Next-generation sequencing panels for the diagnosis of colorectal cancer and polyposis syndromes: A cost-effectiveness analysis

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Abstract

Purpose: To evaluate the cost effectiveness of next-generation sequencing (NGS) panels for the diagnosis of colorectal cancer and polyposis (CRCP) syndromes in patients referred to cancer genetics clinics. Patients and Methods: We developed a decision model to evaluate NGS panel testing compared with current standard of care in patients referred to a cancer genetics clinic. We obtained data on the prevalence of genetic variants from a large academic laboratory and calculated the costs and health benefits of identifying relatives with a pathogenic variant, in life-years and quality-adjusted life-years (QALYs). We classified the CRCP syndromes according to their type of inheritance and penetrance of colorectal cancer. One-way and probabilistic sensitivity analyses were conducted to assess uncertainty. Results: Evaluation with an NGS panel that included Lynch syndrome genes and other genes associated with highly penetrant CRCP syndromes led to an average increase of 0.151 year of life, 0.128 QALY, and $4,650 per patient, resulting in an incremental cost-effectiveness ratio of $36,500 per QALY compared with standard care and a 99% probability that this panel was cost effective at a threshold of $100,000 per QALY. When compared with this panel, the addition of genes with low colorectal cancer penetrance resulted in an incremental cost-effectiveness ratio of $77,300 per QALY. Conclusion: The use of an NGS panel that includes genes associated with highly penetrant CRCP syndromes in addition to Lynch syndrome genes as a first-line test is likely to provide meaningful clinical benefits in a cost-effective manner at a $100,000 per QALY threshold.

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APA

Gallego, C. J., Shirts, B. H., Bennette, C. S., Guzauskas, G., Amendola, L. M., Horike-Pyne, M., … Veenstra, D. L. (2015). Next-generation sequencing panels for the diagnosis of colorectal cancer and polyposis syndromes: A cost-effectiveness analysis. Journal of Clinical Oncology, 33(18), 2084–2091. https://doi.org/10.1200/JCO.2014.59.3665

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