Literature DB >> 12500058

On the expected number of cancer deaths during follow-up of an initially cancer-free cohort.

Peter Sasieni1.   

Abstract

A comparison of expected number of deaths with the observed is a widely used method with an extensive history. Epidemiologists often study the mortality rate from a particular cancer in an initially healthy population. Using cause-specific mortality rates from a reference population will overestimate the expected number of deaths because it does not take into account the fact that the study cohort is initially cancer free. It is more accurate to calculate the expected number of deaths by explicitly considering the probability of getting cancer in a given year and the probability of dying from it before the end of the follow-up.

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Year:  2003        PMID: 12500058     DOI: 10.1097/00001648-200301000-00026

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  4 in total

1.  Prevention of colorectal cancer by colonoscopic surveillance in individuals with a family history of colorectal cancer: 16 year, prospective, follow-up study.

Authors:  Isis Dove-Edwin; Peter Sasieni; Joanna Adams; Huw J W Thomas
Journal:  BMJ       Date:  2005-10-21

2.  The relative risk of second primary cancers in Austria's western states: a retrospective cohort study.

Authors:  Oliver Preyer; Nicole Concin; Andreas Obermair; Hans Concin; Hanno Ulmer; Willi Oberaigner
Journal:  BMC Cancer       Date:  2017-10-24       Impact factor: 4.430

Review 3.  Worldwide Review and Meta-Analysis of Cohort Studies Measuring the Effect of Mammography Screening Programmes on Incidence-Based Breast Cancer Mortality.

Authors:  Amanda Dibden; Judith Offman; Stephen W Duffy; Rhian Gabe
Journal:  Cancers (Basel)       Date:  2020-04-15       Impact factor: 6.639

4.  Increased cancer incidence risk in type 2 diabetes mellitus: results from a cohort study in Tyrol/Austria.

Authors:  Willi Oberaigner; Christoph Ebenbichler; Karin Oberaigner; Martin Juchum; Hans Robert Schönherr; Monika Lechleitner
Journal:  BMC Public Health       Date:  2014-10-10       Impact factor: 3.295

  4 in total

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