Literature DB >> 28027519

Estimation of net survival for cancer patients: Relative survival setting more robust to some assumption violations than cause-specific setting, a sensitivity analysis on empirical data.

Robin Schaffar1, Bernard Rachet2, Aurélien Belot2, Laura M Woods2.   

Abstract

Net survival is the survival that would be observed if the only possible underlying cause of death was the disease under study. It can be estimated with either cause-specific or relative survival data settings, if the informative censoring is properly considered. However, net survival estimators are prone to specific biases related to the data setting itself. We examined which data setting was the most robust against violation of key assumptions (erroneous cause of death and inappropriate life tables). We identified 4285 women in the Geneva Cancer Registry, diagnosed with breast, colorectal, lung cancer and melanoma between 1981 and 1991 and estimated net survival up to 20 years using cause-specific and relative survival settings. We used weights to tackle informative censoring in both settings and performed sensitivity analyses to evaluate the impact of misclassification of cause of death in the cause-specific setting or of using inappropriate life tables on net survival estimates in the relative survival setting. For all the four cancers, net survival was highest when using the cause-specific setting and the absolute difference between the two estimators increased with time since diagnosis. The sensitivity analysis showed that (i) the use of different life tables did not compromise net survival estimation in the relative survival setting, whereas (ii) a small level of misclassification for the cause of death led to a large change in the net survival estimate in the cause-specific setting. The relative survival setting was more robust to the above assumptions violations and is therefore recommended for estimation of net survival.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cause-specific; Informative censoring; Net survival; Relative survival

Mesh:

Year:  2016        PMID: 28027519      PMCID: PMC6191025          DOI: 10.1016/j.ejca.2016.11.019

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


  7 in total

1.  The relative survival rate: a statistical methodology.

Authors:  F EDERER; L M AXTELL; S J CUTLER
Journal:  Natl Cancer Inst Monogr       Date:  1961-09

2.  Estimating net survival: the importance of allowing for informative censoring.

Authors:  Coraline Danieli; Laurent Remontet; Nadine Bossard; Laurent Roche; Aurélien Belot
Journal:  Stat Med       Date:  2012-01-26       Impact factor: 2.373

3.  Cause-specific or relative survival setting to estimate population-based net survival from cancer? An empirical evaluation using women diagnosed with breast cancer in Geneva between 1981 and 1991 and followed for 20 years after diagnosis.

Authors:  Robin Schaffar; Bernard Rachet; Aurélien Belot; Laura Woods
Journal:  Cancer Epidemiol       Date:  2015-04-20       Impact factor: 2.984

4.  On estimation in relative survival.

Authors:  Maja Pohar Perme; Janez Stare; Jacques Estève
Journal:  Biometrics       Date:  2011-06-20       Impact factor: 2.571

5.  Improved estimates of cancer-specific survival rates from population-based data.

Authors:  Nadia Howlader; Lynn A G Ries; Angela B Mariotto; Marsha E Reichman; Jennifer Ruhl; Kathleen A Cronin
Journal:  J Natl Cancer Inst       Date:  2010-10-11       Impact factor: 13.506

6.  A comparison of relative and cause-specific survival by cancer site, age and time since diagnosis.

Authors:  Katrine Damgaard Skyrud; Freddie Bray; Bjørn Møller
Journal:  Int J Cancer       Date:  2013-12-09       Impact factor: 7.396

7.  Accuracy of cause of death data routinely recorded in a population-based cancer registry: impact on cause-specific survival and validation using the Geneva Cancer Registry.

Authors:  Robin Schaffar; Elisabetta Rapiti; Bernard Rachet; Laura Woods
Journal:  BMC Cancer       Date:  2013-12-27       Impact factor: 4.430

  7 in total
  7 in total

1.  Spatial barriers impact upon appropriate delivery of radiotherapy in breast cancer patients.

Authors:  Fabrizio Stracci; Fortunato Bianconi; Chiara Lupi; Manuela Margaritelli; Alessio Gili; Cynthia Aristei
Journal:  Cancer Med       Date:  2018-01-22       Impact factor: 4.452

2.  Correcting for misclassification and selection effects in estimating net survival in clinical trials.

Authors:  Juste Aristide Goungounga; Célia Touraine; Nathalie Grafféo; Roch Giorgi
Journal:  BMC Med Res Methodol       Date:  2019-05-16       Impact factor: 4.615

3.  Errors in determination of net survival: cause-specific and relative survival settings.

Authors:  Chloe J Bright; Adam R Brentnall; Kate Wooldrage; Jonathon Myles; Peter Sasieni; Stephen W Duffy
Journal:  Br J Cancer       Date:  2020-02-10       Impact factor: 7.640

4.  Net survival differences of breast cancer between stages at diagnosis and age groups in the east coast region of West Malaysia: a retrospective cohort study.

Authors:  Tengku Muhammad Hanis; Najib Majdi Yaacob; Suhaily Mohd Hairon; Sarimah Abdullah
Journal:  BMJ Open       Date:  2021-05-18       Impact factor: 2.692

5.  Socioeconomic and demographic inequalities in stage at diagnosis and survival among colorectal cancer patients: evidence from a Swiss population-based study.

Authors:  Anita Feller; Kurt Schmidlin; Andrea Bordoni; Christine Bouchardy; Jean-Luc Bulliard; Bertrand Camey; Isabelle Konzelmann; Manuela Maspoli; Miriam Wanner; Marcel Zwahlen; Kerri M Clough-Gorr
Journal:  Cancer Med       Date:  2018-02-26       Impact factor: 4.452

6.  Changes in conditional net survival and dynamic prognostic factors in patients with newly diagnosed metastatic prostate cancer initially treated with androgen deprivation therapy.

Authors:  Shintaro Narita; Kyoko Nomura; Shingo Hatakeyama; Masahiro Takahashi; Toshihiko Sakurai; Sadafumi Kawamura; Senji Hoshi; Masanori Ishida; Toshiaki Kawaguchi; Shigeto Ishidoya; Jiro Shimoda; Hiromi Sato; Koji Mitsuzuka; Tatsuo Tochigi; Norihiko Tsuchiya; Chikara Ohyama; Yoichi Arai; Kengo Nagashima; Tomonori Habuchi
Journal:  Cancer Med       Date:  2019-09-11       Impact factor: 4.452

7.  Cancer outcomes research-a European challenge: measures of the cancer burden.

Authors:  Mette Kalager; Hans-Olov Adami; Pernilla Lagergren; Karen Steindorf; Paul W Dickman
Journal:  Mol Oncol       Date:  2021-06-22       Impact factor: 6.603

  7 in total

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