Abstract
Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. In the overall survival setting, we describe the overall survival probability, the conditional survival probability and the restricted mean survival time (restricted to a prespecified time window). In the relative survival setting, we describe the net survival probability, the conditional net survival probability, the restricted mean net survival time, the crude probability of death due to each cause and the number of life years lost due to each cause over a prespecified time window. These measures describe survival data either on a probability scale or on a timescale. The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15–80 years old diagnosed with colon cancer in 2001–2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use.
Highlights
In epidemiology, survival data are commonly described with the probability of being alive after a certain time after the diagnosis of a particular disease
Survival and conditional survival (CS) probabilities The 10-year overall survival probability for all ages combined was 0.36 (95% confidence interval [CI]: 0.34, 0.37) for deprivation group 1, and 0.25 for deprivation group 5 (Table 3), and the 10-year overall survival probabilities by deprivation and age group are detailed in Table S1 and Figure S1
The restricted mean survival time (RMST) at 10 years was estimated as 5.14 years, for the least deprived group compared to 4.16 years for the most deprived group of patients (Table 3)
Summary
Survival data are commonly described with the probability of being alive after a certain time after the diagnosis of a particular disease. Depending on the objectives, i) evaluating the patients prognosis or ii) giving useful information for public health policy, alternative measures may be useful For both objectives, data gathered by population-based registries are one of the main sources of information because they represent the whole population.[1] many diseases are more prevalent among older groups of the population, who are more likely to experience competing risks of death. Because the cause of death is not routinely collected in population-based registries, or may be inaccurate or unreliable, especially for long-term studies as it may be diversely coded over time and on different regions,[2,3,4,5] specific methods have been developed to allow the estimation of quantities associated with the disease under study without the need for the cause of death, known as the “relative survival” setting.
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