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| 竞争风险生存分析× | Fine-Gray 竞争风险模型× | |
|---|---|---|
| 领域≠ | 生存分析 | 统计学 |
| 方法族≠ | Survival analysis | Hypothesis test |
| 起源年份 | 1999 | 1999 |
| 提出者≠ | Fine, J.P. & Gray, R.J. | Jason P. Fine & Robert J. Gray |
| 类型≠ | Competing risks survival model | Subdistribution hazard regression |
| 开创性文献 | Fine, J.P. & Gray, R.J. (1999). A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association, 94(446), 496–509. DOI ↗ | Fine, J.P. & Gray, R.J. (1999). A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association, 94(446), 496–509. DOI ↗ |
| 别名 | Rekabet Eden Riskler Analizi, cumulative incidence function, CIF analysis, cause-specific survival analysis | competing risks regression, subdistribution hazard model, Fine-Gray model, Fine-Gray Competing Risks Modeli |
| 相关 | 5 | 5 |
| 摘要≠ | Competing risks analysis, formalized by Fine and Gray in 1999, is a survival analysis framework for settings where a subject can experience one of several mutually exclusive event types. The key quantity is the cumulative incidence function (CIF), which estimates the probability of a specific event occurring by time t in the presence of the other competing events. | The Fine-Gray model is a semiparametric regression method for survival data in which two or more mutually exclusive event types compete to occur first. Proposed by Fine and Gray in 1999, it models the subdistribution hazard of each event type directly, allowing covariates to be linked to the cumulative incidence function (CIF) — the quantity that actually answers 'what is the probability of experiencing event type k by time t?'. It corrects the well-known shortcoming of standard Cox regression, which ignores competing events and thereby overestimates cause-specific probabilities. |
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