Development and validation of lupus nephritis case definitions using United States veterans affairs electronic health records

Efficacy and Safety of Sodium-Glucose Cotransporter 2 Inhibitors for the Primary Prevention of Cardiovascular, Renal Events, and Safety Outcomes in Patients With Systemic Lupus Erythematosus and Comorbid Type 2 Diabetes: A Population-Based Target Trial Emulation

OBJECTIVE

Patients with systemic lupus erythematosus (SLE) were excluded from sodium-glucose cotransporter 2 inhibitors (SGLT2i) clinical trials. It is unknown whether the cardiorenal benefits of SGLT2i extend to patients with SLE and comorbid type 2 diabetes (T2D).

METHODS

We performed an emulated clinical trial in an insurance-based cohort in the United States, evaluating SGLT2i versus dipeptidyl peptidase-4 inhibitors (DPP4i) for primary prevention of cardiovascular, renal, and other clinical outcomes among patients with both SLE and comorbid T2D. SGLT2i initiators were matched to DPP4i initiators using propensity scores (PSs) based on clinical and demographic factors. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using Cox models.

RESULTS

Outcomes among 2,165 patients starting SGLT2i and 2,165 PS-matched patients starting DPP4i were compared. Over 753.1 (±479.2) mean days, SGLT2i recipients had significantly lower risks of incident acute kidney injury (HR 0.49, 95% CI 0.39-0.63), chronic kidney disease (HR 0.61, 95% CI 0.50-0.76), end-stage renal disease (HR 0.40, 95% CI 0.20-0.80), heart failure (HR 0.72, 95% CI 0.56-0.92), emergency department visits (HR 0.90, 0.82-0.99), and severe sepsis (HR 0.61, 95% CI 0.39-0.94). Risks of all-cause mortality (HR 0.89, 95% CI 0.65-1.21), lupus nephritis (HR 0.67, 95% CI 0.38-1.15), myocardial infarction (HR 0.81, 95% CI 0.54-1.23), stroke (HR 1.03, 95% CI 0.74-1.44), and hospitalizations (HR 0.76, 95% CI 0.51-1.12) did not differ. Genital infection risk (HR 1.31, 95% CI 1.07-1.61) was increased, but urinary tract infection risk (HR 0.90, 95% CI 0.79-1.03) did not differ. No significant difference was observed for diabetic ketoacidosis risk (HR 1.07, 95% CI 0.53-2.14) and fractures (HR 0.95, 95% CI 0.66-1.36).

CONCLUSION

In this emulated clinical trial, treatment with SGLT2i, compared to DPP4i therapy, was associated with significantly reduced risks of several cardiorenal complications among patients with both SLE and T2D.

Sodium-Glucose Cotransporter-2 Inhibitors and Nephritis Among Patients With Systemic Lupus Erythematosus

Importance

Lupus nephritis is a major complication of systemic lupus erythematosus (SLE). Randomized clinical trials have shown nephroprotective and cardioprotective effects of sodium-glucose cotransporter-2 inhibitors (SGLT2is).

Objective

To investigate whether the use of SGLT2is is associated with the onset and progression of lupus nephritis and other kidney and cardiac outcomes in patients with SLE and type 2 diabetes.

Design, Setting, and Participants

This multicenter cohort study used the US Collaborative Network of the TriNetX clinical data platform to identify patients with SLE and type 2 diabetes from January 1, 2015, to December 31, 2022. Data collection and analysis were conducted in September 2023.

Exposures

Individuals were categorized into 2 groups by SGLT2i use or nonuse with 1:1 propensity score matching.

Main Outcomes and Measures

The Kaplan-Meier method and Cox proportional hazards regression models were used to calculate the 5-year adjusted hazard ratios (AHRs) of lupus nephritis, dialysis, kidney transplant, heart failure, and mortality for the 2 groups.

Results

From 31 790 eligible participants, 1775 matched pairs of SGLT2i users and nonusers (N = 3550) were selected based on propensity scores. The mean (SD) age of matched participants was 56.8 (11.6) years, and 3012 (84.8%) were women. SGLT2i users had a significantly lower risk of lupus nephritis (AHR, 0.55; 95% CI, 0.40-0.77), dialysis (AHR, 0.29; 95% CI, 0.17-0.48), kidney transplant (AHR, 0.14; 95% CI, 0.03-0.62), heart failure (AHR, 0.65; 95% CI, 0.53-0.78), and all-cause mortality (AHR, 0.35; 95% CI, 0.26-0.47) than SGLT2i nonusers.

Conclusions and Relevance

In this cohort study of patients with SLE and type 2 diabetes, SGLT2i users had a significantly lower risk of lupus nephritis, dialysis, kidney transplant, heart failure, and all-cause mortality than nonusers. The findings suggest that SGLT2is may provide some nephroprotective and cardioprotective benefits.

Natural language processing to identify lupus nephritis phenotype in electronic health records

BACKGROUND

Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one of the major disease manifestations of SLE for organ damage and mortality, is a key component of lupus classification criteria. Accurately identifying lupus nephritis in electronic health records (EHRs) would therefore benefit large cohort observational studies and clinical trials where characterization of the patient population is critical for recruitment, study design, and analysis. Lupus nephritis can be recognized through procedure codes and structured data, such as laboratory tests. However, other critical information documenting lupus nephritis, such as histologic reports from kidney biopsies and prior medical history narratives, require sophisticated text processing to mine information from pathology reports and clinical notes. In this study, we developed algorithms to identify lupus nephritis with and without natural language processing (NLP) using EHR data from the Northwestern Medicine Enterprise Data Warehouse (NMEDW).

METHODS

We developed five algorithms: a rule-based algorithm using only structured data (baseline algorithm) and four algorithms using different NLP models. The first NLP model applied simple regular expression for keywords search combined with structured data. The other three NLP models were based on regularized logistic regression and used different sets of features including positive mention of concept unique identifiers (CUIs), number of appearances of CUIs, and a mixture of three components (i.e. a curated list of CUIs, regular expression concepts, structured data) respectively. The baseline algorithm and the best performing NLP algorithm were externally validated on a dataset from Vanderbilt University Medical Center (VUMC).

RESULTS

Our best performing NLP model incorporated features from both structured data, regular expression concepts, and mapped concept unique identifiers (CUIs) and showed improved F measure in both the NMEDW (0.41 vs 0.79) and VUMC (0.52 vs 0.93) datasets compared to the baseline lupus nephritis algorithm.

CONCLUSION

Our NLP MetaMap mixed model improved the F-measure greatly compared to the structured data only algorithm in both internal and external validation datasets. The NLP algorithms can serve as powerful tools to accurately identify lupus nephritis phenotype in EHR for clinical research and better targeted therapies.

Association between systemic lupus erythematosus and myasthenia gravis: A population-based National Study

BACKGROUND

Systemic lupus erythematosus (SLE) and myasthenia gravis (MG) are autoimmune diseases. Previous case reports and case series suggest an association may exist between these diseases, as well as an increased risk of SLE after thymectomy for MG. We undertook this study to determine whether SLE and MG were associated in large cohorts.

METHODS

We searched the IBM Watson Health Explorys platform and the Department of Veterans Affairs Million Veteran Program (MVP) database for diagnoses of SLE and MG. In addition, we examined subjects enrolled in the Lupus Family Registry and Repository (LFRR) as well as controls for a diagnosis of MG.

RESULTS

Among 59,780,210 individuals captured in Explorys, there were 25,750 with MG and 65,370 with SLE. 370 subjects had both. Those with MG were >10 times more likely to have SLE than those without MG. Those with both diseases were more likely to be women, African American, and at a younger age than MG subjects without SLE. In addition, the MG patients who underwent thymectomy had an increased risk of SLE compared to MG patients who had not undergone thymectomy (OR 3.11, 95% CI: 2.12 to 4.55). Autoimmune diseases such as pernicious anemia and miscellaneous comorbidities such as chronic kidney disease were significantly more common in MG patients who developed SLE. In the MVP, SLE and MG were also significantly associated. Association of SLE and MG in a large SLE cohort with rigorous SLE classification confirmed the association of SLE with MG at a similar level.

CONCLUSION

While the number of patients with both MG and SLE is small, SLE and MG are strongly associated together in very large databases and a large SLE cohort.

Infection-related hospitalisation in young adults with systemic lupus erythematosus: data from the National Inpatient Sample

INTRODUCTION

Care of young adults with SLE (YA-SLE, 18-24 years) is challenging due to major life transitions co-occurring with chronic healthcare needs. Studies have demonstrated poorer outcomes in the post-transition period. Epidemiological studies focused on serious infection-related hospitalisation (SIH) in YA-SLE are lacking.

METHODS

We used National Inpatient Sample from 2010 to 2019 to study the epidemiology and outcomes of SIH for five common infections in SLE, namely sepsis, pneumonia, urinary tract infections, skin and soft tissue infections, and opportunistic infections. For time trends, we extended the dataset to cover 2000-2019. The primary outcome was the rate of SIH in YA-SLE compared with adults (25-44 years) with SLE and with young adults without SLE (YA-no SLE).

RESULTS

From 2010 to 2019, we identified 1 720 883 hospital admissions with SLE in patients aged ≥18 years. Rates of SIH were similar in young adults and adults with SLE (15.0% vs 14.5%, p=0.12), but considerably higher than in the YA-no SLE group (4.2%, p<0.001). Among SLE with SIH, sepsis followed by pneumonia was the most common diagnosis. Significantly higher proportions of SIH among young adults than adults with SLE were comprised of non-white patients, belonged to the lowest income quartile and had Medicaid. However, only race/ethnicity was associated with SIH among YA-SLE. There was a higher prevalence of comorbid lupus nephritis and pleuritis among young adults compared with adults with SLE and SIH, and both comorbidities were associated with SIH in YA-SLE. Increasing rates of SIH, driven by sepsis, were seen over time.

DISCUSSION

YA- SLE had similar rates of SIH to adults with SLE. While hospitalised YA-SLE differed sociodemographically from SLE adults and YA-no SLE, only race/ethnicity was associated with SIH in the YA-SLE group. Lupus nephritis and pleuritis were associated with higher SIH in YA-SLE. Among SLE with SIH, increasing trends of sepsis deserve further study.

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes

BACKGROUND AND OBJECTIVES

Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of patients with SLE. The highest-performing phenotypes were then evaluated across institutions in PEDSnet, a national health care systems network of >6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (n=350) and noncases (n=350).

RESULTS

Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included two or more in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, one or more hydroxychloroquine exposures, and either three or more qualifying diagnosis codes separated by ≥30 days or one or more diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 100% (95% confidence interval [95% CI], 99 to 100), specificity was 92% (95% CI, 88 to 94), positive predictive value was 91% (95% CI, 87 to 94), and negative predictive value was 100% (95% CI, 99 to 100). Lupus nephritis diagnostic criteria included either three or more qualifying lupus nephritis diagnosis codes (or SLE codes on the same day as glomerular/kidney codes) separated by ≥30 days or one or more SLE diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 90% (95% CI, 85 to 94), specificity was 93% (95% CI, 89 to 97), positive predictive value was 94% (95% CI, 89 to 97), and negative predictive value was 90% (95% CI, 84 to 94). Algorithms identified 1508 children with SLE at PEDSnet institutions (537 with lupus nephritis), 809 of whom were seen in the past 12 months.

CONCLUSIONS

Electronic health record-based algorithms for SLE and lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions.