Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Ретроспективный анализ выживаемости× | Ретроспективное когортное исследование× | |
|---|---|---|
| Область | Эпидемиология | Эпидемиология |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1970s–1980s (retrospective variant established) | Mid-20th century (widely formalized 1950s–1970s) |
| Автор метода≠ | Kaplan & Meier (foundational estimator, 1958); Cox (regression model, 1972); retrospective application is a design variant documented since the 1970s | Systematic use attributed to early 20th-century occupational epidemiology; formalized in modern epidemiological theory by Brian MacMahon and others |
| Тип≠ | Retrospective observational analytical study | Observational analytic study |
| Основополагающий источник≠ | Collett, D. (2015). Modelling Survival Data in Medical Research (3rd ed.). CRC Press. ISBN: 978-1439856789 | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Другие названия | historical survival study, retrospective time-to-event analysis, retrospective follow-up survival study, archival survival analysis | historical cohort study, non-concurrent cohort study, retrospective follow-up study, historical prospective study |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Retrospective survival analysis applies time-to-event statistical methods — most commonly the Kaplan-Meier estimator and Cox proportional hazards regression — to data collected from past records rather than through prospective follow-up. The researcher looks back at medical records, disease registries, or administrative databases to reconstruct each patient's journey from a defined starting point (e.g., diagnosis or surgery) to an outcome of interest (e.g., death, relapse, or hospital readmission), making it a cost-efficient approach for studying prognosis and risk factors when prospective follow-up is not feasible. | A retrospective cohort study assembles a group of individuals who share a common starting point and reconstructs their exposure history and subsequent outcomes entirely from pre-existing records. Because the data have already been collected before the study begins, the design is far faster and cheaper than a prospective cohort; however, the researcher must work with whatever information was recorded at the time rather than collecting purpose-built measurements. |
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