by King's College London

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The number of new diagnoses of rheumatoid arthritis fell by 20% in the first year of the COVID-19 pandemic, new research suggests.

The study, published today in The Lancet Rheumatology journal by researchers from King's College London, shows there could be as many as a fifth of new cases that have gone undiagnosed, with cases not jumping up above pre-2020 levels. This suggests many of these patients have not been seen by their general practitioner or been reviewed by a hospital specialist. However, for patients who were diagnosed during the pandemic, there did not appear to be more delays in starting treatment.

The study evaluated the diagnosis and treatment of different types of arthritis in England during the first two years of the pandemic.

Rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis are autoimmune diseases that primarily affect the joints and spine. People with these conditions experience chronic pain that can limit their mobility. If diagnosis and treatment is delayed, these conditions can lead to chronic disability due to joint damage, impaired function, work absence, and reduced quality of life. Early diagnosis and treatment of these types of arthritis improves outcomes for patients. Once diagnosed, patients can start highly effective treatments to control symptoms and prevent irreversible damage.

Each year, the quality of care for people with rheumatoid arthritis is benchmarked through a process of national audit. These audits were paused during the pandemic, however, making comparisons of care challenging.

Researchers from King's College London used OpenSAFELY, a highly secure health data platform, to determine how the diagnosis and management of arthritis was affected by the pandemic. From a study population of over 17 million people in England, they were able to evaluate care for 31,000 people with new diagnoses of arthritis between April 2019 and March 2022.

The results showed that the number of newly recorded arthritis diagnoses fell by 20% in the year after the first COVID-19 lockdown, relative to the year before the pandemic. Arthritis diagnoses fell again as COVID-19 cases rose, before returning to pre-pandemic levels by April 2022. Researchers did not see a rebound in diagnoses after restrictions were lifted, suggesting that there is likely to be a substantial burden of undiagnosed patients.

Importantly, the study also showed that for people who were diagnosed during the pandemic, the time to assessment by a hospital specialist was shorter than before the pandemic. This may be due to fewer hospital referrals overall and increased utilization of virtual appointments during the pandemic.

Additionally, the proportion of patients who were started on treatment was similar before and during the pandemic. However, medications perceived to be safer, but less effective, were prescribed more frequently during the pandemic. This could relate to clinicians' concerns about the effects of stronger medications on COVID-19 infections.

Lead author Dr. Mark Russell, from King's College London, said, "This study highlights that there are likely to be people with joint pain and swelling who remain undiagnosed as a consequence of the pandemic. It is important to speak to a doctor if you have these symptoms, as early diagnosis and treatment of conditions such as rheumatoid arthritis greatly improves outcomes for patients and increases the likelihood of disease remission.

"An important message of this study is that it is possible to assess the quality of care for patients with long-term health conditions using routinely collected health data. This approach could be applied to many other chronic health conditions and be used to provide feedback to NHS organizations and clinicians, with the aim of optimizing care for patients."

More information: The Lancet Rheumatology (2022). Mark D Russell et al, Incidence and management of inflammatory arthritis in England before and during the COVID-19 pandemic: a population-level cohort study using OpenSAFELY, The Lancet Rheumatology (2022). DOI: 10.1016/S2665-9913(22)00305-8, dx.doi.org/10.1016/S2665-9913(22)00305-8

Provided by King's College London