A cost-consequence model of using the 21-gene assay to identify patients with early-stage node-positive breast cancer who benefit from adjuvant chemotherapy in the Netherlands.

BACKGROUND: Patients with early-stage hormone receptor positive, human epidermal growth factor receptor-2 (HER2) negative invasive breast cancer with 1-3 positive lymph nodes (N1) often undergo surgical excisions followed by adjuvant chemotherapy (ACT). Many patients have no benefit from ACT and receive unnecessary, costly treatment often associated with short- and long-term adverse events (AEs). Gene expression profiling (GEP) assays, such as the 21-gene assay (i.e. the Oncotype DX assay), can identify patients at higher risk for recurrence who may benefit from ACT. However, the budgetary consequence of using the Oncotype DX assay versus no GEP testing in the Netherlands is unknown. Our study therefore assessed it using a cost-consequence model. METHODS: A validated model was used to create the N1 model. The model compared the costs and consequences of using the Oncotype DX assay versus no GEP testing and MammaPrint, and subsequent ACT use with corresponding costs for chemotherapy, treatment of AEs, productivity losses, GEP testing, and treatment of recurrences, according to the Oncotype DX results. The model time horizon was 5 years. RESULTS: Costs for the total population amounted to €8.0 million (M), €16.2 M, and €9.5 M, and cost per patient amounted to €13,540, €27,455, and €16,154 for using the Oncotype DX assay, no GEP testing, and MammaPrint, respectively. Total cost savings of using the Oncotype DX assay amounted to €8.2 M versus no GEP testing and €1.5 M versus MammaPrint. Using the Oncotype DX assay would result in fewer patients receiving ACT and thus fewer AEs, sick days, and hospitalizations, leading to overall cost savings compared with no GEP testing and MammaPrint. CONCLUSIONS: Implementing Oncotype DX testing in this population can prevent unnecessary overtreatment, reducing clinical and economic burden on the patient and Dutch healthcare system.

Early-stage invasive breast cancer patients often undergo surgery followed by adjuvant chemotherapy. However, many of these patients have no benefit from adjuvant chemotherapy and thus receive unnecessary and costly treatment often associated with side-effects. Patients who may benefit from adjuvant chemotherapy can be identified by analyzing the genomic profile of the patients' tumors using a molecular diagnostic test called the 21-gene assay (also known as Oncotype DX assay). However, the budgetary consequences of using Oncotype DX for this purpose in the Netherlands are currently unknown and, therefore, assessed using a health-economic model. The model compared the costs and consequences of using the Oncotype DX assay versus no molecular diagnostic testing and an alternative molecular diagnostic test called MammaPrint. The three diagnostic testing strategies resulted in different costs in terms of several different costing categories and were compared with one another. The total costs were lowest for the diagnostic strategy using the Oncotype DX assay, as it would result in fewer patients receiving adjuvant chemotherapy compared with no molecular diagnostic testing and MammaPrint. Implementing the Oncotype DX assay as a molecular diagnostic test can identify the right patient who benefits from chemotherapy (prevent over- and undertreatment) and lead to cost-savings, reducing the clinical and economic burden on the patient and Dutch healthcare system.

Exploring the Cost Effectiveness of a Whole-Genome Sequencing-Based Biomarker for Treatment Selection in Patients with Advanced Lung Cancer Ineligible for Targeted Therapy.

OBJECTIVE: We aimed to perform an early cost-effectiveness analysis of using a whole-genome sequencing-based tumor mutation burden (WGS-TMB), instead of programmed death-ligand 1 (PD-L1), for immunotherapy treatment selection in patients with non-squamous advanced/metastatic non-small cell lung cancer ineligible for targeted therapy, from a Dutch healthcare perspective. METHODS: A decision-model simulating individual patients with metastatic non-small cell lung cancer was used to evaluate diagnostic strategies to select first-line immunotherapy only or the immunotherapy plus chemotherapy combination. Treatment was selected using PD-L1 [A, current practice], WGS-TMB [B], and both PD-L1 and WGS-TMB [C]. Strategies D, E, and F take into account a patient's disease burden, in addition to PD-L1, WGS-TMB, and both PD-L1 and WGS-TMB, respectively. Disease burden was defined as a fast-growing tumor, a high number of metastases, and/or weight loss. A threshold of 10 mutations per mega-base was used to classify patients into TMB-high and TMB-low groups. Outcomes were discounted quality-adjusted life-years (QALYs) and healthcare costs measured from the start of first-line treatment to death. Healthcare costs includes drug acquisition, follow-up costs, and molecular diagnostic tests (i.e., standard diagnostic techniques and/or WGS for strategies involving TMB). Results were reported using the net monetary benefit at a willingness-to-pay threshold of €80,000/QALY. Additional scenario and threshold analyses were performed. RESULTS: Strategy B had the lowest QALYs (1.84) and lowest healthcare costs (€120,800). The highest QALYs and healthcare costs were 2.00 and €140,400 in strategy F. In the base-case analysis, strategy A was cost effective with the highest net monetary benefit (€27,300), followed by strategy B (€26,700). Strategy B was cost effective when the cost of WGS testing was decreased by at least 24% or when immunotherapy results in an additional 0.5 year of life gained or more for TMB high compared with TMB low. Strategies C and F, which combined TMB and PD-L1 had the highest net monetary benefit (≥ €76,900) when the cost of WGS testing, immunotherapy, and chemotherapy acquisition were simultaneously reduced by at least 47%, 39%, and 43%, respectively. Furthermore, strategy C resulted in the highest net monetary benefit (≥ €39,900) in a scenario where patients with both PD-L1 low and TMB low were treated with chemotherapy instead of immunotherapy plus chemotherapy. CONCLUSIONS: The use of WGS-TMB is not cost effective compared to PD-L1 for immunotherapy treatment selection in non-squamous metastatic non-small cell lung cancer in the Netherlands. WGS-TMB could become cost effective provided there is a reduction in the cost of WGS testing or there is an increase in the predictive value of WGS-TMB for immunotherapy effectiveness. Alternatively, a combination strategy of PD-L1 testing with WGS-TMB would be cost effective if used to support the choice to withhold immunotherapy in patients with a low expected benefit of immunotherapy.

Long-Term Outcomes of Eladocagene Exuparvovec Compared with Standard of Care in Aromatic L-Amino Acid Decarboxylase (AADC) Deficiency: A Modelling Study.

INTRODUCTION: Aromatic L-amino acid decarboxylase (AADC) deficiency is a rare disease with symptoms including movement disorders, developmental delays, and autonomic symptoms starting from birth; further, patients with AADC deficiency are at a high risk of death in the first decade of life. Limited information on the impact of treatment with gene therapy on patients' disease trajectories and survival, quality-of-life, and resource usage benefits are available. METHOD: A cohort-based model with a lifetime horizon has been developed, based on motor milestones, to estimate the long-term benefits for patients after treatment with eladocagene exuparvovec compared to best supportive care (BSC). The model takes a National Health Service (NHS) perspective using a UK setting. The model comprises two parts: the developmental phase, in which patients with initially no motor function can progress to other motor milestone states, and a long-term projection phase. Efficacy for eladocagene exuparvovec is derived from clinical trial data with a duration up to 120 months. As the incidence of AADC deficiency is low, data for key model inputs is lacking; therefore estimates of survival by motor milestone were based on proxy diseases. A disease-specific utility study provided quality of life inputs and a burden of illness study informed inputs for disease management. RESULTS: The model indicates survival (25.25 undiscounted life years gained) and quality-of-life benefits (20.21 undiscounted quality-adjusted life years [QALYs] gained) for patients treated with eladocagene exuparvovec compared to BSC. Resource usage costs are greater for patients treated with eladocagene exuparvovec, mainly due to the increased life expectancy during which patients accrue additional healthcare resource usage. Scenario analyses indicate robust results. CONCLUSION: This study assessed long-term outcomes for patients with AADC deficiency. Patients treated with eladocagene exuparvovec were found to have improved survival and quality of life benefits compared to patients treated with BSC.

Modeling Monthly Migraine-Day Distributions Using Longitudinal Regression Models and Linking Quality of Life to Inform Cost-Effectiveness Analysis: A Case Study of Fremanezumab in Japanese-Korean Migraine Patients.

BACKGROUND AND OBJECTIVES: As regression approaches have been used more recently to model the effectiveness and health-related quality of life (HRQOL) of novel migraine treatments, an example is provided for fremanezumab. The objective is to estimate the distribution of mean monthly migraine days (MMD) as a continuous variable and corresponding migraine-specific utility values as a function of the MMD, to inform health states in a cost-effectiveness model (CEM). METHODS: Three longitudinal regression models (zero-adjusted gamma [ZAGA], zero-inflated beta-binomial [ZIBB], and zero-inflated negative binomial [ZINBI]) were fitted to Japanese-Korean clinical trial data of episodic (EM) and chronic migraine (CM) patients treated with fremanezumab or placebo, to estimate MMD over a period of 12 months. The EQ-5D-5L and the migraine-specific quality-of-life (MSQ), mapped to the EQ-5D-3L, questionnaires were used to measure HRQOL. Migraine-specific utility values were estimated as a function of MMD using a linear mixed effects model. RESULTS: The ZIBB models fitted the data best in estimating the distribution of mean MMD over time. MSQ-derived values were more sensitive than the EQ-5D-5L values for the effect of the number of MMD on HRQOL, with higher values for less MMD and more time on treatment. CONCLUSIONS: Using longitudinal regression models to estimate MMD distributions and linking utility values as a function is an appropriate method to inform CEMs and capture inter-patient heterogeneity. The observed distribution shifts demonstrated fremanezumab's effect at reducing MMD for both EM and CM patients, while treatment effect on HRQOL was captured by MMD and time on treatment.

The current study provides an example of an approach that can be used to estimate the number of migraine days per month and the quality of life of migraine patients. The outcomes of this approach can give an impression of how well a patient reacts to a new migraine treatment called fremanezumab. In this study, different mathematical equations were used to measure the migraine days per month and quality of life over a period of 1 year. The data came from Japanese-Korean patients that participated in clinical trials. The patients reported the number of days that they had migraine and their quality of life was measured with two validated questionnaires. With the gathered data, the quality of life was calculated for the number of migraine days that a patient could have per month. Patients who had the fewest migraine days and were treated the longest with the new treatment reported the best quality of life. The investigated approach is an appropriate method to measure the impact of fremanezumab on the number of monthly migraine days and a patient's quality of life. The measurements of this approach can be linked to other parameters in an economic model to estimate the costs required to reach a certain level of treatment effect with this new migraine treatment.

Development and validation of a decision model for the evaluation of novel lung cancer treatments in the Netherlands.

Recent discoveries in molecular diagnostics and drug treatments have improved the treatment of patients with advanced (inoperable) non-squamous non-small cell lung cancer (NSCLC) from solely platinum-based chemotherapy to more personalized treatment, including targeted therapies and immunotherapies. However, these improvements come at considerable costs, highlighting the need to assess their cost-effectiveness in order to optimize lung cancer care. Traditionally, cost-effectiveness models for the evaluation of new lung cancer treatments were based on the findings of the randomized control trials (RCTs). However, the strict RCT inclusion criteria make RCT patients not representative of patients in the real-world. Patients in RCTs have a better prognosis than patients in a real-world setting. Therefore, in this study, we developed and validated a diagnosis-treatment decision model for patients with advanced (inoperable) non-squamous NSCLC based on real-world data in the Netherlands. The model is a patient-level microsimulation model implemented as discrete event simulation with five health events. Patients are simulated from diagnosis to death, including at most three treatment lines. The base-model (non-personalized strategy) was populated using real-world data of patients treated with platinum-based chemotherapy between 2008 and 2014 in one of six Dutch teaching hospitals. To simulate personalized care, molecular tumor characteristics were incorporated in the model based on the literature. The impact of novel targeted treatments and immunotherapies was included based on published RCTs. To validate the model, we compared survival under a personalized treatment strategy with observed real-world survival. This model can be used for health-care evaluation of personalized treatment for patients with advanced (inoperable) NSCLC in the Netherlands.

Characterization of Ethos therapy systems for adaptive radiation therapy: A multi-machine comparison.

PURPOSE: The recently released Ethos therapy system (Varian Medical Systems) allows for online CBCT-guided adaptive radiation therapy (RT). The clinical introduction of multiple systems requires machine characterization and machine variation quantification to allow patient interchangeability between systems. Despite several clinical introductions, limited vendor-independent information on machine performance is available. Our aim was to determine the relevant dosimetric and mechanical characteristics of individual machines and to quantify machine variations. METHODS: Six Ethos treatment machines, equipped with a 6-MV FFF beam including dual-layer MLC and kV-CBCT system, were recently introduced clinically after extensive machine characterization and pre-configured beam model verification. Point doses and profiles were measured and compared to vendor-provided reference data and dose calculations. Also, dose calculations were verified based on point measurements for non-standard fields and dose distributions for optimized treatment plans. Agreements between dose profiles (dose distributions) were quantified using 1D (3D) γ-analysis. Additionally, we quantified leaf transmission, dosimetric leaf gap (DLG) and couch attenuation, determined isocenter accuracy and kV-MV isocenter coincidence and verified the kV-CBCT system. Machine variations were quantified for all dosimetric and mechanical characteristics. RESULTS: For all machines, distinct agreements were found between measurements and vendor-provided reference data as well as measurements and dose calculations. Mean γ1%/1mm values for all profiles were below 0.30. All profiles, point measurements and dose distributions matched well among the six machines. Minimal machine variations were found in terms of DLG (0.05 mm), leaf transmission (0.001%), isocenter accuracy (0.08 mm), kV-MV isocenter coincidence (0.15 mm), couch attenuation (0.69%), and CBCT imaging dose (0.29 mGy). CONCLUSIONS: This study demonstrates excellent agreement between individual Ethos therapy systems and vendor-provided reference data as well as a pre-configured beam model. Furthermore, our results show good consistency among all machines and provide valuable insights on relevant machine characteristics. The systematically obtained results provide benchmark data for future clinical introduction of Ethos therapy systems.

Cost-Effectiveness and Budget Impact of Future Developments With Whole-Genome Sequencing for Patients With Lung Cancer.

OBJECTIVES: This study aimed to investigate the cost-effectiveness, budget impact (BI), and impact of uncertainty of future developments concerning whole-genome sequencing (WGS) as a clinical diagnostic test compared with standard of care (SoC) in patients with locally advanced and metastatic non-small cell lung cancer. METHODS: A total of 3 likely scenarios to take place within 5 years (according to experts) were simulated using a previously developed, peer reviewed, and published decision model. The scenarios concerned "WGS results used for treatment selection" (scenario 1), "WGS-based biomarker for immunotherapy" (scenario 2), and "off-label drug approval for WGS results" (scenario 3). Two diagnostic strategies of the original model, "SoC" and "WGS as a diagnostic test" (base model), were used to compare our scenarios with. Outcomes were reported for the base model, all scenarios separately, combined (combined unweighted), and weighted by likelihood (combined weighted). Cost-effectiveness, BI, and value of information analyses were performed for WGS compared with SoC. RESULTS: Total costs and quality-adjusted life-years for SoC in metastatic non-small cell lung cancer were €149 698 and 1.235. Incremental outcomes of WGS were €1529/0.002(base model), -€222/0.020(scenario 1), -€2576/0.023(scenario 2), €388/0.024(scenario 3), -€5041/0.060(combined unweighted), and -€1715/0.029(combined weighted). The annual BI for adopting WGS for this population in The Netherlands ranged between €682 million (combined unweighted) and €714 million (base model). The consequences of uncertainty amounted to €3.4 million for all scenarios (combined weighted) and to €699 000 for the diagnostic yield of WGS alone (combined weighted). CONCLUSIONS: Our findings suggest that it is likely for WGS to become cost-effective within the near future if it identifies more patients with actionable targets and show the impact of uncertainty regarding its diagnostic yield. Modeling future scenarios can be useful to consider early adoption of WGS while timely anticipating on unforeseen developments before final conclusions are reached.

Early Cost Effectiveness of Whole-Genome Sequencing as a Clinical Diagnostic Test for Patients with Inoperable Stage IIIB,C/IV Non-squamous Non-small-Cell Lung Cancer.

BACKGROUND: Advanced non-small-cell lung cancer (NSCLC) harbours many genetic aberrations that can be targeted with systemic treatments. Whole-genome sequencing (WGS) can simultaneously detect these (and possibly new) molecular targets. However, the exact added clinical value of WGS is unknown. OBJECTIVE: The objective of this study was to determine the early cost effectiveness of using WGS in diagnostic strategies compared with currently used molecular diagnostics for patients with inoperable stage IIIB,C/IV non-squamous NSCLC from a Dutch healthcare perspective. METHODS: A decision tree represented the diagnostic pathway, and a cohort state transition model represented disease progression. Three diagnostic strategies were modelled: standard of care (SoC) alone, WGS as a diagnostic test, and SoC followed by WGS. Treatment effectiveness was based on a systematic review. Probabilistic cost-effectiveness analyses were performed, and threshold analyses (using €80,000 per quality-adjusted life-year [QALY]) was used to explore the early cost effectiveness of WGS. RESULTS: WGS as a diagnostic test resulted in more QALYs (0.002) and costs (€1534 [incremental net monetary benefit -€1349]), and SoC followed by WGS resulted in fewer QALYs (-0.002) and more costs (€1059 [-€1194]) compared with SoC alone. WGS as a diagnostic test was only cost effective if it was priced at €2000 per patient and identified 2.7% more actionable patients than SoC alone. Treating these additional identified patients with new treatments costing >€4069 per month decreased the probability of cost effectiveness. CONCLUSIONS: Our analysis suggests that providing WGS as a diagnostic test is cost effective compared with SoC followed by WGS and SoC alone if costs for WGS decrease and additional patients with actionable targets are identified. This cost-effectiveness model can be used to incorporate new findings iteratively and to support ongoing decision making regarding the use of WGS in this rapidly evolving field.

Whole genome sequencing in oncology: using scenario drafting to explore future developments.

BACKGROUND: In oncology, Whole Genome Sequencing (WGS) is not yet widely implemented due to uncertainties such as the required infrastructure and expertise, costs and reimbursements, and unknown pan-cancer clinical utility. Therefore, this study aimed to investigate possible future developments facilitating or impeding the use of WGS as a molecular diagnostic in oncology through scenario drafting. METHODS: A four-step process was adopted for scenario drafting. First, the literature was searched for barriers and facilitators related to the implementation of WGS. Second, they were prioritized by international experts, and third, combined into coherent scenarios. Fourth, the scenarios were implemented in an online survey and their likelihood of taking place within 5 years was elicited from another group of experts. Based on the minimum, maximum, and most likely (mode) parameters, individual Program Evaluation and Review Technique (PERT) probability density functions were determined. Subsequently, individual opinions were aggregated by performing unweighted linear pooling, from which summary statistics were extracted and reported. RESULTS: Sixty-two unique barriers and facilitators were extracted from 70 articles. Price, clinical utility, and turnaround time of WGS were ranked as the most important aspects. Nine scenarios were developed and scored on likelihood by 18 experts. The scenario about introducing WGS as a clinical diagnostic with a lower price, shorter turnaround time, and improved degree of actionability, scored the highest likelihood (median: 68.3%). Scenarios with low likelihoods and strong consensus were about better treatment responses to more actionable targets (26.1%), and the effect of centralizing WGS (24.1%). CONCLUSIONS: Based on current expert opinions, the implementation of WGS as a clinical diagnostic in oncology is heavily dependent on the price, clinical utility (both in terms of identifying actionable targets as in adding sufficient value in subsequent treatment), and turnaround time. These aspects and the optimal way of service provision are the main drivers for the implementation of WGS and should be focused on in further research. More knowledge regarding these factors is needed to inform strategic decision making regarding the implementation of WGS, which warrants support from all relevant stakeholders.

Early technology assessment of using whole genome sequencing in personalized oncology.

Introduction: Personalized medicine-based treatments in advanced cancer hold the promise to offer substantial health benefits to genetic subgroups, but require efficient biomarker-based patient stratification to match the right treatment and may be expensive. Standard molecular diagnostics are currently very heterogeneous, and tests are often performed sequentially. The alternative to whole genome sequencing (WGS) i.e. simultaneously testing for all relevant DNA-based biomarkers thereby allowing immediate selection of the most optimal therapy, is more costly than current techniques. In the current implementation stage, it is important to explore the added value and cost-effectiveness of using WGS on a patient level and to assess optimal introduction of WGS on the level of the healthcare system.Areas covered: First, an overview of current worldwide initiatives concerning the use of WGS in clinical practice for cancer diagnostics is given. Second, a comprehensive, early health technology assessment (HTA) approach of evaluating WGS in the Netherlands is described, relating to the following aspects: diagnostic value, WGS-based treatment decisions, assessment of long-term health benefits and harms, early cost-effectiveness modeling, nation-wide organization, and Ethical, Legal and Societal Implications.Expert opinion: This study provides evidence to guide further development and implementation of WGS in clinical practice and the healthcare system.

Observed versus modelled lifetime overall survival of targeted therapies and immunotherapies for advanced non-small cell lung cancer patients - A systematic review.

Outcomes used for the effectiveness (median) and cost-effectiveness (mean) on overall survival (OS) are different and can vary from one another. Therefore, we compared median and mean OS gains of targeted therapies and immunotherapies for stage IIIB/IV Non-small cell lung cancer and explored underlying aspect. Eligible trials were searched in PubMed, survival curves were digitized, and parametric survival models fitted to model the mean OS. Twenty-seven trials were found for targeted therapies (n = 17) and immunotherapies (n = 10). Differences between median and mean OS gains in months ranged from -2.8 to 6.8 and -4.9 to 0.3 for two different subgroups of targeted therapies, and -2.4 to 11.4 for immunotherapies. The mean OS gain was substantially larger for most immunotherapy trials, due to relatively long survival. Median and mean OS gains did not differ for targeted therapies. Our findings imply a potential discrepancy between the estimates of effectiveness and cost-effectiveness of cancer treatments.