Cost-effectiveness of proprotein convertase subtilisin/kexin type 9 inhibition with evolocumab in patients with a history of myocardial infarction in Sweden.

AIMS: To assess the cost-effectiveness of proprotein convertase subtilisin/kexin type 9 inhibition with evolocumab added to standard-of-care lipid-lowering treatment [maximum tolerated dose (MTD) of statin and ezetimibe] in Swedish patients with a history of myocardial infarction (MI). METHODS AND RESULTS: Cost-effectiveness was evaluated using a Markov model based on Swedish observational data on cardiovascular event rates and efficacy from the FOURIER trial. Three risk profiles were considered: recent MI in the previous year; history of MI with a risk factor; and history of MI with a second event within 2 years. For each population, three minimum baseline low-density lipoprotein cholesterol (LDL-C) levels were considered: 2.5 mmol/L (≈100 mg/dL), based on the current reimbursement recommendation in Sweden; 1.8 mmol/L (≈70 mg/dL), based on 2016 ESC/EAS guidelines; and 1.4 mmol/L (≈55 mg/dL), or 1.0 mmol/L (≈40 mg/dL) for MI with a second event, based on 2019 ESC/EAS guidelines. Proprotein convertase subtilisin/kexin type 9 inhibition with evolocumab was associated with increased quality-adjusted life-years and costs vs. standard-of-care therapy. Incremental cost-effectiveness ratios (ICERs) were below SEK700 000 (∼€66 500), the generally accepted willingness-to-pay threshold in Sweden, for minimum LDL-C levels of 2.3 (recent MI), 1.7 (MI with a risk factor), and 1.7 mmol/L (MI with a second event). Sensitivity analyses demonstrated that base-case results were robust to changes in model parameters. CONCLUSION: Proprotein convertase subtilisin/kexin type 9 inhibition with evolocumab added to MTD of statin and ezetimibe may be considered cost-effective at its list price for minimum LDL-C levels of 1.7-2.3 mmol/L, depending on risk profile, with ICERs below the accepted willingness-to-pay threshold in Sweden.

Estimating Progression Rates Across the Spectrum of Alzheimer's Disease for Amyloid-Positive Individuals Using National Alzheimer's Coordinating Center Data.

INTRODUCTION: Published estimates of Alzheimer's disease (AD) progression do not capture the full disease continuum. This study provides transition probabilities of individuals with amyloid-ß (Aß+) pathology across the disease continuum. METHODS: Patient-level longitudinal data from the National Alzheimer's Coordinating Center were used to estimate progression rates. Progression rates through five clinically defined AD stages-asymptomatic, mild cognitive impairment due to AD (MCI-AD), mild AD dementia, moderate AD dementia, severe AD dementia-and death were measured as transition probabilities. Rates were assessed in "incident" patients who recently entered the stage, controlling for covariates. Transition probabilities were generated from multinomial logit regression models that predicted an individual's health state as a function of health state at the previous visit and adjusted for time between initial and follow-up visits, age, sex, years of education, and concomitant symptomatic AD medications. RESULTS: Annual transition probabilities to more severe dementia stages for surviving incident Aß+ patients were as follows: asymptomatic to MCI-AD, 40.8%; MCI-AD to mild AD dementia or worse, 21.8%; mild AD dementia to moderate AD dementia or worse, 35.9%; moderate AD dementia to severe AD dementia, 28.6%. Transition probabilities to less severe dementia stages were: 5.3% annual reversion from MCI-AD to asymptomatic, 3.0% mild AD dementia to MCI-AD, 1.8% moderate AD dementia to mild AD dementia, and 1.3% for severe AD dementia to moderate AD dementia. CONCLUSIONS: These transition probabilities reflect the full continuum of AD progression in Aß+ individuals and can be used to assess the impact of treatment on expected transitions.

Predicted Lifetime Health Outcomes for Aducanumab in Patients with Early Alzheimer's Disease.

INTRODUCTION: Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disease that places a substantial burden on patients and caregivers. Aducanumab is the first AD therapy approved by the US Food and Drug Administration to reduce a defining pathophysiological feature of the disease, brain amyloid plaques. In the phase 3 clinical trial EMERGE (NCT02484547), aducanumab reduced clinical decline in patients with mild cognitive impairment (MCI) due to AD and mild AD dementia and confirmed amyloid pathology. METHODS: We used a Markov modeling approach to predict the long-term clinical benefits of aducanumab for patients with early AD based on EMERGE efficacy data. In the model, patients could transition between AD severity levels (MCI due to AD; mild, moderate, and severe AD dementia) and care settings (community vs. institution) or transition to death. The intervention was aducanumab added to standard of care (SOC), and the comparator was SOC alone. Data sources for base-case and scenario analyses included EMERGE, published National Alzheimer's Coordinating Center analyses, and other published literature. RESULTS: Per patient over a lifetime horizon, aducanumab treatment corresponded to 0.65 incremental patient quality-adjusted life-years (QALYs) and 0.09 fewer caregiver QALYs lost compared with patients treated with SOC. Aducanumab treatment translated to a lower lifetime probability of transitioning to AD dementia, a lower lifetime probability of transitioning to institutionalization (25.2% vs. 29.4%), delays in the median time to transition to AD dementia (7.50 vs. 4.92 years from MCI to moderate AD dementia or worse), and an incremental median time in the community of 1.32 years compared with SOC. CONCLUSION: The model predicted long-term benefits of aducanumab treatment in patients with MCI due to AD and mild AD dementia and their caregivers. The predicted outcomes provide a foundation for healthcare decision-makers and policymakers to understand the potential clinical and socioeconomic value of aducanumab.

Estimation of the increased risk associated with recurrent events or polyvascular atherosclerotic cardiovascular disease in the United Kingdom.

AIMS: The aims of this study were to re-estimate the international REduction of Atherothrombosis for Continued Health (REACH) risk equation using United Kingdom data and to distinguish different relative hazards for specific atherosclerotic cardiovascular disease event histories. METHODS AND RESULTS: Patients in the UK Clinical Research Practice Datalink (CPRD) were included as of 1 January 2005 if they were 40 years or older, had 2 or more years of prior data, received one or more moderate or high-intensity statin in the previous year, and had a history of myocardial infarction, ischemic stroke, or other atherosclerotic cardiovascular disease. Patients were followed until a composite endpoint of myocardial infarction, ischemic stroke or cardiovascular death, loss to follow-up, or end of observation. We re-estimated the REACH risk equation hazard ratios (HRs) using CPRD data (re-estimated REACH model). Our event history model replaced the REACH vascular bed variables with more specific event histories. There were 60,838 patients with 5.25 years of mean follow-up. In the validation model, HRs were in the same direction, and generally greater than REACH. In the event history model, HRs compared to other atherosclerotic cardiovascular disease alone included: recurrent myocardial infarction (HR 1.19, 95% confidence interval (CI) 1.05-1.34), recurrent ischemic stroke (HR 1.36, 95% CI 1.03-1.80), myocardial infarction and other atherosclerotic cardiovascular disease (HR 1.31, 95% CI 1.23-1.38), ischemic stroke and other atherosclerotic cardiovascular disease (HR 1.40, 95% CI 1.23-1.60), myocardial infarction and ischemic stroke (HR 1.94, 95% CI 1.23-3.04), and myocardial infarction, ischemic stroke and other atherosclerotic cardiovascular disease (HR 1.93, 95% CI 1.47-2.54). CONCLUSION: A detailed cardiovascular event history may be useful for estimating the relative risk of future cardiovascular events.

Challenges in demonstrating the value of disease-modifying therapies for Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting millions of people worldwide and imposing heavy economic burdens to societies. Currently, only symptomatic treatments are available for patients, but there is ongoing research on potential therapies that can modify the course of disease. The main objective of this work is to identify and explore the challenges surrounding decision modeling for economic evaluation of interventions for AD. AREAS COVERED: This article discusses the challenges in modeling the natural history of disease, particularly regarding the selection of disease progression and outcome measures, the inclusion of biomarker status in models, and the approach to model mortality. Challenges stemming from the use of long-term assumptions regarding treatment effects and the need for real-world evidence to fill data gaps are discussed. Lastly, the overwhelming economic impact of disease and the challenges in estimating these costs for modeling are addressed. EXPERT OPINION: Value assessment frameworks need to be reconsidered in order to demonstrate the full benefit of new disease-modifying therapies spanning beyond the scope of health systems. Data collection efforts that expand the evidence base, upon which economic models are based, will reduce the uncertainties surrounding the long-term outcomes of interventions in AD.

Resurgence of malaria infection after mass treatment: a simulation study.

BACKGROUND: Field studies are evaluating if mass drug administration (MDA) might shorten the time to elimination of Plasmodium falciparum malaria, when vector control measures and reactive surveillance strategies are scaled-up. A concern with this strategy is that there may be resurgence of transmission following MDA. METHODS: A conceptual model was developed to classify possible outcomes of an initial period of MDA, followed by continuously implementing other interventions. The classification considered whether elimination or a new endemic stable state is achieved, and whether changes are rapid, transient, or gradual. These categories were informed by stability analyses of simple models of vector control, case management, and test-and-treat interventions. Individual-based stochastic models of malaria transmission (OpenMalaria) were then used to estimate the probability and likely rates of resurgence in realistic settings. Effects of concurrent interventions, including routine case management and test-and-treat strategies were investigated. RESULTS: Analysis of the conceptual models suggest resurgence will occur after MDA unless transmission potential is very low, or the post-MDA prevalence falls below a threshold, which depends on both transmission potential and on the induction of bistability. Importation rates are important only when this threshold is very low. In most OpenMalaria simulations the approximately stable state achieved at the end of the simulations was independent of inclusion of MDA and the final state was unaffected by importation of infections at plausible rates. Elimination occurred only with high effective coverage of case management, low initial prevalence, and high intensity test-and-treat. High coverage of case management but not by test-and-treat induced bistability. Where resurgence occurred, its rate depended mainly on transmission potential (not treatment rates). CONCLUSIONS: A short burst of high impact MDA is likely to be followed by resurgence. To avert resurgence, concomitant interventions need either to substantially reduce average transmission potential or to be differentially effective in averting or clearing infections at low prevalence. Case management at high effective coverage has this differential effect, and should suffice to avert resurgence caused by imported cases at plausible rates of importation. Once resurgence occurs, its rate depends mainly on transmission potential, not on treatment strategies.

Theory of reactive interventions in the elimination and control of malaria.

BACKGROUND: Reactive case detection (RCD) is an integral part of many malaria control and elimination programmes and can be conceived of as a way of gradually decreasing transmission. However, it is unclear under what circumstances RCD may have a substantial impact on prevalence, how likely it is to lead to local elimination, or how effective it needs to be to prevent reintroduction after transmission has been interrupted. METHODS: Analyses and simulations of a discrete time compartmental susceptible-infectious-susceptible (SIS) model were used to understand the mechanisms of how RCD changes transmission dynamics and estimate the impact of RCD programmes in a range of settings with varying patterns of transmission potential and programme characteristics. Prevalence survey data from recent studies in Zambia were used to capture the effects of spatial clustering of patent infections. RESULTS: RCD proved most effective at low prevalence. Increasing the number of index cases followed was more important than increasing the number of neighbours tested per index case. Elimination was achieved only in simulations of situations with very low transmission intensity and following many index cases. However, RCD appears to be helpful in maintaining the disease-free state after achieving malaria elimination (through other interventions). CONCLUSION: RCD alone can eliminate malaria in only a very limited range of settings, where transmission potential is very low, and improving the coverage of RCD has little effect on this range. In other settings, it is likely to reduce disease burden. RCD may also help maintain the disease-free state in the face of imported infections. Prevalence survey data can be used to estimate a targeting ratio (the ratio of prevalence found through RCD to that in the general population) which is an important determinant of the effect of RCD.

A stochastic model for the probability of malaria extinction by mass drug administration.

BACKGROUND: Mass drug administration (MDA) has been proposed as an intervention to achieve local extinction of malaria. Although its effect on the reproduction number is short lived, extinction may subsequently occur in a small population due to stochastic fluctuations. This paper examines how the probability of stochastic extinction depends on population size, MDA coverage and the reproduction number under control, R c . A simple compartmental model is developed which is used to compute the probability of extinction using probability generating functions. The expected time to extinction in small populations after MDA for various scenarios in this model is calculated analytically. RESULTS: The results indicate that mass drug administration (Firstly, R c must be sustained at R c  < 1.2 to avoid the rapid re-establishment of infections in the population. Secondly, the MDA must produce effective cure rates of >95% to have a non-negligible probability of successful elimination. Stochastic fluctuations only significantly affect the probability of extinction in populations of about 1000 individuals or less. The expected time to extinction via stochastic fluctuation is less than 10 years only in populations less than about 150 individuals. Clustering of secondary infections and of MDA distribution both contribute positively to the potential probability of success, indicating that MDA would most effectively be administered at the household level. CONCLUSIONS: There are very limited circumstances in which MDA will lead to local malaria elimination with a substantial probability.

Role of mass drug administration in elimination of Plasmodium falciparum malaria: a consensus modelling study.

BACKGROUND: Mass drug administration for elimination of Plasmodium falciparum malaria is recommended by WHO in some settings. We used consensus modelling to understand how to optimise the effects of mass drug administration in areas with low malaria transmission. METHODS: We collaborated with researchers doing field trials to establish a standard intervention scenario and standard transmission setting, and we input these parameters into four previously published models. We then varied the number of rounds of mass drug administration, coverage, duration, timing, importation of infection, and pre-administration transmission levels. The outcome of interest was the percentage reduction in annual mean prevalence of P falciparum parasite rate as measured by PCR in the third year after the final round of mass drug administration. FINDINGS: The models predicted differing magnitude of the effects of mass drug administration, but consensus answers were reached for several factors. Mass drug administration was predicted to reduce transmission over a longer timescale than accounted for by the prophylactic effect alone. Percentage reduction in transmission was predicted to be higher and last longer at lower baseline transmission levels. Reduction in transmission resulting from mass drug administration was predicted to be temporary, and in the absence of scale-up of other interventions, such as vector control, transmission would return to pre-administration levels. The proportion of the population treated in a year was a key determinant of simulated effectiveness, irrespective of whether people are treated through high coverage in a single round or new individuals are reached by implementation of several rounds. Mass drug administration was predicted to be more effective if continued over 2 years rather than 1 year, and if done at the time of year when transmission is lowest. INTERPRETATION: Mass drug administration has the potential to reduce transmission for a limited time, but is not an effective replacement for existing vector control. Unless elimination is achieved, mass drug administration has to be repeated regularly for sustained effect. FUNDING: Bill & Melinda Gates Foundation.

Public health impact and cost-effectiveness of the RTS,S/AS01 malaria vaccine: a systematic comparison of predictions from four mathematical models.

BACKGROUND: The phase 3 trial of the RTS,S/AS01 malaria vaccine candidate showed modest efficacy of the vaccine against Plasmodium falciparum malaria, but was not powered to assess mortality endpoints. Impact projections and cost-effectiveness estimates for longer timeframes than the trial follow-up and across a range of settings are needed to inform policy recommendations. We aimed to assess the public health impact and cost-effectiveness of routine use of the RTS,S/AS01 vaccine in African settings. METHODS: We compared four malaria transmission models and their predictions to assess vaccine cost-effectiveness and impact. We used trial data for follow-up of 32 months or longer to parameterise vaccine protection in the group aged 5-17 months. Estimates of cases, deaths, and disability-adjusted life-years (DALYs) averted were calculated over a 15 year time horizon for a range of levels of Plasmodium falciparum parasite prevalence in 2-10 year olds (PfPR2-10; range 3-65%). We considered two vaccine schedules: three doses at ages 6, 7·5, and 9 months (three-dose schedule, 90% coverage) and including a fourth dose at age 27 months (four-dose schedule, 72% coverage). We estimated cost-effectiveness in the presence of existing malaria interventions for vaccine prices of US$2-10 per dose. FINDINGS: In regions with a PfPR2-10 of 10-65%, RTS,S/AS01 is predicted to avert a median of 93,940 (range 20,490-126,540) clinical cases and 394 (127-708) deaths for the three-dose schedule, or 116,480 (31,450-160,410) clinical cases and 484 (189-859) deaths for the four-dose schedule, per 100,000 fully vaccinated children. A positive impact is also predicted at a PfPR2-10 of 5-10%, but there is little impact at a prevalence of lower than 3%. At $5 per dose and a PfPR2-10 of 10-65%, we estimated a median incremental cost-effectiveness ratio compared with current interventions of $30 (range 18-211) per clinical case averted and $80 (44-279) per DALY averted for the three-dose schedule, and of $25 (16-222) and $87 (48-244), respectively, for the four-dose schedule. Higher ICERs were estimated at low PfPR2-10 levels. INTERPRETATION: We predict a significant public health impact and high cost-effectiveness of the RTS,S/AS01 vaccine across a wide range of settings. Decisions about implementation will need to consider levels of malaria burden, the cost-effectiveness and coverage of other malaria interventions, health priorities, financing, and the capacity of the health system to deliver the vaccine. FUNDING: PATH Malaria Vaccine Initiative; Bill & Melinda Gates Foundation; Global Good Fund; Medical Research Council; UK Department for International Development; GAVI, the Vaccine Alliance; WHO.

The time-course of protection of the RTS,S vaccine against malaria infections and clinical disease.

BACKGROUND: Recent publications have reported follow-up of the RTS,S/AS01 malaria vaccine candidate Phase III trials at 11 African sites for 32 months (or longer). This includes site- and time-specific estimates of incidence and efficacy against clinical disease with four different vaccination schedules. These data allow estimation of the time-course of protection against infection associated with two different ages of vaccination, both with and without a booster dose. METHODS: Using an ensemble of individual-based stochastic models, each trial cohort in the Phase III trial was simulated assuming many different hypothetical profiles for the vaccine efficacy against infection in time, for both the primary course and boosting dose and including the potential for either exponential or non-exponential decay. The underlying profile of protection was determined by Bayesian fitting of these model predictions to the site- and time-specific incidence of clinical malaria over 32 months (or longer) of follow-up. Using the same stochastic models, projections of clinical efficacy in each of the sites were modelled and compared to available observed trial data. RESULTS: The initial protection of RTS,S immediately following three doses is estimated as providing an efficacy against infection of 65 % (when immunizing infants aged 6-12 weeks old) and 91 % (immunizing children aged 5-17 months old at first vaccination). This protection decays relatively rapidly, with an approximately exponential decay for the 6-12 weeks old cohort (with a half-life of 7.2 months); for the 5-17 months old cohort a biphasic decay with a similar half-life is predicted, with an initial rapid decay followed by a slower decay. The boosting dose was estimated to return protection to an efficacy against infection of 50-55 % for both cohorts. Estimates of clinical efficacy by trial site are consistent with those reported in the trial for all cohorts. CONCLUSIONS: The site- and time-specific clinical observations from the RTS,S/AS01 trial data allowed a reasonably precise estimation of the underlying vaccine protection against infection which is consistent with common underlying efficacy and decay rates across the trial sites. This calibration suggests that the decay in efficacy against clinical disease is more rapid than that against infection because of age-shifts in the incidence of disease. The dynamical models predict that clinical effectiveness will continue to decay and that likely effects beyond the time-scale of the trial will be small.

Distribution of malaria exposure in endemic countries in Africa considering country levels of effective treatment.

BACKGROUND: Malaria prevalence, clinical incidence, treatment, and transmission rates are dynamically interrelated. Prevalence is often considered a measure of malaria transmission, but treatment of clinical malaria reduces prevalence, and consequently also infectiousness to the mosquito vector and onward transmission. The impact of the frequency of treatment on prevalence in a population is generally not considered. This can lead to potential underestimation of malaria exposure in settings with good health systems. Furthermore, these dynamical relationships between prevalence, treatment, and transmission have not generally been taken into account in estimates of burden. METHODS: Using prevalence as an input, estimates of disease incidence and transmission [as the distribution of the entomological inoculation rate (EIR)] for Plasmodium falciparum have now been made for 43 countries in Africa using both empirical relationships (that do not allow for treatment) and OpenMalaria dynamic micro-simulation models (that explicitly include the effects of treatment). For each estimate, prevalence inputs were taken from geo-statistical models fitted for the year 2010 by the Malaria Atlas Project to all available observed prevalence data. National level estimates of the effectiveness of case management in treating clinical attacks were used as inputs to the estimation of both EIR and disease incidence by the dynamic models. RESULTS AND CONCLUSIONS: When coverage of effective treatment is taken into account, higher country level estimates of average EIR and thus higher disease burden, are obtained for a given prevalence level, especially where access to treatment is high, and prevalence relatively low. These methods provide a unified framework for comparison of both the immediate and longer-term impacts of case management and of preventive interventions.

ARMADA: Using motif activity dynamics to infer gene regulatory networks from gene expression data.

Analysis of gene expression data remains one of the most promising avenues toward reconstructing genome-wide gene regulatory networks. However, the large dimensionality of the problem prohibits the fitting of explicit dynamical models of gene regulatory networks, whereas machine learning methods for dimensionality reduction such as clustering or principal component analysis typically fail to provide mechanistic interpretations of the reduced descriptions. To address this, we recently developed a general methodology called motif activity response analysis (MARA) that, by modeling gene expression patterns in terms of the activities of concrete regulators, accomplishes dramatic dimensionality reduction while retaining mechanistic biological interpretations of its predictions (Balwierz, 2014). Here we extend MARA by presenting ARMADA, which models the activity dynamics of regulators across a time course, and infers the causal interactions between the regulators that drive the dynamics of their activities across time. We have implemented ARMADA as part of our ISMARA webserver, ismara.unibas.ch, allowing any researcher to automatically apply it to any gene expression time course. To illustrate the method, we apply ARMADA to a time course of human umbilical vein endothelial cells treated with TNF. Remarkably, ARMADA is able to reproduce the complex observed motif activity dynamics using a relatively small set of interactions between the key regulators in this system. In addition, we show that ARMADA successfully infers many of the key regulatory interactions known to drive this inflammatory response and discuss several novel interactions that ARMADA predicts. In combination with ISMARA, ARMADA provides a powerful approach to generating plausible hypotheses for the key interactions between regulators that control gene expression in any system for which time course measurements are available.

Age-shifting in malaria incidence as a result of induced immunological deficit: a simulation study.

Effective population-level interventions against Plasmodium falciparum malaria lead to age-shifts, delayed morbidity or rebounds in morbidity and mortality whenever they are deployed in ways that do not permanently interrupt transmission. When long-term intervention programmes target specific age-groups of human hosts, the age-specific morbidity rates ultimately adjust to new steady-states, but it is very difficult to study these rates and the temporal dynamics leading up to them empirically because the changes occur over very long time periods. This study investigates the age and magnitude of age- and time- shifting of incidence induced by either pre-erythrocytic vaccination (PEV) programmes or seasonal malaria chemo-prevention (SMC), using an ensemble of individual-based stochastic simulation models of P. falciparum dynamics. The models made various assumptions about immunity decay, transmission heterogeneity and were parameterized with data on both age-specific infection and disease incidence at different levels of exposure, on the durations of different stages of the parasite life-cycle and on human demography. Effects of transmission intensity, and of levels of access to malaria treatment were considered. While both PEV and SMC programmes are predicted to have overall strongly positive health effects, a shift of morbidity into older children is predicted to be induced by either programme if transmission levels remain static and not reduced by other interventions. Predicted shifting of burden continue into the second decade of the programme. Even if long-term surveillance is maintained it will be difficult to avoid mis-attribution of such long-term changes in age-specific morbidity patterns to other factors. Conversely, short-lived transient changes in incidence measured soon after introduction of a new intervention may give over-positive views of future impacts. Complementary intervention strategies could be designed to specifically protect those age-groups at risk from burden shift.

Perfect quantum routing in regular spin networks.

Motivated by the need for quantum computers to communicate between multiple, well separated qubits, we introduce the task of quantum routing for distributing quantum states, and generating entanglement, between these sites. We describe regular families of coupled quantum networks which perfectly route qubits between arbitrary pairs of nodes with a high transmission rate. The ability to route multiple states simultaneously and the regularity of the networks vastly improve the utility of this scheme in comparison to the task of state transfer, leading us to propose an implementation in optical lattices.