Effectiveness of Osteoarthritis Treatments Put Under the Microscope in a Recent Study

Osteoarthritis, a prevalent joint condition primarily characterized by the gradual degeneration of cartilage, is a significant health issue impacting mobility and causing pain, stiffness, and occasional limitations in motion. Although it’s typically associated with aging, other factors including genetics, obesity, and joint injuries are also known contributors to its development.

Scientists at Lund University in Sweden have drawn attention to potential pitfalls in clinical studies involving osteoarthritis, particularly the flawed results that can be obtained from primarily recruiting patients experiencing severe pain, without taking into account the natural pain fluctuations in this disease.

This chronic joint disease’s prevalence increases with age, often resulting in pain, impaired physical functionality, and disability. Currently, about a quarter of all adults over 45 years in Sweden, translating to approximately one million people, have sought medical attention for osteoarthritis.

Patients with osteoarthritis regularly experience pain fluctuations, characterized by periods of intense pain interspersed with less severe discomfort. This is a natural part of the disease’s progress, but it poses a research challenge when studying potential treatments. Often, research studies recruit participants currently experiencing pain above a specific level, which can obscure the interpretation of the study’s results.

Martin Englund, professor of epidemiology at Lund University and physician at Skåne University Hospital, explains, “Those with extreme pain are likely to experience less pain at a subsequent measurement, a phenomenon known as ‘regression to the mean.’ As a result, follow-up measurements often indicate positive effects, regardless of the actual effectiveness of the treatment.”

Along with Aleksandra Turkiewicz, an associate professor and statistician, Englund assessed the extent of improvement attributed to regression to the mean in a typical osteoarthritis study. The study utilized data from a large population-based study in the United States focusing on individuals with knee osteoarthritis. They discovered that this regression accounted for about a 1 point improvement on a 10-point pain scale.

“This constitutes a significant proportion of the reported improvement in many studies, particularly considering that researchers typically note an average pain reduction of only 1 to 2.5 points in knee osteoarthritis patients,” Englund states.

The researchers emphasize that much of the perceived treatment effect could be misleading. The effectiveness of a treatment can only be accurately determined if there is an appropriate control group receiving a placebo, if the study participants remain unaware of their treatment, and if the treatment is randomly allocated. Therefore, to be deemed effective, a treatment must outperform a placebo, and researchers must consider regression to the mean.

The study, now published in Lancet Rheumatology, is a critical resource for designing and interpreting studies evaluating osteoarthritis pain treatments.

“We urgently need more effective treatments for osteoarthritis, but this also unfortunately paves the way for several treatment forms that falsely claim efficacy or overstate its degree. Treatments like platelet-rich plasma (PRP) injections, for example, have insufficiently proven efficacy, and even exercise studies often lack a relevant control group and frequently exaggerate pain-relief effects,” concludes Englund.

Reference: “Pain in clinical trials for knee osteoarthritis: estimation of regression to the mean” by Martin Englund and Aleksandra Turkiewicz, 21 April 2023, The Lancet Rheumatology.
DOI: 10.1016/S2665-9913(23)00090-5

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