Guided therapy selection in rheumatoid arthritis using a molecular signature response classifier: an assessment of budget impact and clinical utility.

BACKGROUND: Patients with moderate to severe rheumatoid arthritis (RA) can be treated with a range of targeted therapies following inadequate response to conventional synthetic disease-modifying antirheumatic drugs such as methotrexate. Whereas clinical practice guidelines provide no formal recommendations for initial targeted therapies, the tumor necrosis factor alpha inhibitor (TNFi) class is the prevalent first-line selection based on clinician experience, its safety profile, and/or formulary requirements, while also being the costliest. Most patients do not achieve adequate clinical response with a first-line TNFi, however. A molecular signature response classifier (MSRC) test that assesses RA-related biomarkers can identify patients who are unlikely to achieve adequate response to TNFi-class therapies. OBJECTIVE: To model cost-effectiveness of MSRC-guided, first-line targeted therapy selection compared with current standard care. METHODS: This budget impact analysis used data sourced from August to September 2020. The prevalence of each first-line targeted therapy was obtained using market intelligence from Datamonitor/Informa PLC Rheumatology Dashboard Forecast 2020, and the average first-year cost of treatment for each class was calculated using wholesale acquisition costs from IBM Micromedex RED BOOK Online. Average effectiveness for each class was based on manufacturer-reported ACR50 response rates (American College of Rheumatology adequate response criteria of 50% improvement at 6 months after therapy initiation). The impact of MSRC testing on first therapy selection was predicted based on a third party-generated decision-impact study that analyzed potential alterations in rheumatologist prescribing patterns after receiving MSRC test reports. Sensitivity analysis evaluated potential impacts of variation in first-year medication cost, adherence to MSRC report, and test price on the first-year cost of treatment. Cost for response (first-year therapy cost therapy divided by probability of achieving ACR50) was compared between standard care and MSRC-guided care. RESULTS: The estimated cost for first-year, standard-care treatment was $65,117, with 80% of patients initiating treatment with a TNFi. Cost for achieving ACR50 response was $177,046. After applying MSRC-guided patient stratification and therapy selection, the first-year cost was $56,543, net of test price, with 49.0% of patients initiating with a TNFi. First-year MSRC-guided care cost, including test price, was estimated at $117,103, a 33.9% improvement over standard care. Sensitivity analysis showed a net cost improvement for guided care vs standard care across all scenarios. Patients predicted to be inadequate TNFi responders, when modeled with lower-priced alternatives, were predicted to show increased ACR50 response rates. Those with MSRC test results indicating a first-line TNFi were predicted to show an ACR50 response rate superior to that for any other class. In this model, if implemented clinically, MSRC-guided care might save the US health care system more than $850 million annually and improve ACR50 by up to 31.3%. CONCLUSIONS: Precision medicine using MSRC-guided patient stratification and therapy selection may both decrease cost and improve efficacy of targeted RA therapies. DISCLOSURES: This work was funded in full by Scipher Medicine Corporation, which participated in data analysis and interpretation and drafting, reviewing, and approving the publication. All authors contributed to data analysis and interpretation and publication preparation, maintaining control over the final content. Arnell, Withers, and Connolly-Strong are employees of and have stock ownership in Scipher Medicine Corporation. Bergman has received consulting fees from AbbVie, Gilead, GlaxoSmithKline, Novartis, Pfizer, Regeneron, Sanofi, and Scipher Medicine and owns stock or stock options in Johnson & Johnson. Kenney, Logan, and Lim-Harashima are consultants for Scipher Medicine Corporation. Basu has nothing to disclose.

Impact of Payer Constraints on Access to Genetic Testing.

BACKGROUND: With increased demand for hereditary cancer genetic testing, some large national health-care insurance payers (LNHPs) have implemented policies to minimize inappropriate testing by mandating consultation with a geneticist or genetic counselor (GC). We hypothesized such a restriction would reduce access and appropriate testing. METHODS: Test cancellation rates (ie, tests ordered that did not result in a reported test result), mutation-positive rates, and turnaround times for comprehensive BRCA1/2 testing for a study LNHP that implemented a GC-mandate policy were determined over the 12 months before and after policy implementation (excluding a 4-month transition period). Cancellation rates were evaluated based on the reason for cancellation, National Comprehensive Cancer Network testing criteria, and self-identified ancestry. A control LNHP was evaluated over the same period for comparison. RESULTS: The study LNHP cancellation rate increased from 13.3% to 42.1% ( P < .001) after policy implementation. This increase was also observed when only individuals who met National Comprehensive Cancer Network criteria for hereditary breast and ovarian cancer testing were considered (9.5% to 37.7%; P < .001). Cancellation rates increased after policy introduction for all ancestries; however, this was more pronounced among individuals of African or Latin American ancestry, for whom cancellation rates rose to 48.9% and 49.6%, respectively, compared with 33.9% for individuals of European ancestry. Over this same time period, control LNHP cancellation rates decreased or stayed the same for all subgroups. CONCLUSION: These findings demonstrate that a GC-mandate policy implemented by a LNHP substantially decreased access to appropriate genetic testing, disproportionately impacting minority populations without any evidence that inappropriate testing was decreased.

Optimization of quality assurance to increase clinical utility and cost effectiveness of hereditary cancer testing.

AIM: To evaluate one laboratory's hereditary cancer testing clinical quality assurance (QA) process to minimize test-ordering errors. METHODS: The proportion of tests canceled/revised due to pre-analytic QA processes or provider consultation prior to test ordering were determined and the resulting health cost savings were estimated. RESULTS: Over 2000 genetic test orders were canceled/revised over a 1-year period due to the laboratory QA process, saving US$5,801,832 in healthcare costs. Consultation with healthcare providers prior to submitting genetic test requests resulted in 37 canceled/revised test orders in a 2-week period, which extrapolates to a savings of US$3,049,098 over 1 year. CONCLUSION: QA processes can contribute to the curtailment of healthcare costs through canceling or revising test orders.

Patients Tested at a Laboratory for Hereditary Cancer Syndromes Show an Overlap for Multiple Syndromes in Their Personal and Familial Cancer Histories.

OBJECTIVE: Hereditary cancer testing guidelines are based on the premise that the common hereditary cancer syndromes have distinct, recognizable phenotypes. However, many syndromes present with overlapping cancers. The aim of this analysis was to identify the proportion of patients tested for Lynch syndrome (LS) or hereditary breast and ovarian cancer (HBOC) who met testing criteria for the other syndrome. METHOD: We analyzed a commercial laboratory database of patients tested for LS and HBOC in a clinical setting from 2006 to 2013. Patient cancer histories were analyzed using the 2012 NCCN criteria for LS and the 2013 NCCN criteria for HBOC. RESULTS: In all, 7% of the patients tested for HBOC met criteria for LS testing. The majority of these patients had a family history of colorectal (30.9%) and/or endometrial cancer (22.7%). Conversely, 29.5% of the patients tested for LS met criteria for HBOC testing. In this group, 30.5% of the patients had a personal history of breast cancer, and 12.6% had a personal history of ovarian cancer. CONCLUSIONS: Our data demonstrate a substantial phenotypic overlap among patients for multiple common inherited cancer syndromes, which likely complicates diagnosis and test selection. This supports the value of multigene panels to identify pathogenic mutations in the absence of a clinically specific phenotype.

Erratum to: Incidence of BRCA1 and BRCA2 non-founder mutations in patients of Ashkenazi Jewish ancestry.

In Table 2 of the original publication, the HGVS and legacy nomenclature were mismatched and the HGVS nomenclature did not correlate with data listed in the table. The corrected table is listed below.

Incidence of BRCA1 and BRCA2 non-founder mutations in patients of Ashkenazi Jewish ancestry.

An estimated 1:40 individuals of Ashkenazi Jewish (AJ) ancestry carry one of three common founder mutations in BRCA1 or BRCA2, resulting in the inherited cancer condition, Hereditary Breast and Ovarian Cancer (HBOC) syndrome. Targeted testing for these three mutations (BRCA1 187delAG, BRCA1 5385insC, and BRCA2 6174delT) is therefore recommended for all AJ breast and ovarian cancer patients, regardless of age of diagnosis or family history. Comprehensive analysis of both genes is recommended for a subset of AJ patients in whom founder mutations are not identified, but estimates of the yield from comprehensive analysis in this population vary widely. We sought to determine the proportion of non-founder mutations as a percentage of all mutations in BRCA1 and BRCA2 among AJ patients to inform decisions about HBOC testing strategies in this population. We analyzed the genetic testing results for 37,952 AJ patients for whom clinical testing of BRCA1 and BRCA2 was performed at Myriad Genetic Laboratories from January 2006 through August 2013. Analysis was limited to AJ-only patients for whom the initial test order was either (1) comprehensive testing, or (2) founder mutation testing with instructions to automatically "reflex" to comprehensive analysis if negative. Cases were excluded if a separate follow-up order was placed to reflex to comprehensive analysis only after the founder mutation testing was reported out as negative. Among all BRCA1 and BRCA2 mutations detected in these groups, the percentage of non-founder mutations was 13 % (104/802) and 7.2 % (198/2,769). One-hundred and eighty-nine unique non-founder mutations were detected, 76 in BRCA1 and 113 in BRCA2. Non-founder mutations make up between 7.2 and 13.0 % of all BRCA1 and BRCA2 mutations in Ashkenazi Jews. A wide range of mutations are present, most of which are also seen in non-AJ individuals.

Hereditary cancer-associated mutations in women diagnosed with two primary cancers: an opportunity to identify hereditary cancer syndromes after the first cancer diagnosis.

OBJECTIVES: Patients with hereditary cancer syndromes are at high risk for a second primary cancer. Early identification of these patients after an initial cancer diagnosis is the key to implementing cancer risk-reducing strategies. METHODS: A commercial laboratory database was searched for women with a history of both breast and ovarian or colorectal and endometrial cancer who underwent genetic testing for hereditary breast and ovarian cancer (HBOC) or Lynch syndrome (LS). RESULTS: Among women with both breast and ovarian cancer, 22.4% (2,237/9,982) had a BRCA1 or BRCA2 mutation. Among women with both colorectal and ovarian cancer, 28.1% (264/941) had a mutation associated with LS. In 66.6% of BRCA1 or BRCA2 mutation carriers and in 58.3% of LS mutation carriers, >5 years passed between the cancer diagnoses. Of patients with HBOC and LS, 56 and 65.2%, respectively, met the National Comprehensive Cancer Network guidelines for hereditary cancer testing after their initial diagnosis based on their personal cancer history alone. CONCLUSIONS: A substantial number of women tested for LS or HBOC after being diagnosed with two successive primary cancers were diagnosed with a hereditary cancer syndrome. In many cases, the time interval between the diagnoses was long enough to allow for the implementation of surveillance and/or prophylactic measures.

Design and validation of an oligonucleotide microarray for the detection of genomic rearrangements associated with common hereditary cancer syndromes.

BACKGROUND: Conventional Sanger sequencing reliably detects the majority of genetic mutations associated with hereditary cancers, such as single-base changes and small insertions or deletions. However, detection of genomic rearrangements, such as large deletions and duplications, requires special technologies. Microarray analysis has been successfully used to detect large rearrangements (LRs) in genetic disorders. METHODS: We designed and validated a high-density oligonucleotide microarray for the detection of gene-level genomic rearrangements associated with hereditary breast and ovarian cancer (HBOC), Lynch, and polyposis syndromes. The microarray consisted of probes corresponding to the exons and flanking introns of BRCA1 and BRCA2 (≈1,700) and Lynch syndrome/polyposis genes MLH1, MSH2, MSH6, APC, MUTYH, and EPCAM (≈2,200). We validated the microarray with 990 samples previously tested for LR status in BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, MUTYH, or EPCAM. Microarray results were 100% concordant with previous results in the validation studies. Subsequently, clinical microarray analysis was performed on samples from patients with a high likelihood of HBOC mutations (13,124), Lynch syndrome mutations (18,498), and polyposis syndrome mutations (2,739) to determine the proportion of LRs. RESULTS: Our results demonstrate that LRs constitute a substantial proportion of genetic mutations found in patients referred for hereditary cancer genetic testing. CONCLUSION: The use of microarray comparative genomic hybridization (CGH) for the detection of LRs is well-suited as an adjunct technology for both single syndrome (by Sanger sequencing analysis) and extended gene panel testing by next generation sequencing analysis. Genetic testing strategies using microarray analysis will help identify additional patients carrying LRs, who are predisposed to various hereditary cancers.

Clinical significance of large rearrangements in BRCA1 and BRCA2.

BACKGROUND: Current estimates of the contribution of large rearrangement (LR) mutations in the BRCA1 (breast cancer 1, early onset) and BRCA2 (breast cancer 2, early onset) genes responsible for hereditary breast and ovarian cancer are based on limited studies of relatively homogeneous patient populations. The prevalence of BRCA1/2 LRs was investigated in 48,456 patients with diverse clinical histories and ancestries, referred for clinical molecular testing for suspicion of hereditary breast and ovarian cancer. METHODS: Sanger sequencing analysis was performed for BRCA1/2 and LR testing for deletions and duplications using a quantitative multiplex polymerase chain reaction assay. Prevalence data were analyzed for patients from different risk and ethnic groups between July 2007 and April 2011. Patients were designated as "high-risk" if their clinical history predicted a high prior probability, wherein LR testing was performed automatically in conjunction with sequencing. "Elective" patients did not meet the high-risk criteria, but underwent LR testing as ordered by the referring health care provider. RESULTS: Overall BRCA1/2 mutation prevalence among high-risk patients was 23.8% versus 8.2% for the elective group. The mutation profile for high-risk patients was 90.1% sequencing mutations versus 9.9% LRs, and for elective patients, 94.1% sequencing versus 5.9% LRs. This difference may reflect the bias in high-risk patients to carry mutations in BRCA1, which has a higher penetrance and frequency of LRs compared with BRCA2. There were significant differences in the prevalence and types of LRs in patients of different ancestries. LR mutations were significantly more common in Latin American/Caribbean patients. CONCLUSIONS: Comprehensive LR testing in conjunction with full gene sequencing is an appropriate strategy for clinical BRCA1/2 analysis.