Long-term health and economic benefits of switching to tenofovir alafenamide versus continuing on entecavir in chronic hepatitis B patients with low-level viremia in Saudi Arabia.

BACKGROUND: Despite the success of current treatments, many chronic hepatitis B (CHB) patients still live with low-level viremia [LLV] resulting in liver disease progression. This study evaluated the long-term health and economic impact of switching to tenofovir alafenamide (TAF) from entecavir (ETV) in Saudi Arabia (SA) in chronic hepatitis B (CHB) LLV patients. METHODS: A hybrid decision tree Markov state-transition model was developed to simulate a cohort of patients with CHB LLV treated with ETV and switched to TAF over a lifetime horizon in SA. While on treatment, patients either achieved complete virologic response (CVR) or maintained LLV. CVR patients experienced slower progression to advanced liver disease stages as compared to LLV patients. Demographic data, transition probabilities, treatment efficacy, health state costs, and utilities were sourced from published literature. Treatment costs were sourced from publicly available databases. RESULTS: Base case analysis found that over a lifetime horizon, switching to TAF versus remaining on ETV increased the proportion of patients achieving CVR (76% versus 14%, respectively). Switching to TAF versus remaining on ETV resulted in a reduction in cases of compensated cirrhosis (-52%), decompensated cirrhosis (-5%), hepatocellular carcinoma (-22%), liver transplants (-12%), and a 37% reduction in liver-related deaths. Switching to TAF was cost-effective with an incremental cost-effectiveness ratio of $57,222, assuming a willingness-to-pay threshold of three times gross national income per capita [$65,790/QALY]. CONCLUSIONS: This model found that switching to TAF versus remaining on ETV in SA CHB LLV patients substantially reduced long-term CHB-related morbidity and mortality and was a cost-effective treatment strategy.

Real-world value of direct-acting antivirals for hepatitis C at Kaiser Permanente Southern California.

OBJECTIVES: Direct-acting antivirals (DAAs) for chronic hepatitis C virus (HCV) lead to cure in more than 95% of recipients; however, payers may limit access to these lifesaving drugs due to high initial cost. Here, the cost-effectiveness of treating HCV with DAAs vs no treatment over a lifetime horizon is evaluated from the perspective of Kaiser Permanente Southern California (KPSC). STUDY DESIGN: A hybrid decision-tree Markov model. METHODS: The model simulated the health and economic outcomes for a real cohort of patients with HCV treated with either ledipasvir-sofosbuvir or sofosbuvir-velpatasvir between November 1, 2014, and October 31, 2019, at KPSC. Patients entered the model at different stages of liver disease and received either active treatment with DAAs or no treatment. Patients who did not achieve sustained virological response experienced disease progression; those who achieved sustained virological response experienced either significantly slower or no disease progression depending on the stage of fibrosis at model start. Demographics, treatment experience, genotype, baseline fibrosis stage, treatment rates, and treatment efficacy were sourced from KPSC real-world data. Costs and utilities were sourced from published literature. RESULTS: A total of 7255 patients with a mean age of 59 years were treated during the study period. Over a lifetime horizon, DAAs resulted in significant reduction in advanced liver disease events and a total cost savings of $1 billion compared with no treatment based on a hybrid decision-tree Markov state-transition model. Cost savings were achieved after only 3 years. DAA intervention dominated no treatment on a per-patient and cohort basis. CONCLUSIONS: DAA treatment at KPSC is predicted to significantly reduce HCV-related morbidity and mortality, providing an anticipated return on investment in drug costs after 3 years of treatment.

Cost-effectiveness analysis of HIV pre-exposure prophylaxis in Japan.

BACKGROUND: While global efforts have been made to prevent transmission of HIV, the epidemic persists. Men who have sex with men (MSM) are at high risk of infection. Despite evidence of its cost-effectiveness in other jurisdictions, pre-exposure prophylaxis (PrEP) for MSM is neither approved nor reimbursed in Japan. METHOD: The cost-effectiveness analysis compared the use of once daily PrEP versus no PrEP among MSM over a 30-year time horizon from a national healthcare perspective. Epidemiological estimates for each of the 47 prefectures informed the model. Costs included HIV/AIDS treatment, HIV and testing for sexually transmitted infections, monitoring tests and consults, and hospitalization costs. Analyses included health and cost outcomes, as well as the incremental cost-effectiveness ratio (ICER) reported as the cost per quality-adjusted life year (QALY) for all of Japan and each prefecture. Sensitivity analyses were performed. FINDINGS: The estimated proportion of HIV infections prevented with the use of PrEP ranged from 48% to 69% across Japan, over the time horizon. Cost savings due to lower monitoring costs and general medical costs were observed. Assuming 100% coverage, for Japan overall, daily use of PrEP costs less and was more effective; daily use of PrEP was cost-effective at a willingness to pay threshold of ¥5,000,000 per QALY in 32 of the 47 prefectures. Sensitivity analyses found that the ICER was most sensitive to the cost of PrEP. INTERPRETATION: Compared to no PrEP use, once daily PrEP is a cost-effective strategy in Japanese MSM, reducing the clinical and economic burden associated with HIV.

HIV remains an epidemic, and men who have sex with men (MSM) are at higher risk of infection. Pre-exposure prophylaxis (PrEP) is a preventive treatment that can reduce someone's risk of getting infected with HIV and has been shown to provide good value for money. PrEP, however, is neither approved nor reimbursed in Japan. In order to determine the value for money in Japan, an economic model was developed to estimate the number of HIV infections and AIDS cases that could be avoided, along with whether daily use of PrEP among MSM in Japan is cost effective. Findings showed that with use of daily PrEP, the proportion of HIV infections and AIDS cases prevented was 63% and 59%, respectively, across Japan. Over a 30-year time horizon, daily use of PrEP would cost the health system less and be more effective than no use of PrEP. Daily PrEP should therefore be considered for reimbursement in MSM in Japan, given its value for money.

Cost-effectiveness of direct-acting antivirals for chronic hepatitis C virus in the United States from a payer perspective.

BACKGROUND: Direct-acting antivirals (DAAs) have been a breakthrough therapeutic innovation in the treatment of chronic hepatitis C virus (HCV) with significantly improved efficacy, safety, and tolerability. OBJECTIVE: To evaluate the cost-effectiveness of treating patients with HCV with DAAs compared with pre-DAAs or no treatment over a lifetime horizon from the perspective of the US Veterans Affairs (VA) health care system. METHODS: A hybrid decision-tree and Markov model simulated the health outcomes of a cohort of 142,147 patients with HCV with an average age of 63 years. Demographic data, treatment rates and distribution, treatment efficacy by subpopulation, and health state costs were sourced from VA data. Treatment costs and utility values were sourced from publicly available databases and prior publications for older regimens. RESULTS: Over a lifetime horizon, the use of DAAs results in a significant reduction in advanced liver disease events compared with pre-DAA and no treatment. Total cost savings of $7 and $9 billion over a lifetime horizon (50 years) were predicted for patients who received DAA treatments compared with patients treated with pre-DAA treatments and those who were untreated, respectively. Cost savings were achieved quickly after treatment, with DAAs being inexpensive when compared with both the pre-DAA and untreated scenarios within 5 years. The DAA intervention dominated (ie, more effective and less costly) for both the pre-DAA and untreated strategies on both a per-patient and cohort basis. CONCLUSIONS: The use of DAA-based treatments in patients with HCV in the VA system significantly reduced long-term HCV-related morbidity and mortality, while providing cost savings within only 5 years of treatment. DISCLOSURES: This work was supported by Gilead Inc. Health Economic Outcomes Research group, grant number GS-US-18-HCV003. Drs Yehoshua and Kaushik are employees of Gilead in the Health Economic Outcome Research group. These individuals reviewed the manuscript but did not contribute to input or output of the Markov model. Maple Health Group (Dr El-Moustaid, Ms Raad, and Dr Smith) are consultants hired by Gilead for Markov modeling expertise. The model used in this study was previously published and peer reviewed. Data inputted into the model related to patient demographic, treatment outcomes, clinical outcomes, and costs were completely independent in derivation by Drs Kaplan, Serper, and Durkin and were not influenced by the funding sponsor. Dr Kaplan reports grants from Gilead Inc. during the conduct of the study and grants from Gilead Inc., other from Glycotest Inc., other from AstraZeneca, other from Exact Sciences, and other from Bayer outside the submitted work.

Network meta-analysis comparing the effectiveness of a prescription digital therapeutic for chronic insomnia to medications and face-to-face cognitive behavioral therapy in adults.

OBJECTIVE: The purpose of this study was to compare the effectiveness of the only Food and Drug Administration-authorized prescription digital therapeutic (PDT) Somryst versus face-to-face cognitive behavioral therapy for insomnia (CBT-I), or FDA-approved prescription medications for insomnia. METHODS: A systematic literature review was undertaken to identify relevant studies. A Bayesian network meta-analysis (NMA) was conducted to examine (1) mean change in insomnia severity index (ISI); (2) proportional change in ISI remitters; (3) mean change in wake after sleep onset (WASO); and (4) mean change in sleep onset latency (SOL). RESULTS: Twenty studies provided data on the PDT, CBT-I, CBT-I in combination with self-help (SH), or two prescription medications (eszopiclone and zolpidem). The PDT was associated with significant mean change in ISI (-5.77, 95% Credible Interval [CrI] - 8.53, -3.07) and ISI remitters (OR 12.33; 95% CrI 2.28, 155.91) compared to placebo, and had the highest probability of being the most effective treatment overall for ISI mean change (56%), and ISI remitters (64%). All evaluated interventions significantly outperformed placebo for WASO but no significant differences were observed for SOL (five interventions). Sensitivity analyses excluding medications and meta-regression (assessing type, duration, delivery method for CBT-I) did not affect NMA results. CONCLUSIONS: This network meta-analysis demonstrated that a PDT delivering CBT-I had the highest probability of being most effective compared to face-to-face CBT-I, prescription sleep medications, or placebo, as measured by reductions in mean ISI score from baseline and ISI-determined remittance.

Chronic insomnia is the long-term inability to fall asleep easily or to stay asleep. This condition is much more serious than most people realize, raising the risk of many health problems including depression, heart disease, and injuries.Although sleep medications are commonly used to treat insomnia, these drugs may not be effective and can lead to harms such as accidents or clouded thinking. Clinical guidelines recommend a treatment called cognitive behavioral therapy for insomnia (CBT-I) that is safe and effective. Unfortunately, there is a shortage of clinicians trained to provide CBT-I.Prescription digital therapeutics (PDTs) are FDA-approved software programs available on mobile devices such as smartphones. A PDT for insomnia (Somryst) delivers CBT-I and can overcome barriers to access for this important type of therapy. To compare the effectiveness of this PDT with FDA-approved sleep medications and face-to-face CBT-I a special kind of study was conducted called a network meta-analysis. This is a statistical method of combining data from numerous studies in a way that allows the results to be fairly compared.This network meta-analysis of 20 studies found that the PDT was more effective at reducing insomnia symptoms than any of the sleep medications studied and was even more effective than face-to-face CBT-I as measured by scores on a clinically valid scale of insomnia symptoms. These results are encouraging because they suggest that digital delivery of CBT-I could help the millions of people who currently do not have access to this effective treatment.

The Cost-Effectiveness of Axicabtagene Ciloleucel as Second-Line Therapy in Patients with Large B-Cell Lymphoma in the United States: An Economic Evaluation of the ZUMA-7 Trial.

Axicabtagene ciloleucel (axi-cel) was found to have superior clinical outcomes compared to standard of care (SOC; salvage chemoimmunotherapy, followed by high-dose therapy with autologous stem cell rescue for responders) for second-line large B-cell lymphoma (2L LBCL) in the pivotal ZUMA-7 trial. The aim of this analysis was to evaluate the cost effectiveness of using axi-cel compared to the current standard 2L LBCL therapy. A 3-state partitioned-survival model estimated the cost effectiveness and budget impact from a payer perspective in the United States. Clinical outcomes were extrapolated based on the pivotal trial. The model calculated expected quality-adjusted life years (QALYs), total costs (in United States dollars [USD], and the incremental cost-effectiveness ratio (ICER), along with the budget impact. Sensitivity and scenario analyses were performed. The proportion alive at 10 years was estimated as 48% for axi-cel and 38% for SOC; median overall survival was estimated at 59 and 24 months for axi-cel and SOC, respectively. Over a lifetime horizon, the model estimated a total of 5.56 and 7.08 QALYs for SOC and axi-cel, respectively, of which 41% and 74% were in the event-free state, respectively. Incremental QALYs and costs were 1.51 and $100,366 USD, resulting in an ICER of $66,381 USD per QALY for axi-cel versus SOC. Despite crossover to subsequent CAR T in the SOC arm, second-line CAR T use was found to improve the quality and length of life compared to SOC. Cost offsets due to subsequent CAR T use led to a limited incremental cost difference. Treatment with axi-cel is a cost-effective option that addresses an important unmet clinical need for patients with LBCL who relapse or are refractory to front-line therapy.

Both consumptive and non-consumptive effects of predators impact mosquito populations and have implications for disease transmission.

Predator-prey interactions influence prey traits through both consumptive and non-consumptive effects, and variation in these traits can shape vector-borne disease dynamics. Meta-analysis methods were employed to generate predation effect sizes by different categories of predators and mosquito prey. This analysis showed that multiple families of aquatic predators are effective in consumptively reducing mosquito survival, and that the survival of Aedes, Anopheles, and Culex mosquitoes is negatively impacted by consumptive effects of predators. Mosquito larval size was found to play a more important role in explaining the heterogeneity of consumptive effects from predators than mosquito genus. Mosquito survival and body size were reduced by non-consumptive effects of predators, but development time was not significantly impacted. In addition, Culex vectors demonstrated predator avoidance behavior during oviposition. The results of this meta-analysis suggest that predators limit disease transmission by reducing both vector survival and vector size, and that associations between drought and human West Nile virus cases could be driven by the vector behavior of predator avoidance during oviposition. These findings are likely to be useful to infectious disease modelers who rely on vector traits as predictors of transmission.

Mosquitoes are often referred to as the deadliest animals on earth because some species spread malaria, West Nile virus or other dangerous diseases when they bite humans and other animals. Adult mosquitoes fly to streams, ponds and other freshwater environments to lay their eggs. When the eggs hatch, the young mosquitoes live in the water until they are ready to grow wings and transform into adults. In the water, the young mosquitoes are particularly vulnerable to being eaten by dragonfly larvae, fish and other predators. When adult females are choosing where to lay their eggs, they can use their sense of smell to detect these predators and attempt to avoid them. Along with eating the mosquitoes, the predators may also reduce mosquito populations in other ways. For example, predators can disrupt feeding among young mosquitoes, which may affect the time that it takes for them to grow into adults or the size of their bodies once they reach the adult stage. Although the impacts of different predators have been tested separately in multiple settings, the overall effects of predators on the ability of mosquitoes to spread diseases to humans remain unclear. To address this question, Russell, Herzog et al. used an approach called meta-analysis on data from previous studies. The analysis found that along with increasing the death rates of mosquitoes, the presence of predators also leads to a reduction in the body size of those mosquitoes that survive, causing them to have shorter lifespans and fewer offspring. Russell, Herzog et al. found that one type of mosquito known as Culex ­ which carries West Nile virus ­ avoided laying its eggs near predators. During droughts, increased predation in streams, ponds and other aquatic environments may lead adult female Culex mosquitoes to lay their eggs closer to residential areas with fewer predators. Russell, Herzog et al. propose that this may be one reason why outbreaks of West Nile virus in humans are more likely to occur during droughts. In the future, these findings may help researchers to predict outbreaks of West Nile virus, malaria and other diseases carried by mosquitoes more accurately. Furthermore, the work of Russell, Herzog et al. provides examples of mosquito predators that could be used as biocontrol agents to decrease numbers of mosquitoes in certain regions.

Predicting temperature-dependent transmission suitability of bluetongue virus in livestock.

The transmission of vector-borne diseases is governed by complex factors including pathogen characteristics, vector-host interactions, and environmental conditions. Temperature is a major driver for many vector-borne diseases including Bluetongue viral (BTV) disease, a midge-borne febrile disease of ruminants, notably livestock, whose etiology ranges from mild or asymptomatic to rapidly fatal, thus threatening animal agriculture and the economy of affected countries. Using modeling tools, we seek to predict where the transmission can occur based on suitable temperatures for BTV. We fit thermal performance curves to temperature-sensitive midge life-history traits, using a Bayesian approach. We incorporate these curves into S(T), a transmission suitability metric derived from the disease's basic reproductive number, [Formula: see text] This suitability metric encompasses all components that are known to be temperature-dependent. We use trait responses for two species of key midge vectors, Culicoides sonorensis and Culicoides variipennis present in North America. Our results show that outbreaks of BTV are more likely between 15[Formula: see text] C and [Formula: see text], with predicted peak transmission risk at 26 [Formula: see text] C. The greatest uncertainty in S(T) is associated with the following: the uncertainty in mortality and fecundity of midges near optimal temperature for transmission; midges' probability of becoming infectious post-infection at the lower edge of the thermal range; and the biting rate together with vector competence at the higher edge of the thermal range. We compare three model formulations and show that incorporating thermal curves into all three leads to similar BTV risk predictions. To demonstrate the utility of this modeling approach, we created global suitability maps indicating the areas at high and long-term risk of BTV transmission, to assess risk and to anticipate potential locations of disease establishment.

Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23°C and 26°C.

The temperature-dependence of many important mosquito-borne diseases has never been quantified. These relationships are critical for understanding current distributions and predicting future shifts from climate change. We used trait-based models to characterize temperature-dependent transmission of 10 vector-pathogen pairs of mosquitoes (Culex pipiens, Cx. quinquefascsiatus, Cx. tarsalis, and others) and viruses (West Nile, Eastern and Western Equine Encephalitis, St. Louis Encephalitis, Sindbis, and Rift Valley Fever viruses), most with substantial transmission in temperate regions. Transmission is optimized at intermediate temperatures (23-26°C) and often has wider thermal breadths (due to cooler lower thermal limits) compared to pathogens with predominately tropical distributions (in previous studies). The incidence of human West Nile virus cases across US counties responded unimodally to average summer temperature and peaked at 24°C, matching model-predicted optima (24-25°C). Climate warming will likely shift transmission of these diseases, increasing it in cooler locations while decreasing it in warmer locations.

Modeling Temperature Effects on Population Density of the Dengue Mosquito Aedes aegypti.

Mosquito density plays an important role in the spread of mosquito-borne diseases such as dengue and Zika. While it remains very challenging to estimate the density of mosquitoes, modelers have tried different methods to represent it in mathematical models. The goal of this paper is to investigate the various ways mosquito density has been quantified, as well as to propose a dynamical system model that includes the details of mosquito life stages leading to the adult population. We first discuss the mosquito traits involved in determining mosquito density, focusing on those that are temperature dependent. We evaluate different forms of models for mosquito densities based on these traits and explore their dynamics as temperature varies. Finally, we compare the predictions of the models to observations of Aedes aegypti abundances over time in Vitòria, Brazil. Our results indicate that the four models exhibit qualitatively and quantitatively different behaviors when forced by temperature, but that all seem reasonably consistent with observed abundance data.

Linked within-host and between-host models and data for infectious diseases: a systematic review.

The observed dynamics of infectious diseases are driven by processes across multiple scales. Here we focus on two: within-host, that is, how an infection progresses inside a single individual (for instance viral and immune dynamics), and between-host, that is, how the infection is transmitted between multiple individuals of a host population. The dynamics of each of these may be influenced by the other, particularly across evolutionary time. Thus understanding each of these scales, and the links between them, is necessary for a holistic understanding of the spread of infectious diseases. One approach to combining these scales is through mathematical modeling. We conducted a systematic review of the published literature on multi-scale mathematical models of disease transmission (as defined by combining within-host and between-host scales) to determine the extent to which mathematical models are being used to understand across-scale transmission, and the extent to which these models are being confronted with data. Following the PRISMA guidelines for systematic reviews, we identified 24 of 197 qualifying papers across 30 years that include both linked models at the within and between host scales and that used data to parameterize/calibrate models. We find that the approach that incorporates both modeling with data is under-utilized, if increasing. This highlights the need for better communication and collaboration between modelers and empiricists to build well-calibrated models that both improve understanding and may be used for prediction.

Modeling bacterial attachment to surfaces as an early stage of biofilm development.

Biofilms are present in all natural, medical and industrial surroundings where bacteria live. Biofilm formation is a key factor in the growth and transport of both beneficial and harmful bacteria. While much is known about the later stages of biofilm formation, less is known about its initiation which is an important first step in the biofilm formation. In this paper, we develop a non-linear system of partial differential equations of Keller-Segel type model in one-dimensional space, which couples the dynamics of bacterial movement to that of the sensing molecules. In this case, bacteria perform a biased random walk towards the sensing molecules. We derive the boundary conditions of the adhesion of bacteria to a surface using zero-Dirichlet boundary conditions, while the equation describing sensing molecules at the interface needed particular conditions to be set. The numerical results show the profile of bacteria within the space and the time evolution of the density within the free-space and on the surface. Testing different parameter values indicate that significant amount of sensing molecules present on the surface leads to a faster bacterial movement toward the surface which is the first step of biofilm initiation. Our work gives rise to results that agree with the biological description of the early stages of biofilm formation.