Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials.

BACKGROUND: Cost-effectiveness analyses in patients with migraine require estimates of patients' utility values and how these relate to monthly migraine days (MMDs). This analysis examined four different modelling approaches to assess utility values as a function of MMDs. METHODS: Disease-specific patient-reported outcomes from three erenumab clinical studies (two in episodic migraine [NCT02456740 and NCT02483585] and one in chronic migraine [NCT02066415]) were mapped to the 5-dimension EuroQol questionnaire (EQ-5D) as a function of the Migraine-Specific Quality of Life Questionnaire (MSQ) and the Headache Impact Test (HIT-6™) using published algorithms. The mapped utility values were used to estimate generic, preference-based utility values suitable for use in economic models. Four models were assessed to explain utility values as a function of MMDs: a linear mixed effects model with restricted maximum likelihood (REML), a fractional response model with logit link, a fractional response model with probit link and a beta regression model. RESULTS: All models tested showed very similar fittings. Root mean squared errors were similar in the four models assessed (0.115, 0.114, 0.114 and 0.114, for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model respectively), when mapped from MSQ. Mean absolute errors for the four models tested were also similar when mapped from MSQ (0.085, 0.086, 0.085 and 0.085) and HIT-6 and (0.087, 0.088, 0.088 and 0.089) for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model, respectively. CONCLUSIONS: This analysis describes the assessment of longitudinal approaches in modelling utility values and the four models proposed fitted the observed data well. Mapped utility values for patients treated with erenumab were generally higher than those for individuals treated with placebo with equivalent number of MMDs. Linking patient utility values to MMDs allows utility estimates for different levels of MMD to be predicted, for use in economic evaluations of preventive therapies. TRIAL REGISTRATION: ClinicalTrials.gov numbers of the trials used in this study: STRIVE, NCT02456740 (registered May 14, 2015), ARISE, NCT02483585 (registered June 12, 2015) and NCT02066415 (registered Feb 17, 2014).

Migraine day frequency in migraine prevention: longitudinal modelling approaches.

BACKGROUND: Health economic models are critical tools to inform reimbursement agencies on health care interventions. Many clinical trials report outcomes using the frequency of an event over a set period of time, for example, the primary efficacy outcome in most clinical trials of migraine prevention is mean change in the frequency of migraine days (MDs) per 28 days (monthly MDs [MMD]) relative to baseline for active treatment versus placebo. Using these cohort-level endpoints in economic models, accounting for variation among patients is challenging. In this analysis, parametric models of change in MMD for migraine preventives were assessed using data from erenumab clinical studies. METHODS: MMD observations from the double-blind phases of two studies of erenumab were used: one in episodic migraine (EM) (NCT02456740) and one in chronic migraine (CM) (NCT02066415). For each trial, two longitudinal regression models were fitted: negative binomial and beta binomial. For a thorough comparison we also present the fitting from the standard multilevel Poisson and the zero inflated negative binomial. RESULTS: Using the erenumab study data, both the negative binomial and beta-binomial models provided unbiased estimates relative to observed trial data with well-fitting distribution at various time points. CONCLUSIONS: This proposed methodology, which has not been previously applied in migraine, has shown that these models may be suitable for estimating MMD frequency. Modelling MMD using negative binomial and beta-binomial distributions can be advantageous because these models can capture intra- and inter-patient variability so that trial observations can be modelled parametrically for the purposes of economic evaluation of migraine prevention. Such models have implications for use in a wide range of disease areas when assessing repeated measured utility values.

Costs of Acute Headache Medication Use and Productivity Losses Among Patients with Migraine: Insights from Three Randomized Controlled Trials.

BACKGROUND: Migraine is associated with a substantial physical and emotional burden for patients. There is also a large economic burden associated with migraine, in terms of lost productivity and healthcare resource use. By reducing the number of monthly migraine days (MMD) experienced by patients, effective preventive treatments can reduce acute medication use and costs of lost productivity. METHODS: Patient level data from three erenumab clinical trials (NCT02456740, NCT02483585 and NCT02066415) were combined and migraine day frequencies were examined. The number of days per month on which patients used acute medication was estimated as a function of MMD. Productivity losses were estimated based on patient responses to the Migraine Disability Assessment questionnaire. Zero-inflated Poisson regression models were used to predict acute medication use and productivity losses per MMD. RESULTS: The results demonstrated that as MMD increased, use of acute medication also increased. Similarly, as MMD increased, loss of productivity (due to absenteeism and presenteeism) also increased. The relationship of MMD to both acute headache medication use and lost productivity was non-linear, with marginal outcomes increasing with frequency. CONCLUSIONS: As MMD increased, acute medication use and productivity loss also increased, but the relationship was non-linear. Therefore, it is important that the distribution of MMD patients is accounted for when estimating the outcomes of migraine patients. By reducing the MMD experienced by patients, effective preventive agents may reduce the requirement for acute medication and also reduce productivity loss, which may translate into potential economic savings.

Reducing Drug Wastage in Pharmaceuticals Dosed by Weight or Body Surface Areas by Optimising Vial Sizes.

BACKGROUND: When pharmaceuticals are administered based on patient characteristics (for example weight or body surface area), an amount of product will be unused and must be disposed of. This wastage represents inefficiency and can distort decision making. METHODS: We present a method for the analysis of optimum fill volumes of pharmaceuticals to minimise wastage across a patient population, using publicly available data. Wastage for patients at each 'step' e.g. by kg of bodyweight is calculated, the frequency of each of these steps in the structure of the population is then estimated using the method of moments, with wastage then estimated for each 'step' multiplied by its prevalence. Illustrative examples of pembrolizumab and cabazitaxel show how wastage could be reduced using UK population data, whilst simultaneously reducing administrative burden. RESULTS: Changing the available vial sizes for pembrolizumab (available as 50 mg/100 mg vials) to 70 mg/100 mg, wastage could be cut from 13.3% to 8.7%. For cabazitaxel (only 60 mg vials available), increasing the fill to 70 mg could reduce wastage from 19.4% to 18.8%, or alternatively, adding a 12.5 mg vial reduce this to 6.5%. A secondary finding is that wastage is higher when the larger vial size is perfectly divisible by the smaller vial size. CONCLUSIONS: Reductions in wastage have the potential to reduce the cost of manufacturing medicines, which is not necessarily low for novel products. These cost reductions could lead to increased profit (at the same prices), constant profit with a better return rate (at lower prices), or a combination of the two. Most importantly, they would improve the efficiency of the health-care sector, increasing funding available to treat patients.

Estimating the clinical effectiveness and value-based price range of erenumab for the prevention of migraine in patients with prior treatment failures: a US societal perspective.

BACKGROUND: Frequent migraine with four or more headache days per month is a common, disabling neurovascular disease. From a US societal perspective, this analysis models the clinical efficacy and estimates the value-based price (VBP) for erenumab, a fully human monoclonal antibody that inhibits the calcitonin gene-related peptide receptor. METHODS: A Markov health state transition model was developed to estimate the incremental costs, quality-adjusted life-years (QALYs), and value-based price range for erenumab in migraine prevention. The model comprises "on preventive treatment", "off preventive treatment", and "death" health states across a 10-year time horizon. The evaluation compared erenumab to no preventive treatment in episodic and chronic migraine patients that have failed at least one preventive therapy. Therapeutic benefits are based on estimated changes in monthly migraine days (MMD) from erenumab pivotal clinical trials and a network meta-analysis of migraine studies. Utilities were estimated using previously published mapping algorithms. A VBP analysis was performed to identify maximum erenumab annual prices at willingness-to-pay (WTP) thresholds of $100,000-$200,000 per QALY. Estimates of VBP under different scenarios such as choice of different comparators, assumptions around inclusion of placebo effect, and exclusion of work productivity losses were also generated. RESULTS: Erenumab resulted in incremental QALYs of 0.185 vs supportive care (SC) and estimated cost offsets due to reduced MMD of $8,482 over 10 years, with an average duration of treatment of 2.01 years. The estimated VBP at WTP thresholds of $100,000-$200,000 for erenumab compared to SC ranged from $14,238-$23,998. VBP estimates including the placebo effect and excluding work productivity ranged from $7,445-$13,809; increasing to $12,151-$18,589 with onabotulinumtoxinA as a comparator in chronic migraine. CONCLUSION: Erenumab is predicted to reduce migraine-related direct and indirect costs, and increase QALYs compared to SC.