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

British Journal of Cancer volume 129, pages 819–828 (2023)Cite this article

Subjects

Abstract

Background

Routine reporting of cancer patient survival is important, both to monitor the effectiveness of health care and to inform about prognosis following a cancer diagnosis. A range of different survival measures exist, each serving different purposes and targeting different audiences. It is important that routine publications expand on current practice and provide estimates on a wider range of survival measures. We examine the feasibility of automated production of such statistics.

Methods

We used data on 23 cancer sites obtained from the Cancer Registry of Norway (CRN). We propose an automated way of estimating flexible parametric relative survival models and calculating estimates of net survival, crude probabilities, and loss in life expectancy across many cancer sites and subgroups of patients.

Results

For 21 of 23 cancer sites, we were able to estimate survival models without assuming proportional hazards. Reliable estimates of all desired measures were obtained for all cancer sites.

Discussion

It may be challenging to implement new survival measures in routine publications as it can require the application of modeling techniques. We propose a way of automating the production of such statistics and show that we can obtain reliable estimates across a range of measures and subgroups of patients.

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Fig. 1: The figure shows estimated 5-year crude probabilities of dying from colon cancer, dying from other causes and being alive.
Fig. 2: The figure shows estimated expected remaining lifetime, number and proportion of life years lost due to colon cancer.
Fig. 3: The figure shows absolute differences in estimated 5-year net survival, crude probabilities of dying from cancer and other causes, and number of life years lost due to cancer for all models that converged compared to the default model, separately for each cancer site.

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Data availability

Due to privacy protection rules the data cannot be publicly shared.

Code availability

The code used for generating the results can be accessed at https://github.com/CancerRegistryOfNorway/cancer-survival-measures. This page also contains additional material, including simpler example code using a publicly available dataset.

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Authors and Affiliations

  1. Department of Registration, Cancer Registry Norway, Oslo, Norway

    Tor Åge Myklebust, Bjarte Aagnes, Yngvar Nilssen, Anna L. V. Johansson & Bjørn Møller

  2. Department of Research and Innovation, Møre and Romsdal Hospital Trust, Ålesund, Norway

    Tor Åge Myklebust

  3. Biostatistics Research Group, Department of Health Sciences, University of Leicester, Leicester, UK

    Mark Rutherford & Paul C. Lambert

  4. International Agency for Research on Cancer, Lyon, France

    Mark Rutherford

  5. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Paul C. Lambert, Therese M. L. Andersson, Anna L. V. Johansson & Paul W. Dickman

Authors
  1. Tor Åge Myklebust
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  2. Bjarte Aagnes
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  3. Yngvar Nilssen
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  4. Mark Rutherford
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  5. Paul C. Lambert
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  6. Therese M. L. Andersson
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  7. Anna L. V. Johansson
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  8. Paul W. Dickman
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  9. Bjørn Møller
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Contributions

TÅM planned the study, analyzed the data and drafted the manuscript. BA planned the study, analyzed the data, and critically reviewed manuscript drafts. YN planned the study, analyzed the data, and critically reviewed manuscript drafts. MR planned the study, and critically reviewed manuscript drafts. PCL planned the study, and critically reviewed manuscript drafts. TMLA planned the study, and critically reviewed manuscript drafts. ALVJ planned the study, and critically reviewed manuscript drafts. PWD planned the study, and critically reviewed manuscript drafts. BM planned the study, and critically reviewed manuscript drafts.

Corresponding author

Correspondence to Tor Åge Myklebust.

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Competing interests

The authors declare no competing interests.

Ethical approval

All analysis were performed at the Cancer Registry of Norway (CRN), which is statutory, and statistics were made available according to the Norwegian Health Register Act §19. Ethical approval was not required for the produced statistics.

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Myklebust, T.Å., Aagnes, B., Nilssen, Y. et al. Improving communication of cancer survival statistics—feasibility of implementing model-based algorithms in routine publications. Br J Cancer 129, 819–828 (2023). https://doi.org/10.1038/s41416-023-02360-5

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