Systemic Lupus Erythematosus Risk Probability Index: ready for routine use? Results from a Chinese cohort

Performance of the systemic lupus erythematosus risk probability index (SLERPI) in the Egyptian college of rheumatology (ECR) study cohort

OBJECTIVES

This study aimed to evaluate the performance of systemic lupus erythematosus Risk Probability Index (SLERPI) in Egyptian patients with SLE using a national rheumatology database.

METHODS

The Egyptian College of Rheumatology (ECR) database comprised of 1,162 patients with SLE and 4,327 with miscellaneous rheumatological diseases who were recruited from the Rheumatology Departments across the country. The diagnosis of SLE was established by expert rheumatologists. Variables of the SLERPI were extracted and recorded as present or absent for each patient. The absolute value for the SLERPI score was calculated for each patient, and the diagnosis of SLE was accounted for if the score was greater than 7 points.

RESULTS

Of 1,162 SLE patients evaluated, 1,031 (88.7%) patients were diagnosed with SLE according to the SLERPI, with an average score of 13.1 (3.8). Differences in the 14 SLERPI variables were significant between the SLE-SLERPI groups, except for the presence of leukopenia and positive ANA. As a score reduction item, the SLE-SLERPI > 7 group had lower interstitial lung diseases. Patients diagnosed with SLE according to SLERPI had significantly higher disease activity (p < 0.001), and this group more commonly received corticosteroids and mycophenolate mofetil. Compared to other miscellaneous rheumatological groups, all 14 SLERPI items are indeed more common in the SLE group. In terms of the overall performance of SLERPI in the diagnosis of SLE, the accuracy of SLERPI was 91.9% (95% CI 90.9%-92.9%), with a specificity of 96.95% and sensitivity of 86.9%. SLERPI showed that accuracy went up to 93.3% (95%CI 92.4%-94.2%), with a specificity of 94.9% and a sensitivity of 91.6% when patients with connective tissue diseases were taken out of the study.

CONCLUSION

Using a large cohort of SLE, the SLERPI revealed excellent diagnostic efficacy and specificity. The use of SLERPI in clinical practice may contribute to improved patient diagnosis and prognosis. Key Points • SLERPI's performance has high diagnostic efficiency in Egyptian SLE patients. • SLERPI score can efficiently distinguish patients with SLE from other CTDs. • Within the SLERPI score, interstitial lung disease is the lowest predictor of SLE.

Performance of the Systemic Lupus Erythematosus Risk Probability Index (SLERPI) in a cohort of Colombian population

OBJECTIVE

To evaluate the performance of the Systemic Lupus Erythematosus Risk Probability Index (SLERPI) in Colombian patients with systemic lupus erythematosus (SLE).

METHODS

The Colombian cohort included 435 SLE patients and 430 controls with other autoimmune diseases (ADs). Clinical and serological data were collected, and SLE was indicated by SLERPI scores > 7. The American College of Rheumatology (ACR)-1997, Systemic Lupus International Collaborating Clinics (SLICC)-2012, and European League Against Rheumatism (EULAR)/ACR-2019 criteria were used as reference standards. The impact of overt polyautoimmunity (PolyA) on SLERPI performance was assessed. Additionally, multivariate lineal regression analysis was performed to evaluate the contribution of SLERPI features to the overall SLERPI score.

RESULTS

SLE patients had higher SLERPI scores (P < 0.0001), with almost 90% meeting "definite" lupus criteria. Main factors influencing SLERPI included immunological disorder (β:44.75, P < 0.0001), malar/maculopapular rash (β:18.43, P < 0.0001), and anti-nuclear antibody positivity (β:15.65, P < 0.0001). In contrast, subacute cutaneous lupus erythematosus/discoid lupus erythematosus (β:2.40, P > 0.05) and interstitial lung disease (β:-21.58, P > 0.05) were not significant factors to the overall SLERPI score. SLERPI demonstrated high sensitivity for SLE, both for the overall SLE group and for those without overt PolyA (95.4% and 94.6%, respectively), but had relatively low specificity (92.8% and 93.7%, respectively). The model showed high sensitivity for hematological lupus (98.8%) and lupus nephritis (96.0%), but low sensitivity for neuropsychiatric lupus (93.2%). Compared to the ACR-1997, SLICC-2012 and EULAR/ACR-2019 criteria, SLERPI yielded the highest sensitivity and lowest specificity.

CONCLUSION

SLERPI efficiently identified SLE patients in a Colombian cohort, showing high sensitivity but low specificity. The model effectively distinguishes SLE patients, even in the presence of concurrent overt PolyA. Key Points •SLERPI has a high sensitivity, but low specificity compared to ACR-1997, SLICC-2012 and EULAR/ACR-2019 criteria in the Colombian population. •Within the SLERPI score, immunological disorder, malar/maculopapular rash, and anti-nuclear antibody positivity are the strongest predictors of SLE. •SLERPI model can efficiently distinguish patients with SLE, regardless of concomitant overt PolyA. •SLERPI demonstrates high sensitivity in identifying hematological and nephritic subphenotypes of SLE.

Is Idiopathic Granulomatous Mastitis a Subgroup of Systemic Lupus Erythematosus? A Preliminary Study

Objective: The study aimed to use the systemic lupus erythematosus risk probability index (SLERPI) to assess if patients with idiopathic granulomatous mastitis (IGM) meet the criteria for systemic lupus erythematosus (SLE). Methods: A total of 62 patients with IGM and 55 age- and sex-matched healthy controls (HC) were enrolled. The study included patients who were over 18 years old and had been diagnosed with IGM using a true-cut biopsy. The participants' demographic, clinical, and laboratory data were recorded in detail. The presence of autoantibodies, such as RF, CCP, C3, C4, ANA, ENA profile, and Anti-dsDNA was documented. For the detection of SLE in IGM patients, we used the SLERPI (SLE risk probability index). Results: A total of 62 patients diagnosed with idiopathic granulomatous mastitis (age 35.22 ± 8.34, BMI 27.15 ± 3.41) were compared to 55 healthy controls (age 32.54 ± 8.67, BMI 26.97 ± 3.54). The present study assessed the performance of SLERPI in IGM, and SLERPI positivity was observed in 12 out of 62 (19.4%) IGM patients. There was a significant difference in arthritis and ANA levels in the SLERPI subgroups (p < 001). Conclusions: The SLERPI index can be utilized to identify patients suspected of having systemic lupus erythematosus (SLE) in the IGM cohort.

Case report: Case analysis of multiple sclerosis with preclinical systemic lupus erythematosus presenting as rare bilateral horizontal gaze palsy

We present an analysis of a case initially manifesting as bilateral horizontal gaze palsy, eventually diagnosed as multiple sclerosis (MS) with preclinical systemic lupus erythematosus (p-SLE). The patient, a 25-year-old male, exhibited restricted movement in both eyes. Cranial MRI revealed multiple demyelinating lesions; serum analyses indicated elevated levels of antinuclear antibodies (ANA), anti-Sm antibodies, and anti-nRNP antibodies. Oligoclonal bands were identified in the cerebrospinal fluid. Neurophysiological assessments demonstrated damage to the optic, auditory, and facial nerves. Given the clinical presentation, laboratory findings, and the progression of the disease, the final diagnosis was confirmed as MS associated with p-SLE. The onset of MS with oculomotor disturbances is rare and may be easily confused with neuropsychiatric systemic lupus erythematosus (NPSLE). Furthermore, the differentiation of p-SLE from undifferentiated connective tissue disease (UCTD) in the early stages presents significant challenges. Early identification of risk factors and close monitoring of disease activity is crucial for an accurate diagnosis.

The Multiple Faces of Systemic Lupus Erythematosus: Pearls and Pitfalls for Diagnosis

Systemic lupus erythematosus is the prototype multisystem autoimmune disorder characterised by a broad spectrum of organ involvement and a multitude of laboratory abnormalities. Clinical heterogeneity, unpredictable course and lack of pathognomonic clinical and serological features pose a considerable challenge in the diagnosis of SLE. The latter remains largely clinical, typically accompanied however by features of serologic autoimmunity, which are characteristic for the disease. Despite significant improvements in treatment strategies, an early diagnosis often continues to be an unmet need, as the median reported delay from symptom onset to SLE diagnosis is approximately 2 years. Classification criteria are usually used to support the diagnosis, yet with significant caveats. In this article, we provide an updated review of the clinical presentation of lupus and give clues for an accurate diagnosis.

Classifying systemic lupus erythematosus using laboratory items alone: a preliminary study

OBJECTIVES

To explore the performance of laboratory items alone in systemic lupus erythematosus (SLE) classification.

METHODS

Our cohort consisted of 352 and 385 (control) patients with and without SLE. This study evaluated the performance of the American College of Rheumatology (ACR)-1997, Systemic Lupus International Collaborating Clinics (SLICC)-2012, European League Against Rheumatism (EULAR)/ACR-2019, and Systemic Lupus Erythematosus Risk Probability Index (SLERPI) using laboratory items alone, including blood and urine test results.

RESULTS

The median ratio of laboratory items/total items was 66.7%, 75.0%, 60.4%, and 77.4% in ACR-1997, SLICC-2012, EULAR/ACR-2019, and SLERPI, respectively. After including laboratory items alone, the sensitivity of ACR-1997, SLICC-2012, EULAR/ACR-2019, and SLERPI was 31.3% (95% confidence interval [CI]: 26.4%-36.4%), 79.8% (95% CI: 75.3%-83.9%), 75.9% (95% CI: 71.0%-80.2%), and 85.2% (95% CI: 81.1%-88.8%), respectively. We referenced the SLERPI and removed the additional restrictions, i.e., SLICC-2012 criteria only needs to fulfill at least four items (mSLICC-2012) and EULAR/ACR-2019 criteria needs to have ≥ 10 points (mEULAR/ACR-2019) to qualify for SLE classification. The mSLICC-2012 and mEULAR/ACR-2019 criteria, including laboratory items alone, newly identified 13 and 25 patients, respectively. Based on laboratory items alone, the combination of mSLICC-2012, mEULAR/ACR-2019, and SLERPI identified 348 patients with an improved sensitivity of 90.6% (95% CI: 87.1%-93.5%). Patients, who were classified according to the mEULAR/ACR-2019 criteria, all met the other criteria.

CONCLUSION

Incorporating laboratory items alone was clinically feasible to help identify SLE. SLERPI and SLICC-2012, using laboratory items alone, were more worthwhile to promote in the clinic compared with EULAR/ACR-2019. Key Points • Laboratory items play a crucial role in the SLE classification criteria, and incorporating laboratory items alone was clinically feasible to help in the identification of SLE. • The SLERPI and SLICC-2012, using laboratory items alone, were more worthwhile to promote in the clinic compared with EULAR/ACR-2019, and the combination of the two could further improve the sensitivity. • The relative simplicity of evaluating laboratory indices may help nonrheumatologists and inexperienced rheumatologists to identify SLE more quickly, thereby reducing the risk of delayed diagnosis in patients.