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When the mortality among a cancer patient group returns to the same level as in the general population, that is, when the patients no longer experi- ence excess mortality, the patients still alive are considered “statistically cured”. Cure models can be used to estimate the cure proportion...
Persistent link: https://www.econbiz.de/10011002429
When estimating patient survival using data collected by populationbased cancer registries, it is common to estimate net survival in a relative-survival framework. Net survival can be estimated using the relative-survival ratio, which is the ratio of the observed survival of the patients (where...
Persistent link: https://www.econbiz.de/10011265700
Cancer registries are often interested in estimating net survival (NS), the probability of survival if the cancer under study is the only possible cause of death. Pohar Perme, Stare, and Esteve (2012, Biometrics 68: 113–120) proposed a new estimator of NS based on inverse probability...
Persistent link: https://www.econbiz.de/10011265701
Royston and Parmar (2002, Statistics in Medicine 21: 2175 – 2197) developed a class of flexible parametric survival models that were programmed in Stata with the stpm command (Royston, 2001, Stata Journal 1:1-28). In this article, we introduce a new command, stpm2, that extends the...
Persistent link: https://www.econbiz.de/10004982802
Cure models are a special type of survival analysis model where it is assumed that there are a proportion of sub jects who will never experience the event and thus the survival curve will eventually reach a plateau. In population-based cancer studies, cure is said to occur when the mortality...
Persistent link: https://www.econbiz.de/10005568880