Reference-adjusted and standardized all-cause and crude probabilities as an alternative to net survival in population-based cancer studies

• Published in: International journal of epidemiology 2020-10, Vol.49 (5), p.1614-1623
• Main Authors: Lambert, Paul C, Andersson, Therese M-L, Rutherford, Mark J, Myklebust, Tor Åge, Møller, Bjørn
• Format: Article
• Language: English
• Subjects: Cause of Death; England - epidemiology; Humans; Male; Medicin och hälsovetenskap; Neoplasms; Probability; Survival Analysis
• ISSN: 0300-5771; 1464-3685; 1464-3685
• DOI: 10.1093/ije/dyaa112

Abstract Background In population-based cancer survival studies, the most common measure to compare population groups is age-standardized marginal relative survival, which under assumptions can be interpreted as marginal net survival; the probability of surviving if it was not possible to die of causes other than the cancer under study (if the age distribution was that of a common reference population). The hypothetical nature of this definition has led to confusion and incorrect interpretation. For any measure to be fair in terms of comparing cancer survival, then differences between population groups should depend only on differences in excess mortality rates due to the cancer and not differences in other-cause mortality rates or differences in the age distribution. Methods We propose using crude probabilities of death and all-cause survival which incorporate reference expected mortality rates. This makes it possible to obtain marginal crude probabilities and all-cause probability of death that only differ between population groups due to excess mortality rate differences. Choices have to be made regarding what reference mortality rates to use and what age distribution to standardize to. Results We illustrate the method and some potential choices using data from England for men diagnosed with melanoma. Various marginal measures are presented and compared. Conclusions The new measures help enhance understanding of cancer survival and are a complement to the more commonly used measures.