TY - JOUR
T1 - Validation and use of a parametric model for projecting cystic fibrosis survivorship beyond observed data
T2 - A birth cohort analysis
AU - Jackson, Abaigeal D.
AU - Daly, Leslie
AU - Jackson, Andrew L.
AU - Kelleher, Cecily
AU - Marshall, Bruce C.
AU - Quinton, Hebe B.
AU - Fletcher, Godfrey
AU - Harrington, Mary
AU - Zhou, Shijun
AU - McKone, Edward F.
AU - Gallagher, Charles
AU - Foley, Linda
AU - Fitzpatrick, Patricia
N1 - Funding Information:
Funding This work was supported by the Cystic Fibrosis Registry of Ireland Executive Council. Health Research Board, Ireland ( RP/2007/249 ).
PY - 2011/8
Y1 - 2011/8
N2 - Background: The current lifetable approach to survival estimation is favoured by CF registries. Recognising the limitation of this approach, we examined the utility of a parametric survival model to project birth cohort survival estimates beyond the follow-up period, where short duration of follow-up meant median survival estimates were indeterminable. Methods: Parametric models were fitted to observed survivorship data from the US CF Foundation (CFF) Patient Registry 1980-1994 birth cohort. Model-predicted median survival was estimated. The best fitting model was applied to a Cystic Fibrosis Registry of Ireland dataset to allow an evaluation of the model's ability to estimate predicted median survival. This involved a comparison of birth cohort lifetable predicted and observed (Kaplan-Meier) median survival estimates. Results: A Weibull model with main effects of gender and birth cohort was developed using a US CFF dataset (n=13115) for which median survival was not directly estimable. Birth cohort lifetable predicted median survival for male and female patients born between 1985 and 1994 and surviving their first birthday was 50.9 and 42.4 years respectively. To evaluate the accuracy of a Weibull model in predicting median survival, a model was developed for the 1980-1984 Cystic Fibrosis Registry of Ireland birth cohort (n=243), which had an observed (Kaplan-Meier) median survival of 27.7 years. Model-predicted median survival estimates were calculated using data censored at different follow-up periods. The estimates converged to the true value as length of follow-up increased. Conclusions: Accurate prognostic information that is clinically critical for care of patients affected by rare, lifelimiting disorders can be provided by parametric survival models. Problems associated with short duration of follow-up for recent birth cohorts can be overcome using this approach, providing better opportunities to monitor survival and plan services locally.
AB - Background: The current lifetable approach to survival estimation is favoured by CF registries. Recognising the limitation of this approach, we examined the utility of a parametric survival model to project birth cohort survival estimates beyond the follow-up period, where short duration of follow-up meant median survival estimates were indeterminable. Methods: Parametric models were fitted to observed survivorship data from the US CF Foundation (CFF) Patient Registry 1980-1994 birth cohort. Model-predicted median survival was estimated. The best fitting model was applied to a Cystic Fibrosis Registry of Ireland dataset to allow an evaluation of the model's ability to estimate predicted median survival. This involved a comparison of birth cohort lifetable predicted and observed (Kaplan-Meier) median survival estimates. Results: A Weibull model with main effects of gender and birth cohort was developed using a US CFF dataset (n=13115) for which median survival was not directly estimable. Birth cohort lifetable predicted median survival for male and female patients born between 1985 and 1994 and surviving their first birthday was 50.9 and 42.4 years respectively. To evaluate the accuracy of a Weibull model in predicting median survival, a model was developed for the 1980-1984 Cystic Fibrosis Registry of Ireland birth cohort (n=243), which had an observed (Kaplan-Meier) median survival of 27.7 years. Model-predicted median survival estimates were calculated using data censored at different follow-up periods. The estimates converged to the true value as length of follow-up increased. Conclusions: Accurate prognostic information that is clinically critical for care of patients affected by rare, lifelimiting disorders can be provided by parametric survival models. Problems associated with short duration of follow-up for recent birth cohorts can be overcome using this approach, providing better opportunities to monitor survival and plan services locally.
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U2 - 10.1136/thoraxjnl-2011-200038
DO - 10.1136/thoraxjnl-2011-200038
M3 - Article
C2 - 21653925
AN - SCOPUS:79960592523
SN - 0040-6376
VL - 66
SP - 674
EP - 679
JO - Thorax
JF - Thorax
IS - 8
ER -