Three-state Model Research Articles

A cost-effectiveness analysis of capecitabine maintenance therapy versus routine follow-up for early-stage triple-negative breast cancer patients after standard treatment from a perspective of Chinese society

BackgroundCapecitabine maintenance therapy is safe and efficacious for early-stage triple-negative breast cancer (TNBC) patients, but the cost-effectiveness of its long-term use has not been investigated. Here, we evaluated the cost-effectiveness of capecitabine maintenance therapy, compared with routine follow-up, in early-stage TNBC patients after standard treatment from a perspective of Chinese society.MethodsA three-state Markov model based on the data from the SYSUCC-001 trial was constructed to estimate the cost-effectiveness of capecitabine maintenance therapy in a month cycle over a period of 30-year time horizon. A 5% annual discount rate was set for all costs and benefits. One-way and probabilistic sensitivity analyses were performed to explore the model uncertainties. The main outcomes include quality-adjusted life years (QALYs), incremental cost-effectiveness ratio (ICER), and the number needed to treat (NNT) to prevent one additional event.ResultsCompared with routine follow-up, 1-year capecitabine maintenance therapy yielded an additional 1.29 quality-adjusted life years (QALYs) at an additional cost of $3391.70, with an ICER of $2630.53 (95% CI: $1159.81–$5090.12) per QALY gained. The ICER was considerably lower than the recommended willingness-to-pay (WTP) threshold (i.e., $28,130.00 per QALY). The results were sensitive to the discount rate, drug cost, and treatment cost after relapse. Further, the NNT to prevent one additional relapse case was 29.2 (95% CI: 13.2–196.6), 16.7 (95% CI: 8.4–111.6), and 12.0 (95% CI: 5.7–82.6) at 1, 2, and 5 years, respectively.ConclusionsOne-year capecitabine maintenance therapy for early-stage TNBC after standard treatment, compared with routine follow-up, was found to be highly cost-effective with promising clinical benefits and acceptable increased costs. Real-world studies are warranted to validate our findings in the future.

Cost-effectiveness analysis of sugemalimab vs. chemotherapy as first-line treatment of metastatic nonsquamous non-small cell lung cancer.

Objective: Sugemalimab is approved in China as a first-line treatment in combination with chemotherapy for metastatic nonsquamous non-small cell lung cancer (NSCLC). This study aims to evaluate the cost-effectiveness of first-line additional sugemalimab in combination with chemotherapy vs. chemotherapy from the perspective of the Chinese healthcare system. Materials and methods: A three-state Markov model was designed to evaluate the costs and quality-adjusted life years (QALYs) of first-line sugemalimab combination with chemotherapy vs. chemotherapy over a 10-year period. Data on clinical outcomes were obtained from GEMSTONE-302 clinical trials. Costs and health utilities were collected from local databases and published literature. The uncertainty of the model parameters was explored through sensitivity analysis. Results: Compared to chemotherapy, sugemalimab treatment for NSCLC resulted in an extra 0.50 QALYs at an additional cost of $73627.99, with an incremental cost-effectiveness ratio (ICER) of 148354.07/QALY at the willingness-to-pay (WTP) threshold of $37663.26/QALY. One-way sensitivity analysis indicated that the primary motivator in this model was the cost of sugemalimab. However, none of the parameters significantly affected the model’s results. Conclusion: Sugemalimab combination therapy is not economically advantageous for the first-line management of metastatic non-squamous NSCLC, according to the Chinese healthcare system.

Gibbs measures for the three-state SOS model with external field on a Cayley tree

Gibbs measures for the three-state SOS model with external field on a Cayley tree

Economic evaluation of margetuximab vs. trastuzumab for pretreated ERBB2-positive advanced breast cancer in the US and China.

ObjectiveTo assess the economic evaluation of margetuximab plus chemotherapy over trastuzumab plus chemotherapy for women with pretreated ERBB2-positive advanced breast cancer in the United States (US) and China.MethodsBased on the SOPHIA trial, a three-state Markov model was developed to compare the cost and efficacy of margetuximab to trastuzumab for previously treated women with ERBB2-positive advanced breast cancer. The model inputs were derived from existing literature and the US life table. Primary outcomes included lifetime costs in US dollars, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER). Deterministic and probabilistic sensitivity analyses were conducted to evaluate the impact of uncertainty.ResultsThe base case analyses demonstrated that margetuximab plus chemotherapy had an increasing cost of $68,132 and $20,540 over trastuzumab plus chemotherapy in the US and China, respectively, with a gain of 0.11 and 0.09 QALYs both favored margetuximab. The ICERs for two treatment strategies were $260,176 in the US and $630,777 in China, resulting in a poor cost-effectiveness at their respective threshold of willingness to play. One-way sensitivity analyses showed that the results to be most sensitive to the price of margetuximab and that of trastuzumab. And an 11 and 82% price reduction of margetuximab would make this regimen cost-effective in the US and China, respectively.ConclusionIn the US and China, margetuximab plus chemotherapy is not likely to be cost-effective for women with pretreated ERBB2-positive advanced breast cancer, whereas price reduction effectively improves insufficient cost-effectiveness.

Periodic Gibbs measures for the three-state SOS model on a Cayley tree with a translation-invariant external field

Periodic Gibbs measures for the three-state SOS model on a Cayley tree with a translation-invariant external field

Persistent Homology Analysis for Dense QCD Effective Model with Heavy Quarks

The isospin chemical potential region is known as the sign-problem-free region of quantum chromodynamics (QCD). In this paper, we introduce the isospin chemical potential to the three-dimensional three-state Potts model to mimic dense QCD; e.g., the QCD effective model with heavy quarks at finite density. We call it the QCD-like Potts model. The QCD-like Potts model does not have a sign problem, but we expect it to share some properties with QCD. Since we can obtain the non-approximated Potts spin configuration at finite isospin chemical potential, where the simple Metropolis algorithm can work, we perform the persistent homology analysis toward exploring the dense spatial structure of QCD. We show that the averaged birth-death ratio has the same information with the Polyakov loop, but the maximum birth-death ratio has additional information near the phase transition where the birth-death ratio means the ratio of the creation time of a hole and its vanishing time based on the persistent homology.

Gas permeation through nanoporous single-walled carbon nanotubes: the confinement effect

The gas permeation through nanoscale membranes like graphene has been extensively studied by experiments and empirical models. In contrast to planar membranes, the single-walled carbon nanotube has a natural confined hollow structure, which shall affect the gas permeation process. We perform molecular dynamics simulations to investigate the effect of the nanotube diameter on the gas permeation process. It is found that the permeance constant increases with the increase of the nanotube diameter, which can not be explained by existing empirical models. We generalize the three-state model to describe the diameter dependence for the permeance constant, which discloses a distinctive confinement-induced adsorption phenomenon for the gas molecule on the nanotube’s inner surface. This adsorption phenomenon effectively reduces the pressure of the bulk gas, leading to the decrease of the permeance constant. These results illustrate the importance of the adsorption within the confined space on the gas permeation process.

Combined Pulsed Electron Double Resonance EPR and Molecular Dynamics Investigations of Calmodulin Suggest Effects of Crowding Agents on Protein Structures.

Calmodulin (CaM) is a highly dynamic Ca2+-binding protein that exhibits large conformational changes upon binding Ca2+ and target proteins. Although it is accepted that CaM exists in an equilibrium of conformational states in the absence of target protein, the physiological relevance of an elongated helical linker region in the Ca2+-replete form has been highly debated. In this study, we use PELDOR (pulsed electron–electron double resonance) EPR measurements of a doubly spin-labeled CaM variant to assess the conformational states of CaM in the apo-, Ca2+-bound, and Ca2+ plus target peptide-bound states. Our findings are consistent with a three-state conformational model of CaM, showing a semi-open apo-state, a highly extended Ca2+-replete state, and a compact target protein-bound state. Molecular dynamics simulations suggest that the presence of glycerol, and potentially other molecular crowding agents, has a profound effect on the relative stability of the different conformational states. Differing experimental conditions may explain the discrepancies in the literature regarding the observed conformational state(s) of CaM, and our PELDOR measurements show good evidence for an extended conformation of Ca2+-replete CaM similar to the one observed in early X-ray crystal structures.

Active acoustic telemetry reveals ontogenetic habitat-related variations in the coastal movement ecology of the white shark

BackgroundLittle is known about the fine-scale behavioural choices white sharks make. The assessment of movement at high spatio-temporal resolution can improve our understanding of behavioural patterns. Active acoustic telemetry was used along a coastal seascape of South Africa to investigate the movement-patterns of 19 white sharks tracked for 877 h within habitats known to host different prey types.ResultsA three-state hidden Markov model showed higher ontogenetic variability in the movements of white sharks around estuary-related coastal reef systems compared to around a pinniped colony. Our results further suggest white sharks (1) use the same searching strategy in areas where either pinnipeds or fishes are present; (2) occupy sub-tidal reef habitats possibly for either conserving energy or recovering energy spent hunting, and (3) travel directly between the other two states.ConclusionsWhite sharks appear not to simply roam coastal habitats, but rather adopt specific temporally optimized behaviours associated with distinct habitat features. The related behaviours are likely the result of a balance among ontogenetic experience, trophic niche, and energetics, aimed at maximizing the use of temporally and spatially heterogeneous environments and resources. The possible implications for the future conservation of white sharks in coastal areas are discussed, with particular attention to South Africa’s present conservation and management challenges.

A Stochastic Markov Model for Maintenance Scheduling in the Presence of Online Monitoring System

Active electricity distribution systems (AEDS) play an important role on the social welfare that is highly relies on the reliability of these systems. In this regard, maintenance management tries to decrease component failures via repairing component that are more possible to be failed in operation time. In this manuscript, a stochastic MINLP maintenance scheduling model is proposed in which the reliability of AEDS's equipment is considered through employing a three-state Markov model. This model helps us to embed the uncertainty of AEDS's equipment service restoration time by considering online monitoring system for it and FLISR functions in AEDS. In this paper, minimizing the total cost of AEDS is determined as objective function considering total customer interruption cost, total cost of energy not supplied, total cost of prevented maintenance actions, total corrective maintenance actions cost implemented in the AEDS and total cost of implementing online monitoring for AEDS's component in maintenance scheduling. The proposed framework is applied in two different cases, Case I is maintenance scheduling without online monitoring system and Case II is maintenance scheduling with online monitoring system. The aforementioned cases are implemented in an IEEE Test System as well as a real scale distribution network. Moreover, several sensitivity analyses are implemented for indicating the efficiency of the proposed model.

Mathematical modelling of activation-induced heterogeneity in TNF, IL6, NOS2, and IL1β expression reveals cell state transitions underpinning macrophage responses to LPS.

Background:Despite extensive work on macrophage heterogeneity, the mechanisms driving activation induced heterogeneity (AIH) in macrophages remain poorly understood. Here, we aimed to develop mathematical models to explore theoretical cellular states underpinning the empirically observed responses of macrophages following lipopolysaccharide (LPS) challenge. Methods:We obtained empirical data following primary and secondary responses to LPS in two in vitro cellular models (bone marrow-derived macrophages or BMDMs, and RAW 264.7 cells) and single-cell protein measurements for four key inflammatory mediators: TNF, IL-6, pro-IL-1β, and NOS2, and used mathematical modelling to understand heterogeneity. Results:For these four factors, we showed that macrophage community AIH is dependent on LPS dose and that altered AIH kinetics in macrophages responding to a second LPS challenge underpin hypo-responsiveness to LPS. These empirical data can be explained by a mathematical three-state model including negative, positive, and non-responsive states (NRS), but they are also compatible with a four-state model that includes distinct reversibly NRS and non-responsive permanently states (NRPS). Our mathematical model, termed NoRM (Non-Responsive Macrophage) model identifies similarities and differences between BMDM and RAW 264.7 cell responses. In both cell types, transition rates between states in the NoRM model are distinct for each of the tested proteins and, crucially, macrophage hypo-responsiveness is underpinned by changes in transition rates to and from NRS. Conclusions:Overall, we provide a mathematical model for studying macrophage ecology and community dynamics that can be used to elucidate the role of phenotypically negative macrophage populations in AIH and, primary and secondary responses to LPS.

Periodic Gibbs measures for the three-state Potts-SOS model on a Cayley tree

Periodic Gibbs measures for the three-state Potts-SOS model on a Cayley tree

Cost-effectiveness of pembrolizumab for the first-line treatment of recurrent or metastatic head and neck squamous cell carcinoma in the United States

Aims Pembrolizumab, as monotherapy in first-line recurrent or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) with a combined positive score (CPS) ≥1 and in combination with platinum and 5-fluorouracil (5-FU) in the overall R/M HNSCC population, received US FDA approval based on the KEYNOTE-048 trial. Using public drug prices, from a US payer perspective, we evaluated the cost-effectiveness of each pembrolizumab regimen vs. cetuximab + platinum+5-FU (EXTREME regimen, trial comparator), cisplatin + docetaxel + cetuximab (TPEx regimen), cisplatin + paclitaxel, and platinum+5-FU. Methods A three-state partitioned-survival model was used to project costs and outcomes over 20 years with 3% annual discounting. Progression-free and overall survival were modeled using long-term extrapolation of KEYNOTE-048 data and, for alternative comparators, data from a network meta-analysis was used. Time-on-treatment was derived from KEYNOTE-048 or approximated using network meta-analysis progression-free survival estimates. Costs included first-line and subsequent treatments, disease management, adverse events, and terminal care costs. Utilities were derived from the KEYNOTE-048 Euro-QoL five-dimension data and using a US algorithm. Results In the CPS ≥1 R/M HNSCC population, pembrolizumab monotherapy was dominant vs. EXTREME and TPEx regimens, and cost-effective (at $100,000/QALY threshold) vs. platinum+5-FU ($86,827/QALY) and cisplatin + paclitaxel ($81,473/QALY). Pembrolizumab combination therapy in the overall R/M HNSCC population was dominant vs. TPEx regimen, and cost-effective vs. EXTREME regimen ($1769/QALY), platinum+5-FU ($81,989/QALY), and cisplatin + paclitaxel ($89,505/QALY). Sensitivity analyses showed a high cost-effectiveness probability for pembrolizumab at the $100,000/QALY threshold. Conclusions First-line pembrolizumab monotherapy in patients with CPS ≥1, and pembrolizumab combination therapy in the overall R/M HNSCC population is cost-effective from the perspective of the US payers.

Data-Driven Reliability Evaluation of the Integrated Energy System Considering Optimal Service Restoration

The demand for environmental protection and energy utilization transformation has promoted the rapid development of integrated energy systems (IES). Reliability evaluation is a fundamental element in designing IES as it could instruct the planning and operation of IES. This study proposes a novel data-driven reliability improvement and evaluation method considering the three-state reliability model and an optimal service restoration model (OSR). First, a multi-energy flow model is introduced and linearized in order to reduce the computing complexity. Next, a three-state reliability model is developed, considering the transitional process and partial failure mode. Furthermore, an optimal service restoration model is established to determine the best repairment moment for minimizing the load curtailment, and a data-driven reliability evaluation method is developed that integrates OSR and models the stochastic state transition process using the historical measurement data of the smart meters. Finally, the proposed reliability evaluation method is tested on a test IES, and the numerical results validate its effectiveness in evaluating the reliability of IES and improving the overall reliability.

Consensus, Polarization and Hysteresis in the Three-State Noisy q-Voter Model with Bounded Confidence.

In this work, we address the question of the role of the influence of group size on the emergence of various collective social phenomena, such as consensus, polarization and social hysteresis. To answer this question, we study the three-state noisy q-voter model with bounded confidence, in which agents can be in one of three states: two extremes (leftist and rightist) and centrist. We study the model on a complete graph within the mean-field approach and show that, depending on the size q of the influence group, saddle-node bifurcation cascades of different length appear and different collective phenomena are possible. In particular, for all values of , social hysteresis is observed. Furthermore, for small values of , disagreement, polarization and domination of centrists (a consensus understood as the general agreement, not unanimity) can be achieved but not the domination of extremists. The latter is possible only for larger groups of influence. Finally, by comparing our model to others, we discuss how a small change in the rules at the microscopic level can dramatically change the macroscopic behavior of the model.

Mathematical modelling of activation-induced heterogeneity in TNF, IL6, NOS2, and IL1β expression reveals cell state transitions underpinning macrophage responses to LPS

Background: Despite extensive work on macrophage heterogeneity, the mechanisms driving activation induced heterogeneity (AIH) in macrophages remain poorly understood. Here, we aimed to develop mathematical models to explore theoretical cellular states underpinning the empirically observed responses of macrophages following lipopolysaccharide (LPS) challenge. Methods: We obtained empirical data following primary and secondary responses to LPS in two in vitro cellular models (bone marrow-derived macrophages or BMDMs, and RAW 264.7 cells) and single-cell protein measurements for four key inflammatory mediators: TNF, IL-6, pro-IL-1β, and NOS2, and used mathematical modelling to understand heterogeneity. Results: For these four factors, we showed that macrophage community AIH is dependent on LPS dose and that altered AIH kinetics in macrophages responding to a second LPS challenge underpin hypo-responsiveness to LPS. These empirical data can be explained by a mathematical three-state model including negative, positive, and non-responsive states (NRS), but they are also compatible with a four-state model that includes distinct reversibly NRS and non-responsive permanently states (NRPS). Our mathematical model, termed NoRM (Non-Responsive Macrophage) model identifies similarities and differences between BMDM and RAW 264.7 cell responses. In both cell types, transition rates between states in the NoRM model are distinct for each of the tested proteins and, crucially, macrophage hypo-responsiveness is underpinned by changes in transition rates to and from NRS. Conclusions: Overall, we provide a mathematical model for studying macrophage ecology and community dynamics that can be used to elucidate the role of phenotypically negative macrophage populations in AIH and, primary and secondary responses to LPS.

Rapid Autonomous Vehicle Drifting with Deep Reinforcement Learning

Abstract: Now days all types of vehicles run on road are upgrading to automated self-driving techniques. Drifting is a complicated procedure for autonomous vehicle control which is used for high-speed sideslip cornering. It is difficult to drift a vehicle at a high speed of 80-120 km/hr by using traditional techniques like two-state single-track model and three-state singletrack models, which depend on the knowledge of tire or road forces that are not to be known accurately due to the real-world environmental complexity. Because of these inaccuracies in these parameters there will be poor control performance and may lead to road accidents. In this scenario, this project presents a strong drift control algorithm, which is based on the most recent model-free deep reinforcement learning algorithm called soft actor-critic (SAC). SAC is used to control front-wheel drive (FWD) vehicles to drive at high speed (80– 120 km/h), and to drift through sharp corners quickly and stability which in turn helps to prevent road accidents at the time of drifting. The efficiency of this algorithm is evaluated by conducting experiments on Trajectories dataset taken from Git-Hub repository, which consists of some road maps with reference drift trajectories. The SAC algorithm can also deal with vehicle types with various actual properties, like mass, tyre friction, and so on to show its notable generalization ability.

Optimal Control of a Three-State Diabetic Population Model with Interventions

This paper studies an optimal control problem to describe the population dynamics of diabetes in the presence of intervention effects. We propose two control variables representing the interventions to reduce the incidence of diabetes, and the interventions to reduce the incidence of complications. By applying the optimal control theory, we seek to minimize the relative cost associated with the intervention efforts and to reduce the total number of people with diabetes. The solution to the optimality system is approximated by using the Forward-Backward Sweep Method. The numerical simulations show that the number of diabetics who develop complications can be reduced by adopting optimal control strategies.

A progressive three-state model to estimate time to cancer: a likelihood-based approach

BackgroundTo optimize colorectal cancer (CRC) screening and surveillance, information regarding the time-dependent risk of advanced adenomas (AA) to develop into CRC is crucial. However, since AA are removed after diagnosis, the time from AA to CRC cannot be observed in an ethically acceptable manner. We propose a statistical method to indirectly infer this time in a progressive three-state disease model using surveillance data.MethodsSixteen models were specified, with and without covariates. Parameters of the parametric time-to-event distributions from the adenoma-free state (AF) to AA and from AA to CRC were estimated simultaneously, by maximizing the likelihood function. Model performance was assessed via simulation. The methodology was applied to a random sample of 878 individuals from a Norwegian adenoma cohort.ResultsEstimates of the parameters of the time distributions are consistent and the 95% confidence intervals (CIs) have good coverage. For the Norwegian sample (AF: 78%, AA: 20%, CRC: 2%), a Weibull model for both transition times was selected as the final model based on information criteria. The mean time among those who have made the transition to CRC since AA onset within 50 years was estimated to be 4.80 years (95% CI: 0; 7.61). The 5-year and 10-year cumulative incidence of CRC from AA was 13.8% (95% CI: 7.8%;23.8%) and 15.4% (95% CI: 8.2%;34.0%), respectively.ConclusionsThe time-dependent risk from AA to CRC is crucial to explain differences in the outcomes of microsimulation models used for the optimization of CRC prevention. Our method allows for improving models by the inclusion of data-driven time distributions.

P1713: VENETOCLAX IN COMBINATION WITH OBINUTUZUMAB IN FIRST LINE CHRONIC LYMPHOCYTIC LEUKEMIA IN ARGENTINA: A COST-EFFECTIVENESS ANALYSIS

Background: The efficacy of venetoclax plus obinutuzumab (VenG) was examined in the CLL14 clinical trial, in unfit Chronic Lymphocytic Leukemia (CLL) patients who have not been previously treated. Aims: The aim of the study was to estimate the cost-effectiveness of VenG in the treatment of first-line unfit CLL patients in Argentina Methods: A three-state partitioned-survival model (with health states of progression-free survival (PFS), post-progression survival (PPS) and death), developed in accordance with NICE and ISPOR decision modelling guidelines, was adapted to Argentina setting and was used to estimate the accumulated costs and outcomes in terms of life years (LY) and quality-adjusted life years (QALY). A 30-year time horizon and the Social Security’s payer’s perspective were assumed. Cost-effectiveness was estimated by comparing a 12-month fixed duration of VenG versus (vs.) chlorambucil-obinutuzumab (ClbG) based on the CLL14 clinical trial. Other comparators included treat-to-progression therapies, such as ibrutinib (IBR), and a 6-month course of bendamustine + rituximab (BR). Using a network meta-analysis, the relative efficacy of VenG and ClbG vs. other selected comparators was estimated. Health state utilities and adverse event (AE) disutilities were derived from a systematic literature review and published health-technology assessment reports. To generate total quality-adjusted life years (QALYs), these health state utilities and AE disutilities were applied to the relative efficacy data. The cost of medication was based on country level drug prices. The healthcare resources used were validated by local experts through a Delphi panel methodology. Costs of resources used for routine medical attention and the management of adverse events were based on tariffs from social security system of Argentina. Costs were expressed in Argentine Pesos (AR$) (exchange rate 1 US dollars ($) = 100.75AR$, July 2021). A 5% annual discount rate was applied for costs and outcomes. Cost-effectiveness results are presented in terms of incremental cost per QALY. A new treatment that is both lower in total cost and more efficacious (in QALYs) vs. identified comparator treatments is described as being “dominant”. Uncertainty in the model was tested through one-way sensitivity analyses (OWSA) and probabilistic sensitivity analyses (PSA) Results: Over a 30-year time horizon, the total discounted costs were, for VenG, $117,250.19; ClbG, $167,675.26; BR, $206,951.64; and IBR, $432,243.36. The benefits in the cost-effectiveness model (CEM) were measured in terms of total discounted QALYs which were 5.634 for VenG, 5.350 for ClbG, 4.996 for BR and 5.161 for IBR. The incremental discounted QALYs of VenG was: 0.284 vs. ClbG, 0.639 vs. BR, and 0.473 vs. IBR. Thus, VenG with a 12-month fixed duration, has lower total costs and is more efficacious (“dominant”) over all comparators in the CEM. OWSA analyses show that the results are robust, and in the PSA VenG is dominant over all the comparators considered, ICER is ≤$ 6,011.20 (1 GDP per capita for Argentina, 2020), /QALY in 97% of the iterations CE Results - VenG ClbG BR IBR Costs $ 117,250.19 $ 167,675.26 $ 206,951.64 $ 432,243.36 LYs 12.80 12.80 11.88 11.88 QALYs 5.634 5.350 4.996 5.161 Incremental cost (vs VenG) $ -50,425.06 $ -89,701.44 $ -314,993.17 Incremental QALYs 0.284 0.639 0.473 Cost/QALYs gained Dominant Dominant Dominant Summary/Conclusion: This study shows that in Argentina, VenG would be dominant treatment option (better results and lower costs) compared with ClbG, BR and IBR in the treatment of first-line unfit CLL patients.