Aims: The KWAY project aims to investigate the economic sustainability of the up-front NGS technologies adoption in the analysis of clinically relevant molecular alterations in NSCLC patients. Methods: The diagnostic workflow and the related sustained costs of five Italian referral centers were assessed in four different evolving scenarios were analyzed. For each scenario, two alternative testing strategies were evaluated: the Maximized Standard strategy and the Maximized NGS strategy. Results: For each center, the robustness of obtained results was verified through a deterministic sensitivity analysis, observing the variation of total costs based on a variation of ±20 % of the input parameters and ensuring that results would present a consistent behavior compared to the original ones. Conclusions: our project, highlighted that the adoption of NGS allows to save personnel time dedicated to testing activities and to reduce the overall cost of testing per patient.
Pisapia, P., Pepe, F., Baggi, A., Barberis, M., Galvano, A., Gristina, V., et al. (2022). Next generation diagnostic algorithm in non-small cell lung cancer predictive molecular pathology: The KWAY Italian multicenter cost evaluation study. CRITICAL REVIEWS IN ONCOLOGY HEMATOLOGY, 169(January 2022) [10.1016/j.critrevonc.2021.103525].
Next generation diagnostic algorithm in non-small cell lung cancer predictive molecular pathology: The KWAY Italian multicenter cost evaluation study
Pagni F.;
2022
Abstract
Aims: The KWAY project aims to investigate the economic sustainability of the up-front NGS technologies adoption in the analysis of clinically relevant molecular alterations in NSCLC patients. Methods: The diagnostic workflow and the related sustained costs of five Italian referral centers were assessed in four different evolving scenarios were analyzed. For each scenario, two alternative testing strategies were evaluated: the Maximized Standard strategy and the Maximized NGS strategy. Results: For each center, the robustness of obtained results was verified through a deterministic sensitivity analysis, observing the variation of total costs based on a variation of ±20 % of the input parameters and ensuring that results would present a consistent behavior compared to the original ones. Conclusions: our project, highlighted that the adoption of NGS allows to save personnel time dedicated to testing activities and to reduce the overall cost of testing per patient.
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