Inclusion of Non-Criteria Features to SLE Classification Improves Diagnostic Accuracy

Researchers identified criteria and non-criteria features associated with SLE, which can be used in classification criteria.

The inclusion of non-criteria features of systemic lupus erythematosus (SLE) to current classification guidelines can improve diagnostic capacity, according to study results presented at the European League Against Rheumatism (EULAR) 2020 E-Congress, held online from June 3 to 6, 2020.

Classification criteria from the American College of Rheumatology (ACR)-1997, the Systemic Lupus Collaborating Clinics (SLICC)-2012, and EULAR/ACR-2019 classify nonoverlapping groups of patients with SLE. Investigators aimed to evaluate additional features of SLE, which could be used in conjunction with existing criteria to improve diagnostic performance.

Individual items from all 3 classification criteria were analyzed along with non-criteria disease features in a population of 800 adults with a 1:1 ratio of SLE or rheumatologic diseases (control participants). The classification performance of each criteria was analyzed alone and in combination with additional features.

The accuracy of the EULAR/ACR-2019 criteria for SLE classification was the highest (diagnostic odds ratio [DOR], 243.2), followed by the SLICC-2012 criteria (DOR, 157.3) and the ACR-1997 criteria (DOR, 78.8).

Compared to the ACR-1997 criteria alone (area under the curve [AUC], 0.87), inclusion of features such as maculopapular rash, alopecia, and hypocomplementemia significantly enhanced the model predictive capacity of the ACR-1997 classification criteria (AUC, 0.95). Inclusion of photosensitivity to the SLICC-2012 and EULAR/ACR-2019 criteria vs the criteria alone also significantly increased the predictive capacity for SLE. For the SLICC-2012 criteria, inclusion of photosensitivity increased the AUC from 0.91 to 0.94; the AUC associated with the EULAR/ACR-2019 criteria increased from 0.91 to 0.96.

Raynaud phenomenon/livedo reticularis, anti-ribonucleoprotein antibodies, splenomegaly, and myocarditis, which represent disease features not included in current classification criteria, were also independently associated with SLE, and improving the model predictive capacity of the criteria.

“We identified a number of criteria and non-criteria features which can be used in combination with the existing sets of criteria to increase classification of SLE patients in clinical practice,” the researchers concluded. “Photosensitivity could be considered as an additional feature to improve sensitivity of the recent classification criteria.”

Disclosures: Several study authors reported affiliations with the pharmaceutical industry. Please see the original reference for a full list of disclosures.


Adamichou C, Genitsaridi I, Nikolopoulos D, et al. Penalized regression analysis identifies criteria and non-criteria features that may increase the accuracy of existing sets of criteria for classifying systemic lupus erythematosus (SLE). Presented at: EULAR 2020 E-Congress; June 3-6, 2020. Abstract THU0245.