Whole genome sequencing as a ticket to cancer treatment in the Netherlands: Are inequalities in access to molecular diagnostics unfair?

Whole genome sequencing (WGS) of a tumour may sometimes reveal additional potential targets for medical treatment. Practice variation in the use of WGS is therefore a source of unequal access to targeted therapies and, as a consequence, of disparities in health outcomes. Moreover, this may even be more significant if patients seek access to WGS by paying a relatively limited amount of money out of pocket, and sometimes effectively buy themselves a ticket to (very) expensive publicly funded treatments. Should resulting unequal access to WGS be considered unfair? Drawing from current practice in the Dutch healthcare system, known as egalitarian, we argue that differences in employment of WGS between hospitals are the consequence of the fact that medical innovation and its subsequent uptake inevitably takes time. Consequently, temporal inequalities in access can be deemed acceptable, or at least tolerated, because and insofar as, ultimately, all patients benefit. However, we argue against allowing a practice of out-of-pocket payments for WGS in publicly funded healthcare systems, for four reasons: because allowing private spending favours patients with higher socio-economic status significantly more than practice variation between hospitals does, may lead to displacement of publicly funded health care, does not help to ultimately benefit all, and may undermine the solidaristic ethos essential for egalitarian healthcare systems.

Cost Effectiveness of Molecular Diagnostic Testing Algorithms for the Treatment Selection of Frontline Ibrutinib for Patients with Chronic Lymphocytic Leukemia in Australia.

BACKGROUND: Clinical indications for ibrutinib reimbursement in Australia should consider the inclusion of patients with chronic lymphocytic leukemia (CLL) harboring prognostically unfavorable TP53/IGHV genomic aberrations. This study assessed the cost effectiveness of five first-line treatment strategies in CLL for young (aged ≤ 65 years), fit patients without significant comorbidities: (1) no testing (fludarabine, cyclophosphamide and rituximab [FCR] for all), (2) test for del(17p) only, (3) test for TP53 gene mutation status, (4) test for TP53 and IGHV gene mutation status and (5) no testing (ibrutinib for all). METHOD: A decision analytic model (decision tree and partitioned survival model) was developed from the Australian healthcare system perspective with a lifetime horizon. Comparative treatment effects were estimated from indirect treatment comparisons and survival analysis using several studies. Costs, utility and adverse events were derived from public literature sources. Deterministic and probabilistic sensitivity analyses explored the impact of modeling uncertainties on outcomes. RESULTS: Strategy 1 was associated with 5.69 quality-adjusted life-years (QALYs) and cost 458,836 Australian dollars (AUD). All other strategies had greater effectiveness but were more expensive than Strategy 1. At the willingness-to-pay (WTP) threshold of 100,000 AUD per QALY gained, Strategy 1 was most cost effective with an estimated probability of 68.8%. Strategy 4 was cost effective between thresholds 155,000-432,300 AUD per QALY gained, and Strategy 5 >432,300 AUD per QALY gained. CONCLUSION: Population targeting using mutation testing for TP53 and IGHV when performed with del(17p) testing specifically in the context of frontline ibrutinib choice does not make a cost-ineffective treatment into a cost-effective treatment.

Quantifying hospital-associated costs, and accompanying travel costs and productivity losses, before and after withdrawing tumour necrosis factor-alfa inhibitors in juvenile idiopathic arthritis.

OBJECTIVE: To quantify differences in hospital-associated costs, and accompanying travel costs and productivity losses, before and after withdrawing TNFi in JIA patients. METHODS: Retrospective analysis of prospectively collected data from electronic medical records of paediatric JIA patients treated with TNFi, which were either immediately discontinued, spaced (increased treatment interval) or tapered (reduced subsequent doses). Costs of hospital-associated resource use (consultations, medication, radiology procedures, laboratory testing, procedures under general anaesthesia, hospitalisation) and associated travel costs and productivity losses were quantified during clinically inactive disease until TNFi withdrawal (pre-withdrawal period) and compared with costs during the first and second year after withdrawal initiation (first and second year post-withdrawal). RESULTS: Fifty-six patients were included of whom 26 immediately discontinued TNFi, 30 spaced and zero tapered. Mean annual costs were €9,165/patient on active treatment (pre-withdrawal) and decreased significantly to €5,063/patient (-44.8%) and €6,569/patient (-28.3%) in the first and second year post-withdrawal, respectively (p< 0.05). Of these total annual costs, travel costs plus productivity losses were €834/patient, €1,180/patient, and €1,320/patient, in the three periods respectively. Medication comprised 80.7%, 61.5% and 72.4% of total annual costs in the pre-withdrawal, first, and second year post-withdrawal period, respectively. CONCLUSION: In the first two years after initiating withdrawal, the total annual costs are decreased compared with the pre-withdrawal period. However, cost reductions were lower in the second year compared with the first year post-withdrawal, primarily due to restarting or intensifying biologics. To support biologic withdraw decisions, future research should assess the full long-term societal cost impacts, and include all biologics.

Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value.

BACKGROUND: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation. METHODS: A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value. RESULTS: Seven criteria were identified: 'unmet need', 'size of target population', 'eligible participants can access the trial', 'patient outcomes', 'total trial cost', 'academic impact' and 'use of trial results'. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an 'Unmet Need' was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved 'Patient Outcomes' with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials. CONCLUSION: We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway.

A tailored approach to horizon scanning for cancer medicines.

BACKGROUND: Horizon scanning (HS) is the systematic identification of emerging therapies to inform policy and decision-makers. We developed an agile and tailored HS methodology that combined multi-criteria decision analysis weighting and Delphi rounds. As secondary objectives, we aimed to identify new medicines in melanoma, non-small cell lung cancer and colorectal cancer most likely to impact the Australian government's pharmaceutical budget by 2025 and to compare clinician and consumer priorities in cancer medicine reimbursement. METHOD: Three cancer-specific clinician panels (total n = 27) and a consumer panel (n = 7) were formed. Six prioritisation criteria were developed with consumer input. Criteria weightings were elicited using the Analytic Hierarchy Process (AHP). Candidate medicines were identified and filtered from a primary database and validated against secondary and tertiary sources. Clinician panels participated in a three-round Delphi survey to identify and score the top five medicines in each cancer type. RESULTS: The AHP and Delphi process was completed in eight weeks. Prioritisation criteria focused on toxicity, quality of life (QoL), cost savings, strength of evidence, survival, and unmet need. In both curative and non-curative settings, consumers prioritised toxicity and QoL over survival gains, whereas clinicians prioritised survival. HS results project the ongoing prevalence of high-cost medicines. Since completion in October 2021, the HS has identified 70 % of relevant medicines submitted for Pharmaceutical Benefit Advisory Committee assessment and 60% of the medicines that received a positive recommendation. CONCLUSION: Tested in the Australian context, our method appears to be an efficient and flexible approach to HS that can be tailored to address specific disease types by using elicited weights to prioritise according to incremental value from both a consumer and clinical perspective. POLICY SUMMARY: Since HS is of global interest, our example provides a reproducible blueprint for adaptation to other healthcare settings that integrates consumer input and priorities.

Assessing neuro-oncology clinical trial impact and value: Testing a novel multi-criteria decision analysis app.

BACKGROUND: Many clinical trials are conducted globally, creating challenges in deciding which trial outcomes deserve a clinician's focus and where to direct limited resources. Determining the 'value' of a clinical trial relative to others could be useful in this context. The aim of this study was to test a novel web-based application using multi-criteria decision analysis (MCDA) to rank clinical trial value. METHODS: The MCDA tool combines seven metrics: unmet need; target population size; access; outcomes; cost; academic impact and use of results. Clinical trials were ranked according to their calculated 'value' - meaning the importance or worth of a trial. We determined face validity of the app using a set of ten published Phase 3 neuro-oncology clinical trials. A survey of neuro-oncology clinicians asked them to rank the same ten clinical trials, and to rank the seven metrics in terms of importance. RESULTS: The two highest app-ranked trials were in concordance with that of the survey respondents, and consistent with the two studies that have had the most impact on routine clinical practice in neuro-oncology. Of the seven metrics, surveyed clinicians considered patient outcomes and unmet need to be the most important when determining clinical trial value. CONCLUSIONS: The metrics app was able to rank and produce a numerical 'value' for existing phase 3 neuro-oncology clinical trials. In the future, a related app to prospectively rank future trials at the startup stage could be developed to help centers determine which should be prioritized to be conducted at their site.

Health Economic Evidence and Modeling Challenges for Liquid Biopsy Assays in Cancer Management: A Systematic Literature Review.

BACKGROUND: Cancer-derived material circulating in the bloodstream and other bodily fluids, referred to as liquid biopsies (LBs), has become an appealing adjunct or alternative to tissue biopsies, showing vital promise in several clinical applications. PURPOSE: A systematic literature review was conducted to (1) summarize the current health economic evidence for LB assays and (2) identify and analyze the studies addressed or reported on the challenges of health economic modeling in precision medicine. METHODS: Relevant studies were identified in the EMBASE, MEDLINE, Cochrane Library, EconLit, and the University of Melbourne Full Text Journal databases from 1 January 2013 to 16 September 2022. Included papers were selected if they were economic evaluations and/or budget impact analyses. RESULTS: A total of 24 studies were included and analyzed, with the majority being full economic evaluations (n = 19, 79.2%). Four studies (16.7%) were health and budget impact analyses, and one study (4.1%) incorporated both an economic evaluation and a budget impact analysis. Cohort-level modeling techniques were the most common approach (n = 16; 80%). LB technologies were cost-effective in 15 studies (75%) considering different biomarkers, cancer types and stages, and economic analyses. These studies evaluated LBs for screening and early detection (66.7%), treatment selection (26.7%), and monitoring treatment response (6.6%). Budget impact analysis results were varied among included studies, with the majority of studies (n = 4; 80%) reporting either cost savings, minimal, or modest budget impact, while one study (20%) reported LBs as an efficient strategy. The reviewed studies often inadequately reported or addressed modeling challenges, such as patient-level processes, the combination of tests and treatments, preferences, and uncertainty. CONCLUSION: LBs could provide a cost-effective approach for treatment selection in lung cancer and aid in the screening and early detection of other cancers, including colorectal, gastric, breast, and brain cancers. This is in comparison with various alternatives, such as the standard of care (SOC) and no screening scenario. However, it is important to mention that in some comparisons, LBs were used in combination with SOC instead of replacing it. Importantly, few studies have pointed toward LBs' cost-effectiveness for monitoring treatment response. Most health and budget impact analyses, especially those focused on lung cancer, suggest potential cost savings or a minimal-to-moderate budget impact. Nevertheless, additional research is needed to ascertain their effectiveness across various stages of lung and colorectal cancer, as well as to address potential modeling challenges. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022307939.

Health economic evidence for adjuvant chemotherapy in stage II and III colon cancer: a systematic review.

OBJECTIVE: The aims of this study was to appraise the health economic evidence for adjuvant chemotherapy (AC) strategies in stage II and III colon cancer (CC) and identify gaps in the available evidence that might inform further research. METHOD: A systematic review of published economic evaluations was undertaken. Four databases were searched and full-text publications in English were screened for inclusion. A narrative synthesis was performed to summarise the evidence. RESULTS: Thirty-eight studies were identified and stratified by cancer stage and AC strategy. The majority (89%) were full economic evaluations considering both health outcomes, usually measured as quality-adjusted life years (QALYs), and costs. AC was found to be cost-effective compared to no AC for both stage II and III CC. Oral and oxaliplatin-based AC was cost-effective for stage III. Three months of CAPOX was cost-effective compared to 6-month in high-risk stage II and stage III CC. Preliminary evidence suggests that biomarker approaches to AC selection in stage II can reduce costs and improve health outcomes. Notably, assessment of QALYs were predominantly reliant on a small number of non-contemporary health-utility studies. Only 32% of studies considered societal costs such as travel and time off work. CONCLUSIONS: Published economic evaluations consistently supported the use of AC in stage II and III colon cancer. Biomarker-driven approaches to patient selection have great potential to be cost-effective, but more robust clinical and economic evidence is warranted. Patient surveys embedded into clinical trials may address critical knowledge gaps regarding accurate assessment of QALYs and societal costs in the modern era.

Population-Based Screening Using Low-Dose Chest Computed Tomography: A Systematic Review of Health Economic Evaluations.

BACKGROUND: Chest low-dose computed tomography (LDCT) is a promising technology for population-based screening because it is non-invasive, relatively inexpensive, associated with low radiation and highly sensitive to lung cancer. To improve the cost-effectiveness of lung cancer screening, simultaneous screening for other diseases could be considered. This systematic review was conducted to analyse studies that published evidence on the cost-effectiveness of chest LDCT screening programs for different diseases. METHODS: Scopus and PubMed were searched for English publications (1 January 2011-22 July 2022) using search terms related to screening, computed tomography and cost-effectiveness. An additional search specifically searched for the cost-effectiveness of screening for lung cancer, chronic obstructive pulmonary disease or cardiovascular disease. Included publications should present a full health economic evaluation of population screening with chest LDCT. The extracted data included the disease screened for, model type, country context of screening, inclusion of comorbidities or incidental findings, incremental costs, incremental effects and the resulting cost-effectiveness ratio amongst others. Reporting quality was assessed using the 2022 Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. RESULTS: The search yielded 1799 unique papers, of which 43 were included. Most papers focused on lung cancer screening (n = 40), and three were on coronary calcium scoring. Microsimulation was the most commonly applied modelling type (n = 16), followed by life table analysis (n = 10) and Markov cohort models (n = 10). Studies reflected the healthcare context of the US (n = 15), Canada (n = 4), the UK (n = 3) and 13 other countries. The reported incremental cost-effectiveness ratio ranged from US$10,000 to US$90,000/quality-adjusted life year (QALY) for lung cancer screening compared to no screening and was US$15,900/QALY-US$45,300/QALY for coronary calcium scoring compared to no screening. DISCUSSION: Almost all health economic evaluations of LDCT screening focused on lung cancer. Literature regarding the health economic benefits of simultaneous LDCT screening for multiple diseases is absent. Most studies suggest LDCT screening is cost-effective for current and former smokers aged 55-74 with a minimum of 30 pack-years of smoking history. Consequently, more evidence on LDCT is needed to support further cost-effectiveness analyses. Preferably evidence on simultaneous screening for multiple diseases is needed, but alternatively, on single-disease screening. REGISTRATION OF SYSTEMATIC REVIEW: Prospective Register of Ongoing Systematic Reviews registration CRD42021290228 can be accessed https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=290228 .

Real-world clinical outcomes and cost estimates of metastatic castration-resistant prostate cancer treatment: does sequencing of taxanes and androgen receptor-targeted agents matter?

INTRODUCTION: Health economic outcomes of real-world treatment sequencing of androgen receptor-targeted agents (ARTA) and docetaxel (DOC) remain unclear. MATERIAL AND METHODS: Data from the electronic Castration-resistant Prostate cancer Australian Database (ePAD) were analyzed including median overall survival (mOS) and median time-to-treatment failure (mTTF). Mean total costs (mTC) and incremental cost-effectiveness ratios (ICER) of treatment sequences were estimated using the average sample method and Zhao and Tian estimator. RESULTS: Of 752 men, 441 received ARTA, 194 DOC, and 175 both sequentially. Of participants treated with both, first-line DOC followed by ARTA was the more common sequence (n = 125, 71%). mOS for first-line ARTA was 8.38 years (95% CI: 3.48, not-estimated) vs. 3.29 years (95% CI: 2.92, 4.02) for DOC. mTTF was 15.7 months (95% CI: 14.2, 23.7) for the ARTA-DOC sequence and 18.2 months (95% CI: 16.2, 23.2) for DOC-ARTA. In first-line, ARTA cost an additional $13,244 per mTTF month compared to DOC. In second-line, ARTA cost $6726 per mTTF month. The DOC-ARTA sequence saved $2139 per mTTF compared to ARTA-DOC, though not statistically significant. CONCLUSION: ICERs show ARTA had improved clinical benefit compared to DOC but at higher cost. There were no significant cost differences between combined sequences.

The societal impact of implementing an at-home blood sampling device for chronic care patients: patient preferences and cost impact.

BACKGROUND: Diabetes mellitus, cardiovascular diseases, chronic kidney disease, and thyroid diseases are chronic diseases that require regular monitoring through blood tests. This paper first investigates the experiences of chronic care patients with venipuncture and their expectations of an at-home blood-sampling device, and then assesses the impact on societal costs of implementing such a device in current practice. METHODS: An online survey was distributed among chronic care patients to gain insight into their experience of blood sampling in current practice, and their expectations of an at-home blood-sampling device. The survey results were used as input parameters in a patient-level monte carlo analysis developed to represent a hypothetical cohort of Dutch chronically ill patients to investigate the impact on societal costs compared to usual care. RESULTS: In total, 1311 patients participated in the survey, of which 31% experience the time spent on the phlebotomy appointment as a burden. Of all respondents, 71% prefer to use an at-home blood-sampling device to monitor their chronic disease. The cost analysis indicated that implementing an at-home blood-sampling device increases the cost of phlebotomy itself by €27.25 per patient per year, but it reduces the overall societal costs by €24.86 per patient per year, mainly due to limiting productivity loss. CONCLUSIONS: Patients consider an at-home blood-sampling device to be more user-friendly than venous phlebotomy on location. Long waiting times and crowded locations can be avoided by using an at-home blood-sampling device. Implementing such a device is likely cost-saving as it is expected to reduce societal costs.

A scoping review and meta-analysis on the prevalence of pan-tumour biomarkers (dMMR, MSI, high TMB) in different solid tumours.

Immune checkpoint inhibitors have been approved in the USA for tumours exhibiting mismatch repair deficiency (dMMR), microsatellite instability (MSI), or high tumour mutational burden (TMB), with regulatory and reimbursement applications in multiple other countries underway. As the estimated budget impacts of future reimbursements depend on the size of the potential target population, we performed a scoping review and meta-analysis of the prevalence of these pan-tumour biomarkers in different cancers. We systematically searched Medline/Embase and included studies reporting the prevalence of dMMR/MSI/high TMB in solid tumours published 01/01/2018-31/01/2021. Meta-analyses were performed separately for the pan-cancer prevalence of each biomarker, and by cancer type and stage where possible. The searches identified 3890 papers, with 433 prevalence estimates for 32 different cancer types from 201 studies included in meta-analyses. The pooled overall prevalence of dMMR, MSI and high TMB (≥ 10 mutations/Mb) in pan-cancer studies was 2.9%, 2.7% and 14.0%, respectively. The prevalence profiles of dMMR/MSI and high TMB differed across cancer types. For example, endometrial, colorectal, small bowel and gastric cancers showed high prevalence of both dMMR and MSI (range: 8.7-26.8% and 8.5-21.9%, respectively) and high TMB (range: 8.5-43.0%), while cervical, esophageal, bladder/urothelial, lung and skin cancers showed low prevalence of dMMR and MSI (< 5%), but high prevalence of high TMB (range: 23.7-52.6%). For other cancer types, prevalence of all three biomarkers was generally low (< 5%). This structured review of dMMR/MSI/high TMB prevalence across cancers and for specific cancer types and stages provide timely evidence to inform budget impact forecasts in health technology assessments for drug approvals based on these pan-tumour biomarkers.

Do Health Technology Assessment organisations consider manufacturers' costs in relation to drug price? A study of reimbursement reports.

INTRODUCTION: Drug reimbursement decisions are often made based on a price set by the manufacturer. In some cases, this price leads to public and scientific debates about whether its level can be justified in relation to its costs, including those related to research and development (R&D) and manufacturing. Such considerations could enter the decision process in collectively financed health care systems. This paper investigates whether manufacturers' costs in relation to drug prices, or profit margins, are explicitly mentioned and considered by health technology assessment (HTA) organisations. METHOD: An analysis of reimbursement reports for cancer drugs was performed. All relevant Dutch HTA-reports, published between 2017 and 2019, were selected and matched with HTA-reports from three other jurisdictions (England, Canada, Australia). Information was extracted. Additionally, reimbursement reports for three cases of expensive non-oncolytic orphan drugs prominent in pricing debates in the Netherlands were investigated in depth to examine consideration of profit margins. RESULTS: A total of 66 HTA-reports concerning 15 cancer drugs were included. None of these reports contained information on manufacturer's costs or profit margins. Some reports contained general considerations of the HTA organisation which related prices to manufacturers' costs: six contained a statement on the lack of price setting transparency, one mentioned recouping R&D costs as a potential argument to justify a high price. For the case studies, 21 HTA-reports were selected. One contained a cost-based price justification provided by the manufacturer. None of the other reports contained information on manufacturer's costs or profit margins. Six reports contained a discussion about lack of transparency. Reports from two jurisdictions contained invitations to justify high prices by demonstrating high costs. CONCLUSION: Despite the attention given to manufacturers' costs in relation to price in public debates and in the literature, this issue does not seem to get explicit systematic consideration in the reimbursement reports of expensive drugs.

Machine Learning Methods in Health Economics and Outcomes Research-The PALISADE Checklist: A Good Practices Report of an ISPOR Task Force.

Advances in machine learning (ML) and artificial intelligence offer tremendous potential benefits to patients. Predictive analytics using ML are already widely used in healthcare operations and care delivery, but how can ML be used for health economics and outcomes research (HEOR)? To answer this question, ISPOR established an emerging good practices task force for the application of ML in HEOR. The task force identified 5 methodological areas where ML could enhance HEOR: (1) cohort selection, identifying samples with greater specificity with respect to inclusion criteria; (2) identification of independent predictors and covariates of health outcomes; (3) predictive analytics of health outcomes, including those that are high cost or life threatening; (4) causal inference through methods, such as targeted maximum likelihood estimation or double-debiased estimation-helping to produce reliable evidence more quickly; and (5) application of ML to the development of economic models to reduce structural, parameter, and sampling uncertainty in cost-effectiveness analysis. Overall, ML facilitates HEOR through the meaningful and efficient analysis of big data. Nevertheless, a lack of transparency on how ML methods deliver solutions to feature selection and predictive analytics, especially in unsupervised circumstances, increases risk to providers and other decision makers in using ML results. To examine whether ML offers a useful and transparent solution to healthcare analytics, the task force developed the PALISADE Checklist. It is a guide for balancing the many potential applications of ML with the need for transparency in methods development and findings.

Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer.

BACKGROUND: This study shows how dynamic simulation modeling can be applied in the context of the nationwide implementation of Whole Genome Sequencing (WGS) for non-small cell lung cancer (NSCLC) to inform organizational decisions regarding the use of complex and disruptive health technologies and how these decisions affect their potential value. METHODS: Using the case of the nationwide implementation of WGS into clinical practice in lung cancer in the Dutch healthcare system, we developed a simulation model to show that including service delivery features across the diagnostic pathway can provide essential insight into the affordability and accessibility of care at the systems level. The model was implemented as a hybrid Agent-Based Model and Discrete-Event Simulation model in AnyLogic and included 78 hospital agents, 7 molecular tumor board agents, 1 WGS facility agent, and 5313 patient agents each year in simulation time. RESULTS: The model included patient and provider heterogeneity, including referral patterns, capacity constraints, and diagnostic workflows. Patient preference and adoption by healthcare professionals were also modeled. The model was used to analyze a scenario in which only academic hospitals have implemented WGS. To prevent delays in the diagnostic pathway, the capacity to sequence at least 1600 biopsies yearly should be present. There is a two-fold increase in mean diagnostic pathway duration between no patients referred or all patients referred for further diagnostics. CONCLUSIONS: The systems model can complement conventional health economic evaluations to investigate how the organization of the workflow can influence the actual use and impact of WGS. Insufficient capacity to provide WGS and referral patterns can substantially impact the duration of the diagnostic pathway and thus should be considered in the implementation of WGS.

Health economic evidence for the use of molecular biomarker tests in hematological malignancies: A systematic review.

OBJECTIVES: Molecular biomarker tests can inform the clinical management of genomic heterogeneous hematological malignancies, yet their availability in routine care largely depends on the supporting health economic evidence. This study aims to systematically review the economic evidence for recent molecular biomarker tests in hematological malignancies. METHODS: We conducted a systematic search in five electronic databases for studies published between January 2010 and October 2020. Publications were independently screened by two reviewers. Clinical study characteristics, economic methodology, and results were extracted, and reporting quality was assessed. RESULTS: Fourteen studies were identified, of which half (n = 7; 50%) were full economic evaluations examining both health and economic outcomes. Studies were predominantly conducted in a first-line treatment setting (n = 7; 50%) and adopted a non-lifetime time horizon to measure health outcomes and costs (n = 7; 50%). Five studies reported that companion diagnostics for associated therapies were likely cost-effective for acute myeloid leukemia, chronic myeloid leukemia, diffuse large B-cell lymphoma, and multiple myeloma. Four studies suggested molecular biomarker tests for treatment monitoring in chronic myeloid leukemia were likely cost-saving. CONCLUSIONS: Although there is initial confirmation of the promising health economic results, the present research for molecular biomarker tests in hematological malignancies is sparse with many applications of technological advances yet to be evaluated.

Can we increase efficiency of CT lung cancer screening by combining with CVD and COPD screening? Results of an early economic evaluation.

OBJECTIVES: Estimating the maximum acceptable cost (MAC) per screened individual for low-dose computed tomography (LDCT) lung cancer (LC) screening, and determining the effect of additionally screening for chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), or both on the MAC. METHODS: A model-based early health technology assessment (HTA) was conducted to estimate whether a new intervention could be cost-effective by calculating the MAC at a willingness-to-pay (WTP) of €20k/quality-adjusted life-year (QALY) and €80k/QALY, for a population of current and former smokers, aged 50-75 years in The Netherlands. The MAC was estimated based on incremental QALYs gained from a stage shift assuming screened individuals are detected in earlier disease stages. Data were obtained from literature and publicly available statistics and validated with experts. RESULTS: The MAC per individual for implementing LC screening at a WTP of €20k/QALY was €113. If COPD, CVD, or both were included in screening, the MAC increased to €230, €895, or €971 respectively. Scenario analyses assessed whether screening-specific disease high-risk populations would improve cost-effectiveness, showing that high-risk CVD populations were more likely to improve economic viability compared to COPD. CONCLUSIONS: The economic viability of combined screening is substantially larger than for LC screening alone, primarily due to benefits from CVD screening, and is dependent on the target screening population, which is key to optimise the screening program. The total cost of breast and cervical cancer screening is lower (€420) than the MAC of Big-3, indicating that Big-3 screening may be acceptable from a health economic perspective. KEY POINTS: • Once-off combined low-dose CT screening for lung cancer, COPD, and CVD in individuals aged 50-75 years is potentially cost-effective if screening would cost less than €971 per screened individual. • Multi-disease screening requires detailed insight into the co-occurrence of these diseases to identify the optimal target screening population. • With the same target screening population and WTP, lung cancer-only screening should cost less than €113 per screened individual to be cost-effective.

Comparing Modeling Approaches for Discrete Event Simulations With Competing Risks Based on Censored Individual Patient Data: A Simulation Study and Illustration in Colorectal Cancer.

OBJECTIVES: This study aimed to provide detailed guidance on modeling approaches for implementing competing events in discrete event simulations based on censored individual patient data (IPD). METHODS: The event-specific distributions (ESDs) approach sampled times from event-specific time-to-event distributions and simulated the first event to occur. The unimodal distribution and regression approach sampled a time from a combined unimodal time-to-event distribution, representing all events, and used a (multinomial) logistic regression model to select the event to be simulated. A simulation study assessed performance in terms of relative absolute event incidence difference and relative entropy of time-to-event distributions for different types and levels of right censoring, numbers of events, distribution overlap, and sample sizes. Differences in cost-effectiveness estimates were illustrated in a colorectal cancer case study. RESULTS: Increased levels of censoring negatively affected the modeling approaches' performance. A lower number of competing events and higher overlap of distributions improved performance. When IPD were censored at random times, ESD performed best. When censoring occurred owing to a maximum follow-up time for 2 events, ESD performed better for a low level of censoring (ie, 10%). For 3 or 4 competing events, ESD better represented the probabilities of events, whereas unimodal distribution and regression better represented the time to events. Differences in cost-effectiveness estimates, both compared with no censoring and between approaches, increased with increasing censoring levels. CONCLUSIONS: Modelers should be aware of the different modeling approaches available and that selection between approaches may be informed by data characteristics. Performing and reporting extensive validation efforts remains essential to ensure IPD are appropriately represented.

Costs of Hospital-Associated Care for Patients With Juvenile Idiopathic Arthritis in the Dutch Health Care System.

OBJECTIVE: The aim of this study was to quantify costs of hospital-associated care for juvenile idiopathic arthritis (JIA), provide insights in patient-level variation in costs, and investigate costs over time from the moment of JIA diagnosis. Results were reported for all JIA patients in general and by subtype. METHODS: This study was a single-center, retrospective analysis of prospective data from electronic medical records of children with JIA, ages 0-18 years, between April 1, 2011 and March 31, 2019. Patient characteristics (age, sex, JIA subtype) and hospital-based resource use (consultations, medication, radiology procedures, laboratory testing, surgeries, emergency department [ED] visits, hospital stays) were extracted and analyzed. Unit prices were obtained from Dutch reimbursement lists and pharmaceutical and hospital list prices. RESULTS: The analysis included 691 patients. The mean total cost of hospital care was €3,784/patient/year, of which €2,103 (55.6%) was attributable to medication. Other costs involved pediatric rheumatologist visits (€633/patient/year [16.7%]), hospital stays (€439/patient/year [11.6%]), other within-hospital specialist visits (€324/patient/year [8.6%]), radiology procedures (€119/patient/year [3.1%]), laboratory tests (€114/patient/year [3.0%]), surgeries (€46/patient/year [1.2%]), and ED visits (€6/patient/year [0.2%]). Mean annual total costs varied between JIA subtypes and between individuals and were the highest for systemic JIA (€7,772/patient/year). Over the treatment course, costs were the highest in the first month after JIA diagnosis. CONCLUSION: Hospital care costs of JIA vary substantially between individuals, between subtypes, and over the treatment course. The highest annual costs were for systemic JIA, primarily attributable to medication (i.e., biologics). Costs of other hospital-associated care were comparable regardless of subtype.

Lifetime Health and Economic Outcomes of Active Surveillance, Radical Prostatectomy, and Radiotherapy for Favorable-Risk Localized Prostate Cancer.

OBJECTIVES: To estimate the lifetime health and economic outcomes of selecting active surveillance (AS), radical prostatectomy (RP), or radiation therapy (RT) as initial management for low- or favorable-risk localized prostate cancer. METHODS: A discrete-event simulation model was developed using evidence from published randomized trials. Health outcomes were measured in life-years and quality-adjusted life-years (QALYs). Costs were included from a public payer perspective in Australian dollars. Outcomes were discounted at 5% over a lifetime horizon. Probabilistic and scenario analyses quantified parameter and structural uncertainty. RESULTS: A total of 60% of patients in the AS arm eventually received radical treatment (surgery or radiotherapy) compared with 90% for RP and 91% for RT. Although AS resulted in fewer treatment-related complications, it led to increased clinical progression (AS 40.7%, RP 17.6%, RT 19.9%) and metastatic disease (AS 13.4%, RP 6.1%, RT 7.0%). QALYs were 10.88 for AS, 11.10 for RP, and 11.13 for RT. Total costs were A$17 912 for AS, A$15 609 for RP, and A$15 118 for RT. At a willingness to pay of A$20 000/QALY, RT had a 61.4% chance of being cost-effective compared to 38.5% for RP and 0.1% for AS. CONCLUSIONS: Although AS resulted in fewer and delayed treatment-related complications, it was not found to be a cost-effective strategy for favorable-risk localized prostate cancer over a lifetime horizon because of an increase in the number of patients developing metastatic disease. RT was the dominant strategy yielding higher QALYs at lower cost although differences compared with RP were small.