Clinical and analytical validation of FoundationOne®CDx, a comprehensive genomic profiling assay for solid tumors.

FoundationOne®CDx (F1CDx) is a United States (US) Food and Drug Administration (FDA)-approved companion diagnostic test to identify patients who may benefit from treatment in accordance with the approved therapeutic product labeling for 28 drug therapies. F1CDx utilizes next-generation sequencing (NGS)-based comprehensive genomic profiling (CGP) technology to examine 324 cancer genes in solid tumors. F1CDx reports known and likely pathogenic short variants (SVs), copy number alterations (CNAs), and select rearrangements, as well as complex biomarkers including tumor mutational burden (TMB) and microsatellite instability (MSI), in addition to genomic loss of heterozygosity (gLOH) in ovarian cancer. CGP services can reduce the complexity of biomarker testing, enabling precision medicine to improve treatment decision-making and outcomes for cancer patients, but only if test results are reliable, accurate, and validated clinically and analytically to the highest standard available. The analyses presented herein demonstrate the extensive analytical and clinical validation supporting the F1CDx initial and subsequent FDA approvals to ensure high sensitivity, specificity, and reliability of the data reported. The analytical validation included several in-depth evaluations of F1CDx assay performance including limit of detection (LoD), limit of blank (LoB), precision, and orthogonal concordance for SVs (including base substitutions [SUBs] and insertions/deletions [INDELs]), CNAs (including amplifications and homozygous deletions), genomic rearrangements, and select complex biomarkers. The assay validation of >30,000 test results comprises a considerable and increasing body of evidence that supports the clinical utility of F1CDx to match patients with solid tumors to targeted therapies or immunotherapies based on their tumor's genomic alterations and biomarkers. F1CDx meets the clinical needs of providers and patients to receive guideline-based biomarker testing, helping them keep pace with a rapidly evolving field of medicine.

Budget Impact Analysis of Comprehensive Genomic Profiling in Patients With Advanced Non-Small-Cell Lung Cancer.

PURPOSE: This study assessed the economic impact of increased use of comprehensive genomic profiling (CGP) versus conventional testing strategies among patients with advanced non-small-cell lung cancer (aNSCLC) from a US commercial health plan perspective. METHODS: A decision analytic model was developed to estimate the incremental benefits and costs across testing methodologies (CGP v non-CGP), as well as across sample types (tissue-based and liquid-based), for patients with newly diagnosed aNSCLC. Model outcomes included total direct costs, testing costs, and per member per month budget impact. Secondary model outcomes included the number of patients needed to test with CGP to add 1 life-year, and the number of patients needed to test with CGP to treat one individual with a biomarker-matched therapy. RESULTS: In a hypothetical 2,000,000-member health plan, 790 members were estimated to have incident aNSCLC; 609 underwent molecular diagnostic testing with 122 (20%) tested with CGP (109 tissue-based and 13 liquid) in the base-case. An increase in CGP from 20% to 30% (an additional 61 patients tested with CGP) was associated with 3.11 additional life-years gained and a $0.01 in US dollars per member per month budget impact. Approximately 19.6 patients would need to be tested with CGP versus non-CGP to add one life-year and 5.9 patients would need to be tested with CGP to treat at least one patient with a biomarker-matched therapy. CONCLUSION: An increase in CGP from 20% to 30% among patients with aNSCLC undergoing molecular diagnostic testing was associated with modest budget impact, most of which was attributable to prolonged survival associated with increased use of more effective treatments.

Bar-code-assisted medication administration: a method for predicting repackaging resource needs.

PURPOSE: Results of a study at two hospitals to validate and test systems for bar-code-assisted medication administration (BCMA) are reported, including data on bar-code scanning failures and BCMA-related staff resource needs. METHODS: To prepare for BCMA implementation, pharmacy inventories at the two study sites were characterized by scanning product bar codes with a handheld device. The custom database built to house BCMA data was programmed to match National Drug Code (NDC) information on package labels with NDC information in the BCMA database. The data collected during inventory scanning were used (1) to quantify and address failed bar-code scans, (2) to predict the number of products that would require repackaging and relabeling to ensure accurate bedside scans, and (3) to estimate full-time equivalent (FTE) staff resources for BCMA-related repackaging work. RESULTS: During inventory assessment, scanning failures occurred with about 12.5% of products at the two pharmacy sites, mainly due to the absence of a bar-code label (49-53% of failed scans) or the inability to identify NDCs within the package bar code (38-46% of failed scans). It was determined that 8-10% of products inventoried at the two sites would require repackaging before dispensing, with associated technician resource needs estimated at 0.3-0.5 unit of FTE labor. CONCLUSION: The results of inventory scanning revealed that most failed scans were attributable to the lack of a bar code on some products or problems with NDC recognition by the BCMA database. After those problems were addressed, a three-month pilot test on one patient care unit indicated an overall scanning success rate of >96%.