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RESEARCH PRODUCT
Next generation diagnostic algorithm in non-small cell lung cancer predictive molecular pathology: The KWAY Italian multicenter cost evaluation study
Daniela RighiGiuseppe PerroneAntonio GalvanoGiancarlo TronconeUmberto MalapelleSilvia PasiniSilvia NovelloPasquale PisapiaFabrizio MastrilliMassimo BarberisValerio GristinaFabio PagniAntonio RussoFrancesco PepeAnna Baggisubject
Predictive molecular pathologyLung NeoplasmsTotal costCostCost; NGS; NSCLC; Predictive molecular pathology; Single-gene test; Algorithms; High-Throughput Nucleotide Sequencing; Humans; Italy; Multicenter Studies as Topic; Carcinoma Non-Small-Cell Lung; Lung NeoplasmsNSCLCRobustness (computer science)Carcinoma Non-Small-Cell LungCost evaluationMedicineHumansMulticenter Studies as TopicNon-Small-Cell LungMolecular pathologybusiness.industryCarcinomaHigh-Throughput Nucleotide SequencingHematologyReliability engineeringWorkflowOncologyEconomic sustainabilityItalyNGSSingle-gene testNon small cellbusinessAlgorithmsdescription
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.
year | journal | country | edition | language |
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2022-01-01 |