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S2A:5 Development and validation of a score to predict the risk of severe infection in sle
  1. B Segura1,
  2. I Rúa-Figueroa2,
  3. JM Pego-Reigosa3,
  4. V Del Campo4,
  5. D Isenberg5 and
  6. A Rahman5
  1. 1Insular University Hospital, Rheumatology Department, Las Palmas de Gran Canaria, Spain
  2. 2Doctor Negrín University Hospital, Rheumatology Department, Las Palmas de Gran Canaria, Spain
  3. 3Biomedical Research Institute of Vigo (IBIV), University Hospital Complex of Vigo, Rheumatology Department, Vigo, Spain
  4. 4Biomedical Research Institute of Vigo (IBIV), University Hospital Complex of Vigo, Preventive Medicine Department, Vigo, Spain
  5. 5University College London Hospital, Centre for Rheumatology, Department of Medicine, London, UK


Purpose To develop a predictive risk score that assesses the probability of severe infection in SLE patients and to test it in an independent cohort.

Methods The SLE severe infection score (SLESIS) was developed using data from the RELESSER (Spanish Society of Rheumatology Lupus Registry) cohort of 3658 SLE patients using a Cox regression model for repeated events (Andersen-Gill) The results were expressed as hazard ratio (HR) of developing one serious infection/1000 patient-years for patients with the risk factor compared to those without that factor. SLESIS for an individual patient is the sum of the HR values of all factors present at that time.

SLESIS was validated using retrospective data from the UCLH (University College London Hospital) cohort including 699 SLE patients.

Results The risk factors included in SCORE and their HR calculated from RELESSER data are shown in table 1. From 699 SLE UCLH patients, 98 (14%) developed serious infection. We compared these patients with 111 SLE controls who never suffered serious infection. The characteristics of the SLE infection and SLE non-infection groups are summarised in table 2.

Median SLESIS at diagnosis in patients with infection was 4.27 (IQR 3.18) which was significantly higher than in the control group (Median 2.55, IQR 3.79) (z=3.341; p=0.0008). Median SLESIS just before infection was 5.3 (IQR 3.68) which was significantly higher compared to SLESIS at diagnosis (z=−5.733; p≤0.001) in those patients or SLESIS measured at the same time post-diagnosis in the non-infected group (Median 3.73 RI 3.7) (z=−4.765, p≤0.001).

By Receiver Operator Characteristic analysis, we defined three possible cut-offs to distinguish patients with and without infection. For SLESIS just before infection, the area under the ROC curve was 0.75 (CI: 0.66 to 0.84) and the three selected cut offs (3.67, 3.79, 4.24) reached a sensitivity of 90% and specificity of 50%.

Conclusion We have developed a score for predicting risk of serious infection in SLE and validated it in an independent cohort. Given the potential mortality from such infections, SLESIS could be clinically useful though the moderate sensitivity and specificity necessitate caution and further prospective studies.

Abstract S2A:5 Table 1
Abstract S2A:5 Table 2
  • Severe infection
  • Prevention

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