Improved survival modeling in cancer research using a reduced piecewise exponential approach.
Improved survival modeling in cancer research using a reduced piecewise exponential approach.
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DOI:
10.1002/sim.5915
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发表时间:
2014-01-15
影响因子:
2
通讯作者:
Kim, Jongphil
中科院分区:
文献类型:
--
作者:
Han, Gang;Schell, Michael J.;Kim, Jongphil
Statistical models for survival data are typically nonparametric, e.g., the Kaplan-Meier curve. Parametric survival modeling, such as exponential modeling, however, can reveal additional insights and be more efficient than nonparametric alternatives. A major constraint of the existing exponential models is the lack of flexibility due to distribution assumptions. A flexible and parsimonious piecewise exponential model is presented to best use the exponential models for arbitrary survival data. This model identifies shifts in the failure rate over time based on an exact likelihood ratio test, a backward elimination procedure, and an optional presumed order restriction on the hazard rate. Such modeling provides a descriptive tool in understanding the patient survival in addition to the Kaplan-Meier curve. This approach is compared with alternative survival models in simulation examples and illustrated in clinical studies.
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