方法对比
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| 实用生存分析× | Cox比例风险模型× | |
|---|---|---|
| 领域 | 流行病学 | 流行病学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | Conceptual framework: 1967; widespread application: 1990s–2000s | 1972 |
| 提出者≠ | Schwartz & Lellouch (explanatory vs. pragmatic distinction, 1967); extended in survival analysis literature from the 1970s onward | Sir David Roxbee Cox |
| 类型≠ | Observational / experimental hybrid — time-to-event analysis in real-world or pragmatic-trial settings | Semi-parametric regression model |
| 开创性文献≠ | Ford, I., & Norrie, J. (2016). Pragmatic Trials. New England Journal of Medicine, 375(5), 454–463. DOI ↗ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗ |
| 别名 | real-world survival analysis, pragmatic time-to-event analysis, effectiveness survival analysis, PSA | Cox regression, Cox PH model, proportional hazards model, CPH |
| 相关 | 5 | 5 |
| 摘要≠ | Pragmatic survival analysis applies time-to-event statistical methods within pragmatic or real-world settings, estimating how long patients survive, remain event-free, or retain treatment benefit under conditions of routine clinical practice. Unlike explanatory survival analyses conducted under tightly controlled trial conditions, the pragmatic variant embraces the heterogeneity, treatment switching, non-adherence, and competing events that characterise real-world patient populations, prioritising external validity over internal precision. | The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research. |
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