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Contains fulltext : 296924.pdf (Publisher’s version ) (Closed access), OBJECTIVES: Although the ISPOR Value of Information (VOI) Task Force's reports outline VOI concepts and provide good-practice recommendations, there is no guidance for reporting VOI analyses. VOI analyses are usually performed alongside economic evaluations for which the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Statement provides reporting guidelines. Thus, we developed the CHEERS-VOI checklist to provide reporting guidance and checklist to support the transparent, reproducible, and high-quality reporting of VOI analyses. METHODS: A comprehensive literature review generated a list of 26 candidate reporting items. These candidate items underwent a Delphi procedure with Delphi participants through 3 survey rounds. Participants rated each item on a 9-point Likert scale to indicate its relevance when reporting the minimal, essential information about VOI methods and provided comments. The Delphi results were reviewed at 2-day consensus meetings and the checklist was finalized using anonymous voting. RESULTS: We had 30, 25, and 24 Delphi respondents in rounds 1, 2, and 3, respectively. After incorporating revisions recommended by the Delphi participants, all 26 candidate items proceeded to the 2-day consensus meetings. The final CHEERS-VOI checklist includes all CHEERS items, but 7 items require elaboration when reporting VOI. Further, 6 new items were added to report information relevant only to VOI (eg, VOI methods applied). CONCLUSIONS: The CHEERS-VOI checklist should be used when a VOI analysis is performed alongside economic evaluations. The CHEERS-VOI checklist will help decision makers, analysts and peer reviewers in the assessment and interpretation of VOI analyses and thereby increase transparency and rigor in decision making.

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 insigh

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.

OBJECTIVE: Pharmacological treatment is a cornerstone of care for children with juvenile idiopathic arthritis (JIA). The objective of this study is to evaluate prescription patterns of conventional and biologic disease modifying anti-rheumatic drugs (c-DMARDs and b-DMARDs) for patients with JIA. METHODS: We conducted a retrospective cohort study of children diagnosed with JIA at a rheumatology pediatric clinic. Eligibility criteria were defined as children and youth newly diagnosed with enthesis-related arthritis, polyarticular, or oligoarticular JIA between 2011 and 2019, with at least one year of observation. Data on c-DMARDs and b-DMARDs prescriptions were obtained from electronic medical charts. We used descriptive statistics, Kaplan-Meier survival methods, and Sankey diagrams to describe treatment prescription patterns. RESULTS: A total of 325 patients with JIA were included, with a median observation time of 3.7 years. The most frequently prescribed c-DMARD and b-DMARD were methotrexate and etanercept, respectively. Within the first year of rheumatology care, 62% and 21% of patients had a c-DMARD and a b-DMARD prescribed, respectively. These proportions varied greatly by JIA subtype. Among the 147 (147/325, 45%) patients that had at least one b-DMARD prescribed, 24% were prescribed a second, and 7% a third-line of b-DMARD. A total of 112 unique treatment sequences were observed, with c-DMARD monotherapy followed by the addition of either a b-DMARD (56%) or another c-DMARD (30%) being the two most prevalent patterns in this cohort. CONCLUSION: We observed a variety of treatment trajectories, with many patients experiencing multiple treatment lines, illustrating the complexity of the overall JIA treatment path.

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.

Contains fulltext : 286077.pdf (Publisher’s version ) (Open Access)

OBJECTIVE: This study investigates the relationship of child, caregiver, and caring context measurements with the care-related quality of life (CRQoL) and health-related quality of life (HRQoL) of caregivers of children with juvenile idiopathic arthritis (JIA). METHODS: We performed a cross-sectional analysis of baseline data on caregivers of children with JIA from Canada and the Netherlands collected for the "Canada-Netherlands Personalized Medicine Network in Childhood Arthritis and Rheumatic Diseases" study from June 2019 to September 2021. We used the CRQoL questionnaire (CarerQoL), adult EQ-5D-5L, and proxy-reported Youth 5-Level version of EuroQoL (EQ-5D-5L-Y) to assess caregiver CRQoL, caregiver HRQoL, and child HRQoL, respectively. We used a multivariate analysis to assess the relationship between both caregiver CRQoL and HRQoL and patient, caregiver, and caring context measurements. RESULTS: A total of 250 caregivers were included in this study. Most of the caregivers were from the Netherlands (n = 178, 71%) and 77% were females (n = 193). The mean CarerQoL scores was 82.7 (standard deviation (SD) 11.4) and the mean EQ-5D-5L utility score was 0.87 (SD 0.16). Child HRQoL and employment had a positive relationship with both caregiver CarerQoL and EQ-5D-5L utility scores (p < 0.05), while receiving paid or unpaid help had a negative relationship with both scores (p < 0.05). CONCLUSION: Our findings indicated that to understand the impact of JIA on families, we need to consider socio-economic factors, such as employment and support to carry caregiving tasks, in addition to child HRQoL.

Serum tumor markers acquired through a blood draw are known to reflect tumor activity. Their non-invasive nature allows for more frequent testing compared to traditional imaging methods used for response evaluations. Our study aims to compare nine prediction methods to accurately, and with a low false positive rate, predict progressive disease despite treatment (i.e. non-response) using longitudinal tumor biomarker data. Bi-weekly measurements of CYFRA, CA-125, CEA, NSE, and SCC were available from a cohort of 412 advanced stage non-small cell lung cancer (NSCLC) patients treated up to two years with immune checkpoint inhibitors. Serum tumor marker measurements from the first six weeks after treatment initiation were used to predict treatment response at 6 months. Nine models with varying complexity were evaluated in this study, showing how longitudinal biomarker data can be used to predict non-response to immunotherapy in NSCLC patients.

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.

Contains fulltext : 237659.pdf (Publisher’s version ) (Closed access), OBJECTIVES: To evaluate the impact of using clinical stage assessed by multiparametric magnetic resonance imaging (mpMRI) on the performance of two established nomograms for the prediction of pelvic lymph node involvement (LNI) in patients with prostate cancer. PATIENTS AND METHODS: Patients undergoing robot-assisted extended pelvic lymph node dissection (ePLND) from 2015 to 2019 at three teaching hospitals were retrospectively evaluated. Risk of LNI was calculated four times for each patient, using clinical tumour stage (T-stage) assessed by digital rectal examination (DRE) and by mpMRI, in the Memorial Sloan Kettering Cancer Centre (MSKCC; 2018) and Briganti (2012) nomograms. Discrimination (area under the curve [AUC]), calibration, and the net benefit of these four strategies were assessed and compared. RESULTS: A total of 1062 patients were included, of whom 301 (28%) had histologically proven LNI. Using DRE T-stage resulted in AUCs of 0.71 (95% confidence interval [CI] 0.70-0.72) for the MSKCC and 0.73 (95% CI 0.72-0.74) for the Briganti nomogram. Using mpMRI T-stage, the AUCs were 0.72 (95% CI 0.71-0.73) for the MSKCC and 0.75 (95% CI 0.74-0.76) for the Briganti nomogram. mpMRI T-stage resulted in equivalent calibration compared with DRE T-stage. Combined use of mpMRI T-stage and the Briganti 2012 nomogram was shown to be superior in terms of AUC, calibration, and net benefit. Use of mpMRI T-stage led to increased sensitivity for the detection of LNI for all risk thresholds in both models, countered by a decreased specificity, compared with DRE T-stage. CONCLUSION: T-stage as assessed by mpMRI is an appropriate alternative for T-stage assessed by DRE to determine nomogram-based risk of LNI in patients with prostate cancer, and was associated with improved model performance of both the MSKCC 2018 and Briganti 2012 nomograms.

RIVM rapport:Zorginstituut Nederland adviseert de minister van VWS onder andere over vergoedingen van medicijnen en andere behandelingen in het basispakket van de ziektekostenverzekering. Het Zorginstituut gebruikt daarvoor onder andere dossiers van medicijnenfabrikanten waarin zij de gezondheidswinst en kosten inschatten op basis van beslismodellen. Met deze beslismodellen wordt bekeken of medicijnen en andere behandelingen op de lange termijn effect hebben op de gezondheid. Bijvoorbeeld wat een betere bloedsuikerspiegel bij mensen met diabetes betekent voor complicaties, zoals hart- en vaatziekten en amputaties. Ook brengt het model de kosten van een behandeling met een nieuw medicijn in kaart. Denk aan de kosten van het medicijn zelf, maar ook besparingen omdat het medicijn de kans op complicaties met hoge behandelkosten kan verkleinen. Op dit moment beoordeelt het Zorginstituut voor bijna elk medicijn of behandeling een dossier waarvoor een apart beslismodel is gebruikt. Hierdoor zijn de effecten van verschillende medicijnen voor dezelfde ziekte niet goed te vergelijken. Daarnaast is het Zorginstituut veel tijd kwijt om de kwaliteit van elk beslismodel te toetsen. Het is daarom aantrekkelijk om voor elke ziekte één model te hebben, de zogenaamde meervoudig gebruik-modellen. Hiermee kunnen betere en consistentere beslissingen genomen worden. Het RIVM heeft met de universiteiten van Twente, Maastricht, Groningen en Utrecht verkend hoe het Zorginstituut met meervoudig gebruikmodellen kan gaan werken. Mede op basis van dit rapport beslist het Zorginstituut of en hoe zij verder gaan met meervoudig gebruikmodellen. Bovendien is een meervoudig gebruik beslismodel gemaakt voor diabetes en als casus uitgewerkt. Het RIVM heeft vijf business cases ontwikkeld om het werken met meervoudig gebruik-modellen op te zetten, en de voor- en nadelen beschreven. In deze opties verschillen de rol en verantwoordelijkheid van betrokken partijen, zoals het Zorginstituut, onderzoeksinstituten en consu, The National Health Care Institute (hereinafter referred to as ZIN) advises the Minister of Health, Welfare and Sport (VWS) on a variety of topics, including reimbursements for medicines and other treatments in the mandatory health insurance package. For this purpose, among other things, ZIN uses dossiers from pharmaceutical companies, in which they estimate the health benefits and costs based on decision models. These decision models are used to examine whether medicines and other treatments improve the health of individuals in the long term. For example, they calculate how better blood glucose levels in people with diabetes translate to less complications, such as cardiovascular diseases and amputations. The models incorporate the costs of the medicine, but also the savings made because the medicine reduces the likelihood of complications and the resulting high treatment costs. ZIN is currently assessing decision models dossier by dossier, with a different decision model being used for almost every medicine or treatment. Therefore, it is difficult to compare the effects of a number of medicines for the same disease. ZIN also spends a lot of time testing the quality of each decision model. It would be better to have a single model for each disease, or multi-use models, as such models meant for repeated use might be called. This would enable those involved to make better and more consistent decisions. RIVM and the Universities of Twente, Maastricht, Groningen and Utrecht have carried out a study into how ZIN could work with multi-use models. This report will assist ZIN in making the decision of whether to switch to multi-use models and, if so, how. By way of case study, RIVM has also created a multi-use model for diabetes. RIVM and its partners have developed five business cases for working with multi-use models and described their advantages and disadvantages. The roles and responsibilities of the parties involved, i.e. ZIN, other research institutes, academic grou

Contains fulltext : 244572.pdf (Publisher’s version ) (Open Access), OBJECTIVE: To identify clinicopathologic factors predictive of early relapse (platinum-free interval (PFI) of ≤6 months) in advanced epithelial ovarian cancer (EOC) in first-line treatment, and to develop and internally validate risk prediction models for early relapse. METHODS: All consecutive patients diagnosed with advanced stage EOC between 01-01-2008 and 31-12-2015 were identified from the Netherlands Cancer Registry. Patients who underwent cytoreductive surgery and platinum-based chemotherapy as initial EOC treatment were selected. Two prediction models, i.e. pretreatment and postoperative, were developed. Candidate predictors of early relapse were fitted into multivariable logistic regression models. Model performance was assessed on calibration and discrimination. Internal validation was performed through bootstrapping to correct for model optimism. RESULTS: A total of 4,557 advanced EOC patients were identified, including 1,302 early relapsers and 3,171 late or non-relapsers. Early relapsers were more likely to have FIGO stage IV, mucinous or clear cell type EOC, ascites, >1 cm residual disease, and to have undergone NACT-ICS. The final pretreatment model demonstrated subpar model performance (AUC = 0.64 [95 %-CI 0.62-0.66]). The final postoperative model based on age, FIGO stage, pretreatment CA-125 level, histologic subtype, presence of ascites, treatment approach, and residual disease after debulking, demonstrated adequate model performance (AUC = 0.72 [95 %-CI 0.71-0.74]). Bootstrap validation revealed minimal optimism of the final postoperative model. CONCLUSION: A (postoperative) discriminative model has been developed and presented online that predicts the risk of early relapse in advanced EOC patients. Although external validation is still required, this prediction model can support patient counselling in daily clinical practice.

The continued introduction of biomarkers and innovative testing methods makes already complex diagnosis in patients with stage IV non-small-cell lung cancer (NSCLC) even more complex. This study primarily analyzed variations in biomarker testing in clinical practice in patients referred to a comprehensive cancer center in the Netherlands. The secondary aim was to compare the cost of biomarker testing with the cost of whole-genome sequencing. The cohort included 102 stage IV NSCLC patients who received biomarker testing in 2017 or 2018 at the comprehensive cancer center. The complete biomarker testing history of the cohort was identified using linked data from the comprehensive cancer center and the nationwide network and registry of histopathology and cytopathology in the Netherlands. Unique biomarker-test combinations, costs, turnaround times, and test utilization were examined. The results indicate substantial variation in test utilization and sequences. The mean cost per patient of biomarker testing was 2259.92 ± 1217.10 USD, or 1881.23 ± 1013.15 EUR. Targeted gene panels were most frequently conducted, followed by IHC analysis for programmed cell death protein ligand 1. Typically, the most common biomarkers were assessed within the first tests, and emerging biomarkers were tested further down the test sequence. At the cost of current biomarker testing, replacing current testing with whole-genome sequencing would have led to cost-savings in only two patients (2%).

BACKGROUND: In some countries, such as the Netherlands and Norway, point-of-care testing (POCT) is more widely implemented in general practice compared to countries such as England and Australia. To comprehend what is necessary to realize the benefits of POCT, regarding its integration in primary care, it would be beneficial to have an overview of the structure of healthcare operations and the transactions between stakeholders (also referred to as value networks). The aim of this paper is to identify the current value networks in place applying to POCT implementation at general practices in England, Australia, Norway and the Netherlands and to compare these networks in terms of seven previously published factors that support the successful implementation, sustainability and scale-up of innovations. METHODS: The value networks were described based on formal guidelines and standards published by the respective governments, organizational bodies and affiliates. The value network of each country was validated by at least two relevant stakeholders from the respective country. RESULTS: The analysis revealed that the biggest challenge for countries with low POCT uptake was the lack of effective communication between the several organizations involved with POCT as well as the high workload for general practitioners (GPs) aiming to implement POCT. It is observed that countries with a single national authority responsible for POCT have a better uptake as they can govern the task of POCT roll-out and management and reduce the workload for GPs by assisting with set-up, quality control, training and support. CONCLUSION: Setting up a single national authority may be an effective step towards realizing the full benefits of POCT. Although it is possible for day-to-day operations to fall under the responsibility of the GP, this is only feasible if support and guidance are readily available to ensure that the workload associated with POCT is limited and as low as possible.

OBJECTIVE: Point-of-care testing (POCT) has become an essential diagnostic technology for optimal patient care. Its implementation, however, still falls behind. This paper reviews the available evidence on the health economic impact of introducing POCT to assess if poor POCT uptake may be related to lacking evidence. STUDY DESIGN: The Scopus and PubMed databases were searched to identify publications describing a health economic evaluation of a point-of-care (POC) test. Data were extracted from the included publications, including general and methodological characteristics as well as the study results summarized in either cost, effects or an incremental cost-effectiveness ratio. Results were sorted into six groups according to the POC test's purpose (diagnosis, screening or monitoring) and care setting (primary care or secondary care). The reporting quality of the publications was determined using the CHEERS checklist. RESULTS: The initial search resulted in 396 publications, of which 44 met the inclusion criteria. Most of the evaluations were performed in a primary care setting (n = 31; 70.5%) compared with a secondary care setting (n = 13; 29.5%). About two thirds of the evaluations were on POC tests implemented with a diagnostic purpose (n = 28; 63.6%). More than 75% of evaluations concluded that POCT is recommended for implementation, although in some cases only under specific circumstances and conditions. Compliance with the CHEERS checklist items ranged from 20.8% to 100%, with an average reporting quality of 72.0%. CONCLUSION: There were very few evaluations in this review that advised against the implementation of POCT. However, the uptake of POCT in many countries remains low. Even though the evaluations included in this review did not always include the full long-term benefits of POCT, it is clear that health economic evidence across a few dimensions of value already indicate the benefits of POCT. This suggests that the lack of evidence on POCT is not the

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 s

BACKGROUND: Although immunotherapy (IMT) provides significant survival benefits in selected patients, approximately 10% of patients experience (serious) immune-related adverse events (irAEs). The early detection of adverse events will prevent irAEs from progressing to severe stages, and routine testing for irAEs has become common practice. Because a positive test outcome might indicate a clinically manifesting irAE that requires treatment to (temporarily) discontinue, the occurrence of false-positive test outcomes is expected to negatively affect treatment outcomes. This study explores how the UPPAAL modeling environment can be used to assess the impact of test accuracy (i.e., test sensitivity and specificity), on the probability of patients entering palliative care within 11 IMT cycles. METHODS: A timed automata-based model was constructed using real-world data and expert consultation. Model calibration was performed using data from 248 non-small-cell lung cancer patients treated with nivolumab. A scenario analysis was performed to evaluate the effect of changes in test accuracy on the probability of patients transitioning to palliative care. RESULTS: The constructed model was used to estimate the cumulative probabilities for the patients' transition to palliative care, which were found to match real-world clinical observations after model calibration. The scenario analysis showed that the specificity of laboratory tests for routine monitoring has a strong effect on the probability of patients transitioning to palliative care, whereas the effect of test sensitivity was limited. CONCLUSION: We have obtained interesting insights by simulating a care pathway and disease progression using UPPAAL. The scenario analysis indicates that an increase in test specificity results in decreased discontinuation of treatment due to suspicion of irAEs, through a reduction of false-positive test outcomes.

INTRODUCTION: Juvenile idiopathic arthritis (JIA) is a chronic rheumatic disease, whose multifaceted care path can lead to significant expenditure for the healthcare system. We aim to assess the real-world healthcare resource use (HCRU) and associated cost for children with JIA in a single center in Canada. METHODS: A single-center consecutive cohort of newly diagnosed patients with JIA attending the pediatric rheumatology clinic from 2011 to 2019 was identified using an administrative data algorithm and electronic medical charts. HCRU was estimated from six administrative health databases that included hospital admissions, emergency, outpatient care, practitioners' visits, medication, and laboratory and imaging tests. Costs were assigned using appropriate sources. We reported the yearly overall and JIA-associated HCRU and costs 5 years prior to and 6 years after the first visit to the pediatric rheumatologist. The Zhao and Tian estimator was used to calculate cumulative mean costs over a 6-year timeframe. Results were stratified by disease subtype. RESULTS: A total of 389 patients were identified. The yearly total overall mean costs per patient ranged between $804 and $4460 during the 5 years prior to the first visit to the pediatric rheumatologist and $8529 and $10,651 for the 6 years after. Medication cost, driven by use of biologic therapies, and outpatient visits were the greatest contributor to the total cost. The overall cumulative mean cost for 6 years of care was $48,649 per patient, while the JIA-associated cumulative mean cost was $26,820 per patient. During the first year of rheumatology care, systemic onset JIA had the highest cumulative mean overall cost, while oligoarticular JIA had the lowest cumulative mean cost. CONCLUSION: The care pathway for children with JIA can be expensive, and complex-and varies by JIA subtype. Although the yearly total mean cost per patient was constant, the distribution of costs changes over time with the introduction of b