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Cancer survival statistics are typically expressed as the proportion of patients alive at some point subsequent to
the diagnosis of their cancer. Several statistical methods and software tools have been developed for the analysis
and reporting on cancer survival statistics. Overview of Population-based Cancer Survival Statistics
provides detailed information about survival measures, approaches to cohort definition, and available statistics. SEER*Stat Statistical MethodsThere are three measures of cancer survival that can be calculated in SEER*Stat software, including:
Read more about applications of these measures on Overview of Population-based Cancer Survival Statistics. Two of the survival measures, net cancer-specific survival and crude probability of death, each have two methods in which they can be estimated: using cause of death information or expected survival tables. These two approaches to estimation are described in Measures of Cancer Survival: Approaches to Estimation. Cohort definition using diagnosis year - There are different approaches of grouping survival experience (or patients) with respect to year of diagnosis and follow-up to obtain more up-to-date estimates of patients recently diagnosed with cancer or to obtain survival trends. The current appraoches include cohort, multi-year cohort, and period. Cancer Survival Analysis Software (Cansurv)Cansurv is statistical software to analyze population-based survival data. For grouped survival data, it can fit
both standard survival models and mixture cure models and provide graphs and tests for inference and diagnosis. It
can also fit parametric (cure) survival models to individually-listed data. Cansurv uses population-based survival
data extracted from SEER*Stat survival session. See the Cansurv Web site for more information. |
Last modified: 11 Aug 2008 |
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