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Abstract
Background
Aesthetic physicians have several hundred injectable products to select from. Due to differences in their manufacturing technology, these products display varying biophysical qualities, such as their cohesivity and lift capacity. Currently, there is no guidance to objectively selecting the best product for a particular patient. Therefore, an algorithmic approach is required to take specific skin characteristics into consideration.
Objectives
To evaluate (1) whether subjects seeking injectable treatments for midfacial volume loss and/or contour deficiency can be stratified based on specific skin characteristics (eg, thickness, fat quantity, bony structure) and (2) whether particular hyaluronic acid fillers perform best when used in such particular strata.
Methods
This was a prospective, Phase IV, open-label, single-center clinical trial. Thirty female patients with midface/cheek volume loss and/or contour deficiency were recruited (mean age, 53.5 years; SD, 12.57; range, 35–75 years). Subjects were treated with either Restylane Lyft (HAL) or Restylane Volyme (HAV) and followed for 4 months post-injection. Treatment allocation was based on the treating physician’s clinical evaluation and compared with ultrasound evaluation. Ultrasound images were used to confirm stratification. Safety and efficacy assessments were performed at each study visit: baseline, week 2, week 4, week 8, and week 16. Subgroup analyses evaluated whether particular strata performed best when treated with specific products.
Results
The 2 investigative products varied in their efficacy, depending on the characteristics of the subject.
Conclusions
The use of a treatment algorithm may improve outcomes for patients seeking injectable treatments for midfacial volume loss and contour deficiencies.
Level of Evidence: 2
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Details
1 Université de Montreal and McGill University , Montreal, Quebec, Canada
2 Erevna Innovations Inc, Clinical Research Unit , Westmount, Quebec, Canada
3 Galderma Aesthetics , Uppsala, Sweden
4 Division of Surgical Research, McGill University , Montreal, Quebec, Canada