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. Author manuscript; available in PMC: 2017 Feb 1.
Published in final edited form as: J Clin Epidemiol. 2015 Oct 3;70:206–213. doi: 10.1016/j.jclinepi.2015.08.026

Table 2.

Recommendations when Reporting Survival Statistics using CF Registry Data

Key General Points:

  • Registries must diligently capture deaths within the registry in order to avoid biased survival statistics. If available, comparing the number of deaths within the CF registry to national death statistics where the cause of death is CF is a way to estimate the impact of missing deaths.

  • In order to stabilize survival estimates and minimize year-to-year variability, it is recommended that a five-year window be used. Registries with few deaths per year may require a longer time window to produce stable results, while larger registries may find a time period shorter than five years will suffice. Stability of the results can be judged by examining the width of the 95% confidence interval and the consistency between period estimates. In particular circumstances, if the CF population is very small and there are few deaths, it may not be possible to accurately estimate the median age of survival despite maximizing the time window.

  • Registries should minimize the number of patients who are lost-to-follow up when calculating survival statistics. Efforts should be made, where possible, to confirm the vital statistics of patients within the registry prior to survival calculations.

  • Assuming that post-transplant patients are not lost-to-follow-up following transplantation, transplanted patients should be included in the survival analysis rather than being censored at the time of transplant because censoring results in an over- estimation of survival.

  • If the life-table method is used to calculate survival, intervening years must be accounted for in the analysis in order to produce unbiased results.

Registries should consider including the following parameters in their survival reports:

  • The length of the time window under consideration (for example, 2009 to 2013).

  • The number of patients in the time window.

  • The number of deaths in the time window.

  • The statistical methodology used (i.e. life-table method, Cox PH method).

  • How missing data were treated (i.e. listwise deletion, simple imputation, multiple imputation).

  • Whether or not transplanted patients are included in the analysis or whether they are censored at transplant.

  • Proportion of patients lost-to-follow-up, where lost-to-follow-up is defined as those patients alive with their last verified year of contact occurring more than two years before the end of the five-year window (for example, 2011 if the window in question is 2009 to 2013).