Measures of Cancer Survival
Three measures of cancer survival can be calculated in SEER*Stat software:
- Observed all cause survival - Observed survival is an estimate of the probability of surviving
all causes of death.
- Net cancer-specific survival (policy-based statistic) - This is the probability of surviving
cancer in the absence of other causes of death. It is a measure that is not influenced by changes in mortality from
other causes and, therefore, provides a useful measure for tracking survival across time, and comparisons between
racial/ethnic groups or between registries.
- Crude probability of death (patient prognosis measure) - This is the probability of dying
of cancer in the presence of other causes of death. It is a better measure to assess the impact of cancer diagnosis
at an individual level since mortality from other causes play a key role. It measures mortality patterns actually
experienced in a cohort of cancer patients on which many possible causes of death are acting simultaneously. The
crude measure is reported as a cumulative probability of death from cancer rather than survival.
The SEER*Stat
help system includes several frequently asked questions to clarify when net survival and crude probability of
death would be used.
Approaches to Estimation of Cancer-Specific Survival
Net
cancer-specific survival and crude probability of death have two methods in which they can be estimated: using
cause of death information or expected survival tables. When using cause of death information, there has been much
debate over what is the right endpoint. If death certification were perfect, one would just use the specific form
of cancer as the endpoint. However, if a cancer metastasizes, there are instances where the death certificate incorrectly
lists the underlying cause of death as the metastatic site. In this instance, it may be best to use all cancers as
the end point, especially if the patient only has one cancer. Work is ongoing to define more sophisticated algorithms
for defining endpoints based on common sites of metastases for each cancer.
Regardless of whether one uses an approach which utilizes cause of death or expected lifetables, careful consideration
should be given to exclusions from the analysis. A technical report from Boer et
al., (2003) (PDF), summarizes various approaches to exclusions for survival analyses, as well as the choice of endpoints
when death certificate information is utilized. The figure on the right illustrates the survival statistics that result
from the combination of the two measures and twoestimation methods. A description of each is given below.
- Relative survival - Cancer survival in the absence of other causes of death is calculated
using survival life tables. Relative survival is defined as the ratio of the proportion of observed survivors (all
causes of death) in a cohort of cancer patients to the proportion of expected survivors in a comparable cohort of
cancer-free individuals. The formulation is based on the assumption of independent competing causes of death. Since
a cohort of cancer-free individuals is difficult to obtain, we use expected life tables and assume that the cancer
deaths are a negligible proportion of all deaths. (See Ederer et al., 1961 - PDF)
- Cause-specific survival is a net survival measure representing survival of a specified
cause of death in the absence of other causes of death. Estimates are calculated by specifying the cause of death.
Individuals who die of causes other than those specified are considered to be censored. (See Marubini & Valsecchi,
1995)
- Crude Probability of Death Using Expected Survival - This crude measure uses expected survival
(obtained from the expected life tables) to estimate the probability of dying from other causes in each interval.
Since a cohort of cancer-free individuals is difficult to obtain, we use expected life tables and assume that the
cancer deaths are a negligible proportion of all deaths. (See Cronin & Feuer, 2000 - PDF)
- Crude Probability of Death Using Cause of Death Information - The probability of dying
from cancer and dying from other causes in a cohort of cancer patients is calculated using cause of death information.
(See Marubini & Valsecchi, 1995; Schairer et al.,
2004 - PDF)
Example: This figure shows crude and net probability of death from localized colorectal cancer for men and
women diagnosed over the age of 70. Crude probability of death (cancer) is lower than net probability of death because
localized colorectal cancer has good prognosis, and because mortality for other causes is high for that age group.
The SEER*Stat matrix file used to obtain the percentages for the Cumulative
Probability of Death figure shown above is available for download. You must have the SEER*Stat software in order to
open this file - crude.vs.net.ssm.
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