Predictive models of infection in patients with systemic lupus erythematosus: A systematic literature review

Development and Validation of Nosocomial Bacterial Infection Prediction Models for Patients With Systemic Lupus Erythematosus

BACKGROUND

Hospital-acquired bacterial infections are associated with high morbidity and mortality rates in patients with systemic lupus erythematosus (SLE). This study aimed to develop and validate predictive models for the risk of hospital-acquired bacterial infections in patients with SLE.

METHODS

A historical cohort study was designed for development, and another bidirectional cohort study was used for external validation. The risk of bacterial infection was assessed upon admission and after 5 days of hospitalization. Predictor selection employed the least absolute shrinkage and selection operator (LASSO) techniques. Multiple imputations were used to handle missing data. Logistic regression models were applied, and the properties of discrimination, calibration, and decision curve analysis were evaluated.

RESULTS

The development cohort comprised 1686 patients and 237 events (14.1%) from 3 tertiary hospitals. The external validation cohort included 531 patients and 84 infection outcomes (15.8%) from 10 hospital centers in Colombia (secondary and tertiary level). The models applied at admission and after 120 hours of stay exhibited good discrimination (AUC > 0.74). External validation demonstrated good performance among patients from the same tertiary institutions where the models were developed. However, geographic validation at other institutions has been suboptimal.

CONCLUSIONS

Two predictive models for nosocomial bacterial infections in patients with SLE are presented. All infection prevention recommendations should be maximized in patients at moderate/high risk. Further validation studies in diverse contexts, as well as clinical impact trials, are necessary before potential applications in research and clinical care.

SLESIS-R: an improved score for prediction of serious infection in patients with systemic lupus erythematosus based on the RELESSER prospective cohort

OBJECTIVE

To develop an improved score for prediction of severe infection in patients with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and to validate it in a large multicentre lupus cohort.

METHODS

We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review. Performance was analysed using the C-statistic and the area under the receiver operating characteristic curve (AUROC). Internal validation was carried out using a 100-sample bootstrapping procedure. ORs were transformed into score items, and the AUROC was used to determine performance.

RESULTS

A total of 1459 patients who had completed 1 year of follow-up were included in the development cohort (mean age, 49±13 years; 90% women). Twenty-five (1.7%) had experienced ≥1 severe infection. According to the adjusted multivariate model, severe infection could be predicted from four variables: age (years) ≥60, previous SLE-related hospitalisation, previous serious infection and glucocorticoid dose. A score was built from the best model, taking values from 0 to 17. The AUROC was 0.861 (0.777-0.946). The cut-off chosen was ≥6, which exhibited an accuracy of 85.9% and a positive likelihood ratio of 5.48.

CONCLUSIONS

SLESIS-R is an accurate and feasible instrument for predicting infections in patients with SLE. SLESIS-R could help to make informed decisions on the use of immunosuppressants and the implementation of preventive measures.

Major infections in newly diagnosed systemic lupus erythematosus: an inception cohort study

Objective

To evaluate the risk of major infections and the relationship between major infections and mortality in patients with newly diagnosed SLE.

Methods

A newly diagnosed (<3 months) hospitalised Systemic Lupus Inception Cohort (hSLIC) in our centre during 1 January 2013 and 1 November 2020 was established. All patients were followed up for at least 1 year or until death. Patient baseline characteristics were collected. Major infection events were recorded during follow-up, which were defined as microbiological/clinical-based diagnosis treated with intravenous antimicrobials. The cohort was further divided into a training set and a testing set. Independent predictors of major infections were identified using multivariable logistic regression analysis. Kaplan-Meier survival analyses were conducted.

Results

Among the 494 patients enrolled in the hSLIC cohort, there were 69 documented episodes of major infections during the first year of follow-up in 67 (14%) patients. The major infection events predominantly occurred within the first 4 months since enrolment (94%, 65/69) and were associated with all-cause mortality. After adjustments for glucocorticoid and immunosuppressant exposure, a prediction model based on SLE Disease Activity Index >10, peripheral lymphocyte count <0.8×10⁹/L and serum creatinine >104 µmol/L was established to identify patients at low risk (3%–5%) or high risk (37%–39%) of major infections within the first 4 months.

Conclusions

Newly onset active SLE is susceptible to major infections, which is probably due to underlying profound immune disturbance. Identifying high-risk patients using an appropriate prediction tool might lead to better tailored management and better outcome.

A Prospective Study of Cytomegalovirus-Specific Cell-Mediated Immune Monitoring and Cytomegalovirus Infection in Patients With Active Systemic Lupus Erythematosus Receiving Immunosuppressants

Background

The effects of cytomegalovirus (CMV)-specific cell-mediated immunity (CMI) on CMV infection in patients with autoimmune diseases receiving immunosuppressants have not been explored.

Methods

Patients with active systemic lupus erythematosus (SLE) were preemptively monitored for clinically significant CMV infection (CsCMVI; defined as plasma CMV DNA loads >3 log10 IU/mL). CMV-specific CMI was assessed using an enzyme-linked immunosorbent assay (QuantiFERON-CMV [QF]) before as well as 1 and 3 months after intense immunosuppressive therapy.

Results

The study included 55 patients with active SLE; patients were a mean age (SD) of 34 (13) years and had a median SLE Disease Activity Index 2000 score (SD) of 14 (8), and 93% were female. Most patients had renal involvement (67%), received methylprednisolone (93%), and were CMV-seropositive (95%). Thirteen (23.6%) patients developed CsCMVI. Among patients with active SLE who were QF-negative (QF-) and QF-positive (QF+) before receiving immunosuppressive therapy, 28.6% and 25% developed CsCMVI, respectively (P = .69). However, 1 month postimmunosuppression, more QF- than QF+ patients developed CsCMVI (44.4% vs 11.8%; P = .03; adjusted hazard ratio, 4.97; 95% CI, 1.07-23.10; P = .04).

Conclusions

Patients with active SLE and low CMV-specific T-cell responses could develop CMV infection after receiving immunosuppressants. Further studies should focus on CMV-specific CMI among patients with autoimmune diseases.