Literature DB >> 31128623

Spatially-explicit survival modeling with discrete grouping of cancer predictors.

Georgiana Onicescu1, Andrew B Lawson2, Jiajia Zhang3, Mulugeta Gebregziabher2, Kristin Wallace2, Jan M Eberth3.   

Abstract

In this paper, the spatially explicit survival model is extended by allowing the relation with the explanatory covariates to be spatially adaptive using a threshold conditional autoregressive (CAR) model, further extended to allow the inclusion of multiple threshold levels. The model is applied to prostate cancer survival based on Louisiana SEER registry, which holds individual records linked to vital outcomes and is geocoded at the parish level.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bayesian; Latent; Prostate cancer; Spatial

Mesh：

Year:  2018        PMID： 31128623      PMCID： PMC6541023          DOI： 10.1016/j.sste.2018.06.001

Source DB:  PubMed          Journal:  Spat Spatiotemporal Epidemiol        ISSN： 1877-5845


  11 in total

1.  Frailty modeling for spatially correlated survival data, with application to infant mortality in Minnesota.

Authors:  Sudipto Banerjee; Melanie M Wall; Bradley P Carlin
Journal:  Biostatistics       Date:  2003-01       Impact factor: 5.899

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Authors:  Sudipto Banerjee; Dipak K Dey
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3.  Prior choice in discrete latent modeling of spatially referenced cancer survival.

Authors:  Andrew B Lawson; Jungsoon Choi; Jiajia Zhang
Journal:  Stat Methods Med Res       Date:  2012-05-02       Impact factor: 3.021

4.  Geographical epidemiology of prostate cancer in Great Britain.

Authors:  Lars Jarup; Nicky Best; Mireille B Toledano; Jon Wakefield; Paul Elliott
Journal:  Int J Cancer       Date:  2002-02-10       Impact factor: 7.396

5.  A spatial statistical model for landscape genetics.

Authors:  Gilles Guillot; Arnaud Estoup; Frédéric Mortier; Jean François Cosson
Journal:  Genetics       Date:  2004-11-01       Impact factor: 4.562

6.  Spatially explicit survival modeling for small area cancer data.

Authors:  G Onicescu; A Lawson; J Zhang; Mulugeta Gebregziabher; Kristin Wallace; J M Eberth
Journal:  J Appl Stat       Date:  2017-02-11       Impact factor: 1.404

7.  Bayesian Parametric Accelerated Failure Time Spatial Model and its Application to Prostate Cancer.

Authors:  Jiajia Zhang; Andrew B Lawson
Journal:  J Appl Stat       Date:  2011-03       Impact factor: 1.404

8.  Parametric models for spatially correlated survival data for individuals with multiple cancers.

Authors:  Ulysses Diva; Dipak K Dey; Sudipto Banerjee
Journal:  Stat Med       Date:  2008-05-30       Impact factor: 2.373

9.  On the inference of spatial structure from population genetics data.

Authors:  Gilles Guillot
Journal:  Bioinformatics       Date:  2009-07-15       Impact factor: 6.937

10.  Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model.

Authors:  Georgiana Onicescu; Andrew Lawson; Jiajia Zhang; Mulugeta Gebregziabher; Kristin Wallace; Jan M Eberth
Journal:  Stat Methods Med Res       Date:  2015-07-28       Impact factor: 3.021
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