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1.
Health Aff (Millwood) ; : 101377hlthaff202000455, 2020 May 07.
Artigo em Inglês | MEDLINE | ID: mdl-32379502

RESUMO

Knowing the infection fatality rate (IFR) of SARS-CoV and SARS-CoV-2 infections is essential for the fight against the COVID-19 pandemic. Using data through April 20, 2020, we fit a statistical model to COVID-19 case fatality rates over time at the US county level to estimate the COVID-19 IFR among symptomatic cases (IFR-S) as time goes to infinity. The IFR-S in the US was estimated to be 1.3% (95% central credible interval: 0.6% to 2.1%). County-specific rates varied from 0.5% to 3.6%. The overall IFR for COVID-19 should be lower when we account for cases that remain and recover without symptoms. When used with other estimating approaches, our model and our estimates can help disease and policy modelers to obtain more accurate predictions for the epidemiology of the disease and the impact of alternative policy levers to contain this pandemic. The model could also be used with future epidemics to get an early sense of the magnitude of symptomatic infection at the population-level before more direct estimates are available. Substantial variation across patient demographics likely exists and should be the focus of future studies. [Editor's Note: This Fast Track Ahead Of Print article is the accepted version of the peer-reviewed manuscript. The final edited version will appear in an upcoming issue of Health Affairs.].

2.
Artigo em Inglês | MEDLINE | ID: mdl-32232734

RESUMO

BACKGROUND: Previous research assessing medication adherence with P2Y12 inhibitors has shown good adherence rates, ranging from 78% to 92%. Studies that used administrative claims data defined adherence using an arbitrary cut point of ≥ 80% medication possession ratio (MPR) or proportion of days covered (PDC). While this method is used frequently, it does not allow the researcher to observe how each factor impacts adherence along the entire distribution. The objective of the study was to use conditional quantile regression (CQR) and unconditional quantile regression (UQR) to assess heterogenous effects of adherence to P2Y12 inhibitors and covariates of interest and compare these results to those from a traditional logistic regression framework. METHODS AND RESULTS: This study used the commercial claims and encounters databases from IBM® MarketScan® from 2010 to 2017. We included patients who had an incident percutaneous coronary intervention, used a drug-eluting stent, and filled an incident prescription for a P2Y12 inhibitor. Adherence was measured for 185 days using PDC. Adherence to branded clopidogrel, generic clopidogrel, branded prasugrel, and branded ticagrelor was assessed, along with factors that could impact adherence, using logistic regression, CQR, and UQR. We found that while adherence to the antiplatelets was generally high, prasugrel and ticagrelor had significantly lower PDC compared to branded clopidogrel, especially around the 30th percentile. Across all quantiles in both the CRQ and UQR frameworks, comorbidities such as diabetes and depression and living in the southern region had significant negative effects on adherence, although the relative impact differed across quantiles. CONCLUSIONS: Using CQR and UQR allowed for heterogenous assessment of covariates along the adherence distribution, which is not possible with the traditional logistic regression method. The UQR framework revealed patients who initiate prasugrel or ticagrelor generally have lower adherence compared to those treated with branded clopidogrel, especially around the 30th quantile. Using these methods in other types of data sets, such as electronic health records, could help strengthen our results to develop policies to improve antiplatelet adherence in a targeted population.

3.
J Manag Care Spec Pharm ; 26(4): 529-537, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-32223606

RESUMO

BACKGROUND: Although precision medicine using genetic information offers significant promise, its uptake and eventual clinical and economic impacts are uncertain. Health care payers will play an important role in evaluating evidence and costs to develop coverage and reimbursement policies. OBJECTIVE: To elicit U.S. health care payer preference for genomic precision medicine to better understand trade-offs among clinical benefits, uncertainty, and cost. METHODS: Using key informant interviewer discussions (N = 6 payers), we identified 6 key attributes of genetic tests important to payers: type of information the test provides (screening vs. treatment prediction), probability that the member has an informative genetic marker, expert agreement on changing medical care based on the marker, quality-of-life gains, life expectancy gains (with statistical uncertainty), and cost to the plan. We designed a stated preference discrete choice experiment using these attributes and administered a web survey to a sample of U.S. health care payers. We used effects coding and analyzed the data using an error component mixed logit modeling approach. RESULTS: The survey response rate was 58% (150 participants completed the survey). Approximately 53% of respondents had previous experience evaluating genetic tests for reimbursement, and 85% had more than 5 years of health care decision-making experience. Payers valued improvements in quality of life the most (marginal willingness to pay [mWTP] of $1,513-$6,076), followed by medical expert agreement on the treatment change (mWTP of $2,881-$3,489). Payers placed a relatively lower value for genetic tests with lower marker probability (mWTP of $2,776 for highest marker probability to $423 for lowest marker probability). Payers mWTP was lowest for resolving uncertainty in quality of life (mWTP of $1,513-$2,031) and life expectancy gains ($536-$1,537). CONCLUSIONS: Payers exhibited a strong preference for genetic tests that improved quality of life, had high expert agreement on changing medical care, and increased life expectancy. These findings suggest that payers will need evidence of clinical utility to support coverage and reimbursement of genomic precision medicine. DISCLOSURES: This study was supported by a grant from the NIH Common Fund and NIA (1U01AG047109-01) via the Personalized Medicine Economics Research (PriMER) project. Unrelated to this study, Veenstra reports consulting fees from Bayer and Halozyme; Basu reports consulting fees from Salutis Consulting; and Reiger reports consulting fees from Roche. Carlson reports grants from Institute for Clinical and Economic Review, during the conduct of this study, and consulting fees from Bayer, Adaptive Biotechnologies, Allergan, Galderma, and Vifor Pharma, unrelated to this study.

4.
Artigo em Inglês | MEDLINE | ID: mdl-32134729

RESUMO

Precision medicine - individualizing care for patients and addressing variations in treatment response - is likely to be important in improving the nation's health in a cost-effective manner. Despite this promise, widespread use of precision medicine, specifically genomic markers, in clinical care has been limited in practice to date. Lack of evidence, clear evidence thresholds, and reimbursement have been cited as major barriers. Health economics frameworks and tools can elucidate the effects of legal, regulatory, and reimbursement policies on the use of precision medicine while guiding research investments to enhance the appropriate use of precision medicine. Despite the capacity of economics to enhance the clinical and human impact of precision medicine, application of health economics to precision medicine has been limited - in part because precision medicine is a relatively new field - but also because precision medicine is complex, both in terms of its applications and implications throughout medicine and the healthcare system. The goals of this review are several-fold: (1) provide an overview of precision medicine and key policy challenges for the field; (2) explain the potential utility of economics methods in addressing these challenges; (3) describe recent research activities; and (4) summarize opportunities for cross-disciplinary research.

5.
Value Health ; 23(2): 139-150, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-32113617

RESUMO

Healthcare resource allocation decisions made under conditions of uncertainty may turn out to be suboptimal. In a resource constrained system in which there is a fixed budget, these suboptimal decisions will result in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to make better resource allocation decisions. This value can be quantified using a value of information (VOI) analysis. This report, from the ISPOR VOI Task Force, introduces VOI analysis, defines key concepts and terminology, and outlines the role of VOI for supporting decision making, including the steps involved in undertaking and interpreting VOI analyses. The report is specifically aimed at those tasked with making decisions about the adoption of healthcare or the funding of healthcare research. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing the results of VOI analyses.

6.
Value Health ; 23(3): 277-286, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-32197720

RESUMO

The allocation of healthcare resources among competing priorities requires an assessment of the expected costs and health effects of investing resources in the activities and of the opportunity cost of the expenditure. To date, much effort has been devoted to assessing the expected costs and health effects, but there remains an important need to also reflect the consequences of uncertainty in resource allocation decisions and the value of further research to reduce uncertainty. Decision making with uncertainty may turn out to be suboptimal, resulting in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to better inform resource decisions. This value can be quantified using value of information (VOI) analysis. This report from the ISPOR VOI Task Force describes methods for computing 4 VOI measures: the expected value of perfect information, expected value of partial perfect information (EVPPI), expected value of sample information (EVSI), and expected net benefit of sampling (ENBS). Several methods exist for computing EVPPI and EVSI, and this report provides guidance on selecting the most appropriate method based on the features of the decision problem. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing VOI analyses. The software needed to compute VOI is discussed, and areas for future research are highlighted.

7.
J Manag Care Spec Pharm ; 26(3): 325-331, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-32105174

RESUMO

BACKGROUND: Glaucoma is a collection of eye diseases that damage the eye's optic nerve resulting in vision loss and blindness. Treatment for glaucoma is primarily pharmacologic; however, studies have shown patients have difficulty adhering to topical regimens. The reasons for potentially poor adherence are numerous, including influence from a myriad of either physical or mental comorbid conditions faced by many glaucoma patients. Neither adherence nor associated outcomes have been estimated in these 2 groups of glaucoma patients. OBJECTIVES: To (a) characterize glaucoma patients with and without select physical or mental comorbidities and (b) estimate differences between the 2 groups for 3 types of outcomes: health care resource use (HCRU; office-based/outpatient-based provider visits, emergency room visits, inpatient stays, home health provider days, prescription fills); health care expenditures; and health-related quality of life (HRQoL) as measured by the physical and mental component scores of the Short Form-12. METHODS: We used first-year data from each glaucoma patient's 2-year panel survey in the Medical Expenditure Panel Survey (MEPS) database, 2003-2014. Two groups were created using ICD-9-CM codes collected by MEPS to compare glaucoma patients with and without at least 1 selected physical or mental comorbid condition. Between-group comparisons in the outcomes of interest (HCRU, expenditure, HRQoL) were estimated using multivariable regression analyses while adjusting for socio-demographic and clinical characteristics at baseline. RESULTS: We identified 2,928 unique glaucoma patients during the 11 years of collected data, including 1,539 (53%) who had at least 1 physical or mental comorbid condition of interest. Comparing those with at least 1 select physical or mental comorbidity to those without (n = 1,389), unadjusted HCRU and expenditures were greater in patients with a physical or mental comorbidity (all P < 0.05). After adjustment, significant associations with increased HCRU remained for office-based provider visits and home health provider days (each P < 0.01). Average total expenditures were $12,324 in those with comorbidities and $8,590 for those without. HRQoL (unadjusted and adjusted) was lower in those with a physical or mental comorbid condition (all P < 0.05). CONCLUSIONS: Some differences in HCRU and expenditures were accounted for by differences in baseline characteristics between those with and those without 1 or more physical or mental comorbid conditions, but differences remained after adjustment. Results suggest that glaucoma patients with physical and mental comorbidities may experience greater HCRU and associated expenditures, and lower HRQoL, when compared with glaucoma patients without these comorbidities With this knowledge, future work may include estimating the effect of the number of these comorbid conditions on each of the 3 types of outcomes. DISCLOSURES: This study received funding support from Allergan. During the time this work was conducted, Serbin was a postdoctoral fellow who was supported by a training grant from Allergan to the University of Washington. Campbell is an employee of Allergan. Serbin, Devine, and Basu each have nothing to disclose. This study was presented as a poster at the International Society for Pharmacoeconomics and Outcomes Research Meeting; May 20-24, 2017; Boston, MA.

8.
Environ Sci Technol ; 54(4): 2295-2303, 2020 02 18.
Artigo em Inglês | MEDLINE | ID: mdl-31909614

RESUMO

U isotope fractionation may serve as an accurate proxy for U(VI) reduction in both modern and ancient environments, if the systematic controls on the magnitude of fractionation (ε) are known. We model the effect of U(VI) reduction kinetics on U isotopic fractionation during U(VI) reduction by a novel Shewanella isolate, Shewanella sp. (NR), in batch incubations. The measured ε values range from 0.96 ± 0.16 to 0.36 ± 0.07‰ and are strongly dependent on the U(VI) reduction rate. The ε decreases with increasing reduction rate constants normalized by cell density and initial U(VI). Reactive transport simulations suggest that the rate dependence of ε is due to a two-step process, where diffusive transport of U(VI) from the bulk solution across a boundary layer is followed by enzymatic reduction. Our results imply that the spatial decoupling of bulk U(VI) solution and enzymatic reduction should be taken into account for interpreting U isotope data from the environment.


Assuntos
Fracionamento Químico , Cromo , Isótopos , Cinética , Oxirredução
9.
Value Health ; 23(1): 96-103, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31952678

RESUMO

OBJECTIVES: To find an alternative for quality-adjusted life-year (QALY) and equal value of life (EVL) measures. Despite the importance of QALY in cost-effectiveness analysis (CEA)-because it captures the effects of both life expectancy and health-related quality of life (QOL) and enables comparisons across interventions and disease areas-its potential to be discriminatory towards patients with lower QOL presents a critical challenge that has resulted in the exclusion of its use in some public decision making (eg, US Medicare) on healthcare in the United States. Alternatives to QALY, such as EVL, have not gained traction because EVL fails to recognize the QOL gains during added years of life. METHODS: We present a new metric for effectiveness for CEA, health years in total (HYT), which overcomes both the specific distributional issue raised by QALY and the efficiency challenges of EVL. RESULTS: The HYT framework separates life expectancy changes and QOL changes on an additive scale. HYT have the same axiomatic foundations as QALY and perform better than both QALY, in terms of the discriminatory implications, and EVL, in terms of capturing QOL gains during added years of life. HYT are straightforward to calculate within a CEA model. We found that thresholds of $34 000/HYT and $89 000/HYT correspond to CEA thresholds of $50 000/QALY and $150 000/QALY, respectively. CONCLUSIONS: The HYT framework may provide a viable alternative to both the QALY and the EVL; its application to diverse healthcare technologies and stakeholder assessments are important next steps in its development and evaluation.

10.
J Health Econ ; 70: 102287, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31972535

RESUMO

I look at three debates in the health economics literature in the context of cost-effectiveness analysis (CEA): 1) inclusion of future costs, 2) discounting, and 3) consistency with a welfare-economic perspective. These debates thus far have been studied in isolation leading to confusion and lingering questions. I look at these three debates holistically and present a welfare theoretic model that is consistent with the practice of CEA and can help inform all of these three debates. It shows rationales for the recommendations of the Second Panel and clarifies some nuanced implications for the practice of CEA when taking a societal perspective in the context of distributional CEA and multi-sectorial budgets.

11.
Pharmacoeconomics ; 38(1): 57-68, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31489595

RESUMO

BACKGROUND: A limited evidence base and lack of clear clinical guidelines challenge healthcare systems' adoption of precision medicine. The effect of these conditions on demand is not understood. OBJECTIVE: This research estimated the public's preferences and demand for precision medicine outcomes. METHODS: A discrete-choice experiment survey was conducted with an online sample of the US public who had recent healthcare experience. Statistical analysis was undertaken using an error components mixed logit model. The responsiveness of demand in the context of a changing evidence base was estimated through the price elasticity of demand. External validation was examined using real-world demand for the 21-gene recurrence score assay for breast cancer. RESULTS: In total, 1124 (of 1849) individuals completed the web-based survey. The most important outcomes were survival gains with statistical uncertainty, cost of testing, and medical expert agreement on changing care based on test results. The value ($US, year 2017 values) for a test where most (vs. few) experts agreed to changing treatment based on test results was $US1100 (95% confidence interval [CI] 916-1286). Respondents were willing to pay $US265 (95% CI 46-486) for a test that could result in greater certainty around life-expectancy gains. The predicted demand of the assay was 9% in 2005 and 66% in 2014, compared with real-world uptake of 7% and 71% (root-mean-square prediction error 0.11). Demand was sensitive to price (1% increase in price resulted in > 1% change in demand) when first introduced and insensitive to price (1% increase in price resulted in < 0.1% change in demand) as the evidence base became established. CONCLUSIONS: Evidence of external validity was found. Demand was weak and responsive to price in the near term because of uncertainty and an immature evidence base. Clear communication of precision medicine outcomes and uncertainty is crucial in allowing healthcare to align with individual preferences.

12.
Pharmacoeconomics ; 38(2): 171-179, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31631254

RESUMO

BACKGROUND: Value of information (VOI) analysis often requires modeling to characterize and propagate uncertainty. In collaboration with a cancer clinical trial group, we integrated a VOI approach to assessing trial proposals. OBJECTIVE: This paper aims to explore the impact of modeling choices on VOI results and to share lessons learned from the experience. METHODS: After selecting two proposals (A: phase III, breast cancer; B: phase II, pancreatic cancer) for in-depth evaluations, we categorized key modeling choices relevant to trial decision makers (characterizing uncertainty of efficacy, evidence thresholds to change clinical practice, and sample size) and modelers (cycle length, survival distribution, simulation runs, and other choices). Using a $150,000 per quality-adjusted life-year (QALY) threshold, we calculated the patient-level expected value of sample information (EVSI) for each proposal and examined whether each modeling choice led to relative change of more than 10% from the averaged base-case estimate. We separately analyzed the impact of the effective time horizon. RESULTS: The base-case EVSI was $118,300 for Proposal A and $22,200 for Proposal B per patient. Characterizing uncertainty of efficacy was the most important choice in both proposals (e.g. Proposal A: $118,300 using historical data vs. $348,300 using expert survey), followed by the sample size and the choice of survival distribution. The assumed effective time horizon also had a substantial impact on the population-level EVSI. CONCLUSIONS: Modeling choices can have a substantial impact on VOI. Therefore, it is important for groups working to incorporate VOI into research prioritization to adhere to best practices, be clear in their reporting and justification for modeling choices, and to work closely with the relevant decision makers, with particular attention to modeling choices.

13.
Addiction ; 2019 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-31670853

RESUMO

BACKGROUND AND AIMS: Washington Initiative 1183 (I-1183), a 2012 law that privatized liquor retail sales and distribution in Washington State, USA, has had two opposing effects on liquor purchases: it has increased access to liquor and imposed new fees on retailers and distributors. This study aimed to estimate the effect of I-1183 on monthly alcohol purchases during the post-I-1183 period (June 2012-December 2014) compared with the pre-I-1183 period (January 2010-May 2012). DESIGN: DIFFERENCES-IN-DIFFERENCES STUDY: Setting and participants The study included households participating in the Nielsen Consumer Panel Dataset living in metropolitan and surrounding areas in Washington State and 10 control states. Measurements Outcomes were alcohol purchases by type (ounces of liquor, wine, beer and total alcohol or ethanol). Findings I-1183 was associated with a 6.34-ounce (P < 0.001) and a 2.01-ounce (P < 0.001) increase in monthly liquor and ethanol purchases, respectively, per household in the post-policy period spanning 31 months compared with monthly purchases in control states. In a longitudinal subgroup analysis, low and moderate alcohol purchasers increased monthly purchases of ethanol and high purchasers decreased purchases of ethanol. Conclusions Enacting 'Washington Initiative 1183', a law that privatized sale and distribution of liquor and imposed new fees on retailers and distributors, appears to have been associated with an approximate 82% increase in monthly liquor purchases and 26% increase in monthly ethanol purchases by households in metropolitan and surrounding areas in Washington State, USA.

14.
Res Social Adm Pharm ; 2019 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-31706950

RESUMO

BACKGROUND: Academic detailing is an educational outreach program that aligns providers' prescribing with evidence-based practice. The U.S. Department of Veterans Affairs (VA) Opioid Overdose Education and Naloxone Distribution (OEND) Program partnered with the VA Pharmacy Benefits Management National Academic Detailing Service to deliver naloxone education to providers who cared for patients at risk of opioid overdose. In this pilot study, we interviewed providers' who received academic detailing to capture their perceptions of facilitators and barriers to prescribing naloxone. OBJECTIVE: To identify providers' perceptions of facilitators and barriers to prescribing naloxone for patients at risk for opioid overdose after implementation of a national academic detailing program. METHODS: This was a hybrid inductive-deductive qualitative pilot using semi-structured interviews with VA providers to explore constructs associated with facilitators and barriers to prescribing take-home naloxone to patients at risk for opioid overdose from August 2017 to April 2018. RESULTS: Eleven participants were interviewed, six physicians, three clinical psychiatric pharmacists, and two nurse practitioners. Participants identified patient-level barriers (social stigma and lack of homeless patient support), poor data integration, and burden of data validation as barriers to prescribing naloxone. However, they also identified patient lists, repeat visits, and face-to-face/one-on-one video conferencing visits as important facilitators for naloxone prescribing. CONCLUSIONS/IMPORTANCE: Academic detailing will need to address issues of social stigma regarding naloxone, educate providers about existing support systems for homeless veterans, and develop tools for data integration to improve naloxone access for veterans at risk for an opioid overdose.

15.
Am J Manag Care ; 25(11): 540-542, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31747231

RESUMO

Laying a clear path for incorporating reliable evidence on heterogeneity in value assessments could improve their applicability for healthcare decision making.

16.
mSphere ; 4(5)2019 10 02.
Artigo em Inglês | MEDLINE | ID: mdl-31578247

RESUMO

RNA viruses are known to modulate host microRNA (miRNA) machinery for their own benefit. Japanese encephalitis virus (JEV), a neurotropic RNA virus, has been reported to manipulate several miRNAs in neurons or microglia. However, no report indicates a complete sketch of the miRNA profile of neural stem/progenitor cells (NSPCs), hence the focus of our current study. We used an miRNA array of 84 miRNAs in uninfected and JEV-infected human neuronal progenitor cells and primary neural precursor cells isolated from aborted fetuses. Severalfold downregulation of hsa-miR-9-5p, hsa-miR-22-3p, hsa-miR-124-3p, and hsa-miR-132-3p was found postinfection in both of the cell types compared to the uninfected cells. Subsequently, we screened for the target genes of these miRNAs and looked for the biological pathways that were significantly regulated by the genes. The target genes involved in two or more pathways were sorted out. Protein-protein interaction (PPI) networks of the miRNA target genes were formed based on their interaction patterns. A binary adjacency matrix for each gene network was prepared. Different modules or communities were identified in those networks by community detection algorithms. Mathematically, we identified the hub genes by analyzing their degree centrality and participation coefficient in the network. The hub genes were classified as either provincial (P < 0.4) or connector (P > 0.4) hubs. We validated the expression of hub genes in both cell line and primary cells through qRT-PCR after JEV infection and respective miR mimic transfection. Taken together, our findings highlight the importance of specific target gene networks of miRNAs affected by JEV infection in NSPCs.IMPORTANCE JEV damages the neural stem/progenitor cell population of the mammalian brain. However, JEV-induced alteration in the miRNA expression pattern of the cell population remains an open question, hence warranting our present study. In this study, we specifically address the downregulation of four miRNAs, and we prepared a protein-protein interaction network of miRNA target genes. We identified two types of hub genes in the PPI network, namely, connector hubs and provincial hubs. These two types of miRNA target hub genes critically influence the participation strength in the networks and thereby significantly impact up- and downregulation in several key biological pathways. Computational analysis of the PPI networks identifies key protein interactions and hubs in those modules, which opens up the possibility of precise identification and classification of host factors for viral infection in NSPCs.


Assuntos
Vírus da Encefalite Japonesa (Espécie)/patogenicidade , Redes Reguladoras de Genes , Interações Hospedeiro-Patógeno , MicroRNAs/genética , Células-Tronco Neurais/virologia , Linhagem Celular , Células Cultivadas , Perfilação da Expressão Gênica , Humanos
17.
Value Health ; 22(9): 988-994, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31511188

RESUMO

BACKGROUND: The threshold of sufficient evidence for adoption of clinically- and genomically-guided precision medicine (PM) has been unclear. OBJECTIVE: To evaluate evidence thresholds for clinically guided PM versus genomically guided PM. METHODS: We develop an "evidence threshold criterion" (ETC), which is the time-weighted difference between expected value of perfect information and incremental net health benefit minus the cost of research, and use it as a measure of evidence threshold that is proportional to the upper bound of disutility to a risk-averse decision maker for adopting a new intervention under decision uncertainty. A larger (more negative) ETC value indicates that only decision makers with low risk aversion would adopt new intervention. We evaluated the ETC plus cost of research (ETCc), assuming the same cost of research for both interventions, over time for a pharmacogenomic (PGx) testing intervention and avoidance of a drug-drug interaction (aDDI) intervention for acute coronary syndrome patients indicated for antiplatelet therapy. We then examined how the ETC may explain incongruous decision making across different national decision-making bodies. RESULTS: The ETCc for PGx increased over time, whereas the ETCc for aDDI decreased to a negative value over time, indicating that decision makers with even low risk aversion will have doubts in adopting PGx, whereas decision makers who are highly risk-averse will continue to have doubts about adopting aDDI. National recommendation bodies appear to be consistent over time within their own decision making, but had different levels of risk aversion. CONCLUSION: The ETC may be a useful metric for assessing policy makers' risk preferences and, in particular, understanding differences in policy recommendations for genomic versus clinical PM.

18.
J Immunol ; 203(8): 2222-2238, 2019 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-31527198

RESUMO

Microglia being the resident macrophage of brain provides neuroprotection following diverse microbial infections. Japanese encephalitis virus (JEV) invades the CNS, resulting in neuroinflammation, which turns the neuroprotective role of microglia detrimental as characterized by increased microglial activation and neuronal death. Several host factors, including microRNAs, play vital roles in regulating virus-induced inflammation. In the current study, we demonstrate that the expression of miR-301a is increased in JEV-infected microglial cells and human brain. Overexpression of miR-301a augments the JEV-induced inflammatory response, whereas inhibition of miR-301a completely reverses the effects. Mechanistically, NF-κB-repressing factor (NKRF) functioning as inhibitor of NF-κB activation is identified as a potential target of miR-301a in JEV infection. Consequently, miR-301a-mediated inhibition of NKRF enhances nuclear translocation of NF-κB, which, in turn, resulted in amplified inflammatory response. Conversely, NKRF overexpression in miR-301a-inhibited condition restores nuclear accumulation of NF-κB to a basal level. We also observed that JEV infection induces classical activation (M1) of microglia that drives the production of proinflammatory cytokines while suppressing alternative activation (M2) that could serve to dampen the inflammatory response. Furthermore, in vivo neutralization of miR-301a in mouse brain restores NKRF expression, thereby reducing inflammatory response, microglial activation, and neuronal apoptosis. Thus, our study suggests that the JEV-induced expression of miR-301a positively regulates inflammatory response by suppressing NKRF production, which might be targeted to manage viral-induced neuroinflammation.

19.
Pharmacoeconomics ; 37(11): 1321-1327, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31485925

RESUMO

Transparency in decision modeling remains a topic of rigorous debate among healthcare stakeholders, given tensions between the potential benefits of external access during model development and the need to protect intellectual property and reward research investments. Strategies to increase decision model transparency by allowing direct external access to a model's structure, source code, and data can take on many forms but are bounded between the status quo and free publicly available open-source models. Importantly, some level of transparency already exists in terms of methods and other technical specifications for published models. The purpose of this paper is to delineate pertinent issues surrounding efforts to increase transparency via direct access to models and to offer key considerations for the field of health economics and outcomes research moving forward from a US academic perspective. Given the current environment faced by modelers in academic settings, expected benefits and challenges of allowing direct model access are discussed. The paper also includes suggestions for pathways toward increased transparency as well as an illustrative real-world example used in work with the Institute for Clinical and Economic Review to support assessments of the value of new health interventions. Potential options to increase transparency via direct model access during model development include adequate funding to support the additional effort required and mechanisms to maintain security of the underlying intellectual property. Ultimately, the appropriate level of transparency requires balancing the interests of several groups but, if done right, has the potential to improve models and better integrate them into healthcare priority setting and decision making in the US context.

20.
JAMA ; 322(6): 582-583, 2019 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-31408133
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