A Dutch cost-effectiveness analysis of fremanezumab versus best supportive care in patients with chronic migraine and inadequate response to prior preventive therapy.

BACKGROUND: Chronic migraine (CM) is the most severe and burdensome subtype of migraine. Fremanezumab is a monoclonal antibody that targets the calcitonin gene-related peptide pathway as a migraine preventive therapy. This study aimed to conduct a cost-effectiveness analysis of fremanezumab from a societal perspective in the Netherlands, using a Markov cohort simulation model. METHODS: The base-case cost-effectiveness analysis adhered to the Netherlands Authority guidelines. Fremanezumab was compared with best supportive care (BSC; acute migraine treatment only) in patients with CM and an inadequate response to topiramate or valproate and onabotulinumtoxinA (Dutch patient group [DPG]). A supportive analysis was conducted in the broader group of CM patients with prior inadequate response to 2-4 different classes of migraine preventive treatments. One-way sensitivity, probabilistic sensitivity, and scenario analyses were conducted. RESULTS: Over a lifetime horizon, fremanezumab is cost saving compared with BSC in the DPG (saving of €2514 per patient) and led to an increase of 1.45 quality-adjusted life-years (QALYs). In the broader supportive analysis, fremanezumab was cost effective compared with BSC, with an incremental cost-effectiveness ratio of €2547/QALY gained. Fremanezumab remained cost effective in all sensitivity and scenario analyses. CONCLUSION: In comparison to BSC, fremanezumab is cost saving in the DPG and cost effective in the broader population.

Validity of health insurance data to identify people with epilepsy.

BACKGROUND: Large administrative databases may prove useful to assess epilepsy-related comorbidity and mortality. Despite their increased use, their validity as data source in epilepsy is yet under-ascertained. METHODS: Achmea is a large Dutch health insurance company covering about 25% of the population. We performed a retrospective cohort study using data from the Achmea Health Insurance Database (AHID) over the period 2006-2009. To assess the validity of epilepsy codes in the AHID, we randomly invited 1000 individuals (age 18-75 years insured by Achmea), attending an epilepsy centre or a district hospital during 2006-2009, to participate. Informed consent was provided and 293 were eligible for inclusion. We compared the diagnostic codes for epilepsy in AHID with the diagnosis in their case-notes (reference standard). As additional measure of validity, we compared prevalence of epilepsy codes in AHID (based on anonymized data of all 26.297 subjects with this code in AHID) with epilepsy prevalence rates in the general Dutch population to estimate an age-specific standardized prevalence ratio. RESULTS: We identified 293 participants with an epilepsy code in AHID. The majority (278) of them had a definite or possible diagnosis of epilepsy in the case-notes; i.e. a positive predictive value of 0.95 (95% CI 0.92-0.97). The overall prevalence of epilepsy codes in the AHID was slightly higher than the putative prevalence in the general Dutch population (7.4/1.000 vs. 6.8/1.000) with a Standardized Prevalence Ratio of 1.08 (95% CI: 1.08-1.09). CONCLUSIONS: Our findings demonstrate the validity of AHID data for a diagnosis of epilepsy and confirm previous work on using administrative data for epilepsy research.