State Transition Model Research Articles

Health budget implications of mechanical thrombectomy for acute ischaemic stroke in Australia.

This research evaluates the budget impact of treating acute ischaemic stroke (AIS) using a combination of mechanical thrombectomy (MT) with stent retrievers (SR) and intravenous tissue-plasminogen activator (IV-tPA) in Australia. This study examined the economic impact over five years for a patient cohort based on the number of patients treated with MT+ IV-tPA in Australia 2021, versus treatment with IV-tPA alone. A budget impact (BI) model was developed to project direct medical costs (economic impact) of IV-tPA+ MT with SR vs. Intravenous tissue-plasminogen activator alone over a five-year period (2021-2025 inclusive) from a healthcare perspective. The model is composed of a short-run decision tree model based on a 3-month post-treatment modified Rankin Scale (mRS) from the EXTEND-IA study and a published long-run Markov state transition model. Acute, mid-term and long-term care costs were projected based on anticipated mRS scores from the EXTEND-IA trial. Estimated yearly and cumulative budget impact were reported to indicate the economic impact of the two treatment strategies for AIS in the Australian healthcare system. MT+IV-tPA had a greater budgetary impact than IV-tPA alone, with annual savings starting at Year 1 and continuing through to Year 5. Cost savings of 21% or approximately $36 million can be achieved over five years for the patient cohort treated in Australia in 2021. Each MT procedure performed delivers approximately $3280 in annual health system savings per patient. Treatment of AIS with a combination of MT+IV-tPA generates significant savings in the Australian healthcare system compared with IV-tPA alone.

Genotype-driven asthma prescribing of inhaled corticosteroids and long-acting β2-agonist: A cost-effectiveness analysis.

Predicting response to inhaled corticosteroids (ICSs) + long-acting β2-agonist (LABA) by previously detecting the presence of Arg16Gly ADRB2 genotype is a strategy that could reduce and optimize the management of asthmatic patients. There is a need for economic evaluations to facilitate the implementation of such tests. This research aims to evaluate the cost-effectiveness of Arg16Gly ADRB2 screening in children with asthma in Colombia. From the perspective of a third-party payer, we conducted a cost-effectiveness analysis to determine the cost and quality-adjusted life-years (QALYs) of genotype-driven asthma prescribing based on the Arg16Gly ADRB2 genotype versus current treatment based on no genetic testing. Using four state-transition models, we estimate cost and QALYs employing micro-simulation modeling with a time horizon of 10 years and a cycle length of 1 week. Cost-effectiveness was assessed at a willingness-to-pay (WTP) value of US$5180. The mean incremental cost of strategy genetic testing versus no genetic testing is US$ -6809. The mean incremental benefit of strategy genetic testing is 16 QALYs. The incremental net monetary benefit of strategic genetic testing versus no genetic testing is US$ 88,893. Genetic testing is the strategy with the highest expected net benefit. The outcomes derived from our primary analysis remained robust when subjected to variations in all underlying assumptions and parameter values. Genetic testing of Arg16Gly ADRB2 is a cost-effective strategy to address asthma management in asthmatic children requiring ICS+LABA. This result should encourage the generation of more evidence and the incorporation of such evidence into clinical practice guidelines for pediatric asthma.

Evaluating the Long-Term Cost-Effectiveness of the English NHS Diabetes Prevention Programme using a Markov Model.

In 2016, England launched the largest nationwide diabetes mellitus prevention programme, the NHS Diabetes Prevention Programme (NHS DPP). This paper seeks to evaluate the long-term cost-effectiveness of this programme. A Markov cohort state transition model was developed with a 35-year time horizon and yearly cycles to compare referral to the NHS DPPto usual care for individuals with non-diabetic hyperglycaemia. The modelled cohort of individuals mirrored the age profile of referrals received by the programme by April 2020. A health system perspective was taken, with costs in UK £ Sterling (price year 2020) and outcomes in terms of quality-adjusted life-years (QALYs). Probabilistic analysis with 10,000 Monte Carlo simulations was used. Several sensitivity analyses were conducted to explore the uncertainty surrounding the base case results, particularly varying the length of time for which the effectiveness of the programme was expected to last. In the base case, using only the observed effectiveness of the NHS DPP at 3years, it was found that the programme is likely to dominate usual care, by generating on average 40.8 incremental QALYs whilst saving £135,755 in costs for a cohort of 1000. At a willingness to pay of £20,000 per QALY, 98.1% of simulations were on or under the willingness-to-pay threshold. Scaling this up to the number of referrals actually received by the NHS DPP prior to April 2020, cost savings of £71.4 million were estimated over the 35-year time horizon and an additional 21,472 QALYs generated. These results are robust to several sensitivity analyses. The NHS DPP is likely to be cost-effective. Indeed, in the majority of the simulations, the NHS DPP was cost-saving and generated greater QALYs, dominating usual care. This research should serve as evidence to support the continued investment or recommissioning of diabetes prevention programmes.

Economic Evaluation of the Thai Diagnostic Autism Scale for Autism Spectrum Disorder Diagnosis in Children Aged 1-5 Years Old.

The Thai Diagnostic Autism Scale (TDAS) was developed for autism spectrum disorder (ASD) diagnosis in Thai children aged 1-5 years. Previous studies have indicated its good performance; however, additional health resources and healthcare providers are necessary for evaluation. Therefore, this study aimed to assess the cost-effectiveness of TDAS compared to clinical diagnosis (ClinDx) for ASD diagnosis in Thai children aged 1-5 years from a societal perspective. The analysis employed a hybrid model consisting of a decision tree model for a diagnostic phase with a state transition model for a follow-up phase. A literature review was conducted to determine TDAS performance and the relative risk of death in patients with ASD. Direct medical costs were assessed through a retrospective medical records review, and a cross-sectional survey was conducted to determine direct nonmedical costs, ASD severities, and utility values. The cost of TDAS was derived from a healthcare provider interview (n = 10). The incremental cost-effectiveness ratio (ICER) compared the total lifetime cost and quality-adjusted life years (QALY) between TDAS and ClinDx. We found that TDAS could improve QALY by 1.96 but increased total lifetime cost by 5577 USD, resulting in an ICER of 2852 USD/QALY. Sensitivity analysis indicated an 81.16% chance that TDAS is cost-effective. The probabilities of different ASD severities were key influencing factors of the findings. In conclusion, TDAS is the cost-effective option for ASD diagnosis in Thai children aged 1-5 years compared to ClinDx, despite some uncertainties around inputs. Further monitoring and evaluation are warranted if TDAS is to be implemented nationwide.

A systematic review on cost-effectiveness of diagnostic methods and treatments for tuberculosis in India

ObjectiveCost-effectiveness of a treatment is based on additional health benefits offered and for a test it is determined by fast and improved diagnosing capacity. Evidence on cost-effectiveness can help in identifying interventions that give optimal value for money and catalyse the effort of eliminating tuberculosis burden. Our objective is to evaluate and identify the cost-effectiveness of diagnostics and treatments for tuberculosis practiced in India from costing studies. MethodsElectronic databases like PubMed, Web of Science, Scopus, ProQuest, Cochrane Library, and PlosOne are searched, from Jan 1995 to Jan 2023 based on the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. Quality of the selected studies is assessed using a consensus health economic criteria checklist. ResultsAmong the twelve studies selected after quality assessment seven studies were on testing methods and five were on treatment interventions. The included, model-based studies used either state transition or decision tree model for cost analysis primarily in a health system perspective. Sputum smear microscopy test being dominated by other testing methods, strategies like public-private with right diagnostic method yields cost-effective results in tuberculosis healthcare. ConclusionFull economic evaluations on interventions for tuberculosis in India are scarce, particularly from patients’ perspective. The study provides holistic knowledge about the economic evaluations of tuberculosis tests and treatments, highlighting its applications and implemental complications for further development of improved strategies and economic evaluation.

218 Cost-Effectiveness and Quality-Adjusted Life Years Analysis for Endovascular Management of Acute Stroke With a Large Ischemic Region

INTRODUCTION: Mechanical thrombectomy (MT) for acute ischemic stroke is generally avoided when the infarction is large (defined as ASPECT score of < 5). However, a recent trial (RESCUE-Japan) published in NEJM, showed that patients with large cerebral infarctions had better functional outcomes, measured as mRS of 0-3 at 90 days, with MT compared to best medical management (BMM) alone. METHODS: Treeage, a decision-analytic software, was used to construct a cost effectiveness analysis model that compares the cost-effectiveness of MT vs. BMM alone based on the RESCUE-Japan study. The model includes a short-term decision model that examines costs and clinical outcomes of patients with acute ischemic stroke during the initial three months of treatment. Additionally, a long-term Markov state transition model is created to estimate expected outcomes and costs annually over a 20-year timeframe, with patients potentially experiencing recurrent strokes, transitioning to lower health states, and death from stroke. The success of each treatment was evaluated using QALYs. Then, to assess the robustness of this model, a sensitivity analysis was performed. RESULTS: In the base–case analysis of the total study population using a time horizon of 20 years, MT and BMM alone were found to have a 2.86 QALY and 1.44 QALY, respectively. This increase in the number of QALY by MT came at a lower cost of $275,805 compared to BMM alone, which had a cost $282,476. The incremental cost-effectiveness ratio (ICER) was determined at $-4697/QALY. The results were further supported by the 1-way deterministic and probabilistic sensitivity analyses. CONCLUSIONS: This study shows that, besides having a better clinical outcome, MT was more cost effective and associated with higher QALYs compared to BMM alone, when accounting for health care cost associated with treatment outcome.

Healthcare and economic cost burden of emergency medical services treated non-traumatic shock using a population-based cohort in Victoria, Australia

ObjectivesWe aimed to assess the healthcare costs and impact on the economy at large arising from emergency medical services (EMS) treated non-traumatic shock.DesignWe conducted a population-based cohort study, where EMS-treated...

Abstract 2307: State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia (CML)

Abstract Chronic myeloid leukemia (CML) is initiated and initially maintained by BCR-ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). Although TKIs can induce long-term remission, they are frequently not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR-ABL-inducible transgenic mice that recapitulates human chronic phase CML and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape that describes CML state-transition from health to disease. The potential’s stable critical points were used to define three distinct disease states. The Early state was characterized by anti-CML genes (n=35) that opposed leukemia progression, whereas an expanding number of pro-CML genes characterized the Transition state (n=357) and Late states (n=1,858). Gene modules that were co-regulated at the unstable points in the potential landscape were identified as the drivers of transition between stable disease states. To investigate CML therapies we used two treatments: silencing of BCR/ABL by readministering Tet (Tet-on, Tet-off [TOTO]) which represented a best-case scenario of disease being cured, and TKI (nilotinib) therapy which represents current clinical practice. TOTO returned the diseased mice transcriptomes to a near health state, without reaching it, suggesting partly irreversible transformation. TKI, however, only reverted the transcriptome to an intermediate disease state, without approaching health, and disease relapse occurred soon after treatment. Finally, using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response to both therapies for each individual mouse. In conclusion, these results show state-transition analysis is a valuable approach to gain real time insights into CML development, progression and ongoing treatment response that can also be applied to other type of leukemia and cancers in general. We predicted disease evolution and treatment response in a murine model that recapitulates human disease, supporting this as a potentially valuable approach to time clinical intervention even before phenotypic changes become detectable. Citation Format: David E. Frankhouser, Russell C. Rockne, Dandan Zhao, Sergio Branciamore, Lisa Uechi, Denis O'Meally, Yu-Hsuan Fu, Ya-Huei Kuo, Bin Zhang, Guido Marcucci. State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia (CML) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2307.

Abstract 7397: Application of state transition theory for predicting responses of acute myeloid leukemia to chemotherapy

Abstract Acute Myeloid Leukemia (AML) is aggressive cancer that initiates in the bone marrow (BM) and circulates in the peripheral blood (PB). The AML initiation and progressions are complex disease evolution associated with gene mutations and chromosomal abnormalities that change expression profiles of downstream genes characterizing functional networks of leukemic cells. We previously reported the application of the state-transition theory to characterize AML disease progression by modeling transcriptome changes during AML progression as a dynamic system that undergoes state-transition in an AML state-space characterized by an AML potential. Here, we investigate the impact of treatment on transcriptome state-transition and examine the hypothesis that treatment dynamically alters the AML potential. We use the Cbfb-MYH11 (CM) knock-in AML mouse model and a ”5+3” chemotherapy regimen to model the impact of current standard of care for newly diagnosed AML. CM leukemic mice were treated with a combination of cytarabine (Ara-C; 50mg/kg/day; 5 days) and Daunorubicin (DNR; 1.5mg/kg/day; 3 days) after detection of overt leukemia, defined by > 20% leukemia blast (cKit+) detected by flow cytometry in the PB. Time-series samples of peripheral blood mononuclear cell (PBMC) (n=174) were collected weekly before, during, and following “5+3” chemotherapy and subjected to RNA sequencing. All samples were mapped to the AML state-space constructed based on time-sequential RNA-seq collected over the course of CM AML development. Based on the state-transition model, all 10 treated AML mice achieved partial response to chemotherapy with a mean time to relapse (return to leukemia state) of 5 weeks confirming the anti-leukemia effects of treatment by the blast percentages (ckit%). We used the state-transition treatment model to study the dynamics of chemotherapy on the AML potential using state-space trajectories before, during, and after “5+3” chemotherapy. Dynamic changes of concentrations of Ara-C and DNR in the CM mouse model during ”5+3” chemotherapy were modeled by drug doses, half-life, and Heaviside step function. The drug effects were introduced to the AML potential as anti-leukemic treatment forces. Several treatment protocols were examined to find combinations of drug doses and timing that showed the longest survival rates. The model predicted that sequential doses reducing 50% of the original “5+3” chemotherapy dose would produce the longest survival rate. The model suggests that controlling the state-space trajectories in the healthy state with reduced doses will provide the most effective outcomes from “5+3” chemotherapy. Citation Format: Lisa Uechi, Yu-Hsuan Fu, David E. Frankhouser, Lianjun Zhang, Ying-Chieh Chen, Denis O'Meally, Sergio Branciamore, Jihyun Irizarry, Bin Zhang, Guido Marcucci, Ya-Huei Kuo, Russell C. Rockne. Application of state transition theory for predicting responses of acute myeloid leukemia to chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7397.

Cost-Effectiveness of Strategies for Treatment Timing for Perinatally Acquired Hepatitis C Virus

Prevalence of chronic hepatitis C virus (HCV) infection among pregnant people is increasing in the US. HCV is transmitted vertically in 7% to 8% of births. Direct-acting antiviral (DAA) therapy was recently approved for children with HCV who are 3 years or older. The clinical and economic impacts of early DAA therapy for young children with HCV, compared with treating at older ages, are unknown. To develop a state-transition model to project clinical and economic outcomes for children with perinatally acquired HCV to investigate the cost-effectiveness of treating at various ages. The study team modeled the natural history of perinatally acquired HCV to simulate disease progression and costs of a simulated a cohort of 1000 US children with HCV from 3 years old through death. Added data were analyzed January 5, 2021, through July 1, 2022. The study compared strategies offering 8 weeks of DAA therapy at 3, 6, 12, or 18 years old, as well as a comparator of never treating HCV. Outcomes of interest include life expectancy from 3 years and average lifetime per-person health care costs. Other clinical outcomes include cases of cirrhosis, decompensated cirrhosis, and hepatocellular carcinoma (HCC). The study team projected that treating HCV at 3 years old was associated with lower mean lifetime per-person health care costs ($148 162) than deferring treatment until 6 years old ($164 292), 12 years old ($171 909), or 18 years old ($195 374). Projected life expectancy was longest when treating at 3 years old (78.36 life years [LYs]) and decreased with treatment deferral until 6 years old (76.10 LYs), 12 years old (75.99 LYs), and 18 years old (75.46 LYs). In a cohort of 1000 children with perinatally acquired HCV, treating at 3 years old prevented 89 projected cases of cirrhosis, 27 cases of HCC, and 74 liver-related deaths compared with deferring treatment until 6 years old. In sensitivity analyses, increasing loss to follow-up led to even greater clinical benefits and cost savings with earlier treatment. These study results showed that DAA therapy for 3-year-old children was projected to reduce health care costs and increase survival compared with deferral until age 6 years or older. Measures to increase DAA access for young children will be important to realizing these benefits.

Cost-Effectiveness of Faricimab in the Treatment of Diabetic Macular Oedema (DMO): A UK Analysis.

The aim of this work was to evaluate the cost-effectiveness of faricimab against relevant therapeutic alternatives used in clinical practice for the treatment of diabetic macular oedema (DMO) in the UK. A state-transition (Markov) model, with health states based on visual acuity scores and treatment pathways, was developed to conduct cost-utility analysis of faricimab treat and extend (T&E) regimen versus ranibizumab pro re nata (PRN) and aflibercept PRN over a time horizon of 25 years. Comparison against bevacizumab PRN was considered in scenario analysis. Effectiveness data for faricimab was sourced from the pivotal YOSEMITE and RHINE double-blind randomised controlled trials, and from a network meta-analysis for comparators. Costs and (dis)utilities were taken from nationally published sources or literature. The base case included indirect costs (productivity gains, informal care) given the wider impacts of DMO on society. Sensitivity analyses were conducted. In the base case, faricimab T&E dominated ranibizumab PRN and aflibercept PRN, being more effective and resulting in cost savings (between 0.16 and 0.36 mean QALYs gained, and £5483-9655 mean cost savings). In scenario analysis, faricimab was more effective but costlier compared with bevacizumab, with an incremental cost-effectiveness ratio (ICER) of £8898 per QALY gained. Considering only healthcare payer costs, the ICER of faricimab compared with ranibizumab PRN was £7991 per QALY gained and faricimab dominated aflibercept PRN. Faricimab T&E has the potential to reduce the burden of vision loss on society, giving people living with DMO greater independence and contributing to increased healthcare system capacity. At a threshold of £20,000, faricimab T&E is cost-effective compared with relevant comparators, and potentially cost saving.

Forecasting geomagnetic activity: Neural networks, moving windows and state transition models

Geomagnetic activity shows high degrees of nonlinear variability. The probability distribution has heavy tails, and there are intermittent outliers. This has led to increased interest in forecasting using neural networks and nonlinear regressions, which include time-varying coefficient techniques. Because geomagnetic storms pose the greatest threat to satellites and power grids, there is a particular interest in predicting outlying events. The model proposed here combines two techniques. Neural networks and regressions are trained over moving windows of observations, so that the weights or coefficients adjust to new data. Second, logistic regression is used to predict the periods of high activity, and the cumulative distribution function is used as a causal input in time series and machine learning models. The data set is the Aa index, corrected for secular drift. Forecasting experiments are run over horizons of 1–4 days. The other models include time-varying parameter regressions and a recurrent neural network with fixed weights. The model combining the neural net and logistic regression achieves the most accurate forecast, although the regression is a close second. The ability to predict outliers depends on the width of the moving window. With wider windows, the overall error is lower, but the forecasted values fall into a narrower range, missing the outliers. With narrower windows, the model predicts the outliers better but is vulnerable to calling them at the wrong times, so the average error is higher. Further, while the model achieves more accurate predictions at 1 day, at longer horizons the accuracy deteriorates quite rapidly.

A Bayesian approach to identifying the role of hospital structure and staff interactions in nosocomial transmission of SARS-CoV-2.

Nosocomial infections threaten patient safety, and were widely reported during the COVID-19 pandemic. Effective hospital infection control requires a detailed understanding of the role of different transmission pathways, yet these are poorly quantified. Using patient and staff data from a large UK hospital, we demonstrate a method to infer unobserved epidemiological event times efficiently and disentangle the infectious pressure dynamics by ward. A stochastic individual-level, continuous-time state-transition model was constructed to model transmission of SARS-CoV-2, incorporating a dynamic staff-patient contact network as time-varying parameters. A Metropolis-Hastings Markov chain Monte Carlo (MCMC) algorithm was used to estimate transmission rate parameters associated with each possible source of infection, and the unobserved infection and recovery times. We found that the total infectious pressure exerted on an individual in a ward varied over time, as did the primary source of transmission. There was marked heterogeneity between wards; each ward experienced unique infectious pressure over time. Hospital infection control should consider the role of between-ward movement of staff as a key infectious source of nosocomial infection for SARS-CoV-2. With further development, this method could be implemented routinely for real-time monitoring of nosocomial transmission and to evaluate interventions.

How microsimulation translates outcome estimates to patient lifetime event occurrence in the setting of heart valve disease.

Treatment decisions in healthcare often carry lifelong consequences that can be challenging to foresee. As such, tools that visualize and estimate outcome after different lifetime treatment strategies are lacking and urgently needed to support clinical decision-making in the setting of rapidly evolving healthcare systems, with increasingly numerous potential treatments. In this regard, microsimulation models may prove valuable additions to current risk-prediction models. Notable advantages of microsimulation encompass input from multiple data sources, the ability to move beyond time-to-first-event analysis, accounting for multiple types of events, and generating projections of lifelong outcomes. This review aims to clarify the concept of microsimulation, also known as individualized state-transition models, and help clinicians better understand its potential in clinical decision-making. A practical example of a patient with heart valve disease is used to illustrate key components of microsimulation models, such as health states, transition probabilities, input parameters (e.g., evidence-based risks of events), and various aspects of mortality. Finally, this review focuses on future efforts needed in microsimulation to allow for increasing patient-tailoring of the models by extending the general structure with patient-specific prediction models and translating them to meaningful, user-friendly tools that may be used by both clinician and patient to support clinical decision-making.

Cost-Effectiveness of Late Endovascular Thrombectomy vs. Best Medical Management in a Clinical Trial Setting and Real-World Setting.

To assess cost-effectiveness of late time-window endovascular treatment (EVT) in a clinical trial setting and a "real-world" setting. Data are from the randomized ESCAPE trial and a prospective cohort study (ESCAPE-LATE). Anterior circulation large vessel occlusion patients presenting > 6 hours from last-known-well were included, whereby collateral status was an inclusion criterion for ESCAPE but not ESCAPE-LATE. A Markov state transition model was built to estimate lifetime costs and quality-adjusted life-years (QALYs) for EVT in addition to best medical care vs. best medical care only in a clinical trial setting (comparing ESCAPE-EVT to ESCAPE control arm patients) and a "real-world" setting (comparing ESCAPE-LATE to ESCAPE control arm patients). We performed an unadjusted analysis, using 90-day modified Rankin Scale(mRS) scores as model input and analysis adjusted for baseline factors. Acceptability of EVT was calculated using upper/lower willingness-to-pay thresholds of 100,000 USD/50,000 USD/QALY. Two-hundred and forty-nine patients were included (ESCAPE-LATE:n = 200, ESCAPE EVT-arm:n = 29, ESCAPE control-arm:n = 20). Late EVT in addition to best medical care was cost effective in the unadjusted analysis both in the clinical trial and real-world setting, with acceptability 96.6%-99.0%. After adjusting for differences in baseline variables between the groups, late EVT was marginally cost effective in the clinical trial setting (acceptability:49.9%-61.6%), but not the "real-world" setting (acceptability:32.9%-42.6%). EVT for LVO-patients presenting beyond 6 hours was cost effective in the clinical trial setting and "real-world" setting, although this was largely related to baseline patient differences favoring the "real-world" EVT group. After adjusting for these, EVT benefit was reduced in the trial setting, and absent in the real-world setting.

Challenges, considerations, and approaches for developing a cost-effectiveness model for the adjuvant treatment of muscle-invasive urothelial carcinoma: with a spotlight on nivolumab versus placebo

Aims To present challenges and considerations for the development of a decision analytic model for evaluating the cost-effectiveness of adjuvant nivolumab compared with surveillance in patients with high-risk muscle-invasive urothelial carcinoma (MIUC) after radical resection. Methods and Results Alternative approaches related to both structural assumptions and data sources are presented to address challenges and data gaps, as well as discussion of strengths and limitations of each approach. Specifically, challenges and considerations related to the following are presented: (1) selection of a modeling approach (partitioned survival model or state transition model) given the available evidence, (2) choice of health state structure (three- or four-state) to model disease progression and subsequent therapy, (3) modeling of outcomes from subsequent therapy using tunnel states to account for time-dependent transition probabilities or absorbing health states with one-off costs and outcomes applied, and (4) methods for modeling health-state transitions in a setting where treatment has curative intent and available survival data are immature. Conclusions Multiple considerations must be taken into account when developing an economic model for new, emerging oncology treatments in early lines of therapy, all of which can affect the model’s overall ability to estimate (quality-adjusted) survival benefits over a lifetime horizon. This paper identifies a series of key structural and analytic considerations regarding modeling of nivolumab treatment in the adjuvant MIUC setting. Several alternative approaches with regard to structure and data have been included in a flexible cost-effectiveness model so the impact of the alternative approaches on model results can be explored. The impact of these alternative approaches on cost-effectiveness results and validation of outcomes predicted by the model will be presented in two companion articles. Our findings may also help inform the development of future models for other treatments and settings in early-stage cancer.

Cost-effectiveness of surveillance intervals after curative resection of colorectal cancer.

Major guidelines consistently recommend 5years of postoperative surveillance for patients with colorectal cancer. However, they differ in their recommendations for examination intervals and whether they should vary according to disease stage. Furthermore, there are no reports on the cost-effectiveness of the different surveillance schedules. The objective of this study is to identify the most cost-effective surveillance intervals after curative resection of colorectal cancer. A total of 3701 patients who underwent curative surgery for colorectal cancer at the National Cancer Center Hospital were included. A cost-effectiveness analysis was conducted for the five surveillance strategies with reference to the guidelines. Expected medical costs and quality-adjusted life years after colorectal cancer resection were calculated using a state-transition model by Monte Carlo simulation. The incremental cost-effectiveness ratio per quality-adjusted life years gained was calculated for each strategy, with a maximum acceptable value of 43 500-52 200 USD (5-6 million JPY). Stages I, II and III included 1316, 1082 and 1303 patients, respectively, with 45, 140 and 338 relapsed cases. For patients with stage I disease, strategy 4 (incremental cost-effectiveness ratio $26 555/quality-adjusted life year) was considered to be the most cost-effective, while strategies 3 ($83 071/quality-adjusted life year) and 2 ($289 642/quality-adjusted life year) exceeded the threshold value. In stages II and III, the incremental cost-effectiveness ratio for strategy 3 was the most cost-effective option, with an incremental cost-effectiveness ratio of $18 358-22 230/quality-adjusted life year. In stage I, the cost-effectiveness of intensive surveillance is very poor and strategy 4 is the most cost-effective. Strategy 3 is the most cost-effective in stages II and III.

A102 EUS-GUIDED GASTROENTEROSTOMY IS COST-EFFECTIVE COMPARED TO SURGICAL GASTROJEJUNOSTOMY AND ENTERAL STENTING FOR PALLIATION OF MALIGNANT GASTRIC OUTLET OBSTRUCTION

Abstract Background Endoscopic ultrasound-guided gastroenterostomy (EUS-GE) is an emerging modality for the treatment of malignant gastric outlet obstruction (GOO), which combines the benefits of the traditional treatments by providing a robust bypass using a minimally invasive, endoscopic approach. The health economic aspects of this new treatment compared to the traditional treatment approaches are not known. Aims To conduct a cost-consequence analysis to compare the costs and benefits of using EUS-GE, surgical gastrojejunostomy (SGJ) and enteral stenting (ES) for the management of malignant GOO. Methods A decision analytical model, comprising a decision tree and a time-dependent state-transition model with three health states (no recurrent GOO, recurrent GOO, and death), was designed. The costs and benefits of the first month are included in the decision tree, after which, simulated patients enter the time-dependent state-transition model and the costs and consequences of each intervention are estimated for each monthly cycle until the end of a twelve-month time horizon. To address uncertainty around parameters, the expected values of costs and other outcomes were obtained through probabilistic analysis. The model parameters were assigned probability distributions and 10,000 Monte Carlo simulations were conducted using randomly sampled values drawn from these distributions. The outcomes were the estimated total cost and the probability of recurrent GOO in the follow-up time. We compared the incremental cost of avoiding recurrent GOO between these three strategies. A willingness-to-pay threshold of $50,000 to avoid recurrent GOO was established a priori. Results The total estimated costs for EUS-GE, SGJ, and ES, were $82,575 (SD, $16,240), $149,731 (SD, $27,254), and $77,324 (SD, $14,529), respectively. SGJ (6.84% [SD, 1.34]) had a lower GOO recurrence rate compared to EUS-GE (8.70% [SD, 1.64] and ES (23.37% [SD, 3.82]; however, when comparing SGJ with EUS-GE and ES, the incremental cost to avoid GOO recurrence was $ 3,611,345 and $37,854, respectively. The cost of avoiding GOO recurrence using EUS-GE compared to ES was $35,774. Conclusions EUS-GE has emerged as a cost-effective option in treating patients with malignant GOO. It is associated with a much lower cost per avoided recurrent GOO when compared to SGJ, and it is more effective in preventing recurrent GOO than ES at a cost that is well below the pre-set willingness-to-pay threshold of $50,000. Cumulative rate of GOO recurrence for EUS-GE, SGJ and ES Funding Agencies None

An economic evaluation of community pharmacy-dispensed naloxone in Canada.

To determine the cost-effectiveness of pharmacy-based intranasal (IN) and intramuscular (IM) naloxone distribution in Canada. We developed a state-transition model for pharmacy-based naloxone distribution, every 3 years, to illicit, prescription, opioid-agonist therapy and nonopioid use populations compared to no naloxone distribution. We used a monthly cycle length, lifetime horizon and a Canadian provincial Ministry of Health perspective. Transition probabilities, cost and utility data were retrieved from the literature. Costs (2020) and quality-adjusted life years (QALY) were discounted 1.5% annually. Microsimulation, 1-way and probabilistic sensitivity analyses were conducted. Distribution of naloxone to all Canadians compared to no distribution prevented 151 additional overdose deaths per 10,000 persons, with an incremental cost-effectiveness ratio (ICER) of $50,984 per QALY for IM naloxone and an ICER of $126,060 per QALY for IN naloxone. Distribution of any naloxone to only illicit opioid users was the most cost-effective. One-way sensitivity analysis showed that survival rates for illicit opioid users were most influenced by the availability of either emergency medical services or naloxone. Distribution of IM and IN naloxone to all Canadians every 3 years is likely cost-effective at a willingness-to-pay threshold of $140,000 Canadian dollars/QALY (~3 × gross domestic product from the World Health Organization). Distribution to people who use illicit opioids was most cost-effective and prevented the most deaths. This is important, as more overdose deaths could be prevented through nationwide public funding of IN naloxone kits through pharmacies, since individuals report a preference for IN naloxone and these formulations are easier to use, save lives and are cost-effective. Can Pharm J (Ott) 2024;157:xx-xx.

Comparison of partitioned survival modeling with state transition modeling approaches with or without consideration of brain metastasis: a case study of Osimertinib versus pemetrexed-platinum

BackgroundThe partitioned survival model (PSM) and the state transition model (STM) are widely used in cost-effectiveness analyses of anticancer drugs. Using different modeling approaches with or without consideration of brain metastasis, we compared the quality-adjusted life-year (QALY) estimates of Osimertinib and pemetrexed-platinum in advanced non-small cell lung cancer with epidermal growth factor receptor mutations.MethodsWe constructed three economic models using parametric curves fitted to patient-level data from the National Health Insurance Review and Assessment claims database from 2009 to 2020. PSM and 3-health state transition model (3-STM) consist of three health states: progression-free, post-progression, and death. The 5-health state transition model (5-STM) has two additional health states (brain metastasis with continuing initial therapy, and with subsequent therapy). Time-dependent transition probabilities were calculated in the state transition models. The incremental life-year (LY) and QALY between the Osimertinib and pemetrexed-platinum cohorts for each modeling approach were estimated over seven years.ResultsThe PSM and 3-STM produced similar incremental LY (0.889 and 0.899, respectively) and QALY (0.827 and 0.840, respectively). However, 5-STM, which considered brain metastasis as separate health states, yielded a slightly higher incremental LY (0.910) but lower incremental QALY (0.695) than PSM and 3-STM.ConclusionsOur findings indicate that incorporating additional health states such as brain metastases into economic models can have a considerable impact on incremental QALY estimates. To ensure appropriate health technology assessment decisions, comparison and justification of different modeling approaches are recommended in the economic evaluation of anticancer drugs.