Literature DB >> 3629047

Models for temporal variation in cancer rates. I: Age-period and age-cohort models.

D Clayton, E Schifflers.   

Abstract

A main concern of descriptive epidemiologists is the presentation and interpretation of temporal variations in cancer rates. In its simplest form, this problem is that of the analysis of a set of rates arranged in a two-way table by age group and calendar period. We review the modern approach to the analysis of such data which justifies traditional methods of age standardization in terms of the multiplicative risk model. We discuss the use of this model when the temporal variations are due to purely secular (period) influences and when they are attributable to generational (cohort) influences. Finally we demonstrate the serious difficulties which attend the interpretation of regular trends. The methods described are illustrated by examples for incidence rates of bladder cancer in Birmingham, U.K., mortality from bladder cancer in Italy, and mortality from lung cancer in Belgium.

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Year:  1987        PMID: 3629047     DOI: 10.1002/sim.4780060405

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  181 in total

1.  Time trends in incidence of cervical cancer in Lithuania from 1983 to 1997.

Authors:  R Didziapetris; M Stukonis; J Kurtinaitis
Journal:  Eur J Epidemiol       Date:  1999-11       Impact factor: 8.082

2.  Age-incidence relationships and time trends in cervical cancer in Sweden.

Authors:  K Hemminki; X Li; P Mutanen
Journal:  Eur J Epidemiol       Date:  2001       Impact factor: 8.082

3.  Declining rates of hepatocellular carcinoma in urban Shanghai: incidence trends in 1976-2005.

Authors:  Shan Gao; Wan-Shui Yang; Freddie Bray; Puthiery Va; Wei Zhang; Jing Gao; Yong-Bing Xiang
Journal:  Eur J Epidemiol       Date:  2011-12-10       Impact factor: 8.082

4.  Increasing incidence of thyroid cancer in Great Britain, 1976-2005: age-period-cohort analysis.

Authors:  Richard J Q McNally; Karen Blakey; Peter W James; Basilio Gomez Pozo; Nermine O Basta; Juliet Hale
Journal:  Eur J Epidemiol       Date:  2012-07-04       Impact factor: 8.082

5.  Modelling BSE trend over time in Europe, a risk assessment perspective.

Authors:  Christian Ducrot; Carole Sala; Giuseppe Ru; Aline de Koeijer; Hazel Sheridan; Claude Saegerman; Thomas Selhorst; Mark Arnold; Miroslaw P Polak; Didier Calavas
Journal:  Eur J Epidemiol       Date:  2010-04-13       Impact factor: 8.082

6.  The influence of birth cohort and calendar period on global trends in ovarian cancer incidence.

Authors:  Citadel J Cabasag; Melina Arnold; John Butler; Manami Inoue; Britton Trabert; Penelope M Webb; Freddie Bray; Isabelle Soerjomataram
Journal:  Int J Cancer       Date:  2019-04-30       Impact factor: 7.396

7.  Secular trends in proximal femoral fracture, Oxford record linkage study area and England 1968-86.

Authors:  J G Evans; V Seagroatt; M J Goldacre
Journal:  J Epidemiol Community Health       Date:  1997-08       Impact factor: 3.710

8.  Common Model Inputs Used in CISNET Collaborative Breast Cancer Modeling.

Authors:  Jeanne S Mandelblatt; Aimee M Near; Diana L Miglioretti; Diego Munoz; Brian L Sprague; Amy Trentham-Dietz; Ronald Gangnon; Allison W Kurian; Harald Weedon-Fekjaer; Kathleen A Cronin; Sylvia K Plevritis
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

9.  Effects of screening on cervical cancer incidence and mortality in New South Wales implied by influences of period of diagnosis and birth cohort.

Authors:  R J Taylor; S L Morrell; H A Mamoon; G V Wain
Journal:  J Epidemiol Community Health       Date:  2001-11       Impact factor: 3.710

10.  Colorectal cancer in Denmark 1943-1988.

Authors:  C Johansen; A Mellemgaard; T Skov; J Kjaergaard; E Lynge
Journal:  Int J Colorectal Dis       Date:  1993-03       Impact factor: 2.571

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