Randomized Controlled Trials for Platelet-Rich Plasma Use in Knee Osteoarthritis Rarely Report Key Sociodemographic Patient Variables: A Scoping Review.

PURPOSE

To investigate the characteristics and rate of sociodemographic variables reported in randomized controlled trials (RCTs) studying platelet-rich plasma (PRP) injections in the treatment of knee osteoarthritis (OA).

METHODS

In January 2024, PubMed, Scopus, and Web of Science databases were queried for the phrase "Platelet-Rich Plasma Knee Osteoarthritis." Included studies were RCTs investigating PRP use in knee OA published in English between 2012 and 2023. Each RCT was inspected for patient age and sex or gender as well as the following sociodemographic variables: race, ethnicity, insurance status, income, housing status, work status, and education. Data were presented in a descriptive fashion and analyzed using χ test and Fisher's exact test to compare 2 and 3 categorical variables, respectively, with significance defined as < .05.

RESULTS

From 2012 through 2023, 71 RCTs met inclusion criteria. Included publications reported both age and sex or gender in 71/71 papers (100%). Reporting rates for other sociodemographic variables were as follows: race (3/71, 4.23%), work status (5/71, 7.04%), and education (3/71, 4.23%). No studies included the ethnicity, insurance status, income, or housing status of the enrolled patients. There was no difference in reporting sociodemographic variables by journal ( = .083) or by year of publication ( = .340). Sociodemographic variables were reported significantly less frequently than age and sex or gender ( < .001).

CONCLUSIONS

In this study, we found that age and sex or gender are always reported in RCTs of PRP use for knee OA. However, other sociodemographic variables, such as race, work status, and education, that may be important to understand are rarely reported.

CLINICAL RELEVANCE

Sociodemographic variables may affect outcomes in knee osteoarthritis. It is important to understand which of these variables are most studied and which variables are most overlooked. This will help us better understand the quality of the available information.