Tirzepatide 10 and 15 mg vs semaglutide 2.0 mg: A long-term cost-effectiveness analysis in patients with type 2 diabetes in the United States.

BACKGROUND: Tirzepatide is a novel glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist approved for type 2 diabetes (T2D) treatment. OBJECTIVE: To compare the long-term cost-effectiveness of tirzepatide 10 mg and 15 mg vs semaglutide 2.0 mg, an injectable glucagon-like peptide-1 receptor agonist, in patients with T2D from a US health care payer perspective. METHODS: The PRIME T2D Model was used to project clinical and cost outcomes over a 50-year time horizon. Baseline cohort characteristics and treatment effects were sourced from a published adjusted indirect treatment comparison that used data from the SURPASS-2 and SUSTAIN FORTE trials. Patients were assumed to intensify to insulin therapy at a hemoglobin A1c of greater than 7.5%. Costs and health state utilities were derived from published sources. Future costs and clinical benefits were discounted at 3% annually. RESULTS: Tirzepatide 10 mg and 15 mg were associated with improved quality-adjusted life-expectancy (10 mg: 0.085 quality-adjusted life-years [QALYs], 15 mg: 0.121 QALYs), higher direct costs (10 mg: USD 5,990, 15 mg: USD 6,617), and incremental cost-effectiveness ratios of USD 70,147 and 54,699 per QALY gained, respectively, vs semaglutide 2.0 mg. Both doses of tirzepatide remained cost-effective vs semaglutide 2.0 mg over a range of sensitivity analyses. CONCLUSIONS: Long-term projections using the PRIME T2D model and based on treatment effects from an adjusted indirect treatment comparison indicate that tirzepatide 10 mg and 15 mg are likely to be cost-effective vs semaglutide 2.0 mg for the treatment of T2D in the United States.

Generalizability of clinical trial efficacy results to a real-world population: An example in migraine prevention.

BACKGROUND: Health care decision makers are often concerned about the external validity of randomized controlled trials (RCTs), as their results may not apply to certain patients in the real world who intend to receive treatment. OBJECTIVE: To demonstrate a methodology for assessing the generalizability of clinical trial results to a real-world population, before sufficient and appropriate real-world effectiveness data are available, using individual patient-level data from an RCT and aggregated baseline data from a real-world French registry in migraine. METHODS: The analyses were conducted in 2 steps. First, individual patient-level baseline data from the multinational CONQUER RCT were weighted to match aggregated real-world InovPain registry patient characteristic data. Matched patient characteristics were sex, age, migraine type and duration, number of monthly migraine headache days, and number of monthly headache days at baseline. Second, the weighted CONQUER patient data were used to reanalyze the primary endpoint of CONQUER (least squares mean change from baseline in the number of monthly migraine headache days during the 3-month double-blind treatment phase) using predefined methodology. Sensitivity analyses were conducted to assess the robustness of findings. RESULTS: A total of 462 patients with migraine were randomized and treated with galcanezumab or placebo in CONQUER; aggregated InovPain data were available from 130 patients with migraine. We identified no important differences in baseline patient characteristics between the 2 prespecified populations, suggesting good external validity for CONQUER. Although this limited the extent of observed differences between the original and matched CONQUER populations, weighting of CONQUER data did help harmonize the 2 datasets and allow the results obtained in CONQUER to be generalized to patients more representative of the real-world French population with migraine. Results of weighted analyses suggested that galcanezumab would be superior to placebo for reducing monthly migraine headache days in a clinical trial in patients with episodic or chronic migraine who reflected the characteristics of patients eligible to receive the drug in France. CONCLUSIONS: Findings suggest that our methods may be helpful for assessing the generalizability of clinical trial results to a real-world population before the availability of substantial real-world clinical data.

Testing the "RCT augmentation" methodology: A trial simulation study to guide the broadening of trials eligibility criteria and inform on effectiveness.

Background: Exclusion criteria that are treatment effect modifiers (TEM) decrease RCTs results generalisability and the potentials of effectiveness estimation. In "augmented RCTs", a small proportion of otherwise-excluded patients are included to allow for effectiveness estimation. In Hodgkin Lymphoma (HL) RCTs, older age and comorbidity are common exclusion criteria, while also TEM. We simulated HL RCTs augmented with age or comorbidity, and explored in each scenario the impact of augmentation on effectiveness estimation accuracy. Methods: Simulated data with a population of HL individuals initiating drug A or B was generated. There were drug-age and drug-comorbidity interactions in the simulated data, with a greater magnitude of the former compared to the latter. Multiple augmented RCTs were simulated by randomly selecting patients with increasing proportions of older, or comorbid patients. Treatment effect size was expressed using the between-group Restricted Mean Survival Time (RMST) difference at 3 years. For each augmentation proportion, a model estimating the "real-world" treatment effect (effectiveness) was fitted and the estimation error measured (Root Mean Square Error, RMSE). Results: In simulated RCTs including none (0%), or the real-world proportion (30%) of older patients, the interquartile range of RMST difference was 0.4-0.5 years and 0.2-0.3 years, respectively, and RMSE were 0.198 years (highest possible error) and 0.056 years (lowest), respectively. Augmenting RCTs with 5% older patients decreased estimation error substantially (RMSE = 0.076 years). Augmentation with comorbid patients proved less useful for effectiveness estimation. Conclusion: In augmented RCTs aiming to inform the effectiveness of drugs, augmentation should concern in priority those exclusion criteria of suspected important TEM magnitude, so as to minimie the proportion of augmentation necessary for good effectiveness estimations.

Sintilimab plus chemotherapy for first-line treatment of advanced or metastatic nonsquamous non-small-cell lung cancer: network meta-analysis.

Aim: This systematic literature review and network meta-analysis evaluated the efficacy and safety of sintilimab + pemetrexed + platinum versus US FDA-approved/National Comprehensive Cancer Network-recommended immune checkpoint inhibitor (ICI) combination therapies for untreated advanced/metastatic non-squamous non-small-cell lung cancer without EGFR/ALK aberrations. Methods: Bayesian network meta-analysis was the base-case analysis and included assessment of fixed and random effects, and independent and simultaneous models, adjusting for baseline risk (placebo response). Chemotherapy was the common comparator. Results: Sintilimab + pemetrexed + platinum was associated with significantly longer progression-free survival than atezolizumab + platinum + nab-paclitaxel (hazard ratio [HR]: 0.57; 95% credible interval [CrI]: 0.40-0.82) and nivolumab + ipilimumab + pemetrexed + platinum (HR: 0.66; 95% CrI: 0.48-0.92). Sintilimab + pemetrexed + platinum and pembrolizumab + pemetrexed + platinum showed comparable progression-free survival (HR: 0.96; 95% CrI: 0.71-1.30). There was no significant difference in overall survival (HR range: 0.61-0.81) or overall response rates (odds ratio [OR] range: 0.29-0.75) between sintilimab + pemetrexed + platinum and the other ICI combinations. The incidence of high-grade adverse events was higher with sintilimab + pemetrexed + platinum than with nivolumab + ipilimumab (OR: 0.46; 95% CrI: 0.33-0.64) or without chemotherapy (OR: 0.25; 95% CrI: 0.19-0.34), with no significant difference between sintilimab + pemetrexed + platinum and the other ICI combinations. Conclusion: Sintilimab + pemetrexed + platinum showed comparable efficacy and safety versus US standard-of-care first-line ICI combinations for advanced/metastatic non-squamous non-small-cell lung cancer.

Sintilimab is an immunotherapy drug that was successfully developed and tested in China to treat a kind of lung cancer that has spread, called advanced non-squamous non-small-cell lung cancer (NSCLC). The ORIENT-11 clinical study showed that adding sintilimab to two types of chemotherapy (pemetrexed and platinum) as the first treatment for people in China with advanced non-squamous NSCLC was safe and effective in reducing the risk of cancer spreading, growing or getting worse, compared with chemotherapy alone. Our study combined and analyzed the results from 11 clinical studies to look at how well sintilimab with chemotherapy may work compared with immunotherapy drugs approved in the USA. The results showed that sintilimab with chemotherapy is as effective and safe as immunotherapy drugs approved in the USA to treat people with advanced non-squamous NSCLC. These results may help doctors and payers when deciding how to treat people with this disease.

Long-term cost-effectiveness analysis of tirzepatide versus semaglutide 1.0 mg for the management of type 2 diabetes in the United States.

AIM: To evaluate the long-term cost-effectiveness of tirzepatide (5, 10 and 15 mg doses), a novel glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist, versus semaglutide 1.0 mg, an injectable glucagon-like peptide-1 receptor agonist, based on the results of the head-to-head SURPASS-2 trial, from a US healthcare payer perspective. MATERIALS AND METHODS: The PRIME Type 2 Diabetes Model was used to make projections of clinical and cost outcomes over a 50-year time horizon. Baseline cohort characteristics, treatment effects and adverse event rates were derived from the 40-week SURPASS-2 trial. Intensification to insulin therapy occurred when HbA1c reached 7.5%, in line with American Diabetes Association recommendations. Direct costs in 2021 US dollars (US$) and health state utilities were derived from published sources. Future costs and clinical benefits were discounted at 3% annually. RESULTS: All three doses of tirzepatide were associated with lower diabetes-related complication rates, improved life expectancy, improved quality-adjusted life expectancy and higher direct costs versus semaglutide. This resulted in incremental cost-effectiveness ratios of US$ 75 803, 58 908 and 48 785 per quality-adjusted life year gained for tirzepatide 5, 10 and 15 mg, respectively, versus semaglutide. Tirzepatide remained cost-effective versus semaglutide over a range of sensitivity analyses. CONCLUSIONS: Long-term projections based on the SURPASS-2 trial results indicate that 5, 10 and 15 mg doses of tirzepatide are likely to be cost-effective versus semaglutide 1.0 mg for the treatment of type 2 diabetes in the United States.

Cost-effectiveness models for Alzheimer's disease and related dementias: IPECAD modeling workshop cross-comparison challenge.

INTRODUCTION: The credibility of model-based economic evaluations of Alzheimer's disease (AD) interventions is central to appropriate decision-making in a policy context. We report on the International PharmacoEconomic Collaboration on Alzheimer's Disease (IPECAD) Modeling Workshop Challenge. METHODS: Two common benchmark scenarios, for the hypothetical treatment of AD mild cognitive impairment (MCI) and mild dementia, were developed jointly by 29 participants. Model outcomes were summarized, and cross-comparisons were discussed during a structured workshop. RESULTS: A broad concordance was established among participants. Mean 10-year restricted survival and time in MCI in the control group ranged across 10 MCI models from 6.7 to 9.5 years and 3.4 to 5.6 years, respectively; and across 4 mild dementia models from 5.4 to 7.9 years (survival) and 1.5 to 4.2 years (mild dementia). DISCUSSION: The model comparison increased our understanding of methods, data used, and disease progression. We established a collaboration framework to assess cost-effectiveness outcomes, an important step toward transparent and credible AD models.

Validating the Assumptions of Population Adjustment: Application of Multilevel Network Meta-regression to a Network of Treatments for Plaque Psoriasis.

BACKGROUND: Network meta-analysis (NMA) and indirect comparisons combine aggregate data (AgD) from multiple studies on treatments of interest but may give biased estimates if study populations differ. Population adjustment methods such as multilevel network meta-regression (ML-NMR) aim to reduce bias by adjusting for differences in study populations using individual patient data (IPD) from 1 or more studies under the conditional constancy assumption. A shared effect modifier assumption may also be necessary for identifiability. This article aims to demonstrate how the assumptions made by ML-NMR can be assessed in practice to obtain reliable treatment effect estimates in a target population. METHODS: We apply ML-NMR to a network of evidence on treatments for plaque psoriasis with a mix of IPD and AgD trials reporting ordered categorical outcomes. Relative treatment effects are estimated for each trial population and for 3 external target populations represented by a registry and 2 cohort studies. We examine residual heterogeneity and inconsistency and relax the shared effect modifier assumption for each covariate in turn. RESULTS: Estimated population-average treatment effects were similar across study populations, as differences in the distributions of effect modifiers were small. Better fit was achieved with ML-NMR than with NMA, and uncertainty was reduced by explaining within- and between-study variation. We found little evidence that the conditional constancy or shared effect modifier assumptions were invalid. CONCLUSIONS: ML-NMR extends the NMA framework and addresses issues with previous population adjustment approaches. It coherently synthesizes evidence from IPD and AgD studies in networks of any size while avoiding aggregation bias and noncollapsibility bias, allows for key assumptions to be assessed or relaxed, and can produce estimates relevant to a target population for decision-making. HIGHLIGHTS: Multilevel network meta-regression (ML-NMR) extends the network meta-analysis framework to synthesize evidence from networks of studies providing individual patient data or aggregate data while adjusting for differences in effect modifiers between studies (population adjustment). We apply ML-NMR to a network of treatments for plaque psoriasis with ordered categorical outcomes.We demonstrate for the first time how ML-NMR allows key assumptions to be assessed. We check for violations of conditional constancy of relative effects (such as unobserved effect modifiers) through residual heterogeneity and inconsistency and the shared effect modifier assumption by relaxing this for each covariate in turn.Crucially for decision making, population-adjusted treatment effects can be produced in any relevant target population. We produce population-average estimates for 3 external target populations, represented by the PsoBest registry and the PROSPECT and Chiricozzi 2019 cohort studies.

Assessing the Cost-effectiveness of a Hypothetical Disease-modifying Therapy With Limited Duration for the Treatment of Early Symptomatic Alzheimer Disease.

PURPOSE: Clinical trials have produced promising results for disease-modifying therapies (DMTs) for Alzheimer's disease (AD); however, the evidence on their potential cost-effectiveness is limited. This study assesses the cost-effectiveness of a hypothetical DMT with a limited treatment duration in AD. METHODS: We developed a Markov state-transition model to estimate the cost-effectiveness of a hypothetical DMT plus best supportive care (BSC) versus BSC alone among Americans living with mild cognitive impairment (MCI) due to AD or mild AD. AD states included MCI due to AD, mild AD, moderate AD, severe AD, and death. A hypothetical DMT was assumed to confer a 30% reduction in progression from MCI and mild AD. The base case annual drug acquisition cost was assumed to be $56,000. Other medical and indirect costs were obtained from published literature or list prices. Utilities for patients and caregivers were obtained from the published literature and varied by AD state and care setting (community care or long-term care). We considered 3 DMT treatment strategies: (1) treatment administered until patients reached severe AD (continuous strategy), (2) treatment administered for a maximum duration of 18 months or when patients reached severe AD (fixed-duration strategy), and (3) 40% of patients discontinuing treatment at 6 months because of amyloid plaque clearance and the remaining patients continuing treatment until 18 months or until they reached severe AD (test-and-discontinue strategy). Incremental cost-effectiveness ratios (ICERs) were calculated as the incremental cost per quality-adjusted life-year (QALY) gained. FINDINGS: From the health care sector perspective, continuous treatment with a hypothetical DMT versus BSC resulted in an ICER of $612,354 per QALY gained. The ICER decreased to $157,288 per QALY gained in the fixed-duration strategy, driven by large reductions in treatment costs. With 40% of patients discontinuing treatment at 6 months (test-and-discontinue strategy), the ICER was $125,631 per QALY gained. In sensitivity and scenario analyses, the ICER was the most sensitive to changes in treatment efficacy, treatment cost, and the initial population AD state distribution. From the modified societal perspective, ICERs were 6.3%, 20.4%, and 25.1% lower than those from the health care sector perspective for the continuous, fixed-duration, and test-and-discontinue strategies, respectively. IMPLICATIONS: Under a set of assumptions for annual treatment costs and the magnitude and duration of treatment efficacy, DMTs used for a limited duration may deliver value consistent with accepted US cost-effectiveness thresholds.

Health economic modeling for Alzheimer's disease: Expert perspectives.

The successful development of an economic model for the evaluation of future Alzheimer's disease (AD) interventions is critical to accurately inform policy makers and payers. As our understanding of AD expands, this becomes an increasingly complex and challenging goal. Advances in diagnostic techniques for AD and the prospect of disease-modifying treatments raise an urgent need to define specifications for future economic models and to ensure that the necessary data to populate them are available. This Perspective article provides expert opinions from health economists and governmental agency representatives on how future economic models for AD might be structured, validated, and reported. We aim to stimulate much-needed discussion about the detailed specification of future health economic models for AD.

Comparative Effectiveness of Dexamethasone in Hospitalized COVID-19 Patients in the United States.

INTRODUCTION: To compare the mortality of hospitalized patients with COVID-19 between those that required supplemental oxygen and received dexamethasone with a comparable set of patients who did not receive dexamethasone. METHODS: We utilized the Premier Health Database to identify hospitalized adult patients with COVID-19 from July 1, 2020-January 31, 2021. Index date was when patients first initiated oxygen therapy. The primary endpoint was in-hospital mortality for patients receiving dexamethasone versus those not receiving dexamethasone 1-day pre- to 1-day post-index period. Secondary endpoints included 28-day mortality, time to in-hospital mortality, progression to invasive mechanical ventilation or death, time to discharge, and proportion discharged alive by day 28. Twenty-three models using weighting, matching, stratification, and regression were deployed through the concept of frequentist model average (FMA) to estimate the effect of dexamethasone on all-cause mortality up to the 28-day hospitalization period. RESULTS: A total of 1,208,881 patients with COVID-19 were screened; as an inpatient 255,216 used oxygen, and 251,536 were included in the analysis. In the dexamethasone group, odds of in-hospital mortality were higher than those of the comparator (FMA: odds ratio [OR] 1.15, 95% CI 1.08, 1.22). Using a best fit model, OR for in-hospital mortality was non-significant for the dexamethasone group compared with the comparator (OR 1.02, 95% CI 0.92, 1.14). Dexamethasone treatment was associated with poorer outcomes versus the comparator group across the majority of secondary endpoints, except for number of days in hospital, which was lower in the dexamethasone group versus the comparator group (mean difference - 2.14, 95% CI - 2.43, - 1.47). CONCLUSIONS: Hospitalized adult patients with COVID-19 who required supplemental oxygen and received dexamethasone did not have a survival benefit versus similar patients not receiving dexamethasone. The dexamethasone group was not associated with favorable responses for outcomes such as progression to death or mechanical ventilation and time to in-hospital death.

Relative efficacy of lasmiditan versus rimegepant and ubrogepant as acute treatments for migraine: network meta-analysis findings.

BACKGROUND: In the absence of head-to-head trials, comprehensive evidence comparing onset of efficacy of novel agents for acute treatment of migraine is lacking. This study aimed to explore the relative efficacy of lasmiditan (serotonin [5-hydroxytryptamine] 1F receptor agonist) versus rimegepant and ubrogepant (calcitonin gene-related peptide antagonists) for the acute oral treatment of migraine through network meta-analysis (NMA). METHODS: Data included in the NMA were identified through a systematic literature search (conducted April 2018, updated May/December 2020) of phase II-IV, randomised controlled trials (RCTs) in adults with chronic/episodic migraine with/without aura. Treatments included: lasmiditan 50, 100, 200 mg; rimegepant 75 mg; ubrogepant 25, 50, 100 mg. Pairwise treatment comparisons from Bayesian fixed-effect/random-effects NMA, adjusted by baseline risk where appropriate, were conducted. Comparisons were reported as odds ratios with 95% credible intervals. Early-onset efficacy endpoints included: pain freedom at 2 hours and pain relief at 1 and 2 hours. Adverse drug reaction (ADR) profiles were summarised. Heterogeneity and inconsistency in the network were explored; sensitivity analyses investigated robustness of findings. RESULTS: Across 12 RCTs included in the base case, females represented >80% of included patients (mean age 37.9-45.7 years). Odds of achieving both pain freedom and pain relief at 2 hours were higher with lasmiditan 100 and 200 mg versus rimegepant 75 mg and ubrogepant 25 and 50 mg. Results for pain relief at 1 hour were consistent with those at 2 hours, but fewer comparisons were available. There were no statistically significant differences between lasmiditan 50 mg and ubrogepant or rimegepant for any outcome. Sensitivity analyses were in the same direction as base case analyses. Most commonly reported ADRs (incidence ≥2%) were: dizziness, fatigue, paraesthesia, sedation, nausea/vomiting and muscle weakness with lasmiditan; nausea with rimegepant; and nausea, somnolence and dry mouth with ubrogepant. CONCLUSIONS: The efficacy findings of this indirect comparison indicate that lasmiditan 100 mg or 200 mg might be an appropriate acute treatment option for patients with migraine seeking a fast onset of action. Differently from rimegepant and ubrogepant, lasmiditan use is associated with mainly neurological events, which are mostly mild or moderate in severity and self-limiting. 350/350 words.

Demonstration of Clinical Meaningfulness of the Integrated Alzheimer's Disease Rating Scale (iADRS): Association Between Change in iADRS Scores and Patient and Caregiver Health Outcomes.

BACKGROUND: The integrated Alzheimer's Disease Rating Scale (iADRS) is a validated cognitive/functional composite that effectively captures cognitive and functional decline over a broad spectrum of disease. The clinical meaningfulness of change on iADRS can be supported by establishing an association with changes on important health outcome measures. OBJECTIVE: To evaluate the relationship between change on the iADRS and changes in health outcomes in individuals with mild cognitive impairment (MCI) due to Alzheimer's disease (AD), or mild or moderate AD dementia using placebo data from four AD clinical trials and data from one AD observational study. METHODS: Analysis of covariate (ANCOVA) models were used to estimate the relationship between 18-month change on the iADRS and changes on health outcome measures (related to cost, quality of life, and caregiver burden). The regression coefficients for the iADRS were used to compute impact of natural disease progression and disease-modifying treatment on health outcomes. Additional ANCOVAs were conducted to understand whether cognition and/or function was the underlying explanation of any association between iADRS and health outcome change. RESULTS: Across datasets and disease stages, a worsening on the iADRS was significantly associated with increased societal costs, caregiver burden (time and distress) and worsening in measures of patient quality of life. CONCLUSION: Decline on the iADRS was associated with worsening in health outcome measures. These findings suggest that the iADRS can be used in clinical trials as a proxy measure of clinically meaningful outcomes of AD progression.

Complementary pre-screening strategies to uncover hidden prodromal and mild Alzheimer's disease: Results from the MOPEAD project.

INTRODUCTION: The Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project was conceived to explore innovative complementary strategies to uncover hidden prodromal and mild Alzheimer's disease (AD) dementia cases and to raise awareness both in the general public and among health professionals about the importance of early diagnosis. METHODS: Four different strategies or RUNs were used: (a) a web-based (WB) prescreening tool, (2) an open house initiative (OHI), (3) a primary care-based protocol for early detection of cognitive decline (PC), and (4) a tertiary care-based pre-screening at diabetologist clinics (DC). RESULTS: A total of 1129 patients at high risk of having prodromal AD or dementia were identified of 2847 pre-screened individuals (39.7%). The corresponding proportion for the different initiatives were 36.8% (WB), 35.6% (OHI), 44.4% (PC), and 58.3% (DC). CONCLUSION: These four complementary pre-screening strategies were useful for identifying individuals at high risk of having prodromal or mild AD.

Cost-Effectiveness of Combination of Baricitinib and Remdesivir in Hospitalized Patients with COVID-19 in the United States: A Modelling Study.

INTRODUCTION: Baricitinib-remdesivir (BARI-REM) combination is superior to remdesivir (REM) in reducing recovery time and accelerating clinical improvement among hospitalized patients with coronavirus disease 2019 (COVID-19), specifically those receiving high-flow oxygen/noninvasive ventilation. Here we assessed the cost-effectiveness of BARI-REM versus REM in hospitalized patients with COVID-19 in the USA. METHODS: A three-state model was developed addressing costs and patient utility associated with COVID-19 hospitalization, immediate post hospital care, and subsequent lifetime medical care. Analysis was performed from the perspective of a payer and a hospital. Both perspectives evaluated two subgroups: all patients and patients who required oxygen. The primary measures of benefit in the model were patient quality-adjusted life years (QALYs) accrued during and after hospitalization, cost per life years gained, cost per death avoided, and cost per use of mechanical ventilation avoided. RESULTS: In the base-case payer perspective with a lifetime horizon, treatment with BARI-REM versus REM resulted in an incremental total cost of $7962, a gain of 0.446 life years and gain of 0.3565 QALYs over REM. The incremental cost-effectiveness ratios of using BARI-REM were estimated as $22,334 per QALY and $17,858 per life year. The base-case and sensitivity analyses showed that the total incremental cost per QALY falls within the reduced willingness-to-pay threshold of $50,000/QALY applied under health emergencies. In all hospitalized patients, treatment with BARI-REM versus REM reduced total hospital expenditures per patient by $1778 and total reimbursement payments by $1526, resulting in a $252 reduction in net costs per patient; it also resulted in a net gain of 0.0018 QALYs and increased survival of COVID-19 hospitalizations by 2.7%. CONCLUSION: Our study showed that BARI-REM is cost-effective compared to using REM for hospitalized patients with COVID-19. The base-case results of this cost-effectiveness model were most sensitive to average annual medical costs for recovered patients.

Cost-Effectiveness of Baricitinib Compared With Standard of Care: A Modeling Study in Hospitalized Patients With COVID-19 in the United States.

PURPOSE: In the Phase III COV-BARRIER (Efficacy and Safety of Baricitinib for the Treatment of Hospitalised Adults With COVID-19) trial, treatment with baricitinib, an oral selective Janus kinase 1/2 inhibitor, in addition to standard of care (SOC), was associated with significantly reduced mortality over 28 days in hospitalized patients with coronavirus disease-2019 (COVID-19), with a safety profile similar to that of SOC alone. This study assessed the cost-effectiveness of baricitinib + SOC versus SOC alone (which included systemic corticosteroids and remdesivir) in hospitalized patients with COVID-19 in the United States. METHODS: An economic model was developed to simulate inpatients' stay, discharge to postacute care, and recovery. Costs modeled included payor costs, hospital costs, and indirect costs. Benefits modeled included life-years (LYs) gained, quality-adjusted life-years (QALYs) gained, deaths avoided, and use of mechanical ventilation avoided. The primary analysis was performed from a payor perspective over a lifetime horizon; a secondary analysis was performed from a hospital perspective. The base-case analysis modeled the numeric differences in treatment effectiveness observed in the COV-BARRIER trial. Scenario analyses were also performed in which the clinical benefit of baricitinib was limited to the statistically significant reduction in mortality demonstrated in the trial. FINDINGS: In the base-case payor perspective model, an incremental total cost of 17,276 US dollars (USD), total QALYs gained of 0.6703, and total LYs gained of 0.837 were found with baricitinib + SOC compared with SOC alone. With the addition of baricitinib, survival was increased by 5.1% and the use of mechanical ventilation was reduced by 1.6%. The base-case incremental cost-effectiveness ratios were 25,774 USD/QALY gained and 20,638 USD/LY gained; a "mortality-only" scenario analysis yielded similar results of 26,862 USD/QALY gained and 21,433 USD/LY gained. From the hospital perspective, combination treatment with baricitinib + SOC was more effective and less costly than was SOC alone in the base case, with an incremental cost of 38,964 USD per death avoided in the mortality-only scenario. IMPLICATIONS: In hospitalized patients with COVID-19 in the United States, the addition of baricitinib to SOC was cost-effective. Cost-effectiveness was demonstrated from both the payor and the hospital perspectives. These findings were robust to sensitivity analysis and to conservative assumptions limiting the clinical benefits of baricitinib to the statistically significant reduction in mortality demonstrated in the COV-BARRIER trial.

A Cost-Consequence Analysis of Different Screening Procedures in Alzheimer's Disease: Results from the MOPEAD Project.

BACKGROUND: For care planning and support, under-detection and late diagnosis of Alzheimer's disease (AD) is a great challenge. Models of Patient-Engagement for Alzheimer's Disease (MOPEAD) is an EU-funded project aiming at testing different strategies to improve this situation. OBJECTIVE: To make a cost-consequence analysis of MOPEAD. METHODS: Four screening strategies were tested in five countries (Germany, the Netherlands, Slovenia, Spain, and Sweden): 1) a web-approach; 2) Open-House initiative; 3) in primary care; and 4) by diabetes specialists. Persons-at-risk of AD in all strategies were offered referral to a hospital-based specialist. The primary health-economic outcome was the cost per true-positive case (TP) of AD from the screened population. RESULTS: Of 2,847 screened persons, 1,121 screened positive (39%), 402 were evaluated at memory clinics (14%), and 236 got an AD diagnosis (8%). The cost per TP of those screened was €3,115 with the web-approach, €2,722 with the Open-House, €1,530 in primary care, and €1,190 by diabetes specialists. Sensitivity analyses that more likely reflect the real-world situation confirmed the results. The number-needed-to-screen was 30 with the web-approach, 8 with the Open-House and primary care, and 6 with the diabetes specialists.There were country differences in terms of screening rates, referrals to memory clinics, staff-types involved, and costs per TP. CONCLUSION: In primary care and by the diabetes specialist, the costs per TP/screened population were lowest, but the capacity of such settings to identify cases with AD-risk must be discussed. Hence new diagnostic strategies such as web-solutions and Open-House initiatives may be valuable after modifications.

Obtaining EQ-5D-5L utilities from the disease specific quality of life Alzheimer's disease scale: development and results from a mapping study.

PURPOSE: The Quality of Life Alzheimer's Disease Scale (QoL-AD) is commonly used to assess disease specific health-related quality of life (HRQoL) as rated by patients and their carers. For cost-effectiveness analyses, utilities based on the EQ-5D are often required. We report a new mapping algorithm to obtain EQ-5D indices when only QoL-AD data are available. METHODS: Different statistical models to estimate utility directly, or responses to individual EQ-5D questions (response mapping) from QoL-AD, were trialled for patient-rated and proxy-rated questionnaires. Model performance was assessed by root mean square error and mean absolute error. RESULTS: The response model using multinomial regression including age and sex, performed best in both the estimation dataset and an independent dataset. CONCLUSIONS: The recommended mapping algorithm allows researchers for the first time to estimate EQ-5D values from QoL-AD data, enabling cost-utility analyses using datasets where the QoL-AD but no utility measures were collected.

Health-related quality of life in people with predementia Alzheimer's disease, mild cognitive impairment or dementia measured with preference-based instruments: a systematic literature review.

BACKGROUND: Obtaining reliable estimates of the health-related quality of life (HR-QoL) of people with predementia Alzheimer's disease [AD] (preclinical or prodromal AD), mild cognitive impairment (MCI) and dementia is essential for economic evaluations of related health interventions. AIMS: To provide an overview of which quality of life instruments are being used to assess HR-QoL in people with predementia AD, MCI or dementia; and, to summarise their reported HR-QoL levels at each stage of the disease and by type of respondent. METHODS: We systematically searched for and reviewed eligible studies published between January 1990 and the end of April 2017 which reported HR-QoL for people with predementia AD, MCI or dementia. We only included instruments which are preference-based, allowing index scores/utility values to be attached to each health state they describe based on preferences obtained from population surveys. Summary results were presented by respondent type (self or proxy), type of instrument, geographical location and, where possible, stage of disease. Health state utility values derived using the EuroQoL 5-Dimensions (EQ-5D) were meta-analysed by pooling reported results across all studies by disease severity (MCI, mild, mild to moderate, moderate, severe dementia, not specified) and by respondent (person with dementia, carer, general public, not specified), using a fixed-effects approach. RESULTS: We identified 61 studies which reported HR-QoL for people with MCI or dementia using preference-based instruments, of which 48 used the EQ-5D. Thirty-six studies reported HR-QoL for mild and/or moderate disease severities, and 12 studies reported utility values for MCI. We found systematic differences between self-rated and proxy-rated HR-QoL, with proxy-rated utility valued being significantly lower in more severe disease states. CONCLUSIONS: A substantial literature now exists quantifying the impact of dementia on HR-QoL using preference-based measures, giving researchers and modellers a firmer basis on which to select appropriate utility values when estimating the effectiveness and cost-effectiveness of interventions in this area. Further research is required on HR-QoL of people with preclinical and prodromal AD and MCI, possible differences by type of dementia, the effects of comorbidities, study setting and the informal caregiver's own HR-QoL, including any effect of that on their proxy-ratings.

Multilevel network meta-regression for population-adjusted treatment comparisons.

Standard network meta-analysis (NMA) and indirect comparisons combine aggregate data from multiple studies on treatments of interest, assuming that any effect modifiers are balanced across populations. Population adjustment methods relax this assumption using individual patient data from one or more studies. However, current matching-adjusted indirect comparison and simulated treatment comparison methods are limited to pairwise indirect comparisons and cannot predict into a specified target population. Existing meta-regression approaches incur aggregation bias. We propose a new method extending the standard NMA framework. An individual level regression model is defined, and aggregate data are fitted by integrating over the covariate distribution to form the likelihood. Motivated by the complexity of the closed form integration, we propose a general numerical approach using quasi-Monte-Carlo integration. Covariate correlation structures are accounted for by using copulas. Crucially for decision making, comparisons may be provided in any target population with a given covariate distribution. We illustrate the method with a network of plaque psoriasis treatments. Estimated population-average treatment effects are similar across study populations, as differences in the distributions of effect modifiers are small. A better fit is achieved than a random effects NMA, uncertainty is substantially reduced by explaining within- and between-study variation, and estimates are more interpretable.

Reweighting Randomized Controlled Trial Evidence to Better Reflect Real Life - A Case Study of the Innovative Medicines Initiative.

Evidence from randomized controlled trials available for timely health technology assessments of new pharmacological treatments and regulatory decision making may not be generalizable to local patient populations, often resulting in decisions being made under uncertainty. In recent years, several reweighting approaches have been explored to address this important question of generalizability to a target population. We present a case study of the Innovative Medicines Initiative to illustrate the inverse propensity score reweighting methodology, which may allow us to estimate the expected treatment benefit if a clinical trial had been run in a broader real-world target population. We learned that identifying treatment effect modifiers, understanding and managing differences between patient characteristic data sets, and balancing the closeness of trial and target patient populations with effective sample size are key to successfully using this methodology and potentially mitigating some of this uncertainty around local decision making.