Author response: Migraine progression in subgroups of migraine based on comorbidities: Results of the CaMEO Study
Richard B.Lipton, Neurologist, Albert Einstein College of Medicine
Kristina M.Fanning, Statistician, Vedanta Research
Dawn C.Buse, Professor of Neurology, Albert Einstein College of Medicine
Vincent T.Martin, Internist, University of Cincinnati Headache and Facial Pain Center
Lee B.Hohaia, Medical writer, CHC Group, LLC
AubreyManack Adams, Associate VP, Medical Affairs Migraine, Allergan plc
Michael L.Reed, President, Healthcare researcher, Vedanta Research
Peter J.Goadsby, Neurologist, NIHR-Wellcome Trust King’s Clinical Research Facility, King’s College London, UK and University of California, SF
Submitted February 13, 2020
In our article,1 we used latent class analysis (LCA) to identify clinically homogeneous migraine subgroups. Progress in the characterization of familial hemiplegic migraine (FHM) was possible because a specific migraine phenotype was identified, facilitating the discovery of multiple causal genetic variations and biological mechanisms.2 Our approach builds on the FHM model by using LCA to identify specific migraine phenotypes based on comorbidity profiles.3 To show that these subgroups are meaningful, we sought to examine characteristics not included in LCA as external validators; these can include biological markers, treatment response, or clinical course.
Using clinical course, we showed substantial differences in rates of progression to chronic migraine.1 Having identified the groups and confirmed prognostic differences, we must now seek biological explanations for differences in subgroups.
As a long-term goal for the field, we want to map clinical phenotypes onto biology and treatment response. When that happens for all of migraine, as it has for FHM, this work will have delivered on its long-term promise. Like Dr. Gupta, we are eager to make these strides but content ourselves with small steps.
Disclosure
The authors report no relevant disclosures. Contact [email protected] for full disclosures.
References
Lipton RB, Fanning KM, Buse DC, et al. Migraine progression in subgroups of migraine based on comorbidities: Results of the CaMEO Study. Neurology 2019;93:e2224–e2236.
Tolner EA, Houben T, Terwindt GM, et al. From migraine genes to mechanisms. Pain 2015;156 Suppl 1:S64–74.
Lipton RB, Fanning KM, Buse DC, et al. Identifying natural subgroups of migraine based on comorbidity and concomitant condition profiles: results of the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study. Headache 2018;58:933–947.
In our article,1 we used latent class analysis (LCA) to identify clinically homogeneous migraine subgroups. Progress in the characterization of familial hemiplegic migraine (FHM) was possible because a specific migraine phenotype was identified, facilitating the discovery of multiple causal genetic variations and biological mechanisms.2 Our approach builds on the FHM model by using LCA to identify specific migraine phenotypes based on comorbidity profiles.3 To show that these subgroups are meaningful, we sought to examine characteristics not included in LCA as external validators; these can include biological markers, treatment response, or clinical course.
Using clinical course, we showed substantial differences in rates of progression to chronic migraine.1 Having identified the groups and confirmed prognostic differences, we must now seek biological explanations for differences in subgroups.
As a long-term goal for the field, we want to map clinical phenotypes onto biology and treatment response. When that happens for all of migraine, as it has for FHM, this work will have delivered on its long-term promise. Like Dr. Gupta, we are eager to make these strides but content ourselves with small steps.
Disclosure
The authors report no relevant disclosures. Contact [email protected] for full disclosures.
References