Abstract

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Background
Keywords
Findings
Author
What is already known on this subject?
What does this study add?

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Background

In theory, expected survival probabilities used in the derivation of relative survival ratios (RSR) are determined from a control group free of the cancer under study. In practice, expected survival is typically estimated from general population life tables—which include people previously diagnosed with cancer—potentially leading to an overestimation of relative survival.

Data and methods

Data are from the Canadian Cancer Registry with mortality follow-up through record linkage to the Canadian Vital Statistics Death Database. Period method RSRs for 2006-to-2008 were derived using general population life tables adjusted for cancer mortality and then compared with estimates derived using corresponding unadjusted life tables.

Results

For all cancers combined, the use of general population life tables to derive expected survival probabilities overestimated RSRs by 0.6 (1-year), 2.4 (5-year) and 4.6 (10-year) percentage units. Biases in 5-year survival were highest among males (3.0) and among people aged 75 to 99 at diagnosis (4.1). The bias was negligible for most individual cancers; biases were highest for prostate cancer, followed by colorectal and female breast cancer.

Interpretation

Canadian estimates of relative survival for all cancers combined calculated using general life tables warrant adjustment for cancer mortality. Consideration of adjustment for cancer mortality is recommended for estimates of colorectal, female breast and especially prostate cancer.

Keywords

Bias, epidemiologic methods, life tables, neoplasms, registries, survival

Findings

For cancer, relative survival is defined as the ratio of the observed (absolute) survival in a group of people diagnosed with cancer to the expected survival of a comparable group—free of the cancer under study—in the general population. In theory, the relative survival ratio (RSR) provides an estimate of the difference between the all-cause mortality of those diagnosed with cancer and the mortality that would be expected in the absence of cancer (the excess mortality due to cancer). In practical applications, however, expected survival is typically estimated from general population life tables. Because these estimates include people previously diagnosed with cancer, they underestimate expected survival, and hence, overestimate relative survival. [Full Text]

Author

Larry F. Ellison (larry.ellison@statcan.gc.ca) is with the Health Statistics Division at Statistics Canada, Ottawa, Ontario.

What is already known on this subject?

  • Expected survival probabilities used to derive relative survival ratios (RSRs) are typically estimated from general population life tables rather than from the theoretically preferred control group free of the cancer under study.
  • The use of general population life tables—which include people previously diagnosed with cancer—leads to biased estimates of expected survival, and potentially, of relative survival.
  • Researchers in Sweden who had the unique opportunity to calculate expected survival including and excluding individuals with cancer, and thereby, to evaluate the size of this bias, recently reported that adjustment for cancer mortality is recommended in some circumstances.
  • These researchers also demonstrated that cause-of-death statistics can be used to adjust expected survival probabilities from general life tables for cancer mortality.

What does this study adds?

  • The magnitude of the bias introduced into RSR estimates through the use of general population life tables to derive expected survival is negligible for most individual cancers in Canada.
  • Consideration of adjustment for cancer mortality is recommended for Canadian long-term relative survival estimates of colorectal, female breast, and especially, prostate cancer, calculated using general life tables.
  • Canadian estimates of long-term relative survival for all cancers combined calculated using general life tables warrant adjustment for cancer mortality.
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