A standardized approach to estimating survival statistics for population-based cystic fibrosis registry cohorts

Abstract

ObjectivesOur objective was to quantify the effect of different statistical techniques, inclusion/exclusion criteria, and missing data on the predicted median survival age. Study Design and SettingUsing the Canadian cystic fibrosis registry (CCFR), the median age of survival was calculated using both the Cox proportional hazards (PH) and the life-table methods. Through simulations, we examined how the median age of survival would change when: (1) patients were excluded, (2) death dates were inaccurate, (3) patients were lost to follow-up, (4) entire years with no clinic visits were excluded even if the​ patient had a visit in subsequent years, and (5) censoring patients at their date of transplant. Simulations were run assuming 5–35% of data were affected by each scenario. ResultsOver the period 2009–2013, there were 4,666 individuals in the CCFR with 240 deaths. The observed median age of survival calculated by the Cox PH method was 50.9 [95% confidence interval (CI): 47.4, 54.3] and 50.5 from the life-table method (95% CI: 47.5, 53.5). Censoring patients at their transplant date overestimated the median age of survival by 7.2 years (58.1; 95% CI: 53.3, 64.7). Simulations determined that by missing just 15% of deaths, the median age of survival can be overestimated by 3.5 years (54.4; 95% CI: 54.2, 56.1), and having 25% of patients lost to follow-up can underestimate the median age of survival by 3.3 years (47.6; 95% CI: 46.8, 47.7). ConclusionWe present several recommendations to assist national cystic fibrosis registries in calculating and reporting the median age of survival in a standardized fashion. It is imperative to state the statistical method used as well as the proportion lost to follow-up and the treatment of missing data and transplanted patients. Registries must be diligent in their data collection as incomplete data can lead to overestimation and underestimation of survival.