Literature DB >> 23585760

The destructive negative binomial cure rate model with a latent activation scheme.

Vicente G Cancho1, Dipankar Bandyopadhyay, Francisco Louzada, Bao Yiqi.   

Abstract

A new flexible cure rate survival model is developed where the initial number of competing causes of the event of interest (say lesions or altered cells) follow a compound negative binomial (NB) distribution. This model provides a realistic interpretation of the biological mechanism of the event of interest as it models a destructive process of the initial competing risk factors and records only the damaged portion of the original number of risk factors. Besides, it also accounts for the underlying mechanisms that leads to cure through various latent activation schemes. Our method of estimation exploits maximum likelihood (ML) tools. The methodology is illustrated on a real data set on malignant melanoma, and the finite sample behavior of parameter estimates are explored through simulation studies.

Entities:  

Keywords:  competing risks; cure rate models; long-term survival models; negative binomial distribution

Year:  2013        PMID: 23585760      PMCID: PMC3622276          DOI: 10.1016/j.stamet.2013.01.006

Source DB:  PubMed          Journal:  Stat Methodol        ISSN: 1572-3127


  4 in total

1.  Flexible Cure Rate Modeling Under Latent Activation Schemes.

Authors:  Freda Cooner; Sudipto Banerjee; Bradley P Carlin; Debajyoti Sinha
Journal:  J Am Stat Assoc       Date:  2007-06-01       Impact factor: 5.033

2.  Modelling geographically referenced survival data with a cure fraction.

Authors:  Freda Cooner; Sudipto Banerjee; A Marshall McBean
Journal:  Stat Methods Med Res       Date:  2006-08       Impact factor: 3.021

3.  A stochastic two-stage carcinogenesis model: a new approach to computing the probability of observing tumor in animal bioassays.

Authors:  G L Yang; C W Chen
Journal:  Math Biosci       Date:  1991-05       Impact factor: 2.144

4.  High- and low-dose interferon alfa-2b in high-risk melanoma: first analysis of intergroup trial E1690/S9111/C9190.

Authors:  J M Kirkwood; J G Ibrahim; V K Sondak; J Richards; L E Flaherty; M S Ernstoff; T J Smith; U Rao; M Steele; R H Blum
Journal:  J Clin Oncol       Date:  2000-06       Impact factor: 44.544

  4 in total
  1 in total

1.  The new Neyman type A generalized odd log-logistic-G-family with cure fraction.

Authors:  Valdemiro P Vigas; Edwin M M Ortega; Gauss M Cordeiro; Adriano K Suzuki; Giovana O Silva
Journal:  J Appl Stat       Date:  2021-05-03       Impact factor: 1.416

  1 in total

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