Early economic evaluation of a predictive tool to test CFTR modulator treatment response in people with cystic fibrosis

BackgroundInnovative treatments for rare diseases often strain healthcare budgets. Precision medicine can improve care and reduce costs by guiding treatment allocation. One example is the forskolin-induced swelling (FIS) assay, which uses patient-derived organoids to predict-response to Cystic Fibrosis Transmembrane conductance Regulator (CFTR) modulators in people with Cystic Fibrosis (pwCF). However, it remains unclear when and for whom this assay adds most value. Therefore, the impact of assay accuracy and target population on health-benefits and costs needs assessment. Research questionTo quantify the impact of sensitivity, specificity and target population on health benefits and costs to inform further development of a predictive assay to guide treatment allocation in pwCF. Study design and methodsAn early economic evaluation was conducted using a decision tree and Markov model. Two strategies were compared over a 40-year horizon: (i) treat all pwCF with CFTR modulators and (ii) predict-response using the FIS assay to guide treatment. Scenario analyses varied assay sensitivity, specificity and treatment responsiveness, reflecting subpopulations of pwCF, including rare CFTR variants. Outcomes included quality-adjusted life years (QALY), false negative rates and costs. Model inputs were based on literature on pwCF with F508del mutations. ResultsThe primary analysis yielded a loss of 1.22 QALYs, with {euro}2,16 million cost-savings per patient in the predict-response strategy. Increasing assay sensitivity reduced QALY loss and false negatives while maintaining cost-savings, while specificity had limited effect on outcomes. Lower treatment responsiveness reduced QALY loss and false negatives while maintaining cost-savings. ConclusionThe assay appears most valuable in pwCF with rare CFTR variants, where treatment response is uncertain. Improving sensitivity is crucial to prevent QALY loss, especially in high-responder populations like pwCF with F508del. The model provides insights into variables impacting personalized testing and serves as a dynamic dashboard to explore scenarios once clinical data becomes available. Key pointsO_LIThis early economic evaluation provides insights in key variables affecting personalized testing to guide CFTR treatment allocation to inform further assay development. C_LIO_LIHigh assay sensitivity is crucial to prevent QALY loss in high responder CF populations, such as pwCF with F508del. C_LIO_LIThe FIS assay appears most value for pwCF with rare CFTR variants and uncertain treatment response. C_LI