Which survival measure requires an expected rate from the general population matched on age, sex, race, and other factors?

• A. Observed all-cause survival
• B. Cause-specific survival
• C. Relative survival
• D. Net survival

Answer: (C)

The main concept here is comparing how patients with cancer actually fare against how people in the general population of similar demographic characteristics would fare, to isolate the effect of cancer on survival. This approach uses an expected survival rate derived from life tables that are matched to characteristics like age, sex, race, and calendar year.

Relative survival works by taking the observed survival in the cancer patient group and dividing it by the expected survival from the general population that matches those same characteristics. The result reflects survival related to cancer after accounting for background mortality. For example, if 5-year observed survival in the cancer group is 60% and the 5-year expected survival for a comparable general population is 80%, the relative survival would be 0.60 / 0.80 = 0.75, indicating 25% excess mortality attributable to cancer beyond what would be expected from other causes.

This method is particularly useful when cause-of-death information is unreliable or unavailable, or when you want an overall measure of cancer’s impact on survival without needing precise cause-specific death data.