Literature DB >> 22961565

Cancer net survival on registry data: use of the new unbiased Pohar-Perme estimator and magnitude of the bias with the classical methods.

Laurent Roche1, Coraline Danieli, Aurélien Belot, Pascale Grosclaude, Anne-Marie Bouvier, Michel Velten, Jean Iwaz, Laurent Remontet, Nadine Bossard.   

Abstract

Net survival, the survival which might occur if cancer was the only cause of death, is a major epidemiological indicator required for international or temporal comparisons. Recent findings have shown that all classical methods used for routine estimation of net survival from cancer-registry data, sometimes called "relative-survival methods," provide biased estimates. Meanwhile, an unbiased estimator, the Pohar-Perme estimator (PPE), was recently proposed. Using real data, we investigated the magnitude of the errors made by four "relative-survival" methods (Ederer I, Hakulinen, Ederer II and a univariable regression model) vs. PPE as reference and examined the influence of time of follow-up, cancer prognosis, and age on the errors made. The data concerned seven cancer sites (2,51,316 cases) collected by FRANCIM cancer registries. Net survivals were estimated at 5, 10 and 15 years postdiagnosis. At 5 years, the errors were generally small. At 10 years, in good-prognosis cancers, the errors made in nonstandardized estimates with all classical methods were generally great (+2.7 to +9% points in prostate cancer) and increased in age-class estimations (vs. 5-year ones). At 15 years, in bad- or average-prognosis cancers, the errors were often substantial whatever the nature of the estimation. In good-prognosis cancers, the errors in nonstandardized estimates of all classical methods were great and sometimes very important. With all classical methods, great errors occurred in age-class estimates resulting in errors in age-standardized estimates (+0.4 to +3.2% points in breast cancer). In estimating net survival, cancer registries should abandon all classical methods and adopt the new Pohar-Perme estimator.
Copyright © 2012 UICC.

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Year:  2012        PMID: 22961565     DOI: 10.1002/ijc.27830

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  21 in total

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2.  Cancer survival: an overview of measures, uses, and interpretation.

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4.  Ethnicity, deprivation and screening: survival from breast cancer among screening-eligible women in the West Midlands diagnosed from 1989 to 2011.

Authors:  M Morris; L M Woods; N Rogers; E O'Sullivan; O Kearins; B Rachet
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5.  Comparison of different approaches to estimating age standardized net survival.

Authors:  Paul C Lambert; Paul W Dickman; Mark J Rutherford
Journal:  BMC Med Res Methodol       Date:  2015-08-15       Impact factor: 4.615

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7.  Are international differences in breast cancer survival between Australia and the UK present amongst both screen-detected women and non-screen-detected women? survival estimates for women diagnosed in West Midlands and New South Wales 1997-2006.

Authors:  Laura M Woods; Bernard Rachet; Dianne L O'Connell; Gill Lawrence; Michel P Coleman
Journal:  Int J Cancer       Date:  2016-02-23       Impact factor: 7.396

Review 8.  Cancer Patients' Survival: Standard Calculation Methods And Some Considerations Regarding Their Interpretation: POPULACIJSKO PREŽIVETJE BOLNIKOV Z RAKOM: UPORABA RAZLIČNIH PRISTOPOV IN PROBLEMI INTERPRETACIJE REZULTATOV.

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Journal:  Zdr Varst       Date:  2016-02-11

9.  Under-treatment of elderly patients with ovarian cancer: a population based study.

Authors:  Elisabeth Fourcadier; Brigitte Trétarre; Claudine Gras-Aygon; Fiona Ecarnot; Jean-Pierre Daurès; Faïza Bessaoud
Journal:  BMC Cancer       Date:  2015-11-26       Impact factor: 4.430

10.  Analysing population-based cancer survival - settling the controversies.

Authors:  Maja Pohar Perme; Jacques Estève; Bernard Rachet
Journal:  BMC Cancer       Date:  2016-12-03       Impact factor: 4.430

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