Markov Model Research Articles

N-glycosylation-modifications-driven conformational dynamics attenuate substrate inhibition of d-lactonohydrolase.

Achieving enzyme catalysis at high substrate concentrations is a substantial challenge in industrial biocatalysis, and the role of glycosylation in post-translational modifications that modulate enzyme substrate inhibition remains poorly understood. This study provides insights into the role of N-glycosylation in substrate inhibition by comparing the catalytic properties of d-lactonohydrolase (d-Lac) derived from Fusarium moniliforme expressed in prokaryotic and eukaryotic hosts. Experimental evidence indicates that recombinant d-Lac expressed in Pichia pastoris (PpLac-WT) exhibits higher hydrolysis rates at a substrate concentration of 400g/L, with reduced substrate inhibition and enhanced stability compared to the recombinant d-Lac expressed in Escherichia coli (EcLac-WT). Mutant PpLac-M1 achieves a conversion rate of 40% at a substrate concentration of 400g/L, with a space-time yield of d-pantoic acid reaching 91.1g/L/h. Proteomics analysis reveals that residues N29 and N278, located approximately 10-20Å from the active site undergo N-glycosylation in PpLac-WT. Using microsecond-scale molecular dynamics simulations and Markov state models, we elucidate the effects of glycosylation on the conformational flexibility of two key loops at the entrance of the binding pocket. Specifically, the loops in PpLac-WT can transition between open and closed states, whereas those in EcLac-WT tend to remain open. In high substrate concentration conditions, the open state causes congestion, leading to substrate inhibition. Shortest-path map analysis confirms that substrate entry is dynamically controlled by residue N29 on the loops surrounding the active site. Our findings enhance the understanding of the effects of glycosylation on enzyme conformational dynamics and provide insights into mitigating inhibition at high substrate concentrations.

Use of a hidden Markov model for interpretation of serial cow milk paratuberculosis antibody enzyme-linked immunosorbent assay results adjusted for milk yield and quality.

Paratuberculosis (Johne's disease), caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a common, economically-important and potentially zoonotic contagious disease of cattle, with worldwide distribution. Disease management relies on identification of animals which are at high-risk of being infected or infectious. The disease is chronic in nature, and infected animals may be infectious in the absence of overt clinical signs. Coupled with limited sensitivity of available diagnostic tests, this creates difficulties in identifying high-risk animals. In some disease-control programmes, dairy cows are classified with regards to risk according to the results of serial tests which quantify MAP antibodies in milk samples. Such classification systems are limited by the influence of non-disease factors on test results, dichotomisation of continuous results into "positive" or "negative" according to an imperfect threshold, and subjectivity in defining which patterns of serial test results indicate different risk-categories. An unsupervised learning (clustering) approach was applied to paratuberculosis test results and milk-recording data collated from 47 farms over an approximately ten-year period between 2010 and 2021. Paratuberculosis test results were first adjusted according to influential non-disease factors using linear models. Continuous-time hidden Markov models were fit to the adjusted test results. The final model revealed four distinct latent states (clusters). Examination of the distribution of adjusted test results associated with each latent state suggested that states were ordinal and aligned with disease progression. Model transition probabilities demonstrated that the probability of an animal progressing to the highest state was dependent on its current state. Of particular note was the existence of a latent state, characterised by paratuberculosis test results below the conventional test-positive threshold, which was associated with a relatively high probability of progression to the highest cluster. This research has led to objective classification of animals according to serial test results, and furthermore suggests the presence of groups of different disease risk amongst animals whose test results fall below the routinely used test-positive threshold. Identification of such groups could be used to better manage disease on farms, through implementation of management practices which limit disease transmission from high-risk animals.

Dapagliflozin for the treatment of heart failure with reduced ejection fraction in Brazil: a cost-effectiveness analysis.

Heart failure, a complex clinical syndrome with high morbidity and mortality, has become a significant burden on public health. Recently, a new class of antidiabetic agents-the sodium-glucose cotransporter 2 (SGLT2) inhibitors-was associated with a significant reduction on mortality and hospitalization in HF with reduced ejection fraction (HFrEF) when added to standard pharmacological treatment. Considering the lack of data on its cost-effectiveness, the present study aims to estimate the incremental cost-effectiveness ratio of add-on dapagliflozin treatment for HFrEF from the Brazilian public healthcare system perspective. We built a Markov model to estimate the clinical outcomes and costs of 1,000 hypothetical subjects with established HFrEF in a lifetime horizon. The model inputs were based on the Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure (DAPA-HF) trial and local data. The main outcome was the incremental cost-effectiveness ratio (ICER) per quality-adjusted life year (QALY) gained. Deterministic and probabilistic sensitivity analyses, as well as scenario analyses, were performed. The addition of dapagliflozin to standard care treatment in 1,000 HFrEF patients yielded an expected value of 366.99 additional QALYs at an incremental cost of US$ 1,517,878.49, resulting in an ICER of US$ 4,136.08 per QALY gained, being a cost-effective strategy considering the Brazilian official cost-effectiveness threshold (US$ 8,000/QALY). In probabilistic sensitivity analyses, 96.60% of the simulations were also cost-effective. In the scenario analyses, results were similar for individuals with and without diabetes. Dapagliflozin is likely to be cost-effective when added to standard HFrEF therapy in Brazil. This study was supported by the National Institute of Science and Technology for Health Technology Assessment (Instituto de Avaliação de Tecnologias em Saúde-IATS).

Abstract WP90: Cost of Stroke Treatment: A Comparative Analysis of Mobile Stroke and Standard Treatment

Introduction: Over the past decade, Mobile Stroke Treatment Units (MSTU) have enhanced the quality of stroke care in the United States by bringing the hospital to the patient. While MSTUs improve stroke patient outcomes compared to standard hospital care, there are still limited units operating. The implementation of a MSTU requires considerable initial and long-term investment limiting their widespread programmatic formation. We evaluated a MSTU program in Florida between August 2023 and April 2024 for comparative patient associated out of pocket costs with MSTU and standard stroke care. Methods: A discrete time Markov Chain Monte Carlo (MCMC) model was used to estimate incremental cost-savings associated with MSTU treatment compared to standard hospital care. The Markov model captured treatment costs for the care of patients at two functional levels as defined by the modified Rankin Scale (mRS). The potential cost-savings was determined by comparing the estimated costs incurred by the MSTU cohort to a counterfactual scenario of standard care of Emergency Medical Services (EMS) transport to the Emergency Department (ED). Since the model focused on the cost of patient care, costs included only billed ED, inpatient, and outpatient hospital care and services provided in the baseline year and then estimated cost of care over the next four years. All values represent 2024 dollars ($) and a 3% discount rate was applied to years two through four. Results: The MSTU treated 59 acute stroke patients with an average age of 71.86 (SD=13.78). Overall, 76% (N=45) were diagnosed with ischemic stroke, 9% with intracerebral hemorrhage (ICH), and 15% with transient ischemic attack (TIA). At discharge, 54% were independent and 46% dependent. In Year 1 (baseline), out of pocket cost differential between MSTU patients and the standard care was estimated to be $5,306 and $6,485 for the independent and dependent patients respectively. Projected future cost differentials in Years 2 to 4 were $4,571, $3,845, and $2,817 for the independent functioning cohort and $5,586, $4,700, and $4,188 for the dependent functioning cohort. Conclusion: These results suggest that the out of pocket cost for MSTU patients was significantly lower than standard care both at baseline and over the first four years post-stroke, making MSTU acute stroke management a better economic system of care for time metrics, long term patient outcomes, and cost effectiveness.

Deep learning-based fault diagnosis of high-power PEMFCs with ammonia-based hydrogen sources

The fault diagnosis of high-power proton exchange membrane fuel cells (PEMFCs) with ammonia-based hydrogen sources (AHSs) is studied by an ensemble machine learning methods as considering various operating conditions. Under various operating conditions, the results show that when the single-fault state and the multiple-faults state, appear in a single high-power PEMFC system, the overall diagnostic accuracy of 98.89% is realized by the optimized hidden Markov model (HMM) coupling with the convolutional neural network (CNN) and the t-distributed stochastic neighbor embedding (t-SNE). When using the t-SNE-CNN-HMM fault diagnosis model, the overall diagnostic accuracy is 100% in a single AHS system. Similarly, the overall diagnostic accuracy is 98.58% for the single-fault and the multiple-faults states in the AHSs-PEMFCs coupled system. Based on these single-fault and multiple-faults states, the overall diagnostic accuracy of t-SNE-CNN-HMM model is larger in comparison with these of other diagnosis models, of which these diagnosis models are composed of the support vector machine (SVM), backpropagation neural network (BPNN) and only-CNN models. The t-SNE-CNN-HMM method integrates the generalization and identification ability of CNN and HMM, leading to provide an efficient and accurate fault diagnosis for the AHSs-PEMFCs coupled system.

Decoding the silent dialogue: Unveiling driver-pedestrian communication dynamics with a hidden Markov model

Decoding the silent dialogue: Unveiling driver-pedestrian communication dynamics with a hidden Markov model

24-week, all-oral regimens for pulmonary rifampicin-resistant tuberculosis in TB-PRACTECAL trial sites: an economic evaluation.

New 6-month rifampicin-resistant tuberculosis treatment regimens containing bedaquiline, pretomanid, and linezolid (BPaL) with or without moxifloxacin or clofazimine, could improve treatment efficacy, safety, and tolerability, and free up resources within the health system. Following a change to WHO rifampicin-resistant tuberculosis treatment guidelines, countries are facing difficult decisions about when and how to incorporate new drug regimens into national guidelines. We aimed to assess the probability of BPaL-based regimens being cost-saving using data collected in the TB-PRACTECAL trial. This economic evaluation using a cost-utility analysis was embedded in five TB-PRACTECAL trial sites in Belarus, Uzbekistan, and South Africa. Between Nov 19, 2020, and Sept 27, 2022, we collected detailed primary unit cost data in six hospitals and four ambulatory health facilities and collected data on patient-incurred costs from 73 trial participants. The primary efficacy endpoint of the main trial, a composite of unfavourable outcomes (death, disease recurrence, treatment failure, early discontinuation of therapy, withdrawal, or loss to follow-up) and clinically important safety outcomes by 72 weeks of follow-up were incorporated into the analysis. Societal perspective cost data and effect outcome data were input into a Markov model to estimate the cost per disability-adjusted life-year (DALY) averted by BPaL-based regimens compared with the standard of care over a 20-year time horizon. We conducted a range of univariate and probabilistic sensitivity analyses to test our findings. BPaL-based regimens averted a mean of 1·28 DALYs and saved a mean of US$14 868 (SD 291) per person from the provider perspective compared with standard-of-care regimens over 20 years. Patient-incurred costs were reduced by a mean of $172 (SD 0·84) in BPaL-based regimen groups compared with standard of care. The main cost drivers for both providers and patients were inpatient bed-days; the duration of the inpatient period varied across countries. Varying a range of model parameters affected the degree of cost savings but did not change the finding that BPaL-based regimens are cost-saving compared with standard of care. This trial-based evidence adds to consistent indications from modelling studies that BPaL-based regimens are cost-saving for both the patient and health system. Urgent implementation of BPaL-based regimens in countries with a high burden of tuberculosis could improve treatment of rifampicin-resistant tuberculosis, reduce pill burden, and free up desperately needed resources within the health system. Médecins Sans Frontières.

Predicting individual traits from models of brain dynamics accurately and reliably using the Fisher kernel.

Predicting an individual's cognitive traits or clinical condition using brain signals is a central goal in modern neuroscience. This is commonly done using either structural aspects, such as structural connectivity or cortical thickness, or aggregated measures of brain activity that average over time. But these approaches are missing a central aspect of brain function: the unique ways in which an individual's brain activity unfolds over time. One reason why these dynamic patterns are not usually considered is that they have to be described by complex, high-dimensional models; and it is unclear how best to use these models for prediction. We here propose an approach that describes dynamic functional connectivity and amplitude patterns using a Hidden Markov model (HMM) and combines it with the Fisher kernel, which can be used to predict individual traits. The Fisher kernel is constructed from the HMM in a mathematically principled manner, thereby preserving the structure of the underlying model. We show here, in fMRI data, that the HMM-Fisher kernel approach is accurate and reliable. We compare the Fisher kernel to other prediction methods, both time-varying and time-averaged functional connectivity-based models. Our approach leverages information about an individual's time-varying amplitude and functional connectivity for prediction and has broad applications in cognitive neuroscience and personalised medicine.

Systematic bias in malaria parasite relatedness estimation.

Genetic studies of Plasmodium parasites increasingly feature relatedness estimates. However, various aspects of malaria parasite relatedness estimation are not fully understood. For example, relatedness estimates based on whole-genome-sequence (WGS) data often exceed those based on sparser data types. Systematic bias in relatedness estimation is well documented in the literature geared towards diploid organisms, but largely unknown within the malaria community. We characterise systematic bias in malaria parasite relatedness estimation using three complementary approaches: theoretically, under a non-ancestral statistical model of pairwise relatedness; numerically, under a simulation model of ancestry; and empirically, using data on parasites sampled from Guyana and Colombia. We show that allele frequency estimates encode, locus-by-locus, relatedness averaged over the set of sampled parasites used to compute them. Plugging sample allele frequencies into models of pairwise relatedness can lead to systematic underestimation. However, systematic underestimation can be viewed as population-relatedness calibration, i.e., a way of generating measures of relative relatedness. Systematic underestimation is unavoidable when relatedness is estimated assuming independence between genetic markers. It is mitigated when relatedness is estimated using WGS data under a hidden Markov model (HMM) that exploits linkage between proximal markers. The extent of mitigation is unknowable when a HMM is fit to sparser data, but downstream analyses that use high relatedness thresholds are relatively robust regardless. In summary, practitioners can either resolve to use relative relatedness estimated under independence, or try to estimate absolute relatedness under a HMM. We propose various tools to help practitioners evaluate their situation on a case-by-case basis.

Dihydropyrimidine Dehydrogenase Deficiency (DPYD) Genotyping-Guided Fluoropyrimidine-Based Adjuvant Chemotherapy for Breast Cancer. A Cost-Effectiveness Analysis.

While standard doses of adjuvant fluoropyrimidine-based chemotherapies are generally safe for most patients, the risk of severe adverse drug reactions (ADRs) is increased for those with dihydropyrimidine dehydrogenase deficiency (DPYD), a genetic variation that affects drug metabolism. The objective of this study was to examine the cost effectiveness of offering DPYD pharmacogenetic-guided care, where genetic testing informs personalized dosing versus the current standard of care (SoC), which involves administering fluoropyrimidine-based therapies without prior genetic screening, for local or metastatic breast cancer patients in Qatar. We developed a two-stage decision analysis, with an analytic tree model over a 6-month period, followed by a life-table Markov model over a lifetime horizon. We compared the current SoC with the alternate strategy of DPYD genetic screening in patients living in Qatar with local or metastatic breast cancer who were eligible for adjuvant fluoropyrimidine therapy. Clinical outcomes and utilities were obtained from published studies, while healthcare costs were estimated from Hamad Medical Corporation, Qatar. The short-term outcome included the incremental cost-effectiveness ratio (ICER), defined as cost per success (survival without grade III/IV ADRs) at 6 months. The long-term outcome was the ICER, defined as cost per quality-adjusted life year (QALY) gained, with a 3% annual discount rate. The study adopted a public healthcare perspective in Qatar. Sensitivity analyses were conducted to explore the impact of key input parameters on the robustness of the model. In the short-term model, at its base case, DPYD genomic screening was dominant over SoC with a mean cost-saving of QAR84,585 (95% confidence interval [CI], 45,270-151,657). This cost saving reflects the overall economic benefits associated with the implementation of DPYD genomic screening. In the long-term model, compared to the current SoC, DPYD genetic screening would result in an ICER of QAR21,107 (95% CI -59,382-145,664) per QALY gained. Based on our model, implementing DPYD genetic screening to detect DPYD mutations in breast cancer patients before therapy initiation seems to be a cost-saving and cost-effective strategy in Qatar.

Modelling the cost effectiveness and budget impact of uterine botulinum toxin injections versus conventional treatment in severe dysmenorrhoea: A French Perspective.

To assess the cost-effectiveness sand the budgetary impact of the combination of botulinum toxin (BT) + conventional treatment (CT) (hormonal treatments + analgesics) compared with CT alone in patients suffering from severe dysmenorrhoea, using a Markov model. A Markov model was developed to estimate, from the perspective of French Health Insurance (HI), the cost effectiveness and the budgetary impact of BT+CT compared with CT alone. The main health states in the model were based on Visual Analogue Scale (VAS) scores and expert opinion. All model parameters were derived from a cohort of patients treated for 12 months at the Centre de Recherche de la Santé et de la Femme (CRSF) for severe dysmenorrhoea in 2021. A Cost-Utility Analysis (CUA) was carried out to assess the quality of life of patients, crucial in this context, in which the direct healthcare costs were considered in and Budget Impact Analysis (BIA). The main decision-making criteria were the Incremental Cost-Utility Ratio (ICUR) for the CUA and the net impact for the BIA. Deterministic and probabilistic univariate sensitivity analyses were performed to assess the robustness of our results. Over the 1-year time horizon (main analysis), the costs and quality-adjusted life year (QALY) of BT+CT versus CT alone were equal to €1895.65 vs €3055.20 and 2.03 QALYs vs 1.23 QALYs, respectively. Consequently, the ICUR equalled -€1651.5/QALY, which shows that, although the initial costs of BT are higher than those of CT, the reduced follow-up costs associated with the long-term efficacy of BT make it the most effective and economically dominant option at 1, 5 and 10 years. Sensitivity analyses show that 100% of Monte Carlo iterations are below the willingness-to-pay threshold of €30,0001/QALY, making BT+CT an efficient strategy that could be adopted and reimbursed. In the absence of a reference treatment for the management of severe dysmenorrhoea, BT+CT offering an improvement in quality of life, as well as a reduction in follow-up costs. It is therefore the most cost-effective strategy over 10 years.

P-2047. Public Health Impact and Economic Value of an Additional Dose of Pfizer-BioNTech XBB.1.5-adapted COVID-19 Vaccine for Older Adults in the United States

Abstract Background To assess the public health impact and economic value of an additional dose of BNT162b2 XBB.1.5-adapted COVID-19 vaccine 6 months after initial dose for those aged ≥65 years, compared to a single dose in the United States.Table 1.Clinical and Economic Outcomes of 2-dose vs 1-dose Strategy in the Population Aged ≥65 Years.LY = life year; QALY = quality adjusted life year; ICER = incremental cost effectiveness ratio Methods A combined Markov and decision tree model was used to estimate the public health impact of those aged ≥65 years receiving an additional BNT162b2 XBB.1.5-adapted dose over for a one-year time horizon (Oct 2023-Sept 2024). Age-stratified (65-74, 75+) annual attack, hospitalization, and vaccine coverage rates were informed by public health national surveillance data. Other age-stratified clinical, cost, and vaccine effectiveness parameters were informed by publications. Parameter uncertainty was examined through scenario and sensitivity analyses. Conservatively, indirect effects (e.g. reduced transmission) and broad societal benefits were not considered. Results For individuals aged 65 years and older, the model demonstrated that compared to a single dose, an additional dose of the BNT162b2 XBB.1.5-adapted COVID-19 Vaccine resulted in 338,148 fewer symptomatic cases, 19,947 fewer hospitalizations, and 591 fewer deaths. Cost of additional vaccinations were offset by costs averted (e.g., Long COVID (∼$1.3B), inpatient (∼$384M), indirect (∼$280M), and outpatient (∼$252M) costs), leading to a total cost savings of ∼$270.5M. The two-dose strategy for older adults improved health outcomes and lowered costs resulting in a dominant ICER (Table 1). The additional dose was predicted to be a budget-efficient solution for payers. Results were most sensitive to variation in the symptomatic rate of infection and the hospitalization rate. Conclusion An additional dose of BNT162b2 XBB.1.5-adapted COVID-19 vaccination for adults aged 65 years and older in the US may generate notable reductions in symptomatic cases, hospitalizations, and deaths and result in cost savings. The results demonstrate that administering an additional COVID-19 vaccine dose to older adults in the US should be an important public health goal, supporting current ACIP and CDC recommendations. Disclosures Alon Yehoshua, PharmD, MS, Pfizer Inc: Employer|Pfizer Inc: Stocks/Bonds (Public Company) Benjamin Yarnoff, PhD, Pfizer Inc: Grant/Research Support Manuela Di Fusco, PhD, Pfizer Inc.: Employee|Pfizer Inc.: Stocks/Bonds (Public Company) Santiago M.C. Lopez, MD, Pfizer Inc.: Employee|Pfizer Inc.: Stocks/Bonds (Public Company) Elizabeth A. Thoburn, MPH, Pfizer Inc: Employer|Pfizer Inc: Stocks/Bonds (Public Company) Abby Rudolph, PhD, Pfizer Inc: Employer|Pfizer Inc: Stocks/Bonds (Public Company) Kinga Marczell, PhD, Pfizer Inc: Grant/Research Support

Regime switching forecasting for cryptocurrencies

Abstract There are many ways to model complex time series. The simplest approach is to increase the complexity, and thus, the flexibility of the model, for the entire time series. As an example, one could use a neural network. Another solution would be to change the parameters of a model dependent on the “state” or “regime” of the time series. A typical example here would be the Hidden Markov model (HMM). This paper combines the two concepts to create a Reinforcement Learning (RL) model that adds variables that depend on the state of the time series. To test the concept, the RL model is used with cryptocurrency data to determine the share to invest into the cryptocurrency index CRIX in order to maximize wealth. The results have shown that cryptocurrency metadata is useful as supplementary data for analysis of the respective prices. The Reinforcement learning model with regimes shows potential for investment management, but comes with some caveats.

Cost-Utility Analysis of Non-Invasive Tests to Initiate Hepatocellular Carcinoma Surveillance in Metabolic Dysfunction-Associated Steatotic Liver Disease.

Non-invasive tests (NITs), e.g. Fibrosis-4 Index (FIB-4) and vibration-controlled elastography (VCTE), have been used to identify metabolic dysfunction-associated steatotic liver disease (MASLD) patients at high risks for hepatocellular carcinoma (HCC). This study investigates the cost-effectiveness of NITs to identify MASLD patients with advanced liver fibrosis and initiate HCC surveillance. A cost-utility analysis using a Markov model compared no use of NITs with three NIT strategies: 1) FIB-4 and VCTE (FIB-4/VCTE), 2) FIB-4 alone, and 3) VCTE alone to identify advanced liver fibrosis and initiate HCC surveillance with biannual ultrasonography with alpha-fetoprotein in 4 MASLD populations: 1) general MASLD patients, 2) MASLD patients with body mass index (BMI) >30 kg/m2, 3) MASLD patients with diabetes, and 4) MASLD patients with three metabolic traits (diabetes, hypertension and BMI >30). FIB-4/VCTE was the most cost-effective approach across all groups, showing the lowest ICER, followed by FIB-4 alone and VCTE alone. In the general MASLD population, both FIB-4/VCTE and FIB-4 alone were cost-effective in the US, while only FIB-4/VCTE was cost-effective in Thailand. For MASLD patients with BMI >30, all strategies were cost-effective in the US, while only FIB-4/VCTE was cost-effective in Thailand. In MASLD patients with diabetes or 3 metabolic traits, all strategies were cost-effective in the US, while FIB-4/VCTE and FIB-4 alone were cost-effective in Thailand. Using FIB-4/VCTE to initiate HCC surveillance is cost-effective for MASLD patients. If VCTE is unavailable, FIB-4 alone is a cost-effective alternative for MASLD patients with diabetes or 3 metabolic traits.

P-2262. Outcomes of Patients with Severe Persistent BK Polyomavirus DNAemia

Abstract Background BK polyomavirus (BKPyV) is the leading cause of polyomavirus associated nephropathy (PyVAN) in kidney transplant recipients (KRT). The goal of this study was to determine risk factors and outcomes associated with severe persistent BKPyV (SPBK).Figure 1A:Total estimated length of stay in a lymphocyte state: SPBK vs LBK Methods This is a single center, matched retrospective case control study of KTR with SPBK compared to 1) KTR with low/no BKPyV-DNAemia (LBK) and 2) KTR with high, transient BKPyV-DNAemia (HTBK). Definitions were as follows, SPBK: BKPyV load > 6 log10 for >90 consecutive days. LBK: BKPyV load remaining < 3 log10. HTBK: BKPyV load >4 log10 for < 90 consecutive days, all within the first 2 years post-transplant. SPBK were exact matched 1:3 to LBK controls on race, sex, donor type immunosuppression protocol, and genetic matched with robust Mahalanobis distance on age. SPBK cases were exact matched 1:2 with HTBK controls on race, gender, immunosuppression protocol, and genetic matched with robust Mahalanobis distance on age and donor type. Differences between case and control groups were analyzed using Wilcoxon-rank sum test and Fisher’s exact test. A multistate Markov model was used to evaluate whether time spent in a state of lymphopenia (< 1,000 cells/µL) was associated with SPBK.Figure 1A:Total estimated length of stay in a lymphocyte state: SPBK vs HTBK Results 20 KTR with SPBK were matched to 60 LBK and 40 HTBK. Significantly more SPBK experienced acute cellular rejection within the first 2 years of transplant relative to LBK (75% vs 27%, p< 0.001) and HTBK (22%, p< 0.001). SPBK had a longer estimated duration of lymphopenia in the first 200 days post-transplant relative to LBK and HTBK (SPBK: 107.5 days, 95% CI 92.1, 122.7 vs LBK: 68.5 days, 95% CI 55.3, 84.8, vs HTBK 70.3 days 95% CI 58.8, 82.4, Figure 1A-B). Median eGFR at 6 months post-transplant for SPBK was lower than patients with LBK and HTBK (44 vs 56, p=0.016; 44 vs 60, p=0.004, respectively). Burden of lab draws was significantly higher for SPBK vs LBK and HTBK (69 days vs 55, p< 0.001; 69 days vs 56, p=0.006, respectively). Total cost of labs was $7836 for SPBK vs $4,691 for LBK (p< 0.001) and $5922 for HTBK (p< 0.001). Conclusion Patients with SPBK spent more time in a state of lymphopenia in the first 200 days post-transplant vs LBK and HTBK. SPBK is associated with worse renal function at 6 months post-transplant and is accompanied by a higher burden of lab draws and cost. Disclosures Christian P. Larsen, MD, PhD, Bristol-Myers Squibb: Advisor/Consultant|CareDx: Advisor/Consultant|Eledon: Advisor/Consultant

P-658. Cost-Effectiveness of V116, an Adult Specific 21-Valent Pneumococcal Conjugate Vaccine, vs. PCV20 on Pneumococcal Disease in Japan--A Delta-Price Approach

Abstract Background V116 is an investigational 21-valent pneumococcal conjugate vaccine (PCV) specifically designed for adults. It includes eight unique serotypes (15A, 15C [generated from deOAc-15B], 16F, 23A, 23B, 24F, 31 and 35B) not covered by any currently licensed pneumococcal vaccine (Figure 1). This study used the delta-price approach to conduct a cost-effectiveness analysis (CEA) of vaccinating adults aged 65+ years with V116 vs. PCV20 in Japan. Methods A Markov model was built to track the lifetime health and economic outcomes of using V116 compared to PCV20 among adults in Japan. The same vaccine effectiveness values were assumed for the two vaccines. We assumed a vaccination coverage rate of 39% based on current Japanese reports of vaccination rates in 65-year-olds. Costs were adjusted to 2024 JPY and a 2% discount rate for both costs and quality-adjusted life-years (QALYs) were used to perform the CEA. The CEA was conducted from societal (direct and indirect costs included) and health care (only direct costs) perspectives. A premium price (price difference vs. PCV20) was used in the analysis. The summary results were presented as incremental cost-effectiveness ratios (ICERs). Results Vaccinating 39% of adults aged 65+ years with V116 prevented approximately 113,000 total cases of pneumococcal disease (PD) and 6,700 disease-related deaths; meanwhile PCV20 prevented approximately 91,000 total cases of PD and 5,400 disease-related deaths (Table 1). When compared to PCV20, V116 yielded an additional 8,500 QALYs, reduced medical costs by 17.15 billion JPY, and reduced indirect costs by 5.68 billion JPY. V116 was cost-saving up to a premium price of 1,213 JPY and 1,615 JPY from the health care and societal perspectives, respectively. At an ICER of 5 million JPY/QALY gained, V116 was cost-effective up to a premium price of 4,210 JPY and 4,612 JPY from the health care and societal perspectives, respectively (Figure 2). Model outcomes were most sensitive to discount rates and medical costs for NBPP (Figure 3). Conclusion At a premium price between 4,210 and 4,612 JPY, V116 remained cost-effective when compared to PCV20 in Japanese adults 65+ years; and a premium price between 1,213 and 1,615 JPY was found to be cost-saving for the same strategy comparison. Disclosures Peter P. Mueller, PhD, Merck & Co. Inc.: Stocks/Bonds (Public Company) Atsushi Tajima, n/a, Merck & Co. Inc.: Stocks/Bonds (Public Company)|MSD: Employee Taizo Matsuki, n/a, GSK: Past employee by October 2023|MSD: Study and publication fund|MSD: Stocks/Bonds (Public Company) Nicole Cossrow, PhD, Merck: Stocks/Bonds (Public Company) Zinan Yi, n/a, Merck: Stocks/Bonds (Public Company) Kelly D. Johnson, PhD, Merck & Co., Inc.: Employee|Merck & Co., Inc.: Stocks/Bonds (Public Company) Kwame Owusu-Edusei, Ph.D., Merck & Co., Inc., Rahway, NJ, USA: Employee|Merck & Co., Inc., Rahway, NJ, USA: Stocks/Bonds (Public Company)

Cardiovascular disease, bone fracture, and all-cause mortality risks among postmenopausal women by arthritis and veteran status: A multistate Markov transition analysis.

Arthritis, a chronic inflammatory condition linked to cardiovascular disease (CVD) and bone fracture, is more frequent among military veterans and postmenopausal women. This study examined correlates of arthritis and relationships of arthritis with risks of developing CVD, bone fractures, and mortality among postmenopausal veteran and non-veteran women. We analyzed longitudinal data on 135,790 (3,436 veteran and 132,354 non-veteran) postmenopausal women from the Women's Health Initiative who were followed-up for an average of 16years between enrollment (1993-1998) and February 17, 2024. Regression and multistate Markov modeling were applied to meet study objectives. The prevalence of arthritis at enrollment (1993-1998) did not differ by veteran status in a fully adjusted logistic model. Variable selection yielded 5 key predictors of prevalent arthritis among veterans and 15 key predictors among non-veterans. In fully-adjusted Cox models, prevalent arthritis was associated with CVD (hazard ratio [HR] = 1.08, 95% confidence interval [CI]: 1.05, 1.10) and all-cause mortality (HR = 1.03, 95% CI: 1.01, 1.05) risks among non-veterans only, but was not associated with bone fracture risk irrespective of veteran status. Transition probabilities between health and CVD and between bone fracture and death were higher among women with vs. without arthritis. The latter transition was more strongly related to arthritis among non-veteran vs. veteran women. In conclusion, among postmenopausal women, prevalent arthritis was associated with greater probabilities of transitioning from a healthy state to CVD and from bone fracture to death, with worse prognosis after bone fracture among those who did not serve in the military.

P-175. Assessing the Dynamics of Fecal Colonization with Antibiotic-Resistant Bacteria in a Chilean Cohort: A Longitudinal Study

Abstract Background In low- and middle-income countries, the community burden of antibiotic-resistant Gram-negative bacteria (AR-GNB) colonization is high. Understanding factors influencing AR-GNB colonization is crucial for controlling antimicrobial resistance. Methods We conducted a cohort study from December 2019 to November 2020 with community-dwelling adults in Molina, an agricultural town in Central Chile. We collected questionnaires and fecal samples every two weeks for six months to identify colonization by extended-spectrum cephalosporin-resistant Enterobacterales (ESCRE). ESCRE detection involved selective media screening, MALDI-TOF identification, and disk-diffusion antibiotic-susceptibility testing. We assessed the impact of epidemiological and clinical features and exposure to various water sources, foods, and animals on i) baseline ESCRE fecal colonization, ii) ESCRE acquisition during follow-up, and iii) ESCRE clearance. The study included 198 subjects, using multiple imputations for missing predictor values. We used two hidden Markov models for each dataset, with Model 1 assuming perfect sensitivity and specificity and Model 2 estimating sensitivity. A Bayesian approach with Markov chain Monte Carlo algorithms estimated odds ratios (OR) and credible intervals (CI). Results The sample consisted of 198 residents with a mean age of 60.9 and a predominance of women (75%). Model 1 showed that treating drinking water before consumption reduced the risk of baseline ESCRE colonization (OR: 0.38; 95% CI: 0.02 – 0.89). No significant associations were found for ESCRE acquisition during follow-up. Males and individuals with comorbidities had a lower risk of clearing ESCRE (ORs: 0.58, 0.54; CIs: 0.24 – 0.97, 0.258 – 0.88, respectively). Model 2, with imperfect sensitivity, showed similar results. Conclusion This study highlights the significance of environmental and individual health factors in ESCRE colonization. Interventions like treating drinking water could reduce baseline ESCRE colonization risk. The varied impacts of gender and comorbidities on ESCRE clearance provide insights for targeted AR-GNB management strategies. Further research is needed to understand these associations and develop effective community-level interventions against AMR. Disclosures All Authors: No reported disclosures

P-2261. Belatacept-based immunosuppression does not confer increased risk of BK Polyomavirus -DNAemia relative to Tacrolimus-based immunosuppression

Abstract Background BK polyoma virus (BKPyV) DNAemia imparts significant morbidity in kidney transplant recipients (KTR). It can lead to polyomavirus-associated nephropathy (PyVAN), impaired graft function, and graft failure. The effect of belatacept on BK polyoma virus (BKPyV) control remains largely unknown. Methods This is a propensity matched retrospective cohort study in adult kidney transplant recipients (KTR) transplanted between 2016-2020 who received a belatacept- versus tacrolimus-based immunosuppression regimen. A multi-state Markov model was used to evaluate BKPyV replication dynamics (BKPyV-dyn). Three BKPyV-dyn states were defined: BKPyV-dyn1 (viral load < 3 log10), BKPyV-dyn2 (viral load > 3 log10 and < 4 log10), and BKPyV-dyn3 (viral load > 4 log10). Estimated total length of stay in a BKPyV replication dynamic state after evolution of the entire Markov process Results 280 KTR on belatacept- and 280 KTR on tacrolimus-based regimens were compared. The probability of transitioning between BKPyV-dyn states and time spent in each state in both groups was comparable. Total duration in BKPyV-dyn-1 was 632.1 days (95%CI 612.1, 648.5) for belatacept vs 615.2 days (95% CI 592.5, 635.8) for tacrolimus, BKPyV-dyn-2 was 49.2 days (95% CI 41.3, 58.4) for belatacept vs 55.6 days (95% CI 46.5, 66.8) for tacrolimus, and BKPyV-dyn-3 was 48.7 days (95% CI 52.3, 79.5) for belatacept vs 60.9 days (95% CI 48.3, 76.4) for tacrolimus (Figure 1). Estimated mean sojourn time did (time spent in a given BKPyV-dyn state prior to transitioning to another state) did not differ by immunosuppression (Figure 2). BKPyV associated nephropathy (PyVAN) occurred in 3.9% in belatacept- and 3.9% tacrolimus-treated KRT (P >0.9). Estimated mean sojourn time by immunosuppression Average single occupancy time in a BKPyV replication dynamic state Conclusion Collectively, our results indicate that relative to patients on tacrolimus-based regimens, patients on belatacept-based immunosuppression regimens do not require more frequent BKPyV QNAT monitoring or more aggressive immunosuppression reduction when BKPyV-DNAemia 3 log10 or greater is detected. Disclosures Christian P. Larsen, MD, PhD, Bristol-Myers Squibb: Advisor/Consultant|CareDx: Advisor/Consultant|Eledon: Advisor/Consultant

P-282. Cost Effectiveness Analysis of Ceftolozane/Tazobactam for the Treatment of Patients with Ventilated Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia in the Philippines

Abstract Background Ceftolozane/tazobactam (C/T) was licensed by Philippine Food and Drug Administration for the treatment of ventilated hospital-acquired bacterial pneumonia (vHABP) and ventilator-associated bacterial pneumonia (VABP) last 2019. Increasing resistance rates to antibiotics available in the Philippine National Formulary (PNF) by Pseudomonas aeruginosa associated vHABP/VABP has concerned clinicians due to its overall morbidity and mortality. This study assessed the cost-effectiveness of C/T treatment compared with existing antimicrobials among adult patients with confirmed susceptibility profile of Pseudomonas aeruginosa associated vHABP/VABP. Methods An economic model was developed to compare the lifetime costs and quality-adjusted life-years (QALYs) associated with C/T and the currently listed antimicrobials (meropenem, aminoglycosides, colistin) in the PNF for the treatment of patients with Pseudomonas aeruginosa associated vHABP/VABP. A short-term decision tree was used for the in-hospital period, followed by a long-term Markov model to depict lifetime costs and outcomes. Pathogen susceptibility was sourced from the Program to Assess Ceftolozane/Tazobactam Susceptibility (PACTS) database; clinical efficacy was obtained from the published literature. The model assumed a public payer perspective, capturing direct costs incurred by the health system, and direct health outcomes for treated patients. Discount rates applied followed local HTA methods guide. Results On treating Pseudomonas aeruginosa associated vHABP/VABP, C/T was associated with a higher absolute cure rate (17%) and lower absolute mortality rate (-3%) than meropenem. The incremental cost-effectiveness ratio (ICER) for C/T compared to meropenem, amikacin, and colistin were ₱267,396, ₱164,570, and ₱47,504 per QALY gained, respectively. C/T generated more QALYs than exiting antimicrobials at an increased cost per patient, but resulting in ICER less than one times the Gross Domestic Product (GDP) of ₱233,902 for amikacin, and colistin, and ∼ 1.2x GDP per capita for meropenem. Conclusion C/T represents a cost-effective treatment for payers and an important option to be listed in the PNF for clinicians treating patients with Pseudomonas aeruginosa vHABP/VABP in the Philippines. Disclosures GEOVIN DEXTER C. UY, RPh, MPH, MSD Philippines: employee|MSD Philippines: Stocks/Bonds (Private Company) Karlo Paredes, RN, MPH, PhD (cand), MSD Philippines: employee|MSD Philippines: Stocks/Bonds (Private Company) Gillian Camille Abello, MD, MSD Philippines: employee Carolyn Cameron, MPH, MSD Australia: employee|MSD Australia: Stocks/Bonds (Private Company) Joe Yang, PhD, Merck & Co., Inc: employee|Merck & Co., Inc: Stocks/Bonds (Private Company)