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Purpose: This study aimed to estimate the cost-effectiveness of exome sequencing (ES) and genome sequencing (GS) for children., Methods: We modeled costs, diagnoses, and quality-adjusted life years (QALYs) for diagnostic strategies for critically ill infants (aged <1 year) and children (aged <18 years) with suspected genetic conditions: (1) standard of care (SOC) testing, (2) ES, (3) GS, (4) SOC followed by ES, (5) SOC followed by GS, (6) ES followed by GS, and (7) SOC followed by ES followed by GS. We calculated the 10-year incremental cost per additional diagnosis, and lifetime incremental cost per QALY gained, from a health care perspective., Results: First-line GS costs $15,048 per diagnosis vs SOC for infants and $27,349 per diagnosis for children. If GS is unavailable, ES represents the next most efficient option compared with SOC ($15,543 per diagnosis for infants and $28,822 per diagnosis for children). Other strategies provided the same or fewer diagnoses at a higher incremental cost per diagnosis. Lifetime results depend on the patient's assumed long-term prognosis after diagnosis. For infants, GS ranged from cost-saving (vs all alternatives) to $18,877 per QALY (vs SOC). For children, GS (vs SOC) ranged from $119,705 to $490,047 per QALY., Conclusion: First-line GS may be the most cost-effective strategy for diagnosing infants with suspected genetic conditions. For all children, GS may be cost-effective under certain assumptions. ES is nearly as efficient as GS and hence is a viable option when GS is unavailable., Competing Interests: Conflict of Interest T.A.L., J.T.C., P.J.N., J.L.M., and M.K. received funding from the Personalized Medicine Coalition for their work on this project. T.A.L. has consulted for Merck and has received compensation. J.T.C. has consulted for Biogen, Iqvia Inc, Novartis AG, Partnership for Health Analytic Research, Pharmerit International, Precision Health Economics, Sage Pharmaceuticals, Sanofi, Sarepta, and RA Capital and has received compensation. P.J.N. has consulted for Precision HEOR, Sarepta and Cytokinetics and has received compensation. P.J.N. also served on the advisory board for Biogen; PhRMA Foundation; AveXis; Intercept; Bayer AG; Amgen Inc; Sanofi; Panalogo, LLC; and Merck. D.P. is employed by the Personalized Medicine Coalition, a 501(c)(3) non-profit organization that provided funding for the study. B.E.S. is an employee and stockholder of Illumina, Inc. X.F., D.S., P.S.E., and S.B.W. declare no conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: To estimate the cost-effectiveness of genome sequencing (GS) for diagnosing critically ill infants and noncritically ill pediatric patients (children) with suspected rare genetic diseases from a United States health sector perspective., Methods: A decision-analytic model was developed to simulate the diagnostic trajectory of patients. Parameter estimates were derived from a targeted literature review and meta-analysis. The model simulated clinical and economic outcomes associated with 3 diagnostic pathways: (1) standard diagnostic care, (2) GS, and (3) standard diagnostic care followed by GS., Results: For children, costs of GS ($7284) were similar to that of standard care ($7355) and lower than that of standard care followed by GS pathways ($12,030). In critically ill infants, when cost estimates were based on the length of stay in the neonatal intensive care unit, the lowest cost pathway was GS ($209,472). When only diagnostic test costs were included, the cost per diagnosis was $17,940 for standard, $17,019 for GS, and $20,255 for standard care followed by GS., Conclusion: The results of this economic model suggest that GS may be cost neutral or possibly cost saving as a first line diagnostic tool for children and critically ill infants., Competing Interests: Conflict of Interest Brock E. Schroeder, Nina Gonzaludo, John W. Belmont are employees and stockholders of Illumina, Inc. Devin Incerti, Xiang-Ming Xi, and Jacquelyn W. Chou are employed by Precision Health Economics, a health economics and outcomes research consultancy. The work described in this manuscript was funded by Illumina, Inc., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Accurate tumor classification is fundamental to inform predictive biomarker testing and optimize therapy. Gene expression-based tests are proposed as diagnostic aids in cases with uncertain diagnoses. This study directly compared the diagnostic accuracy of IHC analysis versus molecular classification using a 92-gene RT-PCR assay for determination of the primary tumor site. This prospectively defined blinded study of diagnostically challenging cases included 131 high-grade, primarily metastatic tumors. Cases were reviewed and reference diagnoses established through clinical correlation. Blinded FFPE sections were evaluated by either IHC/morphology analysis or the 92-gene assay. The final analysis included 122 cases. The 92-gene assay demonstrated overall accuracy of 79% (95% CI, 71% to 85%) for tumor classification versus 69% (95% CI, 60% to 76%) for IHC/morphology analysis (P = 0.019). Mean IHC use was 7.9 stains per case (median, 8; range, 2 to 15). IHC/morphology analysis accuracy was 79%, 80%, and 46% when 1 to 6 (n = 42), 7 to 9 (n = 41), and >9 (n = 39) IHC stains were used, respectively, versus 81%, 85%, and 69%, respectively, with the 92-gene assay. Results from this blinded series of high-grade metastatic cases demonstrate superior accuracy with the 92-gene assay versus standard-of-care IHC analysis and strongly support the diagnostic utility of molecular classification in difficult-to-diagnose metastatic cancer., (Copyright © 2013 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)