Literature DB >> 10482487

Analyzing incidence of testis cancer by means of a frailty model.

O O Aalen1, S Tretli.   

Abstract

There are two striking epidemiological features of testicular cancer. First, the incidence has increased strongly over the past few decades. Secondly, the incidence is greatest among younger men, and then declines from a certain age. We have constructed a statistical model to fit these observations. The idea of the model is that a subgroup of men is particularly susceptible to testicular cancer. In statistical terminology this is called a frailty model, since it focuses on varying frailty of the individuals. The frailty, or susceptibility, is considered as being established by birth, and due to a mixture of genetic and environmental effects. The strong increase in incidence over calendar time points to strong environmental effects, which are thought to operate in fetal life, causing damage to the fetus. Based on data from the Norwegian Cancer Registry we fit a frailty model to incidence data collected during 1953-93. The model gives a good fit and we discuss the interpretations of our findings.

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Year:  1999        PMID: 10482487     DOI: 10.1023/a:1008916718152

Source DB:  PubMed          Journal:  Cancer Causes Control        ISSN: 0957-5243            Impact factor:   2.506


  17 in total

1.  Prostate-specific antigen testing for prostate cancer: Depleting a limited pool of susceptible individuals?

Authors:  Morten Valberg; Tom Grotmol; Steinar Tretli; Marit B Veierød; Tron A Moger; Susan S Devesa; Odd O Aalen
Journal:  Eur J Epidemiol       Date:  2016-07-18       Impact factor: 8.082

2.  A distribution for multivariate frailty based on the compound Poisson distribution with random scale.

Authors:  Tron Anders Moger; Odd O Aalen
Journal:  Lifetime Data Anal       Date:  2005-03       Impact factor: 1.588

Review 3.  Conditions in utero and cancer risk.

Authors:  Tom Grotmol; Elisabete Weiderpass; Steinar Tretli
Journal:  Eur J Epidemiol       Date:  2006-09-13       Impact factor: 8.082

4.  Frailty modelling of colorectal cancer incidence in Norway: indications that individual heterogeneity in risk is related to birth cohort.

Authors:  Elisabeth Svensson; Tron A Moger; Steinar Tretli; Odd O Aalen; Tom Grotmol
Journal:  Eur J Epidemiol       Date:  2006-09-20       Impact factor: 8.082

5.  Etiology of testicular germ cell tumors: lumping or splitting? A plea against lumping.

Authors:  Andreas Stang
Journal:  Eur J Epidemiol       Date:  2008-12-25       Impact factor: 8.082

6.  Special issue dedicated to Odd O. Aalen.

Authors:  Ørnulf Borgan; Håkon K Gjessing
Journal:  Lifetime Data Anal       Date:  2019-08-28       Impact factor: 1.588

7.  Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model.

Authors:  Rebecca Yates Coley; Elizabeth R Brown
Journal:  Stat Med       Date:  2016-02-11       Impact factor: 2.373

8.  A Frailty-Model-Based Method for Estimating Age-Dependent Penetrance from Family Data.

Authors:  Yun-Hee Choi
Journal:  J Biom Biostat       Date:  2012-02-15

9.  Frailty modeling of age-incidence curves of osteosarcoma and Ewing sarcoma among individuals younger than 40 years.

Authors:  Morten Valberg; Tom Grotmol; Steinar Tretli; Marit B Veierød; Susan S Devesa; Odd O Aalen
Journal:  Stat Med       Date:  2012-06-29       Impact factor: 2.373

10.  Significant calendar period deviations in testicular germ cell tumors indicate that postnatal exposures are etiologically relevant.

Authors:  Crystal Speaks; Katherine A McGlynn; Michael B Cook
Journal:  Cancer Causes Control       Date:  2012-07-28       Impact factor: 2.506

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