark application, 1951-1954); cohort methodology formalised by modern epidemiology textbooks |
| Typ≠ | Longitudinal observational or experimental study design with time-to-event analysis | Observational longitudinal study design |
| Wegweisende Quelle≠ | Kleinbaum, D. G., & Klein, M. (2012). Survival Analysis: A Self-Learning Text (3rd ed.). Springer. ISBN: 978-1441966452 | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Aliasnamen | prospective time-to-event analysis, prospective failure-time analysis, forward-looking survival study, prospective event-time study | longitudinal cohort study, prospective follow-up study, incidence study, prospective observational cohort |
| Verwandt≠ | 5 | 6 |
| Zusammenfassung≠ | Prospective survival analysis is a longitudinal study design in which participants are enrolled before the event of interest occurs, followed forward in time under standardised conditions, and analysed using survival-analytic methods to estimate the time until a defined clinical endpoint — such as death, disease recurrence, or treatment failure. Because data are collected prospectively, exposure and covariate information are recorded before outcomes are known, substantially reducing recall and selection bias relative to retrospective approaches. | A prospective cohort study assembles a group of participants who are free of the outcome of interest at baseline, measures their exposures, and then follows them forward in time to record who develops the outcome. By collecting exposure data before outcomes occur, it establishes a clear temporal sequence that supports causal inference — a major advantage over retrospective designs. It is the cornerstone observational method in epidemiology and clinical research. |
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