Literature DB >> 21549589

Choosing the relative survival method for cancer survival estimation.

Timo Hakulinen1, Karri Seppä, Paul C Lambert.   

Abstract

BACKGROUND: The methods on how to calculate cumulative relative survival have been ambiguous and have given differences in empirical results.
METHODS: The gold standard for the cumulative relative survival ratio is the weighted average of age-specific cumulative relative survival ratios, with weights proportional to numbers of patients at diagnosis. Mathematics and representative empirical materials from the population-based Finnish Cancer Registry were studied for the different relative survival methods and compared with the gold standard.
RESULTS: The theoretical and empirical results show a good agreement between the method suggested in 1959 by Ederer and Heise (the so-called Ederer II method) and the gold standard. This result is in part due the fact that as follow-up time increases the conditional (annual) relative survival ratios become increasingly more independent of age. Moreover, the dependence between the excess mortality due to cancer and the baseline general mortality does not introduce an important enough selection in practice to cause a notable bias.
CONCLUSION: The use of the method by Ederer and Heise, multiplication of the annual relative survival ratios, instead of direct standardisation, should be considered in future applications. This would be particularly important for the long-term follow-up when age-specific relative survival is not available in the oldest age categories.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21549589     DOI: 10.1016/j.ejca.2011.03.011

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   9.162


  38 in total

1.  Relative survival of patients with supratentorial low-grade gliomas.

Authors:  Nicolas R Smoll; Oliver P Gautschi; Bawarjan Schatlo; Karl Schaller; Damien C Weber
Journal:  Neuro Oncol       Date:  2012-07-06       Impact factor: 12.300

2.  Excess mortality attributable to chronic kidney disease. Results from the PIRP project.

Authors:  Dino Gibertoni; Marcora Mandreoli; Paola Rucci; Maria Pia Fantini; Angelo Rigotti; Roberto Scarpioni; Antonio Santoro
Journal:  J Nephrol       Date:  2015-10-26       Impact factor: 3.902

3.  Socioeconomic inequalities in relative survival of rectal cancer most obvious in stage III.

Authors:  L I Olsson; F Granstrom
Journal:  World J Surg       Date:  2014-12       Impact factor: 3.352

4.  Five-year relative survival in sleep apnea patients with a subsequent cancer diagnosis.

Authors:  Arthur Sillah; Faiza Faria; Nathaniel F Watson; David Gozal; Amanda I Phipps
Journal:  J Clin Sleep Med       Date:  2020-02-06       Impact factor: 4.062

5.  Survival trends in chronic lymphocytic leukemia across treatment eras: US SEER database analysis (1985-2017).

Authors:  Neda Alrawashdh; Joann Sweasy; Brian Erstad; Ali McBride; Daniel O Persky; Ivo Abraham
Journal:  Ann Hematol       Date:  2021-07-19       Impact factor: 3.673

6.  Treatment and Survival of Patients with Colon Cancer Aged 80 Years and Older: A EURECCA International Comparison.

Authors:  Nina C A Vermeer; Yvette H M Claassen; Marloes G M Derks; Lene H Iversen; Elizabeth van Eycken; Marianne G Guren; Pawel Mroczkowski; Anna Martling; Robert Johansson; Tamara Vandendael; Arne Wibe; Bjorn Moller; Hans Lippert; Johanneke E A Portielje; Gerrit Jan Liefers; Koen C M J Peeters; Cornelis J H van de Velde; Esther Bastiaannet
Journal:  Oncologist       Date:  2018-03-22

7.  The clinical prognostic value of molecular intrinsic tumor subtypes in older breast cancer patients: A FOCUS study analysis.

Authors:  Charla C Engels; Mandy Kiderlen; Esther Bastiaannet; Antien L Mooyaart; Ronald van Vlierberghe; Vincent T H B M Smit; Peter J K Kuppen; Cornelis J H van de Velde; G J Liefers
Journal:  Mol Oncol       Date:  2015-11-24       Impact factor: 6.603

8.  Outcome of older patients with acute myeloid leukemia: an analysis of SEER data over 3 decades.

Authors:  Mya S Thein; William B Ershler; Ahmedin Jemal; Jerome W Yates; Maria R Baer
Journal:  Cancer       Date:  2013-04-30       Impact factor: 6.860

9.  Avoidable deaths and random variation in patients' survival.

Authors:  K Seppä; T Hakulinen; E Läärä
Journal:  Br J Cancer       Date:  2012-04-24       Impact factor: 7.640

10.  Conditional survival of cancer patients: an Australian perspective.

Authors:  Xue Qin Yu; Peter D Baade; Dianne L O'Connell
Journal:  BMC Cancer       Date:  2012-10-08       Impact factor: 4.430

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