Osteoarthritis: Study grasps complexity of pain and treatment efficacy

Osteoarthritis, a chronic joint disease affecting millions, brings pain, physical limitations and disability.

In this article, we explore the challenges researchers face in studying the treatments and shed light on the phenomenon of regression to the mean, which can impact treatment efficacy evaluation.

By unraveling these complexities, we aim to foster a better understanding of this condition and the need for reliable treatment assessments.

---

Osteoarthritis: As incidence rises, so does impact

Osteoarthritis, a prevalent joint disease, is on the rise, particularly among aging individuals.

In Sweden alone, approximately one million people above the age of 45 have sought medical attention for this condition. This chronic condition brings forth pain, compromised physical capabilities, and even disability.

---

Unraveling intricacies of osteoarthritis research

What does this research stress on? (Image via Freepik)

Patients experience fluctuating pain levels, with intense episodes intermingled with periods of lesser discomfort.

These natural variations pose a challenge for researchers studying treatment options. Typically, studies recruit participants with pain above a specific threshold, which complicates result interpretation.

In collaboration with statistician Aleksandra Turkiewicz, Professor Martin Englund of Lund University conducted a study to estimate the impact of regression to the mean in osteoarthritis research.

This phenomenon refers to the tendency of individuals with high initial pain levels to experience a decrease over time, independent of treatment effects. The study utilized data from a large population-based study in the United States.

---

The illusion of improvement

Englund and Turkiewicz's study found that regression to the mean accounted for an approximate one-point improvement on a pain scale ranging from zero to ten.

Considering that knee health studies often report an average pain reduction of only 1 to 2.5 points, this phenomenon significantly influences perceived treatment efficacy.

---

Implications for reliable research

Academic implications (Image via Freepik)

To accurately assess treatment efficacy, researchers must account for regression to the mean.

Adequate control groups receiving placebos, randomized treatment allocation and blinding participants are vital components of robust study design. Without these measures, the reported treatment effects can be distorted, leading to inaccurate claims of efficacy.

With a pressing need for more effective treatments, the market is susceptible to treatments lacking sufficient evidence or overstating their efficacy. Platelet-rich plasma injections and exercise interventions are examples where efficacy claims often lack rigorous control groups and exaggerate pain relief effects.

Englund emphasizes the importance of careful evaluation and adherence to rigorous scientific standards.

---

Reference:

Englund, M., & Turkiewicz, A. (2023). Pain in clinical trials for knee osteoarthritis: estimation of regression to the mean. The Lancet Rheumatology.

DOI: 10.1016/S2665-9913(23)00090-5