Literature DB >> 2349404

Relative survival and the estimation of net survival: elements for further discussion.

J Estève1, E Benhamou, M Croasdale, L Raymond.   

Abstract

The methods of calculation of survival corrected for independent cause of death are discussed, and a maximum likelihood method is proposed and illustrated by survival of colon cancer patients in Geneva. The methods which are at present favoured for doing such calculations are subject to various biases when estimating net survival if the populations are heterogeneous for life expectancy. The proposed maximum likelihood approach would eliminate these biases by enabling relevant adjustment for covariates which influence survival. The routine use of such methods would permit better comparison of survival within and between populations.

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Year:  1990        PMID: 2349404     DOI: 10.1002/sim.4780090506

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


  83 in total

1.  Estimating potential savings in cancer deaths by eliminating regional and social class variation in cancer survival in the Nordic countries.

Authors:  P W Dickman; R W Gibberd; T Hakulinen
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2.  Differences in Cancer Survival with Relative versus Cause-Specific Approaches: An Update Using More Accurate Life Tables.

Authors:  Gonçalo Forjaz de Lacerda; Nadia Howlader; Angela B Mariotto
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-06-20       Impact factor: 4.254

3.  Estimation and projections of stomach cancer trends in Italy.

Authors:  R Capocaccia; R De Angelis; L Frova; M Sant; E Buiatti; G Gatta; A Micheli; F Berrino; A Barchielli; E Conti
Journal:  Cancer Causes Control       Date:  1995-07       Impact factor: 2.506

4.  Socioeconomic inequalities in cancer survival in England after the NHS cancer plan.

Authors:  B Rachet; L Ellis; C Maringe; T Chu; U Nur; M Quaresma; A Shah; S Walters; L Woods; D Forman; M P Coleman
Journal:  Br J Cancer       Date:  2010-06-29       Impact factor: 7.640

5.  How many deaths have been avoided through improvements in cancer survival?

Authors:  M A Richards; D Stockton; P Babb; M P Coleman
Journal:  BMJ       Date:  2000-04-01

6.  Breast cancer survival in South Asian women in England and Wales.

Authors:  Sabya Farooq; Michel P Coleman
Journal:  J Epidemiol Community Health       Date:  2005-05       Impact factor: 3.710

7.  A class of transformation covariate regression models for estimating the excess hazard in relative survival analysis.

Authors:  Binbing Yu
Journal:  Am J Epidemiol       Date:  2013-03-13       Impact factor: 4.897

8.  Incidence and survival time trends for Spanish children and adolescents with leukaemia from 1983 to 2007.

Authors:  R Marcos-Gragera; J Galceran; C Martos; A L de Munain; M Vicente-Raneda; C Navarro; J R Quirós-Garcia; M-J Sánchez; E Ardanaz; M Ramos; A Mateos; D Salmerón; S Felipe; R Peris-Bonet
Journal:  Clin Transl Oncol       Date:  2016-07-22       Impact factor: 3.405

9.  No socioeconomic inequalities in colorectal cancer survival within a randomised clinical trial.

Authors:  U Nur; B Rachet; M K B Parmar; M R Sydes; N Cooper; C Lepage; J M A Northover; R James; M P Coleman
Journal:  Br J Cancer       Date:  2008-10-28       Impact factor: 7.640

10.  What if cancer survival in Britain were the same as in Europe: how many deaths are avoidable?

Authors:  M Abdel-Rahman; D Stockton; B Rachet; T Hakulinen; M P Coleman
Journal:  Br J Cancer       Date:  2009-12-03       Impact factor: 7.640

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