1. 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.
- Author
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McGarry LJ, Bhaiwala Z, Lopez A, Chandler C, Pelligra CG, Rubin JL, and Liou TG
- Subjects
- Humans, United States, Cystic Fibrosis Transmembrane Conductance Regulator genetics, Calibration, Routinely Collected Health Data, Aminophenols therapeutic use, Mutation, Cystic Fibrosis drug therapy, Cystic Fibrosis genetics
- Abstract
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., Competing Interests: All authors received nonfinancial support from ArticulateScience LLC (editorial assistance) and Complete HealthVizion, IPG Health Medical Communications (project management and editing support), which both received funding from Vertex Pharmaceuticals Incorporated. Additional disclosures are as follows: Lisa J. McGarry, Zahra Bhaiwala, Andrea Lopez, and Jaime L. Rubin are employees of Vertex Pharmaceuticals Incorporated and may own stock or stock options in that company; in addition, Zahra Bhaiwala reports consulting fees from Evidera. Conor Chandler and Christopher G. Pelligra are employed by Evidera, an independent research company that provides consulting and other research services to pharmaceutical, medical device, and related organizations; in their salaried positions, they work with a variety of companies and are precluded from receiving payment or honoraria directly from these organizations for services rendered. Evidera received payment from Vertex Pharmaceuticals Incorporated for the conduct of this study. Theodore G. Liou, MD, is an employee of the University of Utah and is supported by the NIH/NHLBI (R01 HL125520), the Cystic Fibrosis Foundation, Bethesda, MD (grants CC-132-16AD, LIOU13A0, LIOU14Y0, and LIOU14Y4), the Ben B. and Iris M. Margolis Family Foundation of Utah, and the Claudia Ruth Goodrich Stevens Endowment Fund. The target data used for model validation included patients treated with ivacaftor, which is manufactured by Vertex Pharmaceuticals Incorporated. This does not alter our adherence to PLOS ONE policies on sharing data and materials" and added to the Financial Disclosure statement., (Copyright: © 2023 McGarry et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
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