A real-world study on the association of clinical characteristics of systemic lupus erythematosus with flare

Systemic lupus erythematosus (SLE) is an autoimmune disorder affecting multiple organs and leading to diverse features. It is reported to be at a two to threefold higher risk of death in SLE than the general population.1 Common causes of death include infection, cardiovascular disease, and renal disease.2 The exact pathogenetic mechanisms of SLE are yet unclear. Since the clinical presentation is known to vary across geographical locations, genders, and ethnicity, researches from various sites covering different population groups can help gain valuable insight regarding clinical characteristics of the disease worldwide as well as in particular groups.3 Lupus takes a chronic course with remitting and relapsing patterns.4, 5 Furthermore, repeated flares can lead to chronic damage accrual, especially for lupus nephritis patients. Hence, instituting measures to ensure prompt diagnosis of flares will protect against damage development.6, 7 Therefore, it may help clinical management to further understand the unique characteristics associated with flares during the course of lupus. And a real-world study is useful in reflecting on the real situations in the clinical setting. SLE patients, who visited the inpatients department (IPD) and outpatient department (OPD) of the Department of Rheumatology and Immunology at First Affiliated Hospital of Kunming Medical University and fulfilled the inclusion criteria mentioned below, were enrolled for the study. Patients who were newly diagnosed and those already under treatment were both recruited in the study. Patients who did not show up for follow-up visits during the study period were defined as drop-outs. This study fulfills the recommendations put forth by the Institutional Review Board of Kunming Medical University. All patients underwent regular history taking and physical examinations (all clinical data collected are shown in Table 1). Patients who experienced at least one episode of flare were recorded as flare, and patients without any episode of flare during the observation period were recorded as censored. Features specific to SLE were noted and definitions were accepted and incorporated by SLICC in their 2012 classification criteria for SLE.8 ANA was examined with the indirect immunofluorescence method with Hep-2 cells as substrates. Anti-dsDNA antibody was also detected using indirect immunofluorescence method and anti-Smith antibody was detected by western blot. Hypocomplementemia was defined as the presence of either low C3 or C4 or both. According to the reference value of the test, low C3 was defined as a serum level less than 0.7 g/L as well as C4 below 0.1 g/L as low C4. Disease activity was measured by SLEDAI-2K scores.9 For research, a score of 3 or 4 has been used as an appropriate cutoff to differentiate active versus inactive disease.10, 11 For patients with active disease at baseline and improved SLEDAI-2K scores in subsequent visits, the minimum SLEDAI-2K score in follow-up was considered as the new baseline for re-evaluating flare. SLEDAI-2K scores ≥3 points increase in subsequent visits from new baseline scores was defined as flare, and the period from the new baseline to the flare was calculated as time to flare.12 Statistical software IBM SPSS version 26 was used for analysis. A p value of <.05 was taken to be statistically significant. Kaplan–Meier analysis was used to estimate the difference in time to flare between binary variables. Univariate analysis with log-rank test was done to seek potential factors affecting flare. Multivariate analysis with COX proportional hazards regression was carried out to identify adjusted predictors for the occurrence of flare. Data were collected from 199 patients with ages ranging from 18 to 59 years old (31.9 ± 9.5), out of which 94.97% (189) were female and 5.03%10 were male. A detailed description of the patient's clinical characteristics and treatments at baseline has been produced in Table 1. Among all 199, the flare was seen in 31.7% (63) patients, whereas 68.3% experienced no flare during the study period (585 patient-days), and the average follow-up duration was 159.5 days. The predicted percentage with the flare at 182 and 365 days was 21.4% and 56.5% (shown in Figure 1A). Gender (p = .016) and anti-dsDNA antibody (p = .042) were revealed to be potentially significant predictors of flare, and acute rash (p = .072) came close to being a potential predictor of flare. (Comparison of time to flare among factors is shown in Figure 1B–D). (Shown in Table S1). Potential predictors of time to flare identified by the Kaplan–Meier analysis. Acute rash, anti-dsDNA antibody, and gender associated with flare were plugged into the COX regression model as variation, time to flare/censor was set as time, and flare was set as status. Acute rash (p = .026) and anti-dsDNA antibody (p = .047) were found to be independent predictors of flare in lupus patients. On the other hand, the male gender (p = .042) was found to be more susceptible to flare (shown in Table S2). In this study, as time extension, the drop-out rate increased. A high drop-out rate could be the result of this being a real-world study in which patients were not strictly advised to follow-up at a fixed time. In natural clinical working in our IPD, patients with active or severe disease or suffer from new symptom(s) usually are asked to come back to the clinic every month after discharge, as well as patients with the mild disease come back every 3 months, and patients in remission visit every 6–12 months, or go to the local hospital to complete visit. Hence, the high drop-out rate in this study may result from that most patients in remission make less frequent visits during follow-up, or go to local hospitals. Even so, drop-outs due to non-adherence are concerning, in that non-compliant behavior may increase the risk for flares and morbidity in SLE.13 Physicians should devote more attention to counseling non-compliant patients to ensure better follow-up and management. In this study, acute rash conferred two times higher risk of developing flare. This was similar to a study done by Nikpour et al.14 And we found an anti-dsDNA antibody to be associated with a twofold higher risk of developing flare earlier in the course of the disease. Peng et a found the anti-dsDNA antibody to be a potential predictor of flare in univariate analysis.15 A prospective study conducted by Petri et al. found baseline anti-dsDNA antibodies to be associated with only hematological flares 1 year after the start of the study, but not with global flares.12 Similarly, Nickpour et al. found that antibodies were able to predict only hematological and renal flares, but not successive global flares in disease activity.15 Interestingly, the male gender was seen as more susceptible to flare. Male lupus patients faced 2.5 times the hazards of a female patient developing flare and had a shorter flare-free time. This study was limited by the small sample size as well as the short duration of follow-up. A study conducted for a longer duration of time as well as recruiting patients from both IPD and OPD may be more useful for detecting any flare, damage accrual, and survival of patients over time, which could identify predictors of SLE outcome with better precision. In conclusion, the increase in the onset of flare in lupus is gradual. Acute rash and anti-dsDNA antibody at baseline are recognized as factors predicting time to flare. And male gender is a risk factor for earlier flare. This work is supported by grants from the National Natural Science Foundation of China (32270947, 82060259 and 81760296), Yunnan Province High-level health technical talents (leading talents) (L-2019004, L2019011), Yunnan Province Special Project for Famous Medical Talents of the “Ten Thousand Talents Program” (YNWR-MY-2018-040, YNWR-MY-2018-041), and Yunnan Province Clinical Center for Skin Immune Diseases (ZX2019-03-02), the Funding of Ministry of Science and Technology of Yunnan Province (2018ZF016). XW, BU, and YY contributed equally to this work and were responsible for the management of the research and drafting of the article. XW and BU were responsible for recruiting and following up with patients. SL, RC, and YC provided invaluable research consultation. RB contributed to re-arrange the following up data used in revision. JX oversaw the entire research project and the writing of the manuscript. We thank all the study participants for their participation. None. The data that support the findings of this study are available from the corresponding author upon reasonable request. Table S1 Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.