Cognitive debriefing and content validation of the Functional Disability Scale (FDS), Activity Level Scale (ALS), Cognitive Function Scale (CFS), and PROMIS Cognitive Function Abilities-Short Form 6a (CFA-SF6a) for interpretability, clarity, relevance, and minimum meaningful improvement in participants with menstrual migraine (MM).

Women with MM have attacks in association with most of their menstrual cycles. Clarifying the translational value of existing patient-reported outcome measures (PROMs) in reflecting the experience of individuals with MM will improve the utility of data collected in clinical trials.

Adults with MM (≥4 attacks/month, at least two thirds associated with menstruation, and <15 monthly headache days) were recruited through an online platform. Semi-structured interviews queried the content validity of the FDS, ALS, CFS, and CFA-SF6a. Participants also estimated the minimum change necessary to achieve meaningful improvement on each PROM.

Participants (n=20) had a mean (SD) age of 39.2 (7.8) years and were 100% (20/20) female and 90% (18/20) White; the mean (SD) duration of migraine was 12.3 (8.9) years. Participants considered the CFS, FDS, ALS, and CFA-SF6a to be relevant, clear, and interpretable. The proportions endorsing a 1-point item-level change as meaningful improvement were 92% (12/13) on the CFS, 100% (14/14) on the FDS, and 100% (11/11) on the ALS. A 1-point change on the CFA-SF6a would be meaningful for the following proportions of participants: 83% (10/12, clarity/ease of thinking); 90% (9/10, memory); 92% (11/12, thinking speed); 94% (15/16, mental acuity); 100% (14/14, concentration); and 100% (14/14, keeping track of activities).

These qualitative data support the content validity of the FDS, ALS, CFS, and CFA-SF6a in adults with MM and suggest they may be fit for purpose in a clinical trial setting. Most participants indicated a 1-point item-level improvement on each PROM is meaningful. These proposed thresholds can complement those derived from statistical methods (e.g., anchor-based analyses).