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626 The trajectory of Multimorbidity in patients with Systemic Lupus Erythematosus in the United States
  1. Ali Duarte-Garcia,
  2. Maria Stevens,
  3. Herbert Heien,
  4. Gabriel Figueroa-Parra,
  5. Jose Meade,
  6. Molly M Jeffery,
  7. Uma Thanarajasingam,
  8. Cynthia Crowson and
  9. Rozalina McCoy
  1. All authors from Mayo Clinic


Background/Purpose The presence of multiple chronic conditions (multimorbidity) is associated with disability and premature death. We determined the trajectory of multimorbidity in SLE compared to the general population.

Methods An SLE cohort was assembled using OptumLabs Datawarehouse (OLDW) from 1/2006-9/2015. SLE cases were identified using > 3 SLE ICD-9 codes separated by > 30 days; the date of the third SLE code was considered the index date. Incident SLE was identified by requiring 12 months without SLE diagnostic codes. Patients with SLE were matched to non-SLE comparators on age, sex, race, region, and enrollment date. Diagnosis codes from the period between enrollment and the end of follow-up (disenrollment or 9/30/2015) were used to determine the presence of comorbidities. We assembled 57 chronic condition categories based on previously described 44 categories (England, B. ARD 2020). The 13 additional categories were added based on the SLICC/ACR damage index (SDI) or otherwise considered relevant to SLE. Two or more ICD-9 codes at least 30 days apart were used to define a comorbidity. We defined multimorbidity as the presence of > 2 comorbidities (excluding SLE). Conditional logistic regression models were performed to estimate the prevalence of multimorbidity. The trajectory of multimorbidity in people with SLE (vs without SLE) was estimated utilizing generalized estimating equations. We looked at overall trajectory after index date, expanding the observation time one year before index date, and excluding silent conditions to mitigate surveillance bias (hypertension, hypothyroidism, etc.)

Odds ratios (OR) and estimates of the linear coefficient and 95% confidence intervals (CI) were reported.

Results A total of 34,893 SLE patients were matched to 34,893non-SLE comparators. Of these, 13,531 were incident cases. The mean age was 48 (SD 14.2) years, and 90.6% were female. 66.4% were White, 18.4% Black, 3.4% Asian, and 18.4% Hispanic. From enrollment to the index date, the mean observation time was 2.3 years (SD: 2.4) and 4.4 years (SD: 2.6) for the incident cohort. Multimorbidity was present in 72% of SLE vs. 47% of non-SLE subjects (OR 4.3; 95%CI: 4.1-4.5). Patients with SLE had 4.5 comorbidities compared to 2.4 for non-SLE subjects (OR: 1.91 (1.89-1.94).

Compared to baseline, multimorbidity increased among the incident cases, multimorbidity frequency was higher in incident SLE (vs non-SLE) throughout the follow-up compared to baseline (β: 1.85, 95%CI 1.79, 1.91). The rate of accrual chronic conditions was significantly higher in SLE than in non-SLE (figure 1A; β: 0.63; 95%CI: 0.60, 0.65). Patients with lupus had accelerated multimorbidity accrual after excluding silent conditions (figure 1B). Patients with SLE had increased multimorbidity even one year before SLE onset (figure 1C).

Conclusion In this nationwide commercial database insurance study, patients with SLE were four times more likely to suffer from multimorbidity than the general population. Trajectory analysis shows that multimorbidity progresses more rapidly in patients with SLE than those without SLE and may begin before SLE onset.

Abstract 626 Figure 1

Predicted burden of multimorbidity in incident SLE compared with patients without SLE after diagnosis. Panel A, primary analytical approach requiring 1 year in the data set without SLE diagnostic codes chronic conditions. Panel B, similar analytical approach removing silent conditions. Panel C, restricting the population to individuals with at least 2 years of data prior to index date and beginning follow-up at 1 years before the index date.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: .

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