State Transition Model Research Articles

Cost-Effectiveness of Diffusion-Weighted Magnetic Resonance Imaging Versus Second-Look Surgery in Treating Cholesteatoma: A Modeling Study.

To evaluate whether canal wall-up (CWU) tympanomastoidectomy with diffusion-weighted magnetic resonance imaging (DW-MRI) is a cost-effective method of treating cholesteatoma compared with CWU with second-look surgery. Cost-effectiveness analysis was conducted using a Markov state transition model. The simulation model adhered to the Panel Recommendations on Cost-Effectiveness in Health and Medicine established by the US Public Health Service. One-way and Monte Carlo probability sensitivity analyses were conducted for validation. Tympanomastoidectomy with DW-MRI versus tympanomastoidectomy with second-look surgery. Effectiveness and health utility were measured using quality-adjusted life years (QALYs). Costs were derived from Medicare reimbursement using the perspective of the payer. Probabilities for outcomes and complications were taken from existing literature. Cost-effectiveness was assessed using the incremental cost-effectiveness ratio. With base case analysis, the total cost was $15,069 when treated with CWU and second-look surgery versus $13,126 when treated with CWU and DW-MRI. The second-look treatment pathway yielded 17.05 QALYs, whereas the DW-MRI pathway yielded 16.91 QALYs in terms of health benefit accrued across the lifetime of the patient. The cost-effectiveness incremental cost-effectiveness ratio was $21,800/QALY. Using the conventional $50,000 willingness-to-pay threshold, second-look surgery was the more cost-effective approach 63.7% of the time by simulation. Both treatment pathways were found to be cost-effective, with second-look surgery incrementally cost-effective 63.7% of the time. Assumptions were validated by one-way and Monte Carlo probability sensitivity analysis. There is ample variation in treatment pathways regarding usage of DW-MRI and second-look surgery for cholesteatoma. To evaluate the cost-effectiveness of DW-MRI and second-look surgery approaches, accounting for health-related quality-of-life outcomes and costs for the duration of the patient lifetimes. To inform the discussion on the treatment for cholesteatoma given emergent noninvasive technologies.Level of Evidence: Level III.Indicate IRB or IACUC: Exempt.

Cost Effectiveness of Endovascular Ultrasound Renal Denervation in Patients with Resistant Hypertension.

Resistant hypertension (rHTN) is defined as blood pressure (BP) of ≥ 140/90mmHg despite treatment with at least three antihypertensive medications, including a diuretic. Endovascular ultrasound renal denervation (uRDN) aims to control BP alongside conventional BP treatment with antihypertensive medication. This analysis assesses the cost effectiveness of the addition of the Paradise uRDN System compared with standard of care alone in patients with rHTN from the perspective of the United Kingdom (UK) health care system. Using RADIANCE-HTN TRIO trial data, we developed a state-transition model. Baseline risk was calculated using Framingham and Prospective Cardiovascular Münster (PROCAM) risk equations to estimate the long-term cardiovascular risks in patients treated with the Paradise uRDN System, based on the observed systolic BP (SBP) reduction following uRDN. Relative risks sourced from a meta-analysis of randomised controlled trials were then used to project cardiovascular events in patients with baseline SBP ('control' patients); utility and mortality inputs and costs were derived from UK data. Costs and outcomes were discounted at 3.5% per annum. Modelled outcomes were validated against trial meta-analyses and the QRISK3 algorithm and real-world evidence of RDN effectiveness. One-way and probabilistic sensitivity analyses were conducted to assess the uncertainty surrounding the model inputs and sensitivity of the model results to changes in parameter inputs. Results were reported as incremental cost-effectiveness ratios (ICERs). A mean reduction in office SBP of 8.5mmHg with uRDN resulted in an average improvement in both absolute life-years (LYs) and quality-adjusted life-years (QALYs) gained compared with standard of care alone (0.73 LYs and 0.67 QALYs). The overall base-case ICER with uRDN was estimated at £5600 (€6500) per QALY gained (95% confidence interval £5463-£5739 [€6341-€6661]); modelling demonstrated > 99% probability that the ICER is below the £20,000-£30,000 (€23,214-€34,821) per QALYs gained willingness-to-pay threshold in the UK. Results were consistent across sensitivity analyses and validation checks. Endovascular ultrasound RDN with the Paradise system offers patients with rHTN, clinicians, and healthcare systems a cost-effective treatment option alongside antihypertensive medication.

Dynamic-Projection-Integrated Particle-Filtering-Based Identification of Friction Characteristic Curve for Train Wheelset on Slipping Fault Condition

This paper proposes a dynamic-projection-integrated particle-filtering-based identification strategy for the friction characteristic curve of a train wheelset under the slipping fault condition. This strategy aims to achieve the identification of the fault friction characteristic curve (FFCC) in the early slipping fault stage. First, a multi-dimensional integrated particle-filtering (MDIPF)-based parameters correction method is proposed. The MDIPF constructs an error particle state transition model encompassing multi-dimensional parameters, which integrates inter-particle correlation to facilitate error fusion during the state transition process. Then, a dynamic projection domain (DPD)-based particle refinement method is proposed. The DPD constructed the contraction factors to dynamically fine-tune the particle projection domain. Finally, a multi-level evaluation-based identification method for the FFCC is proposed. And the dynamic-projection-integrated particle-filtering-based identification strategy is validated, which can actualize the rapid and accurate identification of the FFCC.

Cost-Effectiveness of Fractional Flow Reserve–Guided Treatment for Acute Myocardial Infarction and Multivessel Disease

Complete revascularization by non-infarct-related artery (IRA) percutaneous coronary intervention (PCI) in patients with acute myocardial infarction is standard practice to improve patient prognosis. However, it is unclear whether a fractional flow reserve (FFR)-guided or angiography-guided treatment strategy for non-IRA PCI would be more cost-effective. To evaluate the cost-effectiveness of FFR-guided compared with angiography-guided PCI in patients with acute myocardial infarction and multivessel disease. In this prespecified cost-effectiveness analysis of the FRAME-AMI randomized clinical trial, patients were randomly allocated to either FFR-guided or angiography-guided PCI for non-IRA lesions between August 19, 2016, and December 24, 2020. Patients were aged 19 years or older, had ST-segment elevation myocardial infarction (STEMI) or non-STEMI and underwent successful primary or urgent PCI, and had at least 1 non-IRA lesion (diameter stenosis >50% in a major epicardial coronary artery or major side branch with a vessel diameter of ≥2.0 mm). Data analysis was performed on August 27, 2023. Fractional flow reserve-guided vs angiography-guided PCI for non-IRA lesions. The model simulated death, myocardial infarction, and repeat revascularization. Future medical costs and benefits were discounted by 4.5% per year. The main outcomes were quality-adjusted life-years (QALYs), direct medical costs, incremental cost-effectiveness ratio (ICER), and incremental net monetary benefit (INB) of FFR-guided PCI compared with angiography-guided PCI. State-transition Markov models were applied to the Korean, US, and European health care systems using medical cost (presented in US dollars), utilities data, and transition probabilities from meta-analysis of previous trials. The FRAME-AMI trial randomized 562 patients, with a mean (SD) age of 63.3 (11.4) years. Most patients were men (474 [84.3%]). Fractional flow reserve-guided PCI increased QALYs by 0.06 compared with angiography-guided PCI. The total cumulative cost per patient was estimated as $1208 less for FFR-guided compared with angiography-guided PCI. The ICER was -$19 484 and the INB was $3378, indicating that FFR-guided PCI was more cost-effective for patients with acute myocardial infarction and multivessel disease. Probabilistic sensitivity analysis showed consistent results and the likelihood iteration of cost-effectiveness in FFR-guided PCI was 97%. When transition probabilities from the pairwise meta-analysis of the FLOWER-MI and FRAME-AMI trials were used, FFR-guided PCI was more cost-effective than angiography-guided PCI in the Korean, US, and European health care systems, with an INB of $3910, $8557, and $2210, respectively. In probabilistic sensitivity analysis, the likelihood iteration of cost-effectiveness with FFR-guided PCI was 85%, 82%, and 31% for the Korean, US, and European health care systems, respectively. This cost-effectiveness analysis suggests that FFR-guided PCI for non-IRA lesions saved medical costs and increased quality of life better than angiography-guided PCI for patients with acute myocardial infarction and multivessel disease. Fractional flow reserve-guided PCI should be considered in determining the treatment strategy for non-IRA stenoses in these patients. ClinicalTrials.gov Identifier: NCT02715518.

Estimating Transition Probabilities for Modeling Major Depression in Adolescents by Sex and Race or Ethnicity Combinations in the USA.

About one-fifth of US adolescents experienced major depressive symptoms, but few studies have examined longitudinal trends of adolescents developing depression or recovering by demographic factors. We estimated new transition probability inputs, and then used them in a simulation model to project the epidemiologic burden and trajectory of depression of diverse adolescents by sex and race or ethnicity combinations. Transition probabilities were first derived using parametric survival analysis of data from the National Longitudinal Study of Adolescent to Adult Health and then calibrated to cross-sectional data from the National Survey on Drug Use and Health. We developed a cohort state-transition model to simulate age-specific depression outcomes of US adolescents. A hypothetical adolescent cohort was modeled from 12-22years with annual transitions. Model outcomes included proportions of youth experiencing depression, recovery, or depression-free casesand were reported for a US adolescent population by sex, race or ethnicity, and sex and race or ethnicity combinations. At 22 years of age, approximately 16% of adolescents had depression, 12% were in recovery, and 72% had never developed depression. Depression prevalence peaked around 16-17years-old. Adolescents of multiracial or other race or ethnicity, White, American Indian or Alaska Native, and Hispanic, Latino, or Spanish descent were more likely to experience depression than other racial or ethnic groups. Depression trajectories generated by the model matched well with historical observational studies by sex and race or ethnicity, except for individuals from American Indian or Alaska Native and multiracial or other race or ethnicity backgrounds. This study validated new transition probabilities for future use in decision models evaluating adolescentdepression policies or interventions. Different sets of transition parameters by demographic factors (sex and race or ethnicity combinations) were generated to support future health equity research, including distributional cost-effectiveness analysis. Further data disaggregated with respect to race, ethnicity, religion, income, geography, gender identity, sexual orientation, and disability would be helpful to project accurate estimates for historicallyminoritized communities.

Kernel-based diffusion approximated Markov decision processes for autonomous navigation and control on unstructured terrains

We propose a diffusion approximation method to the continuous-state Markov decision processes that can be utilized to address autonomous navigation and control in unstructured off-road environments. In contrast to most decision-theoretic planning frameworks that assume fully known state transition models, we design a method that eliminates such a strong assumption that is often extremely difficult to engineer in reality. We first take the second-order Taylor expansion of the value function. The Bellman optimality equation is then approximated by a partial differential equation, which only relies on the first and second moments of the transition model. By combining the kernel representation of the value function, we design an efficient policy iteration algorithm whose policy evaluation step can be represented as a linear system of equations characterized by a finite set of supporting states. We first validate the proposed method through extensive simulations in 2D obstacle avoidance and 2.5D terrain navigation problems. The results show that the proposed approach leads to a much superior performance over several baselines. We then develop a system that integrates our decision-making framework with onboard perception and conduct real-world experiments in both cluttered indoor and unstructured outdoor environments. The results from the physical systems further demonstrate the applicability of our method in challenging real-world environments.

A cost-effectiveness analysis of lung cancer screening with low-dose computed tomography and a polygenic risk score

IntroductionSeveral studies have proved that Polygenic Risk Score (PRS) is a potential candidate for realizing precision screening. The effectiveness of low-dose computed tomography (LDCT) screening for lung cancer has been proved to reduce lung cancer specific and overall mortality, but the cost-effectiveness of diverse screening strategies remained unclear.MethodsThe comparative cost-effectiveness analysis used a Markov state-transition model to assess the potential effect and costs of the screening strategies incorporating PRS or not. A hypothetical cohort of 300,000 heavy smokers entered the study at age 50–74 years and were followed up until death or age 79 years. The model was run with a cycle length of 1 year. All the transition probabilities were validated and the performance value of PRS was extracted from published literature. A societal perspective was adopted and cost parameters were derived from databases of local medical insurance bureau. Sensitivity analyses and scenario analyses were conducted.ResultsThe strategy incorporating PRS was estimated to obtain an ICER of CNY 156,691.93 to CNY 221,741.84 per QALY gained compared with non-screening with the initial start age range across 50–74 years. The strategy that screened using LDCT alone from 70–74 years annually could obtain an ICER of CNY 80,880.85 per QALY gained, which was the most cost-effective strategy. The introduction of PRS as an extra eligible criteria was associated with making strategies cost-saving but also lose the capability of gaining more LYs compared with LDCT screening alone.ConclusionThe PRS-based conjunctive screening strategy for lung cancer screening in China was not cost-effective using the willingness-to-pay threshold of 1 time Gross Domestic Product (GDP) per capita, and the optimal screening strategy for lung cancer still remains to be LDCT screening for now. Further optimization of the screening modality can be useful to consider adoption of PRS and prospective evaluation remains a research priority.

Risk-Aware Markov Decision Process Contingency Management Autonomy for Uncrewed Aircraft Systems

Uncrewed aircraft systems (UASs) are being increasingly adopted for a variety of applications. The risk UAS poses to people and property must be kept to acceptable levels. This paper proposes risk-aware contingency management autonomy to prevent an accident in the event of component malfunction, specifically propulsion unit failure and/or battery degradation. The proposed autonomy is modeled as a Markov decision process (MDP), whose solution is a contingency management policy that appropriately executes emergency landing, flight termination, or continuation of planned flight actions. Motivated by the potential for errors in fault/failure indicators, the partial observability of the MDP state space is investigated. The performance of optimal policies is analyzed over varying observability conditions in a high-fidelity simulator. Results indicate that both partially observable MDP and maximum a posteriori MDP policies had similar performance over different state observability criteria, given the nearly deterministic state transition model.

Real-world diagnostic outcomes and cost-effectiveness of genome-wide sequencing for developmental and seizure disorders: Evidence from Canada

PurposeTo determine real-world diagnostic rates, cost trajectories, and cost-effectiveness of exome sequencing (ES) and genome sequencing (GS) for children with developmental and/or seizure disorders in British Columbia, Canada. MethodsBased on medical records review, we estimated real-world costs and outcomes for 491 patients who underwent standard of care (SOC) diagnostic testing at British Columbia Children’s Hospital. Results informed a state-transition Markov model examining cost-effectiveness of 3 competing diagnostic strategies: (1) SOC with last-tier access to ES, (2) streamlined ES access, and (3) first-tier GS. ResultsThrough SOC, 49.4% (95% CI: 40.6, 58.2) of patients were diagnosed at an average cost of C$11,683 per patient (95% CI: 9200, 14,166). Compared with SOC, earlier ES or GS access yielded similar or improved diagnostic rates and shorter times to genetic diagnosis, with 94% of simulations demonstrating cost savings for streamlined ES and 60% for first-tier GS. Net benefit from the perspective of the health care system was C$2956 (95% CI: −608, 6519) for streamlined ES compared with SOC. ConclusionUsing real-world data, we found earlier access to ES may yield more rapid genetic diagnosis of childhood developmental and seizure disorders and cost savings compared with current practice in a Canadian health care system.

Cost-effectiveness of interferon-γ release assay for screening of latent tuberculosis infection in individuals with schizophrenia.

Schizophrenia is recognized as a significant risk factor for tuberculosis (TB). This study aimed to evaluate the effectiveness and cost-effectiveness of interferon-γ release assay (IGRA) with preventive treatment for screening of latent tuberculosis infection (LTBI) in individuals with schizophrenia. A state transition model was developed from a healthcare payer perspective on a lifetime horizon. Ten strategies were compared by combining two different tests for LTBI, i.e. IGRA and tuberculin skin test (TST), and five different preventive treatments, i.e. 9-month isoniazid (9H), 3-month isoniazid and rifapentine (3HP) by directly observed therapy, 3HP by self-administered therapy, 3-month isoniazid and rifampin (3RH), and 4-month rifampin (4R). The main outcomes were costs, quality-adjusted life-years (QALYs), life expectancy life-years (LYs), incremental cost-effectiveness ratios, drug-sensitive tuberculosis (DS-TB) cases, and TB-related deaths. For both bacillus Calmette-Guérin (BCG)-vaccinated and non-BCG-vaccinated individuals, IGRA with 4R was the most cost-effective and TST with 3RH was the least effective. Among schizophrenic individuals in Japan, IGRA with 4R saved US$17.8 million, increased 58,981 QALYs and 935 LYs, and prevented 222 DS-TB cases and 75 TB-related deaths compared with TST with 3RH. In individuals with schizophrenia, IGRA with 4R is recommended for LTBI screening with preventive treatment to reduce costs, morbidity, and mortality from TB.

Cost-Effectiveness of Adjuvant Olaparib for Patients With Breast Cancer and Germline BRCA1/2 Mutations

The OlympiA trial found that 1 year of adjuvant olaparib therapy can improve distant disease-free survival and overall survival from early-stage breast cancer in patients with a germline BRCA1/2 mutation. However, olaparib, an oral poly-adenosine diphosphate ribose polymerase inhibitor, is estimated to cost approximately $14 000 per month in the US. To estimate the incremental cost-effectiveness of adjuvant olaparib compared with no olaparib in eligible patients. In an economic evaluation from a health care system perspective, the cost-effectiveness of adjuvant olaparib was analyzed using a Markov state-transition model. The model simulated costs and lifetime health outcomes of 42-year-old women with high-risk early-stage breast cancer and a known BRCA1/2 mutation who completed definitive primary therapy and neoadjuvant or adjuvant systemic therapy. The study was conducted from August 2021 to July 2023. The effectiveness of olaparib was based on the findings of the OlympiA randomized clinical trial, and other model parameters were identified from the literature. The model was calibrated to the 1-, 2-, 3-, and 4-year distant disease-free and overall survival observed in the OlympiA trial, and olaparib was assumed to reduce the risk of distant recurrence only in the first 4 years. One year of adjuvant olaparib or no adjuvant olaparib. Incremental cost-effectiveness ratio (ICER) in 2021 US dollars per quality-adjusted life-year (QALY) gained. All outcomes were discounted by 3% annually. In the base case, adjuvant olaparib was associated with a 1.25-year increase in life expectancy and a 1.20-QALY increase at an incremental cost of $133 133 compared with no olaparib. The resulting ICER was approximately $111 000 per QALY gained. At a willingness-to-pay threshold of $150 000 per QALY, olaparib was cost-effective at its 2021 price and in more than 92% of simulations in probabilistic sensitivity analysis. The results were sensitive to assumptions about the effectiveness of olaparib and quality of life for patients with no disease recurrence. In this study, from a US health care system perspective, adjuvant olaparib was a cost-effective option for patients with high-risk, early-stage breast cancer and a germline BRCA1/2 mutation.

Tracking Emotions Using an Evolutionary Model of Mental State Transitions: Introducing a New Paradigm

Owing to rapid advancements in artificial intelligence, the role of emotion recognition has become paramount in human–computer interaction. Traditional approaches often reduce this intricate task to a mere classification problem by relying heavily on perceptual pattern-recognition techniques. However, this simplification overlooks the dynamic and multifaceted nature of human emotions. According to theories in emotion psychology, existing pattern recognition methods primarily capture external emotional expressions—termed “external emotional energy” (EEE)—rather than the nuanced underlying emotions. To address this gap, we introduce the evolutionary mental state transition model (EMSTM). In the initial phase, EMSTM employs standard pattern-recognition algorithms to extract EEE from multi-modal human expressions. Subsequently, it leverages a mental state transition network to model the dynamic transitions between emotional states, thereby predicting real-time emotions with higher fidelity. We validated the efficacy of EMSTM through experiments on 2 multi-label emotion datasets: CMU Multimodal Opinion Sentiment and Emotion Intensity (CMU-MOSEI) and Ren Chinese Emotion Corpus (Ren-CECps). The results indicate a marked improvement over conventional methods. By synergistically combining principles from psychology with computational techniques, EMSTM offers a holistic and accurate framework for real-time emotion tracking, aligning closely with the dynamic mental processes that govern human emotions.

State Transition Modeling Method for Optimal Dispatching for Integrated Energy System Based on Cyber-Physical System

State Transition Modeling Method for Optimal Dispatching for Integrated Energy System Based on Cyber-Physical System

The Emotional State Transition Model Empowered by Genetic Hybridization Technology on Human–Robot Interaction

The Emotional State Transition Model Empowered by Genetic Hybridization Technology on Human–Robot Interaction

Cost-effectiveness of endovascular treatment after 6-24 h in ischaemic stroke patients with collateral flow on CT-angiography: A model-based economic evaluation of the MR CLEAN-LATE trial.

The MR CLEAN-LATE trial has shown that patient selection for endovascular treatment (EVT) in the late window (6-24 h after onset or last-seen-well) based on the presence of collateral flow on CT-angiography is safe and effective. We aimed to assess the cost-effectiveness of late-window collateral-based EVT-selection compared to best medical management (BMM) over a lifetime horizon (until 95 years of age). A model-based economic evaluation was performed from a societal perspective in The Netherlands. A decision tree was combined with a state-transition (Markov) model. Health states were defined by the modified Rankin Scale (mRS). Initial probabilities at 3-months post-stroke were based on MR CLEAN-LATE data. Transition probabilities were derived from previous literature. Information on short- and long-term resource use and utilities was obtained from a study using MR CLEAN-LATE and cross-sectional data. All costs are expressed in 2022 euros. Costs and quality-adjusted life years (QALYs) were discounted at a rate of 4% and 1.5%, respectively. The effect of parameter uncertainty was assessed using probabilistic sensitivity analysis (PSA). On average, the EVT strategy cost €159,592 (95% CI: €140,830-€180,154) and generated 3.46 QALYs (95% CI: 3.04-3.90) per patient, whereas the costs and QALYs associated with BMM were €149,935 (95% CI: €130,841-€171,776) and 2.88 (95% CI: 2.48-3.29), respectively. The incremental cost-effectiveness ratio per QALY and the incremental net monetary benefit were €16,442 and €19,710, respectively. At a cost-effectiveness threshold of €50,000/QALY, EVT was cost-effective in 87% of replications. Collateral-based selection for late-window EVT is likely cost-effective from a societal perspective in The Netherlands.

Cost-effectiveness of intravenous resuscitation fluids in sepsis patients: a patient-level data analysis in Jordan

Aim Albumin role as fluid resuscitation in sepsis remains understudied in low- and middle-income countries. This study aimed to evaluate the cost-effectiveness of intravenous (IV) Albumin compared to Crystalloids in sepsis patients using patient-level data in Jordan. Methods This was a retrospective cohort study of sepsis patients aged 18 or older admitted to intensive care units (ICU) at two major tertiary hospitals during the period 2018–2019. Patients information, type of IV fluid, and clinical outcomes were retrieved from medical records, and charges were retrieved from the billing system. A 90-day partitioned survival model with two health states (alive and dead) was constructed to estimate the survival of sepsis patients receiving either Albumin or Crystalloids as IV fluids for resuscitation. Overall survival was predicted by fitting a Weibull model on the patient-level data from the current study. To further validate the results, and to support the assessment of uncertainty, time-dependent transition probabilities of death at each cycle were estimated and used to construct a state-transition patient-level simulation model with 10,000 microsimulation trials. Adopting the healthcare system perspective, incremental cost-effectiveness ratios(ICERs) of Albumin versus Crystalloids were calculated in terms of the probability to be discharged alive from the ICU. Uncertainty was explored using probabilistic sensitivity analysis. Results In the partitioned survival model, Albumin was associated with an incremental cost of $1,007 per incremental1% in the probability of being discharged alive from the ICU. In the state-transition patient-level simulation model, ICER was $1,268 per incremental 1% in the probability of being discharged alive. Probabilistic sensitivity analysis showed that Albumin was favored at thresholds >$800 per incremental 1%in the probability of being discharged alive from the ICU. Conclusion IV Albumin use in sepsis patients might not be cost-effective from the healthcare perspective of Jordan. This has important implications for policymakers to readdress Albumin prescribing practice in sepsis patients.

Improved estimation of overall survival and progression-free survival for state transition modeling.

Aim: National Institute for Health and Care Excellence guidance (Technical Support Document 19) highlights a key challenge of state transition models (STMs) being their difficulty in achieving a satisfactory fit to the observed within-trial endpoints. Fitting poorly to data over the trial period can then have implications for long-term extrapolations. A novel estimation approach is defined in which the predicted overall survival (OS) and progression-free survival (PFS) extrapolations from anSTM are optimized to provide closer estimates of the within-trial endpoints. Materials & methods: An STM was fitted to the SQUIRE trial data in non-small-cell lung cancer (obtained from Project Data Sphere). Two methods were used: a standard approach whereby the maximum likelihood was utilized for the individual transitions and the best-fitting parametric model selected based on AIC/BIC, and a novel approach in which parameters were optimized by minimizing the area between the STM-predicted OS and PFS curves and the corresponding OS and PFS Kaplan-Meier curves. Sensitivity analyses were conducted to assess uncertainty. Results: The novel approach resulted in closer estimations to the OS and PFS Kaplan-Meier for all combinations of parametric distributions analyzed compared with the standard approach. Though the uncertainty associated with the novel approach was slightly larger, it provided better estimates to the restricted mean survival time in 10 of the 12 parametric distributions analyzed. Conclusion: A novel approach is defined which provides an alternative STM estimation method enabling improved fits to modeled endpoints, which can easily be extended to more complex model structures.

Sotorasib versus Docetaxel for treatment of US and Chinese patients with advanced non-small-cell lung cancer with KRAS p.G12C-mutated: A cost-effectiveness analysis to inform drug pricing.

The cost-effectiveness of sotorasib and its reasonable price in the United States (US) and China remain unknown. Our objective was to estimate the price at which sotorasib could be economical as second-line treatment for advanced non-small-cell lung cancer patients with Kirsten rat sarcoma viral oncogene homolog p.G12C-mutation in 2 countries. We conducted an economic evaluation from the perspective of US and Chinese payers. To analyze US patients, we built a partitioned survival model. However, since we lacked Asian-specific overall survival data, we created a state transition model for the Chinese patients. We obtained patients' baseline characteristics and clinical data from CodeBreaK200, while utilities and costs were gathered from public databases and published literature. We calculated costs (US dollar), life years, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios. We conducted price simulation to guide pricing strategies. Additionally, we assessed the reliability of our results through sensitivity analyses, scenario analyses, and subgroup analyses. The incremental cost-effectiveness ratios of sotorasib compared to docetaxel were $1501,852 per quality-adjusted life-years (QALY) in the US and $469,106/QALY in China, respectively, which meant sotorasib was unlikely to be economical at the currently available price of $20,878 (240 × 120 mg) in both countries. Price simulation results revealed that sotorasib would be preferred at a price lower than $1400 at the willingness-to-pay threshold of $37,376 in China and a price lower than $2220 at the willingness-to-pay threshold of $150,000 in the US. Sensitivity, scenario, and subgroup analyses showed that these conclusions were generally robust, the model was most sensitive to the utilities of progression-free survival and post-progression survival. Sotorasib could potentially be a cost-effective therapy in the US and China following price reductions. Our evidence-based pricing strategy can assist decision-makers and clinicians in making optimal decisions. However, further analysis of budget impact and affordability is needed.

Cost-effectiveness of volume computed tomography in lung cancer screening: a cohort simulation based on Nelson study outcomes

Objectives This study aimed to evaluate the cost-effectiveness of lung cancer screening (LCS) with volume-based low-dose computed tomography (CT) versus no screening for an asymptomatic high-risk population in the United Kingdom (UK), utilising the long-term insights provided by the NELSON study, the largest European randomized control trial investigating LCS. Methods A cost-effectiveness analysis was conducted using a decision tree and a state-transition Markov model to simulate the identification, diagnosis, and treatments for a lung cancer high-risk population, from a UK National Health Service (NHS) perspective. Eligible participants underwent annual volume CT screening and were compared to a cohort without the option of screening. Screen-detected lung cancers, costs, quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) were predicted. Results Annual volume CT screening of 1.3 million eligible participants resulted in 96,474 more lung cancer cases detected in early stage, and 73,825 fewer cases in late stage, leading to 53,732 premature lung cancer deaths averted and 421,647 QALYs gained, compared to no screening. The ICER was £5,455 per QALY. These estimates were robust in sensitivity analyses. Limitations Lack of long-term survival data for lung cancer patients; deficiency in rigorous micro-costing studies to establish detailed treatment costs inputs for lung cancer patients. Conclusions Annual LCS with volume-based low-dose CT for a high-risk asymptomatic population is cost-effective in the UK, at a threshold of £20,000 per QALY, representing an efficient use of NHS resources with substantially improved outcomes for lung cancer patients, as well as additional societal and economic benefits for society as a whole. These findings advocate evidence-based decisions for the potential implementation of a nationwide LCS in the UK.

Proposal of uncertainty analysis methodology for L1PRA using Markov state-transition model

ABSTRACT Following the severe accident at the Fukushima Daiichi Nuclear Power Plant in 2011, the revised nuclear safety regulation in Japan requires continuous safety improvement and states that PRA methods that reflect the latest knowledge should be used in activities related to continuous safety improvement. In this context, the construction of PRA models for the digital RPS (DRPS) has been addressed as an important issue within the Working Group on Risk Assessment (WGRISK) of the OECD/NEA, and several studies have been conducted. And there are challenges in aligning them with the conventional probabilistic risk assessment methodology. In a previous study, the authors developed a simultaneous differential equation describing the relationship between state transitions and state probabilities based on Markov state transition diagrams to calculate them numerically. However, the analytical method for uncertainty analysis commonly used in conventional PRA evaluations is not explicitly presented. The purpose of this study is to provide a methodology for more accurate evaluation of core damage frequency in nuclear power plants equipped with digital RPS, taking into account the uncertainties, and to contribute to the continuous improvement of safety.