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

Yolanda M. Gómez, Diego I. Gallardo, Marcelo Bourguignon (), Eduardo Bertolli and Vinicius F. Calsavara
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Yolanda M. Gómez: Universidad de Atacama
Diego I. Gallardo: Universidad de Atacama
Marcelo Bourguignon: Universidade Federal do Rio Grande do Norte
Eduardo Bertolli: A.C.Camargo Cancer Center
Vinicius F. Calsavara: Cedars-Sinai Medical Center

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2023, vol. 29, issue 1, No 3, 66-86

Abstract: Abstract 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.

Keywords: Compound Poisson distributions; Concurrent causes; Cure rate models; Promotion time cure model; Weibull distribution (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10985-022-09575-3

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