一类具有新的生物学解释的促进时间治愈率模型。

IF 1.2 3区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Yolanda M Gómez, Diego I Gallardo, Marcelo Bourguignon, Eduardo Bertolli, Vinicius F Calsavara
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引用次数: 0

摘要

在过去的几十年里,生存模型的挑战已经发生了很大的变化,全概率建模在许多医学应用中至关重要。基于对癌症转移的一种新的生物学解释,我们介绍了一种获得更灵活治愈率模型的一般方法。建议模型扩展了推广时间固成率模型。在此基础上,将几种已知的模型作为特例,并定义了许多新的特殊模型。我们推导了该模型的几个性质,并建立了与提升时间固化率模型的数学关系。我们考虑用频率方法进行推理,并采用极大似然方法估计模型参数。通过仿真研究对其性能进行了评价,并对所得结果进行了讨论。本文详细讨论了巴西圣保罗州诊断的黑色素瘤病例的基于人群的研究的真实数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A general class of promotion time cure rate models with a new biological interpretation.

A general class of promotion time cure rate models with a new biological interpretation.

Over the last decades, the challenges in survival models have been changing considerably and full probabilistic modeling is crucial in many medical applications. Motivated from a new biological interpretation of cancer metastasis, we introduce a general method for obtaining more flexible cure rate models. The proposal model extended the promotion time cure rate model. Furthermore, it includes several well-known models as special cases and defines many new special models. We derive several properties of the hazard function for the proposed model and establish mathematical relationships with the promotion time cure rate model. We consider a frequentist approach to perform inferences, and the maximum likelihood method is employed to estimate the model parameters. Simulation studies are conducted to evaluate its performance with a discussion of the obtained results. A real dataset from population-based study of incident cases of melanoma diagnosed in the state of São Paulo, Brazil, is discussed in detail.

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来源期刊
Lifetime Data Analysis
Lifetime Data Analysis 数学-数学跨学科应用
CiteScore
2.30
自引率
7.70%
发文量
43
审稿时长
3 months
期刊介绍: The objective of Lifetime Data Analysis is to advance and promote statistical science in the various applied fields that deal with lifetime data, including: Actuarial Science – Economics – Engineering Sciences – Environmental Sciences – Management Science – Medicine – Operations Research – Public Health – Social and Behavioral Sciences.
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