PRS31 Modelling Survival of People with Cystic Fibrosis (PWCF) Aged ≥12 YEARS Homozygous for the F508DEL Mutation Treated with Ivacaftor/Tezacaftor/Elexacaftor and Ivacaftor (IVA/TEZ/ELX)

Vega-Hernández, Gabriela; MacGregor, Gordon; Lopez, A.; Daly, C.; Rubin, J.L.

doi:10.1016/j.jval.2021.04.1095

Cited by 1 publication

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“…CFTRm such as ivacaftor are projected to change the trajectory of CF disease and extend survival by upwards of 30 years based on a published patient-level lifetime simulation model [24][25][26][27][28][29][30][31][32]. With the availability of real-world survival data from a recent post-authorization safety study that evaluated the long-term treatment benefits of ivacaftor using data from the US CFFPR over 5 years (2012 to 2016) [18], we were able to test the predictive validity of the simulation model.…”

Section: Discussionmentioning

confidence: 99%

“…The CF patient-level simulation model (CF-PSM) has been developed for ivacaftor and used to project the impact of therapy on both survival and economic outcomes [24]. This model's structure has been refined over time and has been used to evaluate additional CFTRm, including lumacaftor/ivacaftor, tezacaftor/ivacaftor and ivacaftor, and, most recently, elexacaftor/tezacaftor/ivacaftor and ivacaftor [24][25][26][27][28][29][30][31][32]. The CF-PSM combines inputs from national CF proposed, and the intended use of the model.…”

Section: Introductionmentioning

confidence: 99%

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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

et al. 2023

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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.

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