Improving communication of cancer survival statistics—feasibility of implementing model-based algorithms in routine publications

Author:

Myklebust Tor ÅgeORCID,Aagnes Bjarte,Nilssen Yngvar,Rutherford MarkORCID,Lambert Paul C.,Andersson Therese M. L.ORCID,Johansson Anna L. V.,Dickman Paul W.,Møller Bjørn

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Oncology

Reference29 articles.

1. Ferlay JEM, Lam F, Colombet M, Mery L, Piñeros M, Znaor A, et al. Global cancer observatory: cancer today. Lyon, France: International Agency for Research on Cancer; 2020. https://gco.iarc.fr/today.

2. Dickman PW, Adami HO. Interpreting trends in cancer patient survival. J Intern Med. 2006;260:103–17.

3. Putter H, Fiocco M, Geskus RB. Tutorial in biostatistics: competing risks and multi-state models. Stat Med. 2007;26:2389–430.

4. Andersson TM, Dickman PW, Eloranta S, Lambe M, Lambert PC. Estimating the loss in expectation of life due to cancer using flexible parametric survival models. Stat Med. 2013;32:5286–300.

5. Cancer Registry of Norway. Cancer in Norway 2021—cancer incidence, mortality, survival and prevalence in Norway. Oslo: Cancer Registry Norway; 2022.

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