Format

Send to

Choose Destination
See comment in PubMed Commons below
Eur J Cancer. 2011 Nov;47(17):2626-32. doi: 10.1016/j.ejca.2011.08.010. Epub 2011 Sep 15.

Estimating expected survival probabilities for relative survival analysis--exploring the impact of including cancer patient mortality in the calculations.

Author information

  • 1Unit for Epidemiology, Department of Statistics, Monitoring and Evaluation, National Board of Health and Welfare, Stockholm, Sweden. mats.talback@socialstyrelsen.se

Abstract

Relative survival is a widely used measure of cancer patient survival, defined as the observed survival of the cancer patients divided by the expected survival of a comparable group from the general population, free from the cancer under study. In practise, expected survival is usually calculated from general population life tables. Such estimates are known to be biased since they also include mortality from the cancer patients, but the bias is ignored since mortality among individuals with a specific cancer is thought to constitute only a small proportion of total mortality. Using the computerised population registers that exist in Sweden we had the unique opportunity to calculate expected survival both including and excluding individuals with cancer, and thereby estimate the size of the bias arising from using general population estimates. We also evaluated a simple method to adjust expected survival probabilities estimated from general population statistics as an aid to researchers who do not have access to computerised registers of the entire national population. Our results show that the bias is sufficiently small to be ignorable for most applications, notably for cancers with high or low mortality and for younger age groups (<60 years). However, the bias in relative survival estimates can be greater than 1 percent unit for older age groups for common cancers and even larger for all sites combined. For example, the bias in 10-year relative survival for men aged 75+ diagnosed with prostate cancer was 2.6 percent units, which we think is of sufficient magnitude to warrant adjustment.

PMID:
21924892
DOI:
10.1016/j.ejca.2011.08.010
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Elsevier Science
    Loading ...
    Support Center