Scientists ID 4 SSc-ILD subtypes to better predict patient outcomes
Study found differing survival rates for each subgroup
Scientists in China have identified four distinct subtypes of systemic sclerosis-associated interstitial lung disease (SSc-ILD), each characterized by different clinical characteristics, a new study found.
With these four subtypes identified, the team then analyzed outcomes for each subtype and found differing survival rates and factors associated with mortality, which may help better predict and improve patient outcomes, according to researchers.
The new study, “A noval identification of 4 systemic sclerosis – interstitial lung disease subgroups using principal component analysis-based cluster analysis,” was published in BMC Pulmonary Medicine.
Five key clinical and imaging variables identified
In SSc, also known as scleroderma, scar tissue builds up in the skin and internal organs. The lungs are particularly vulnerable, which can lead to interstitial lung disease, or ILD. This disorder is marked by damage to the tissue around the tiny air sacs in the lungs, or alveoli, making breathing difficult.
Lung function tests, clinical exams, and CT scans are established ways to assess SSc-ILD, but they often fail to capture the disease’s variability among patients, the researchers noted. Surgical lung biopsy, which is regarded as the gold standard for ILD classification, is rarely performed in SSc-ILD patients due to the associated risks of complications.
To learn more, a research team in China conducted a cluster analysis using a combination of clinical variables and imaging results to identify subgroups of SSc-ILD patients with similar clinical characteristics. This may allow clinicians to tailor treatments to each patient’s disease manifestations, according to the team.
The researchers retrospectively reviewed the medical records of 103 adults with SSc-ILD, most of whom were women (84%). Nearly all (97.1%) had skin manifestations and tested positive for antinuclear antibodies (96.1%), the self-reactive antibodies (autoantibodies) commonly found in SSc that react against components of the cell’s nucleus. CT scans revealed extensive lung involvement in most patients.
The team extracted five key clinical and imaging variables from patient records. Blood test variables were white blood cell count, the levels of the self-reactive antibody anti-SCL-70, and the C-reactive protein-to-albumin ratio, an inflammation-based marker for mortality. The imaging variable was ILD features based on CT scans. The fifth variable was the Warrick score, a standard measure of the severity of lung involvement, with scores of 15 or more indicating severe lung disease.
Analysis reveals 4 subgroups of SSc-ILD patients
When the scientists input all data into computer algorithms for cluster, or group, analysis, four subgroups of SSc-ILD patients with shared features emerged.
In cluster 1, skin involvement was the most common clinical sign in all 23 patients. Lung function in this group was generally better than in the other clusters. The mean Warrick score was 11.57, with all patients in this group scoring less than 15. About one-third had anti-SCL-70 antibodies, and one-fourth had anti-ACA antibodies.
The most common signs of lung involvement were lung nodules, areas of abnormal growth in the lungs, and traction bronchiectasis, when scarring causes the airways to widen abnormally. The predominant CT scan feature was lymphocytic interstitial pneumonia, a lung disease marked by the presence of numerous white blood cells.
Cluster 2, also with 23 patients, had a higher proportion of men and a longer disease duration than the other clusters. Lung function was poorer, and the mean Warrick score was 23.43, with all patients scoring 15 or higher, “reflecting the severity of lung disease in this group,” the team wrote. Nearly half tested positive for anti-SCL-70 antibodies.
Nearly all patients in this group had traction bronchiectasis. The most dominant CT scan feature was nonspecific interstitial pneumonia (NSIP), characterized by widespread lung scarring and inflammation, alongside usual interstitial pneumonia (UIP), which is marked by more patchy scarring.
[Cluster analysis identified] four homogeneous groups among 103 SSC-ILD patients with significant differences in clinical manifestations, autoantibody patterns, [CT] signs, and prognosis, in order to guide early detection of ILD and precise treatment.
All 20 patients in cluster 3 tested negative for anti-SCL-70 antibodies, but they more commonly tested positive for RF antibody, a self-reactive antibody first found in rheumatoid arthritis, than the other groups. More of these patients also had involvement in the esophagus. The mean Warrick score was lower at 11.52, with all patients presenting with NSIP and none with UIP.
The disease duration in cluster 4 was significantly shorter than in the other clusters, with all testing positive for anti-SCL-70 antibodies. The mean Warrick score was the lowest across all groups at 10.90. All patients had reticular, or mesh-like, patterns in the lungs that is indicative of inflammation and thickening of the lung tissue. All had NSIP and none had UIP.
During the follow-up period, 19 (18.4%) patients died. Mortality in cluster 2 was significantly higher (34.8%) than in clusters 1 (30.4%), 3 (10%), and 4 (3.6%). A separate analysis confirmed that cluster 2 patients had a higher risk of death than those in the other three clusters.
In a survival analysis adjusted for significant clinical variables, albumin level was a protective factor against death in SSC-ILD patients. In contrast, older age and elevated levels of an antibody type called immunoglobulin M (IgM) were risk factors.
While the relationship between IgM and ILD has been reported in previous studies, the exact mechanism is not clear, the team noted.
“We developed a clinical prediction model that combined clinical manifestations, laboratory tests, antibody tests, and [CT] signs,” the researchers wrote. Cluster analysis identified “four homogeneous groups among 103 SSC-ILD patients with significant differences in clinical manifestations, autoantibody patterns, [CT] signs, and prognosis, in order to guide early detection of ILD and precise treatment.”
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