Population Genomic Screening for Three Common Hereditary Conditions : A Cost-Effectiveness Analysis.

BACKGROUND: The cost-effectiveness of screening the U.S. population for Centers for Disease Control and Prevention (CDC) Tier 1 genomic conditions is unknown. OBJECTIVE: To estimate the cost-effectiveness of simultaneous genomic screening for Lynch syndrome (LS), hereditary breast and ovarian cancer syndrome (HBOC), and familial hypercholesterolemia (FH). DESIGN: Decision analytic Markov model. DATA SOURCES: Published literature. TARGET POPULATION: Separate age-based cohorts (ages 20 to 60 years at time of screening) of racially and ethnically representative U.S. adults. TIME HORIZON: Lifetime. PERSPECTIVE: U.S. health care payer. INTERVENTION: Population genomic screening using clinical sequencing with a restricted panel of high-evidence genes, cascade testing of first-degree relatives, and recommended preventive interventions for identified probands. OUTCOME MEASURES: Incident breast, ovarian, and colorectal cancer cases; incident cardiovascular events; quality-adjusted survival; and costs. RESULTS OF BASE-CASE ANALYSIS: Screening 100 000 unselected 30-year-olds resulted in 101 (95% uncertainty interval [UI], 77 to 127) fewer overall cancer cases and 15 (95% UI, 4 to 28) fewer cardiovascular events and an increase of 495 quality-adjusted life-years (QALYs) (95% UI, 401 to 757) at an incremental cost of $33.9 million (95% UI, $27.0 million to $41.1 million). The incremental cost-effectiveness ratio was $68 600 per QALY gained (95% UI, $41 800 to $88 900). RESULTS OF SENSITIVITY ANALYSIS: Screening 30-, 40-, and 50-year-old cohorts was cost-effective in 99%, 88%, and 19% of probabilistic simulations, respectively, at a $100 000-per-QALY threshold. The test costs at which screening 30-, 40-, and 50-year-olds reached the $100 000-per-QALY threshold were $413, $290, and $166, respectively. Variant prevalence and adherence to preventive interventions were also highly influential parameters. LIMITATIONS: Population averages for model inputs, which were derived predominantly from European populations, vary across ancestries and health care environments. CONCLUSION: Population genomic screening with a restricted panel of high-evidence genes associated with 3 CDC Tier 1 conditions is likely to be cost-effective in U.S. adults younger than 40 years if the testing cost is relatively low and probands have access to preventive interventions. PRIMARY FUNDING SOURCE: National Human Genome Research Institute.

Cost-effectiveness of population-wide genomic screening for familial hypercholesterolemia in the United States.

BACKGROUND: Population genomic screening for familial hypercholesterolemia (FH) in unselected individuals can prevent premature cardiovascular disease. OBJECTIVE: To estimate the clinical and economic outcomes of population-wide FH genomic screening versus no genomic screening. METHODS: We developed a decision tree plus 10-state Markov model evaluating the identification of patients with an FH variant, statin treatment status, LDL-C levels, MI, and stroke to compare the costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness of population-wide FH genomic screening. FH variant prevalence (0.4%) was estimated from the Geisinger MyCode Community Health Initiative (MyCode). Genomic test costs were assumed to be $200. Age and sex-based estimates of MI, recurrent MI, stroke, and recurrent stroke were obtained from Framingham risk equations. Additional outcomes independently associated with FH variants were derived from a retrospective analysis of 26,025 participants screened for FH. Sensitivity and threshold analyses were conducted to evaluate model assumptions and uncertainty. RESULTS: FH screening was most effective at younger ages; screening unselected 20-year-olds lead to 111 QALYs gained per 100,000 individuals screened at an incremental cost of $20 M. The incremental cost-effectiveness ratio (ICER) for 20-year-olds was $181,000 per QALY, and there was a 38% probability of cost-effectiveness at a $100,000 per QALY willingness-to-pay threshold. If genomic testing cost falls to $100, the ICER would be $91,000 per QALY. CONCLUSION: Population FH screening is not cost-effective at current willingness to pay thresholds. However, reducing test costs, testing at younger ages, or including FH within broader multiplex screening panels may improve clinical and economic value.

Cost-effectiveness of population-wide genomic screening for Lynch syndrome in the United States.

PURPOSE: Genomic screening for Lynch syndrome (LS) could prevent colorectal cancer (CRC) by identifying high-risk patients and instituting intensive CRC screening. We estimated the cost-effectiveness of a population-wide LS genomic screening vs family history-based screening alone in an unselected US population. METHODS: We developed a decision-analytic Markov model including health states for precancer, stage-specific CRC, and death and assumed an inexpensive test cost of $200. We conducted sensitivity and threshold analyses to evaluate model uncertainty. RESULTS: Screening unselected 30-year-olds for LS variants resulted in 48 (95% credible range [CR] = 35-63) fewer overall CRC cases per 100,000 screened individuals, leading to 187 quality-adjusted life-years (QALYs; 95% CR = 123-260) gained at an incremental cost of $24.6 million (95% CR = $20.3 million-$29.1 million). The incremental cost-effectiveness ratio was $132,200, with an 8% and 71% probability of being cost-effective at $100,000 and $150,000 per QALY willingness-to-pay thresholds, respectively. CONCLUSION: Population LS screening may be cost-effective in younger patient populations under a $150,000 willingness-to-pay per QALY threshold and with a relatively inexpensive test cost. Further reductions in testing costs and/or the inclusion of LS testing within a broader multiplex screening panel are needed for screening to become highly cost-effective.

Cost-effectiveness of obinutuzumab versus rituximab biosimilars for previously untreated follicular lymphoma.

BACKGROUND: In the randomized phase 3 GALLIUM trial, first-line treatment with obinutuzumab (GA101; G) plus chemotherapy (G + chemo) resulted in superior progression-free survival (PFS) compared with rituximab plus chemotherapy (R + chemo) for patients with follicular lymphoma (FL). G + chemo was found to be cost-effective when compared with R + chemo (incremental cost-effectiveness ratio [ICER] of approximately $2,300 per quality-adjusted life-year [QALY] gained). Two rituximab biosimilars, rituximab-abbs (Ra) and rituximab-pvvr (Rp), have been approved by the FDA for use in this setting. However, the cost-effectiveness of G + chemo versus Ra + chemo and Rp + chemo has not yet been estimated. OBJECTIVE: To evaluate the cost-effectiveness of G + chemo versus Ra + chemo and Rp + chemo in the first-line treatment of FL. METHODS: We adapted an existing Markov model that compared G + chemo with R + chemo, using investigator-assessed PFS and postprogression survival data from the GALLIUM trial to model overall survival. All patients in the study received induction chemoimmunotherapy with either G + chemo or R + chemo, with responders then receiving obinutuzumab or rituximab maintenance therapy for 2 years or until disease progression. We assumed that the efficacy and safety of the rituximab biosimilars plus chemotherapy were the same as the R + chemo arm of the GALLIUM study. Drug utilization and treatment duration were also derived from GALLIUM. Health care costs were based on Medicare reimbursements, and drug costs were average sale prices for intravenous therapies or wholesale acquisition costs for oral therapies used after progression. Utility estimates were based on the GALLIUM trial data and published literature. Sensitivity analyses were conducted to assess the key drivers of the model and uncertainty in the results. Results: Treatment with G + chemo led to an increase of 0.93 QALYs relative to rituximab biosimilars plus chemotherapy (95% credible range [CR] = 0.36-1.46). The total cost of G + chemo was $191,317, whereas the total costs of Ra + chemo and Rp + chemo were $164,340 (Δ14.1%) and $169,755 (Δ11.3%), respectively, with G + chemo resulting in incremental costs of $26,978 (95% CR = $19,781-$33,119) and $21,562 (95% CR = $14,473-$28,389), respectively. The incremental total drug and administration costs were $32,678 (Δ25.4%) and $27,263 (Δ21.2%) for G + chemo versus Ra + chemo and G + chemo versus Rp + chemo, respectively. There were cost savings of $7,050 (Δ-12.4%) related to disease progression for G + chemo ($56,727) compared with Ra + chemo and Rp + chemo ($63,777). ICERs were $28,879 and $23,082 per QALY gained for G + chemo versus Ra + chemo and Rp + chemo, respectively. In probabilistic sensitivity analyses, G + chemo was cost-effective at the $50,000 and $100,000 per QALY thresholds versus both Ra + chemo (88% and 98% probabilities of cost-effectiveness, respectively) and Rp + chemo (93% and 98%, respectively). CONCLUSIONS: G + chemo is projected to be cost-effective versus rituximab biosimilars plus chemotherapy in the United States as first-line treatment for FL, driven by increased QALYs for G + chemo and cost savings from delayed disease progression. DISCLOSURES: This study was funded by Genentech, a member of the Roche Group. The study sponsor was involved in study design, data interpretation, and writing of the report. All authors approved the decision to submit the report for publication. Spencer and Guzauskas report fees from Genentech during the conduct of the study. Felizzi was employed by F. Hoffmann-La Roche at the time this study was conducted; Launonen is an employees of F. Hoffmann-La Roche. Felizzi and Launonen previously had share ownership in Novartis. Dawson and Masaquel are employees of Genentech, and they have stock options in F. Hoffmann-La Roche. Veenstra reports fees from Genentech, during the conduct of this study and outside of the submitted work. This work was presented, in part, at the AACR Virtual Meeting Advances in Malignant Lymphoma meeting (virtual; August 17-19, 2020) and the SOHO annual meeting (virtual; September 9-12, 2020).

Cost-effectiveness of Population-Wide Genomic Screening for Hereditary Breast and Ovarian Cancer in the United States.

Importance: Genomic screening for hereditary breast and ovarian cancer (HBOC) in unselected women offers an opportunity to prevent cancer morbidity and mortality, but the potential clinical impact and cost-effectiveness of such screening have not been well studied. Objective: To estimate the lifetime incremental incidence of HBOC and the quality-adjusted life-years (QALYs), costs, and cost-effectiveness of HBOC genomic screening in an unselected population vs family history-based testing. Design, Setting, and Participants: In this study conducted from October 27, 2017, to May 3, 2020, a decision analytic Markov model was developed that included health states for precancer, for risk-reducing mastectomy (RRM) and risk-reducing salpingo-oophorectomy (RRSO), for earlier- and later-stage HBOC, after cancer, and for death. A complimentary cascade testing module was also developed to estimate outcomes in first-degree relatives. Age-specific RRM and RRSO uptake probabilities were estimated from the Geisinger MyCode Community Health Initiative and published sources. Parameters including RRM and RRSO effectiveness, variant-specific cancer risk, costs, and utilities were derived from published sources. Sensitivity and scenario analyses were conducted to evaluate model assumptions and uncertainty. Main Outcomes and Measures: Lifetime cancer incidence, QALYs, life-years, and direct medical costs for genomic screening in an unselected population vs family history-based testing only were calculated. The incremental cost-effectiveness ratio (ICER) was calculated as the difference in cost between strategies divided by the difference in QALYs between strategies. Earlier-stage and later-stage cancer cases prevented and total cancer cases prevented were also calculated. Results: The model found that population screening of 30-year-old women was associated with 75 (95% credible range [CR], 60-90) fewer overall cancer cases and 288 QALYs (95% CR, 212-373 QALYs) gained per 100 000 women screened, at an incremental cost of $25 million (95% CR, $21 millon to $30 million) vs family history-based testing; the ICER was $87 700 (78% probability of being cost-effective at a threshold of $100 000 per QALY). In contrast, population screening of 45-year-old women was associated with 24 (95% CR, 18-29) fewer cancer cases and 97 QALYs (95% CR, 66-130 QALYs) gained per 100 000 women screened, at an incremental cost of $26 million (95% CR, $22 million to $30 million); the ICER was $268 200 (0% probability of being cost-effective at a threshold of $100 000 per QALY). A scenario analysis without cascade testing increased the ICER to $92 600 for 30-year-old women and $354 500 for 45-year-old women. A scenario analysis assuming a 5% absolute decrease in mammography screening in women without a variant was associated with the potential for net harm (-90 QALYs per 100 000 women screened; 95% CR, -180 to 10 QALYs). Conclusions and Relevance: The results of this study suggest that population HBOC screening may be cost-effective among younger women but not among older women. Cascade testing of first-degree relatives added a modest improvement in clinical and economic value. The potential for harm conferred by inappropriate reduction in mammography among noncarriers should be quantified.

Consideration for Employer-Based and Geographic Attributes Included in Value Assessment Methods of Next-Generation Sequencing Tests.

There is a need for formal cost-effectiveness evidence to better model the real-world payer decision context in which general economic models are currently being used, specifically regarding clinical genomics health services (for next-generation sequencing (NGS) tests). We reviewed literature focused on cost-effectiveness studies after completion of the Human Genome Project within the Tufts Cost-Effectiveness Analysis (CEA) Registry and found that only 33% of eligible studies were conducted from the U.S. payer perspective. Additional interpretation challenges include economic models that do not account for true payer-negotiated costs, limits in internal expertise for quality-adjusted life-year inferences, and limited internal policies to use CEA research in decision making. This Viewpoints article highlights numerous opportunities to increase the translational effect of economic modeling work. Specifically, geographically relevant cost and outcomes data should be considered for integration within best practices for economic evaluations of NGS tests. Such data integration may provide more informed decision making regarding the allocation of constrained resources for health care services and technology. DISCLOSURES: No outside funding supported the writing of this article. Hart is supported by an unrestricted gift from Pfizer, which played no role in the study referred to in this article. The authors have no conflicts of interest to report.