Predictors of treatment‐response to caffeine combination products, acetaminophen, acetylsalicylic acid (aspirin), and nonsteroidal anti‐inflammatory drugs in acute treatment of episodic migraine
Authors: Ezzati Ali , Fanning Kristina M. , Reed Michael L. , Lipton Richard B. 
Published: February 2023

Objective

To identify predictors of acute treatment optimization for migraine with “over‐the‐counter” (OTC) or prescription nonsteroidal anti‐inflammatory drugs (NSAIDs) as well as other widely used OTCs including acetaminophen, caffeine combination products (CCP), and acetylsalicylic acid (ASA, aspirin) among people with episodic migraine and to develop models that predict treatment response to each class of OTCs.

Background

Efficacy of acute OTC medications for migraine varies greatly. Identifying predictors of treatment response to particular classes of medication is a step toward evidence‐based personalized therapy.

Methods

For this prediction model development study, we used data from 2224 participants from the American Migraine Prevalence and Prevention (AMPP) study who were aged ≥18 years, met criteria for migraine, had <15 monthly headache days, and reported being on monotherapy for acute migraine attacks with one of the following classes medications: CCP (N = 711), acetaminophen (N = 643), ASA (N = 110), and prescription or OTC NSAIDs (N = 760). The primary outcome measures of treatment optimization were adequate 2‐h pain freedom (2hPF) and adequate 24‐h pain relief (24hPR), which were defined by responses of half the time or more to the relevant items on the Migraine Treatment Optimization Questionnaire‐6.

Results

The mean (SD) age of the participants was 46.2 (13.1) years, 79.4% (1765/2224) were female, 43.7% (972/2224) reported adequate 2hPF, and 46.1% (1025/2224) reported adequate 24hPR. Those taking CCP had better 2hPF and 24PR outcomes. For those taking NSAIDs, better outcomes were associated with lower average pain intensity (2hPF: odds ratio [OR] 0.89, 95% confidence interval [CI] 0.80–0.99; 24PR: OR 0.86, 95% CI 0.77–0.96), cutaneous allodynia (2hPF: OR 0.92, 95% CI 0.89–0.96; 24PR: OR 0.91, 95% CI 0.87–0.95), depressive symptoms (2hPF: OR 0.95, 95% CI 0.92–0.98; 24PR: OR 0.95, 95% CI 0.91–0.99), and Migraine Disability Assessment Scale (MIDAS) grade (2hPF: OR 0.76, 95% CI 0.64–0.90; 24PR: OR 0.79, 95% CI 0.65–0.95). Adequate 2hPF for those taking CCP was associated with male gender (OR 1.83, 95% CI 1.21–2.77), lower average pain intensity (OR 0.80, 95% CI 0.70–0.91), lower cutaneous allodynia (OR 0.94, 95% CI 0.90–0.97), and lower Migraine Symptom Severity Scale Score (MSSS; OR 0.91, 95% CI 0.86–0.97). Adequate 24hPR for those taking CCP was associated with lower average pain intensity (OR 0.85, 95% CI 0.75–0.96), lower cutaneous allodynia (OR 0.92, 95% CI 0.89–0.96), and lower MIDAS grade (OR 0.81, 95% CI 0.68–0.96). Participants who were married (OR 1.51, 95% CI 1.05–2.19), had lower average pain intensity (OR 0.79, 95% CI 0.70–0.89), lower MSSS (OR 0.93, 95% CI 0.88–0.99), less depression (OR 0.96, 95% CI 0.93–0.99), and lower MIDAS grade (OR 0.72, 95% CI 0.59–0.87) had adequate 2hPF after taking acetaminophen. Participants who were married (OR 1.50, 95% CI 1.02–2.21), had lower pain intensity (OR 0.78, 95% CI 0.69–0.88), less depression (OR 0.95, 95% CI 0.91–0.98) and lower MIDAS grade (OR 0.53, 95% CI 0.42–0.67) had higher 24hPR following use of acetaminophen. A lower MSSS was the only factor associated with higher 2hPF and 24PR after using ASA (OR 0.78, 95% CI 0.67–0.92 and OR 0.79, 95% CI 0.67–0.93). Predictive models had modest performance in identifying responders to each class of OTC.

Conclusion

A large subgroup of people with migraine had an inadequate response to their usual acute OTC migraine treatment 2‐ and 24‐h after dosing. These findings suggest a need to improve OTC treatment for some and to offer prescription acute medications for others. Predictive models identified several factors associated with better treatment‐response in each OTC class. Selecting OTC treatment based on factors predictive of treatment optimization might improve patient outcomes.