PloS one · 2023
Calibration and validation of modeled 5-year survival predictions among people with cystic fibrosis treated with the cystic fibrosis transmembrane conductance regulator modulator ivacaftor using United States registry data.
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McGarry Lisa J, Bhaiwala Zahra, Lopez Andrea, Chandler Conor, Pelligra Christopher G, Rubin Jaime L, Liou Theodore G
Аннотация
OBJECTIVES: Cystic fibrosis (CF) is a rare genetic disease characterized by life-shortening lung function decline. Ivacaftor, a CF transmembrane conductance regulator modulator (CFTRm), was approved in 2012 for people with CF with specific gene mutations. We used real-world evidence of 5-year mortality impacts of ivacaftor in a US registry population to validate a CF disease-progression model that estimates the impact of ivacaftor on survival.
METHODS: The model projects the impact of ivacaftor vs. standard care in people with CF aged ≥6 years with CFTR gating mutations by combining parametric equations fitted to historical registry survival data, with mortality hazards adjusted for fixed and time-varying person-level characteristics. Disease progression with standard care was derived from published registry studies and the expected impact of ivacaftor on clinical characteristics was derived from clinical trials. Individual-level baseline characteristics of the registry ivacaftor-treated population were entered into the model; 5-year model-projected mortality with credible intervals (CrIs) was compared with registry mortality to evaluate the model's validity.
RESULTS: Post-calibration 5-year mortality projections closely approximated registry mortality in populations treated with standard care (6.4% modeled [95% CrI: 5.3% to 7.6%] vs. 6.0% observed) and ivacaftor (3.4% modeled [95% CrI: 2.7% to 4.4%] vs. 3.1% observed). The model accurately predicted 5-year relative risk of mortality (0.53 modeled [0.47 to 0.60] vs. 0.51 observed) in people treated with ivacaftor vs. standard care.
CONCLUSIONS: Modeled 5-year survival projections for people with CF initiating ivacaftor vs. standard care align closely with real-world registry data. Findings support the validity of modeling CF to predict long-term survival and estimate clinical and economic outcomes of CFTRm.
METHODS: The model projects the impact of ivacaftor vs. standard care in people with CF aged ≥6 years with CFTR gating mutations by combining parametric equations fitted to historical registry survival data, with mortality hazards adjusted for fixed and time-varying person-level characteristics. Disease progression with standard care was derived from published registry studies and the expected impact of ivacaftor on clinical characteristics was derived from clinical trials. Individual-level baseline characteristics of the registry ivacaftor-treated population were entered into the model; 5-year model-projected mortality with credible intervals (CrIs) was compared with registry mortality to evaluate the model's validity.
RESULTS: Post-calibration 5-year mortality projections closely approximated registry mortality in populations treated with standard care (6.4% modeled [95% CrI: 5.3% to 7.6%] vs. 6.0% observed) and ivacaftor (3.4% modeled [95% CrI: 2.7% to 4.4%] vs. 3.1% observed). The model accurately predicted 5-year relative risk of mortality (0.53 modeled [0.47 to 0.60] vs. 0.51 observed) in people treated with ivacaftor vs. standard care.
CONCLUSIONS: Modeled 5-year survival projections for people with CF initiating ivacaftor vs. standard care align closely with real-world registry data. Findings support the validity of modeling CF to predict long-term survival and estimate clinical and economic outcomes of CFTRm.