Migraine day frequency in migraine prevention

Longitudinal modelling approaches

Gian Luca Di Tanna, Joshua K. Porter, Richard B. Lipton, Alan Brennan, Stephen Palmer, Anthony J. Hatswell, Sandhya Sapra, Guillermo Villa

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Article number20
JournalBMC Medical Research Methodology
Volume19
Issue number1
DOIs
StatePublished - Jan 23 2019

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Migraine Disorders
Economic Models
Clinical Trials
Binomial Distribution
Statistical Models
Cost-Benefit Analysis
Placebos
Delivery of Health Care
Health

Keywords

  • Beta-binomial
  • Erenumab
  • Migraine
  • Migraine frequency
  • Modelling
  • Negative binomial

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics

Cite this

Di Tanna, G. L., Porter, J. K., Lipton, R. B., Brennan, A., Palmer, S., Hatswell, A. J., ... Villa, G. (2019). Migraine day frequency in migraine prevention: Longitudinal modelling approaches. BMC Medical Research Methodology, 19(1), [20]. https://doi.org/10.1186/s12874-019-0664-5

Migraine day frequency in migraine prevention : Longitudinal modelling approaches. / Di Tanna, Gian Luca; Porter, Joshua K.; Lipton, Richard B.; Brennan, Alan; Palmer, Stephen; Hatswell, Anthony J.; Sapra, Sandhya; Villa, Guillermo.

In: BMC Medical Research Methodology, Vol. 19, No. 1, 20, 23.01.2019.

Research output: Contribution to journalArticle

Di Tanna, GL, Porter, JK, Lipton, RB, Brennan, A, Palmer, S, Hatswell, AJ, Sapra, S & Villa, G 2019, 'Migraine day frequency in migraine prevention: Longitudinal modelling approaches', BMC Medical Research Methodology, vol. 19, no. 1, 20. https://doi.org/10.1186/s12874-019-0664-5
Di Tanna, Gian Luca ; Porter, Joshua K. ; Lipton, Richard B. ; Brennan, Alan ; Palmer, Stephen ; Hatswell, Anthony J. ; Sapra, Sandhya ; Villa, Guillermo. / Migraine day frequency in migraine prevention : Longitudinal modelling approaches. In: BMC Medical Research Methodology. 2019 ; Vol. 19, No. 1.
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