Value of information dynamics in Disease X vaccine clinical trials.

BACKGROUND: Solutions have been proposed to accelerate the development and rollout of vaccines against a hypothetical disease with epidemic or pandemic potential called Disease X. This may involve resolving uncertainties regarding the disease and the new vaccine. However the value for public health of collecting this information will depend on the time needed to perform research, but also on the time needed to produce vaccine doses. We explore this interplay, and its effect on the decision on whether or not to perform research. METHOD: We simulate numerically the emergence and transmission of a disease in a population using a susceptible-infected-recovered (SIR) compartmental model with vaccination. Uncertainties regarding the disease and the vaccine are represented by parameter prior distributions. We vary the date at which vaccine doses are available, and the date at which information about parameters becomes available. We use the expected value of perfect information (EVPI) and the expected value of partially perfect information (EVPPI) to measure the value of information. RESULTS: As expected, information has less or no value if it comes too late, or (equivalently) if it can only be used too late. However we also find non trivial dynamics for shorter durations of vaccine development. In this parameter area, it can be optimal to implement vaccination without waiting for information depending on the respective durations of dose production and of clinical research. CONCLUSION: We illustrate the value of information dynamics in a Disease X outbreak scenario, and present a general approach to properly take into account uncertainties and transmission dynamics when planning clinical research in this scenario. Our method is based on numerical simulation and allows us to highlight non trivial effects that cannot otherwise be investigated.

Optimal Epidemic Control under Uncertainty: Tradeoffs between Information Collection and Other Actions.

BACKGROUND: Recent epidemics and measures taken to control them-through vaccination or other actions-have highlighted the role and importance of uncertainty in public health. There is generally a tradeoff between information collection and other uses of resources. Whether this tradeoff is solved explicitly or implicitly, the concept of value of information is central to inform policy makers in an uncertain environment. METHOD: We use a deterministic SIR (susceptible, infectious, recovered) disease emergence and transmission model with vaccination that can be administered as 1 or 2 doses. The disease parameters and vaccine characteristics are uncertain. We study the tradeoffs between information acquisition and 2 other measures: bringing vaccination forward and acquiring more vaccine doses. To do this, we quantify the expected value of perfect information (EVPI) under different constraints faced by public health authorities (i.e., the time of the vaccination campaign implementation and the number of vaccine doses available). RESULTS: We discuss the appropriateness of different responses under uncertainty. We show that, in some cases, vaccinating later or with less vaccine doses but more information about the epidemic, and the efficacy of control strategies may bring better results than vaccinating earlier or with more doses and less information, respectively. CONCLUSION: In the present methodological article, we show in an abstract setting how clearly defining and treating the tradeoff between information acquisition and the relaxation of constraints can improve public health decision making. HIGHLIGHTS: Uncertainties can seriously hinder epidemic control, but resolving them is costly. Thus, there are tradeoffs between information collection and alternative uses of resources.We use a generic SIR model with vaccination and a value-of-information framework to explore these tradeoffs.We show in which cases vaccinating later with more information about the epidemic and the efficacy of control measures may be better-or not-than vaccinating earlier with less information.We show in which cases vaccinating with fewer vaccine doses and more information about the epidemic and the efficacy of control measures may be better-or not-than vaccinating with more doses and less information.

Cost-effectiveness of monoclonal antibody and maternal immunization against respiratory syncytial virus (RSV) in infants: Evaluation for six European countries.

BACKGROUND: Respiratory syncytial virus (RSV) imposes a substantial burden on pediatric hospital capacity in Europe. Promising prophylactic interventions against RSV including monoclonal antibodies (mAb) and maternal immunizations (MI) are close to licensure. Therefore, we aimed to evaluate the cost-effectiveness of potential mAb and MI interventions against RSV in infants, for six European countries. METHODS: We used a static cohort model to compare costs and health effects of four intervention programs to no program and to each other: year-round MI, year-round mAb, seasonal mAb (October to April), and seasonal mAb plus a catch-up program in October. Input parameters were obtained from national registries and literature. Influential input parameters were identified with the expected value of partial perfect information and extensive scenario analyses (including the impact of interventions on wheezing and asthma). RESULTS: From the health care payer perspective, and at a price of €50 per dose (mAb and MI), seasonal mAb plus catch-up was cost-saving in Scotland, and cost-effective for willingness-to-pay (WTP) values ≥€20,000 (England, Finland) or €30,000 (Denmark) per quality adjusted life-year (QALY) gained for all scenarios considered, except when using ICD-10 based hospitalization data. For the Netherlands, seasonal mAb was preferred (WTP value: €30,000-€90,000) for most scenarios. For Veneto region (Italy), either seasonal mAb with or without catch-up or MI was preferred, depending on the scenario and WTP value. From a full societal perspective (including leisure time lost), the seasonal mAb plus catch-up program was cost-saving for all countries except the Netherlands. CONCLUSION: The choice between a MI or mAb program depends on the level and duration of protection, price, availability, and feasibility of such programs, which should be based on the latest available evidence. Future research should focus on measuring accurately age-specific RSV-attributable hospitalizations in very young children.

Cost-effectiveness and budget impact of venetoclax in combination with rituximab in relapsed/refractory chronic lymphocytic leukemia in Switzerland.

INTRODUCTION: Venetoclax in combination with rituximab (VEN + R) demonstrated prolonged overall survival (OS) and progression-free survival (PFS) for patients with relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL) in comparison to standard chemoimmunotherapy [bendamustine + rituximab (BR)]. We conducted a cost-effectiveness and budget impact analysis comparing VEN + R versus six comparators from the Swiss healthcare payer perspective. METHODS: A three-state partitioned survival model, developed in accordance with NICE and ISPOR decision modelling guidelines, was adapted to Switzerland. Model inputs were informed by the MURANO trial (survival data, patient characteristics), publicly available Swiss sources (drug prices, inpatient and outpatient costs), Swiss National Institute of Cancer Epidemiology and Registration data (incidence and prevalence values), and Swiss medical expert feedback. We used published (dis-)utility values and adverse event probabilities. RESULTS: Over a lifetime, VEN + R resulted in an expected gain of 2.60 quality-adjusted life years (QALYs) per patient and incremental costs of Swiss Francs (CHF) 147,851 compared to BR, leading to an incremental cost-effectiveness ratio of CHF 56,881/QALY gained. Other treatment strategies (for example ibrutinib versus VEN + R) resulted in higher costs and lower QALYs. Results were not different for subgroups of patients with/without deletion of chromosome 17p/tumour protein 53 mutation. In scenario analysis, changes in post-progression treatment costs demonstrated a high impact on results. We estimated an expected value of perfect information of CHF 3,318/patient. A moderate VEN + R uptake was estimated to save CHF 12.3 million during 5 years. CONCLUSIONS: Using a threshold of CHF 100,000 per QALY, VEN + R was projected to be cost-effective vs BR.

Value of Information Analytical Methods: Report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

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

A cost-utility analysis of phosphodiesterase type 5 inhibitors in the treatment of erectile dysfunction.

INTRODUCTION: Patent expiration for erectile dysfunction (ED) treatments like sildenafil means loss of exclusivity (LOE), and other manufacturers may bring generics to the market. This has resulted in price reductions, which influences the cost-effectiveness. In Norway, this development has led to a discussion on whether reimbursement should be granted. Cost-effectiveness analysis in this treatment area is scarce and more research is demanded. OBJECTIVE: The objective of this study was to assess the cost-effectiveness of three separate phosphodiesterase type 5 (PDE5) inhibitors in ED therapy in a Norwegian setting. METHODS: The cost-effectiveness was analyzed using two patient populations: (1) 55-year-old patients diagnosed with ED and with no specific underlying illness, and (2) 55-year-old patients diagnosed with ED and with diabetes as an underlying illness. Using a state-transition Markov model with a 10-year time horizon, a "no-treatment" option was compared with three treatment strategies: (1) treatment using 50/100 mg sildenafil; (2) treatment using 10/20 mg tadalafil; (3) treatment using 10 mg vardenafil. A societal perspective was applied. RESULTS: All PDE5 inhibitor treatment strategies were cost-effective compared to a "no-treatment" option, with cost per additional quality-adjusted life-year of less than €15,000. With a willingness-to-pay threshold greater than €13,500, sildenafil was estimated as the dominant treatment strategy. The probabilistic sensitivity analysis indicated robust results. However, as the expected value of information was considerable, the cost-effectiveness of conducting further research to reduce uncertainty should be considered. Treating a diabetic population was less cost-effective for all PDE5 inhibitors and was associated with greater uncertainty with regard to choosing the optimal strategy. CONCLUSIONS: Sildenafil treatment of erectile dysfunction was a cost-effective alternative compared to tadalafil and vardenafil, as well as compared to a "no-treatment" option. Treating a diabetic population is less cost-effective for all PDE5 inhibitors and was associated with greater uncertainty.

Cost-effectiveness of Human Papilloma Virus (HPV) vaccination in Nigeria: a decision analysis using pragmatic parameter estimates for cost and programme coverage.

BACKGROUND: World Health Organisation recommends routine Human Papilloma Virus (HPV) vaccination for girls when its cost-effectiveness in the country or region has been duly considered. We therefore aimed to evaluate cost-effectiveness of HPV vaccination in Nigeria using pragmatic parameter estimates for cost and programme coverage, i.e. realistically achievable in the studied context. METHODS: A microsimulation frame-work was used. The natural history for cervical cancer disease was remodelled from a previous Nigerian model-based study. Costing was based on health providers' perspective. Disability adjusted life years attributable to cervical cancer mortality served as benefit estimate. Suitable policy option was obtained by calculating the incremental costs-effectiveness ratio. Probabilistic sensitivity analysis was used to assess parameter uncertainty. One-way sensitivity analysis was used to explore the robustness of the policy recommendation to key parameters alteration. Expected value of perfect information (EVPI) was calculated to determine the expected opportunity cost associated with choosing the optimal scenario or strategy at the maximum cost-effectiveness threshold. RESULTS: Combination of the current scenario of opportunistic screening and national HPV vaccination programme (CS + NV) was the only cost-effective and robust policy option. However, CS + NV scenario was only cost-effective so far the unit cost of HPV vaccine did not exceed $5. EVPI analysis showed that it may be worthwhile to conduct additional research to inform the decision to adopt CS + NV. CONCLUSIONS: National HPV vaccination combined with opportunist cervical cancer screening is cost-effective in Nigeria. However, adoption of this strategy should depend on its relative efficiency when compared to other competing new vaccines and health interventions.

Immigrant screening for latent tuberculosis in Norway: a cost-effectiveness analysis.

The incidence of tuberculosis (TB) disease has increased in Norway since the mid-1990s. Immigrants are screened, and some are treated, for latent TB infection (LTBI) to prevent TB disease (reactivation). In this study, we estimated the costs of both treating and screening for LTBI and TB disease, which has not been done previously in Norway. We developed a model to indicate the cost-effectiveness of four different screening algorithms for LTBI using avoided TB disease cases as the health outcome. Further, we calculated the expected value of perfect information (EVPI), and indicated areas of LTBI screening that could be changed to improve cost-effectiveness. The costs of treating LTBI and TB disease were estimated to be €1938 and €15,489 per case, respectively. The model evaluates four algorithms, and suggests three cost-effective algorithms depending on the cost-effectiveness threshold. Screening all immigrants with interferon-gamma release assays (IGRA) requires the highest threshold (€28,400), followed by the algorithms "IGRA on immigrants with risk factors" and "no LTBI screening." EVPI is approximately €5 per screened immigrant. The costs for a cohort of 20,000 immigrants followed through 10 years range from €12.2 million for the algorithm "screening and treatment for TB disease but no LTBI screening," to €14 million for "screening all immigrants for both TB disease and LTBI with IGRA." The results suggest that the cost of TB disease screening and treatment is the largest contributor to total costs, while LTBI screening and treatment costs are relatively small. Increasing the proportion of IGRA-positive immigrants who are treated decreases the costs per avoided case substantially.

Potential impact of vaccination against Neisseria meningitidis on Neisseria gonorrhoeae in the United States: results from a decision-analysis model.

Components in 4CMenB vaccine against Neisseria meningitidis serogroup B have shown to potentially cross-react with Neisseria gonorrhoeae. We modeled the theoretical impact of a US 4CMenB vaccination program on gonorrhea outcomes. A decision-analysis model was populated using published healthcare utilization and cost data. A two-dose adolescent vaccination campaign was assumed, with protective immunity starting at age 15 years and a base-case efficacy against gonorrhea of 20%. The 20%-efficacy level is an assumption since no clinical data have yet quantified the efficacy of 4CMenB against Neisseria gonorrhoea. Key outcome measures were reductions in gonorrhea and HIV infections, reduction in quality-adjusted life-years (QALYs) lost, and the economically justifiable price assuming a willingness-to-pay threshold of $75,000 per QALY gained. Adolescent vaccination with 4CMenB would prevent 83,167 (95% credible interval [CrI], 44,600-134,600) gonorrhea infections and decrease the number of HIV infections by 55 (95% CrI, 2-129) per vaccinated birth cohort in the USA. Excluding vaccination costs, direct medical costs for gonorrhea would reduce by $28.7 million (95% CrI, $6.8-$70.0 million), and income and productivity losses would reduce by $40.0 million (95% CrI, $8.2-$91.7 million). Approximately 83% of the reduction in lost productivity is generated by avoiding HIV infections. At a cost of $75,000 per QALY gained, and incremental to the vaccine's effect on meningococcal disease, a price of $26.10 (95% CrI, $9.10-$57.20) per dose, incremental to the price of the meningococcal vaccine, would be justified from the societal perspective. At this price, the net cost per infection averted would be $1,677 (95% CrI, $404-$2,564). Even if the cross-immunity of 4CMenB vaccine and gonorrhea is only 20%, the reduction in gonorrhea infections and associated costs would be substantial.

An optimization approach to calculating sample sizes with binary responses.

In this article, we discuss an optimization approach to the sample size question, founded on maximizing the value of information in comparison studies with binary responses. The expected value of perfect information (EVPI) is calculated and the optimal sample size is obtained by maximizing the expected net gain of sampling (ENGS), the difference between the expected value of sample information (EVSI) and the cost of conducting the trial. The data are assumed to come from two independent binomial distributions, while the parameter of interest is the difference between the two success probabilities, [Formula: see text]. To formulate our prior knowledge on the parameters, a Dirichlet prior is used. Monte Carlo integration is used in the computation and optimization of ENGS. We also compare the results of this approach with existing Bayesian methods and show how the new approach reduces the computational complexity considerably.

When is enough evidence enough? - Using systematic decision analysis and value-of-information analysis to determine the need for further evidence.

Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with diabetes) as well as key references from the literature, including examples for the use of the decision-analytic VoI framework by health technology assessment agencies to guide further research. These concepts may guide stakeholders involved or interested in how to determine whether or not and, if so, which additional evidence is needed to make decisions.

Value of research and value of development in early assessments of new medical technologies.

OBJECTIVES: In early stages of development of new medical technologies, there are conceptually separate but related societal decisions to be made concerning adoption, further development (i.e., technical improvement), and research (i.e., clinical trials) of new technologies. This article presents a framework to simultaneously support these three decisions from a societal perspective. The framework is applied to the 70-gene signature, a gene-expression profile for breast cancer, deciding which patients should receive adjuvant systemic therapy after surgery. The "original" signature performed on fresh frozen tissue (70G-FFT) could be further developed to a paraffin-based signature (70G-PAR) to reduce test failures. METHODS: A Markov decision model comparing the "current" guideline Adjuvant Online (AO), 70G-FFT, and 70G-PAR was used to simulate 20-year costs and outcomes in a hypothetical cohort in The Netherlands. The 70G-PAR strategy was based on projected data from a comparable technology. Incremental net monetary benefits were calculated to support the adoption decision. Expected net benefit of development for the population and expected net benefit of sampling were calculated to support the development and research decision. RESULTS: The 70G-PAR had the highest net monetary benefit, followed by the 70G-FFT. The population expected net benefit of development amounted to €91 million over 20 years (assuming €250 development costs per patient receiving the test). The expected net benefit of sampling amounted to €61 million for the optimal trial (n = 4000). CONCLUSIONS: We presented a framework to simultaneously support adoption, development, and research decisions in early stages of medical technology development. In this case, the results indicate that there is value in both further development of 70G-FFT into 70G-PAR and further research.