ESTIMATING mortality due to kidney failure can be problematic, due to difficulties separating mortality attributed to comorbid conditions. Research has emerged which provides an alternative method to reduce this bias, in a longitudinal cohort design using life tables to estimate relative survival.
Included in this study were 31,944 adults with kidney failure (mean age: 77±7 years). Data were taken from the United States Renal Data System (USRDS). Comorbidity, age, sex, race, and year-specific life tables were created to estimate relative survival of patients with incident kidney failure, and to attain an estimate of excess kidney failure-related deaths. These estimates were compared with those based on standard life tables, and were not adjusted for comorbidity.
Five-year relative survival was 31% using standard life tables, versus 36% in tables adjusted for comorbidities. This research uncovered that, compared with other chronic diseases, patients with kidney failure have among the lowest relative survival. Patients with incident kidney failure aged 66–70 and 76–80 have a survival comparable to adults without kidney failure of approximately 86–90 and 91–95 years, respectively.
The investigators did note a limitation with their work. The relative survival estimates can be improved by narrowing the specificity of the covariates collected, such as disease severity or ethnicity. They were able to conclude, based on their results, that kidney failure creates an immense burden on mortality. Their findings highlight the importance of disease prevention efforts in older adults.
By comparing survival in patients with kidney failure to survival of the general population, patients with kidney failure were found to have one-third the chance of survival in 5 years compared with those of a similar demographic and comorbidity without kidney failure. The critical advancement from this work is the provision of a quantifiable estimate of the mortality burden from kidney failure, which is expected to be carried forward into further study.
