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

Objectives: Our 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 setting: Using 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.

Results: Over 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).

Conclusion: We 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.