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Revealing the Patient Perspective: Evolution of Patient-Reported Outcome Measures in Botulinum Toxin Studies in
Steven Dayan1,2, Alexander Z Rivkin3, Patricia Ogilvie4
1Division of Facial Plastic and Reconstructive Surgery, Department of Otolaryngology, University of Illinois at Chicago, Chicago, Illinois, USA.
Background:
OnabotulinumtoxinA has been licensed for the treatment of upper facial lines for over 20 years. Patient benefits extend well beyond correction of the lines themselves-including positive effects on confidence, self-esteem, feelings of attractiveness, and age appearance. Regulatory bodies recommend that patient-reported outcomes (PROs) are routinely included in registrational studies to ensure the patient perspective is considered. Essential guidance is available from regulators and other expert groups to aid the development, validation, and use of appropriate PROs.
Aims:
To reflect on the evolution of patient experience data collection in onabotulinumtoxinA aesthetic medicine development programs within the context of PRO usage across approved botulinum toxins.
Methods:
Literature searches were performed to identify relevant publications.
Results:
Several PRO instruments have been rigorously developed and validated following regulatory guidance and implemented in onabotulinumtoxinA clinical programs. These include the Facial Line Outcomes Questionnaire (FLO-11) and Facial Line Satisfaction Questionnaire (FLSQ). The data generated have supported the licensing process and enabled a deeper understanding of patient perspectives. Although these instruments were developed for clinical studies, the concepts obtained directly from patient interviews align with patient goals in clinical practice. Similarly, PROs such as FACE-Q are now employed more widely across approved botulinum toxins.
Conclusions:
A patient-centric approach, in lockstep with regulatory requirements, has been central to onabotulinumtoxinA development. Awareness of the comprehensive benefits of aesthetic treatments should continue to improve based on increasingly robust PROs.
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