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AI may detect osteoarthritis eight years earlier than X-rays: Research

Blood tests with the help of AI may predict knee osteoarthritis up to 8 years before an X-ray shows changes. This could help identify people at risk and allow for early intervention to slow disease progression.

Written By: Rahul Pratyush New Delhi Published on: May 09, 2024 14:14 IST
Image Source : GOOGLE AI detects osteoarthritis 8 years earlier than X-rays

A recent study suggests that a basic blood test might have the capability to identify knee osteoarthritis in individuals who haven't shown any symptoms yet. This detection could occur up to eight years before changes in their bones become apparent on an X-ray, according to scientists.

In this research, scientists examined the blood samples of 200 white women who initially displayed no signs of osteoarthritis and were considered "low-risk" for developing the condition based on traditional risk factors like prior knee injuries or surgeries.

Using the novel test, which focused on analyzing proteins present in the bloodstream to predict individuals' risk, researchers assessed the same participants. They discovered that a person's chance of acquiring knee osteoarthritis within ten years could be predicted with accuracy using just six bloodborne proteins. This discovery was detailed in a study published in the journal Science Advances.

In certain instances, the test has the potential to forecast the disease a significant eight years ahead of the visible signs on an X-ray, which marks a notable advancement given that X-rays are presently the primary diagnostic tool for osteoarthritis. The researchers emphasize the significance of early detection, highlighting that while there isn't a cure for the condition, there exist preventive strategies to decelerate its advancement. These strategies involve lifestyle adjustments like participating in low-impact physical activities, managing weight, and utilizing medications to alleviate symptoms.

Dr. Virginia Byers Kraus, the lead author of the study and a professor of medicine at Duke University in North Carolina, suggests that identifying osteoarthritis earlier could serve as a "wake-up call" for individuals to adopt preventive therapies. These measures could potentially prevent the onset of subsequent complications like pain, disability, and the necessity for joint replacement surgeries.

In the future, the research findings may contribute to the development of improved preventative treatments for osteoarthritis. Dr. Kraus speculates that these treatments could target specific proteins in the bloodstream that are linked to the disease, offering more effective options for prevention.

Osteoarthritis, affecting over 32.5 million adults in the United States, stands as the most prevalent type of arthritis. Originally dubbed as a result of "wear and tear," it emerges when the cartilage in a joint, typically found in the hands, hips, and knees, deteriorates. Consequently, this breakdown prompts alterations in the underlying bone, leading to sensations of pain, stiffness, and swelling.

Yet, emerging evidence now indicates that inflammation plays a crucial role in driving the deterioration of joints observed in osteoarthritis. This suggests the potential existence of "biomarkers," measurable indicators within the body, that could signify the onset of the disease long before structural damage is detected through X-rays.

In the recent study, Kraus and his team examined two sets of blood samples from a well-established group of white, middle-aged women in the United Kingdom. These women have been regularly evaluated for osteoarthritis since 1989. From this group, 200 women were selected based on their age and body mass indices (BMI). Over a 10-year period, half of these women were diagnosed with osteoarthritis while the other half remained unaffected.

Using artificial intelligence, the researchers pinpointed six proteins in the blood samples that seemed to indicate the likelihood of developing osteoarthritis. These blood samples were collected either eight or four years before the individuals were diagnosed with the condition. The identified proteins are associated with triggering inflammation and are involved in hemostasis, which is an initial stage in the body's response to injury.

To evaluate the accuracy of the test, the team employed a statistical measure known as the area under the curve (AUC). An AUC value at or below 50% suggests that the test cannot effectively distinguish between individuals with and without the disease. A value exceeding 70% is considered "acceptable" performance, while anything surpassing 80% is deemed "excellent." In this study, the six proteins yielded an AUC of 77%. This is notably higher compared to predictions based solely on age and BMI (around 50%) or knee pain (approximately 57%).

The implementation of this test in clinics is not imminent, despite the promising initial findings, according to Kraus. The research team now faces the task of determining if these results can be reproduced in men and individuals from diverse ethnic backgrounds. Osteoarthritis is more prevalent in women, especially after the age of 50.

Kraus mentioned that following this, there could be potential clinical trials for new treatments. These biomarkers might serve as indicators to assess whether specific medications can halt the progression of osteoarthritis. Should these trials prove successful in animal models, the drugs could then undergo testing in individuals at risk of developing the condition.


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