Cost-effective Screening and Treatment of Hepatitis C

In just five years, hepatitis C has changed from a difficult-to-treat chronic condition to one that is readily cured by a short course of medication. Medical breakthroughs have now created the possibility of eliminating the transmission of HCV, but also bring a new challenge for the health system—how to identify individuals carrying the hepatitis C virus (HCV), and how to pay for life-saving treatments. This Issue Brief reviews recent evidence on the cost-effectiveness of screening and treatment strategies, and makes the case for universal, one-time HCV screening for all US adults

Abatacept Pharmacokinetics and Exposure Response in Patients Hospitalized With COVID-19: A Secondary Analysis of the ACTIV-1 IM Randomized Clinical Trial

IMPORTANCE: The pharmacokinetics of abatacept and the association between abatacept exposure and outcomes in patients with severe COVID-19 are unknown. OBJECTIVE: To characterize abatacept pharmacokinetics, relate drug exposure with clinical outcomes, and evaluate the need for dosage adjustments. DESIGN, SETTING, AND PARTICIPANTS: This study is a secondary analysis of data from the ACTIV-1 (Accelerating COVID-19 Therapeutic Interventions and Vaccines) Immune Modulator (IM) randomized clinical trial conducted between October 16, 2020, and December 31, 2021. The trial included hospitalized adults who received abatacept in addition to standard of care for treatment of COVID-19 pneumonia. Data analysis was performed between September 2022 and February 2024. EXPOSURE: Single intravenous infusion of abatacept (10 mg/kg with a maximum dose of 1000 mg). MAIN OUTCOMES AND MEASURES: Mortality at day 28 was the primary outcome of interest, and time to recovery at day 28 was the secondary outcome. Drug exposure was assessed using the projected area under the serum concentration time curve over 28 days (AUC0-28). Logistic regression modeling was used to analyze the association between drug exposure and 28-day mortality, adjusted for age, sex, and disease severity. The association between time to recovery and abatacept exposure was examined using Fine-Gray modeling with death as a competing risk, and was adjusted for age, sex, and disease severity. RESULTS: Of the 509 patients who received abatacept, 395 patients with 848 serum samples were included in the population pharmacokinetic analysis. Their median age was 55 (range, 19-89) years and most (250 [63.3%]) were men. Abatacept clearance increased with body weight and more severe disease activity at baseline. Drug exposure was higher in patients who survived vs those who died, with a median AUC0-28 of 21 428 (range, 8462-43 378) mg × h/L vs 18 262 (range, 9628-27 507) mg × h/L (P \u3c .001). Controlling for age, sex, and disease severity, an increase of 5000 units in AUC0-28 was associated with lower odds of mortality at day 28 (OR, 0.52 [95% CI, 0.35-0.79]; P = .002). For an AUC0-28 of 19 400 mg × h/L or less, there was a higher probability of recovery at day 28 (hazard ratio, 2.63 [95% CI, 1.70-4.08] for every 5000-unit increase; P \u3c .001). Controlling for age, sex, and disease severity, every 5000-unit increase in AUC0-28 was also associated with lower odds of a composite safety event at 28 days (OR, 0.46 [95% CI, 0.33-0.63]; P \u3c .001). Using the dosing regimen studied in the ACTIV-1 IM trial, 121 of the 395 patients (30.6%) would not achieve an abatacept exposure of at least 19 400 mg × h/L, particularly at the extremes of body weight. Using a modified, higher-dose regimen, only 12 patients (3.0%) would not achieve the hypothesized target abatacept exposure. CONCLUSIONS AND RELEVANCE: In this study, patients who were hospitalized with severe COVID-19 and achieved higher projected abatacept exposure had reduced mortality and a higher probability of recovery with fewer safety events. However, abatacept clearance was high in this population, and the current abatacept dosing (10 mg/kg intravenously with a maximum of 1000 mg) may not achieve optimal exposure in all patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04593940

Estimated clinical outcomes and cost-effectiveness associated with provision of addiction treatment in US primary care clinics

IMPORTANCE: US primary care practitioners (PCPs) are the largest clinical workforce, but few provide addiction care. Primary care is a practical place to expand addiction services, including buprenorphine and harm reduction kits, yet the clinical outcomes and health care sector costs are unknown. OBJECTIVE: To estimate the long-term clinical outcomes, costs, and cost-effectiveness of integrated buprenorphine and harm reduction kits in primary care for people who inject opioids. DESIGN, SETTING, AND PARTICIPANTS: In this modeling study, the Reducing Infections Related to Drug Use Cost-Effectiveness (REDUCE) microsimulation model, which tracks serious injection-related infections, overdose, hospitalization, and death, was used to examine the following treatment strategies: (1) PCP services with external referral to addiction care (status quo), (2) PCP services plus onsite buprenorphine prescribing with referral to offsite harm reduction kits (BUP), and (3) PCP services plus onsite buprenorphine prescribing and harm reduction kits (BUP plus HR). Model inputs were derived from clinical trials and observational cohorts, and costs were discounted annually at 3%. The cost-effectiveness was evaluated over a lifetime from the modified health care sector perspective, and sensitivity analyses were performed to address uncertainty. Model simulation began January 1, 2021, and ran for the entire lifetime of the cohort. MAIN OUTCOMES AND MEASURES: Life-years (LYs), hospitalizations, mortality from sequelae (overdose, severe skin and soft tissue infections, and endocarditis), costs, and incremental cost-effectiveness ratios (ICERs). RESULTS: The simulated cohort included 2.25 million people and reflected the age and gender of US persons who inject opioids. Status quo resulted in 6.56 discounted LYs at a discounted cost of $203 500 per person (95$203 000-$222 000). Each strategy extended discounted life expectancy: BUP by 0.16 years and BUP plus HR by 0.17 years. Compared with status quo, BUP plus HR reduced sequelae-related mortality by 33$34 400 per LY). During a 5-year time horizon, BUP plus HR cost an individual PCP practice approximately $13 000. CONCLUSIONS AND RELEVANCE: This modeling study of integrated addiction service in primary care found improved clinical outcomes and modestly increased costs. The integration of addiction service into primary care practices should be a health care system priority

The Hepatitis C Cascade of Care: Identifying Priorities to Improve Clinical Outcomes

Background: As highly effective hepatitis C virus (HCV) therapies emerge, data are needed to inform the development of interventions to improve HCV treatment rates. We used simulation modeling to estimate the impact of loss to follow-up on HCV treatment outcomes and to identify intervention strategies likely to provide good value for the resources invested in them. Methods: We used a Monte Carlo state-transition model to simulate a hypothetical cohort of chronically HCV-infected individuals recently screened positive for serum HCV antibody. We simulated four hypothetical intervention strategies (linkage to care; treatment initiation; integrated case management; peer navigator) to improve HCV treatment rates, varying efficacies and costs, and identified strategies that would most likely result in the best value for the resources required for implementation. Main measures Sustained virologic responses (SVRs), life expectancy, quality-adjusted life expectancy (QALE), costs from health system and program implementation perspectives, and incremental cost-effectiveness ratios (ICERs). Results: We estimate that imperfect follow-up reduces the real-world effectiveness of HCV therapies by approximately 75%. In the base case, a modestly effective hypothetical peer navigator program maximized the number of SVRs and QALE, with an ICER compared to the next best intervention of $48,700/quality-adjusted life year. Hypothetical interventions that simultaneously addressed multiple points along the cascade provided better outcomes and more value for money than less costly interventions targeting single steps. The 5-year program cost of the hypothetical peer navigator intervention was$14.5 million per 10,000 newly diagnosed individuals. Conclusions: We estimate that imperfect follow-up during the HCV cascade of care greatly reduces the real-world effectiveness of HCV therapy. Our mathematical model shows that modestly effective interventions to improve follow-up would likely be cost-effective. Priority should be given to developing and evaluating interventions addressing multiple points along the cascade rather than options focusing solely on single points

Simulated cost-effectiveness and long-term clinical outcomes of addiction care and antibiotic therapy strategies for patients with injection drug use-associated infective endocarditis

Importance: Emerging evidence supports the use of outpatient parenteral antimicrobial therapy (OPAT) and, in many cases, partial oral antibiotic therapy for the treatment of injection drug use-associated infective endocarditis (IDU-IE); however, long-term outcomes and cost-effectiveness remain unknown. Objective: To compare the added value of inpatient addiction care services and the cost-effectiveness and clinical outcomes of alternative antibiotic treatment strategies for patients with IDU-IE. Design, Setting, and Participants: This decision analytical modeling study used a validated microsimulation model to compare antibiotic treatment strategies for patients with IDU-IE. Model inputs were derived from clinical trials and observational cohort studies. The model included all patients with injection opioid drug use (N = 5 million) in the US who were eligible to receive OPAT either in the home or at a postacute care facility. Costs were annually discounted at 3%. Cost-effectiveness was evaluated from a health care sector perspective over a lifetime starting in 2020. Probabilistic sensitivity, scenario, and threshold analyses were performed to address uncertainty. Interventions: The model simulated 4 treatment strategies: (1) 4 to 6 weeks of inpatient intravenous (IV) antibiotic therapy along with opioid detoxification (usual care strategy), (2) 4 to 6 weeks of inpatient IV antibiotic therapy along with inpatient addiction care services that offered medication for opioid use disorder (usual care/addiction care strategy), (3) 3 weeks of inpatient IV antibiotic therapy along with addiction care services followed by OPAT (OPAT strategy), and (4) 3 weeks of inpatient IV antibiotic therapy along with addiction care services followed by partial oral antibiotic therapy (partial oral antibiotic strategy). Main Outcomes and Measures: Mean percentage of patients completing treatment for IDU-IE, deaths associated with IDU-IE, life expectancy (measured in life-years [LYs]), mean cost per person, and incremental cost-effectiveness ratios (ICERs). Results: All modeled scenarios were initialized with 5 million individuals (mean age, 42 years; range, 18-64 years; 70% male) who had a history of injection opioid drug use. The usual care strategy resulted in 18.63 LYs at a cost of $416 570 per person, with 77.6$412 150 per person. Compared with the OPAT strategy, the partial oral antibiotic strategy had an ICER of $163 370 per LY. Increasing IDU-IE treatment uptake and decreasing treatment discontinuation made the partial oral antibiotic strategy more cost-effective compared with the OPAT strategy. When assuming that all patients with IDU-IE were eligible to receive partial oral antibiotic therapy, the strategy was cost-saving and resulted in 0.0247 additional discounted LYs. When treatment discontinuation was decreased from 3.30$100 000 per LY threshold. Conclusions and Relevance: In this decision analytical modeling study, incorporation of OPAT or partial oral antibiotic approaches along with addiction care services for the treatment of patients with IDU-IE was associated with increases in the number of people completing treatment, decreases in mortality, and savings in cost compared with the usual care strategy of providing inpatient IV antibiotic therapy alone

“Community members have more impact on their neighbors than celebrities”: Leveraging community partnerships to build COVID-19 vaccine confidence

Vaccines are a strong public health tool to protect against severe disease, hospitalization, and death from COVID-19. Still, inequities in COVID-19 vaccination rates and health outcomes continue to exist among Black and Latino populations. Boston Medical Center (BMC) has played a significant role in vaccinating medically underserved populations, and organized a series of community-engaged conversations to better understand community concerns regarding the COVID-19 vaccine. We accessed and analyzed nine publicly available recordings of the community-engaged conversations which were held between Mar 2021-Sep 2021 (n=8-122 attendees). We employed a Consolidated Framework for Implementation Research-driven codebook to code our data and utilized a modified version of qualitative rapid analysis methods. Five main themes emerged: (1) Structural factors are important barriers to COVID-19 vaccination; (2) Mistrust exists due to the negative impact of systemic oppression and perceived motivation of the government; (3) There is a desire to learn more about biological and clinical characteristics of the COVID-19 vaccine as well as the practical implications of being vaccinated; (4) Community engagement is important for delivering COVID-19 information and education and; (5) Community leaders believe that the COVID-19 vaccine is a solution to address the pandemic. In highlighting the themes which resulted from these community-engaged conversations, this study illustrates a need for community-engaged COVID-19 vaccine messaging which reflects the nuances of the COVID-19 vaccine and pandemic without oversimplifying information and underscores important considerations for public health and healthcare leadership in the development of initiatives which work to advance health equity

Cost Effectiveness and Cost Containment in the Era of Interferon-Free Therapies to Treat Hepatitis C Virus Genotype 1

Abstract Background. Interferon-free regimens to treat hepatitis C virus (HCV) genotype 1 are effective but costly. At this time, payers in the United States use strategies to control costs including (1) limiting treatment to those with advanced disease and (2) negotiating price discounts in exchange for exclusivity. Methods. We used Monte Carlo simulation to investigate budgetary impact and cost effectiveness of these treatment policies and to identify strategies that balance access with cost control. Outcomes included nondiscounted 5-year payer cost per 10000 HCV-infected patients and incremental cost-effectiveness ratios. Results. We found that the budgetary impact of HCV treatment is high, with 5-year undiscounted costs of $1.0 billion to 2.3 billion per 10000 HCV-infected patients depending on regimen choices. Among noncirrhotic patients, using the least costly interferon-free regimen leads to the lowest payer costs with negligible difference in clinical outcomes, even when the lower cost regimen is less convenient and/or effective. Among cirrhotic patients, more effective but costly regimens remain cost effective. Controlling costs by restricting treatment to those with fibrosis stage 2 or greater disease was cost ineffective for any patient type compared with treating all patients. Conclusions. Treatment strategies using interferon-free therapies to treat all HCV-infected persons are cost effective, but short-term cost is high. Among noncirrhotic patients, using the least costly interferon-free regimen, even if it is not single tablet or once daily, is the cost-control strategy that results in best outcomes. Restricting treatment to patients with more advanced disease often results in worse outcomes than treating all patients, and it is not preferred

Current Practices of Screening for Incident Hepatitis C Virus (HCV) Infection Among HIV-Infected, HCV-Uninfected Individuals in Primary Care

Background. Human immunodeficiency virus (HIV)-infected, hepatitis C virus (HCV)-uninfected patients are at risk for incident HCV infection, but little is known about screening practices for incident HCV among HIV-infected individuals in HIV primary care clinics

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages