Insufficient Representation of Patients With Obesity in Randomized Controlled Trials Evaluating the Efficacy and Safety of Antimicrobials for Treatment of Skin and Skin Structure Infections: A Scoping Review.
Jamie L WagnerJamie L WagnerMargaret VugrinRebecca T BrandenburgJeremy LeeLindsey MillerStephen RaybornRonald G HallPublished in: Open forum infectious diseases (2023)
Persons with obesity (PwO) represent approximately 50% of acute bacterial skin and skin structure infections (ABSSSIs) in the United States (US). There are currently insufficient data in PwO for drugs used for ABSSSIs. We conducted a scoping review of randomized controlled trials (RCTs) published between 2000 and 2022 to describe how frequently body size measures were reported. Weight and/or body mass index (BMI) were recorded in approximately 50% of the 69 RCTs. The average weights or BMIs were lower than US averages for most RCTs reporting data. None evaluated the impact of body size on outcomes in the original publication. Only 30% of newly approved drugs mention PwO representation in the prescribing information. More representative recruitment of PwO into RCTs is needed to help clinicians evaluate efficacy in these patients. We suggest that the Food and Drug Administration require companies to submit plans to ensure adequate PwO inclusion and that authors of RCTs report subgroup results based on body size.
Keyphrases
- body mass index
- weight gain
- soft tissue
- drug administration
- weight loss
- wound healing
- insulin resistance
- metabolic syndrome
- end stage renal disease
- type diabetes
- electronic health record
- ejection fraction
- physical activity
- big data
- liver failure
- primary care
- newly diagnosed
- high fat diet induced
- drug induced
- peritoneal dialysis
- palliative care
- adverse drug
- prognostic factors
- chronic kidney disease
- clinical trial
- health insurance
- climate change
- emergency department
- intensive care unit
- systematic review
- cross sectional
- machine learning
- risk assessment
- social media
- health information
- meta analyses
- human health