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Open Access 08.01.2025 | Original Research

Real-World Prevalence, Incidence and Management of Systemic Lupus Erythematosus in Germany: A Retrospective Claims Data Analysis

verfasst von: Tobias Alexander, Philipp Sewerin, Anja Strangfeld, Marcus Schulte, Julia Borchert, Tarcyane Barata Garcia, Eva Schrom

Erschienen in: Rheumatology and Therapy | Ausgabe 2/2025

Abstract

Introduction

This study evaluated the prevalence and incidence of systemic lupus erythematosus (SLE) in Germany and explored real-world data on sequence of therapy (SOT; sequence of drugs as prescribed in clinical practice).

Methods

This retrospective, observational, longitudinal cohort study using German claims data from the WIG2 GmbH Scientific Institute for Health Economics and Health System Research database (January 2011–December 2019), extrapolated to the statutory health insurance (SHI)-insured population, evaluated prevalence and incidence in an epidemiological analysis group and SLE treatment patterns in an incident cohort (subgroup ≥ 18 years of age with incident disease and ≥ 24-month follow-up post index date). Analyses were descriptive.

Results

Based on the epidemiological analysis (N = 3017), annual SLE prevalence per 100,000 gradually increased from 40.47 in 2012 to 59.87 in 2019 in the SHI population. In contrast, annual SLE incidence was relatively stable, ranging from 8.83 in 2012 to 8.86 in 2019. In the incident cohort (n = 941), based on SOT analysis (n = 681), treatment gaps of > 60 days were common: 67.1%, 51.2% and 54.9% in SOT1, SOT2 and SOT3, respectively. Corticosteroids were the most frequent monotherapy in SOT1 (31.0% vs 0% in SOT2/SOT3); 30.0–70.0% of patients received a corticosteroid combination therapy across SOTs. Over 50% of patients in each SOT received an antimalarial therapy (combination or monotherapies). The use of biologic disease-modifying drugs was low, ranging from 0.4% in SOT1 to 9.7% in SOT3.

Conclusions

Our data demonstrate an increased prevalence of SLE with stable incidence in Germany, suggesting improved survival of affected patients. Nevertheless, suboptimal treatment patterns, including limited use of biologics, reflect a high unmet need for optimised and personalised therapies in patients with SLE.
Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1007/​s40744-024-00735-5.
Prior Presentation: Alexander T, et al. Incidence, prevalence and management of Systemic Lupus Erythematosus in 4 Cohorts: A German claims data analysis. Presented at Deutscher Rheumatologiekongress, 30 August 2023.
Key Summary Points
Why carry out this study?
Recent epidemiological data for systemic lupus erythematosus (SLE) in Germany are limited, with no incidence data available beyond 2014. Moreover, real-world data on the sequence of SLE drugs prescribed in clinical practice are lacking.
Our study addresses the existing gap in epidemiological data for SLE in Germany by using claims data from various statutory health insurers, spanning from 2012 to 2019, and reports the linear increase in prevalence, and relatively stable incidence, of SLE.
What was learned from the study?
A lack of improvement in the management of SLE over the study period was observed, with a frequent occurrence of treatment gaps among patients, along with limited use of biologics and continued use of corticosteroids.
Our data highlight suboptimal disease management in patients with SLE in Germany, underlining the need for improved, personalised care and treatment options.

Introduction

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease with high clinical heterogeneity and an unpredictable disease course, with periods of active disease and remission [1, 2]. SLE prevalence and incidence vary globally, with the disease predominantly affecting women [35]. Worldwide prevalence ranges from 15.87 to 108.92 per 100,000 people and incidence from 1.5 to 11.0 per 100,000 person-years, depending on geographic region and genetic background [5, 6]. SLE is characterised by autoantibody production and immune complex depositions, resulting in tissue damage [1, 7]. As a result of persistent systemic inflammation, damage may accumulate in various organs, including the kidneys, central nervous system (CNS), heart, skin, lungs and joints, leading to significant morbidity and mortality. Consequently, SLE poses a huge burden on patients and healthcare systems, largely driven by the unpredictable disease course and organ manifestations [2, 8].
Lupus nephritis (LN) is a severe renal manifestation of SLE, reported in up to 30–‍50% of patients with SLE, and is associated with a sixfold increase in mortality compared with the general population [9, 10]. SLE also affects the nervous system (neuropsychiatric SLE), with varying prevalence depending on age, sex and ethnicity [11]. As a result of challenges in achieving a complete remission in patients with severe LN, and the complexity of diverse CNS manifestations and a broad range of severities, there is a major unmet need in determining optimal disease management in these patient populations [12, 13].
Heterogeneity in disease manifestations still represents a challenge to SLE diagnosis, classification and patient care [1, 14]. The European Alliance of Associations for Rheumatology (EULAR) recommendations and the EULAR/European Renal Association-European Dialysis and Transplant Association (EULAR/ERA-EDTA) joint recommendations are key guidelines used in SLE disease management [15, 16]. The current treat-to-target recommendations in SLE aim to achieve remission or a lupus low disease activity state to prevent organ damage and improve patients’ quality of life [17, 18]. The EULAR-recommended treatment schemes are based on disease severity, the need for managing flares and avoiding drug toxicity [15, 16]. The antimalarial drug hydroxychloroquine is recommended as first-line therapy for all patients with SLE, unless contraindicated [16]. Corticosteroids may be added if needed and should be reduced to a maintenance dose of ≤ 5 mg/day, and withdrawn when possible. In patients not responding to hydroxychloroquine (alone or in combination with corticosteroids), or in patients for whom it is not possible to reduce corticosteroid doses below those acceptable for chronic use, the addition of immunomodulating or immunosuppressive agents (e.g. methotrexate, azathioprine or mycophenolate) and/or biologic agents (e.g. belimumab or anifrolumab) should be considered [16]. Only two biologic therapies are currently approved for the treatment of SLE by the European Medicines Agency: belimumab, approved in 2011, and anifrolumab, approved in 2022 [19, 20]. Adapting therapies to the frequently changing needs of patients is a key part of effective disease management in SLE [21]. However, real-world treatment does not always adhere to available guidelines, a potential reason being the disparity in clinical outcomes from controlled, restricted clinical trials compared with those from dynamic, complex, real-world settings [22, 23].
Epidemiological data for SLE from central Europe are limited [5, 24]. Prevalence estimates for Germany were reported in the National Database of the German Collaborative Arthritis Centres in 2021 and 2022, in the German National Cohort (NAKO) Health Study from 2014 to 2017 and by Schwarting et al. from 2009 to 2014, whereas SLE incidence estimates are not available beyond 2014 [2528]. SLE treatment guidelines provide guidance on the recommended sequence of treatment for patients with SLE. However, there is a lack of recent data on the sequence of drugs prescribed in real-world clinical practice (i.e. sequence of therapy [SOT]). To help fill this evidence gap, we performed an observational study to investigate the trends in prevalence and incidence of SLE in Germany. We also explored real-world treatment patterns in patients with incident SLE.

Methods

Study Design

This was a retrospective, observational, longitudinal cohort study using routinely collected healthcare claims data from the WIG2 GmbH Scientific Institute for Health Economics and Health System Research, German claims database, from 1 January 2011 to 31 December 2019. The WIG2 database has been demonstrated to provide representative data for the whole statutory health insurance (SHI; Gesetzliche Krankenversicherung) population with regard to age, sex and morbidity, thus allowing for the extrapolation of data to the SHI-insured population [29].
Trends in prevalence and incidence were evaluated on the basis of an epidemiological analysis of the overall study population. To analyse SLE treatment patterns, a subpopulation of adult patients with incident SLE (the incident cohort) was evaluated. The identification period for the epidemiological analysis group was 1 January 2012–31 December 2019; for the incident cohort, the identification period was 1 January 2012–31 December 2017 (Fig. 1). Patients were followed up from the index date, which was defined as the first day of the quarter with the first SLE claim. All patients were required to have continuous enrolment of 12 months prior to the index date, referred to as the baseline period.

Study Population

Inclusion Criteria

Patients with a diagnosis of SLE, identified by one inpatient diagnosis (International Classification of Diseases, 10th revision, German modification [ICD-10-GM] M32.1, M32.8 and/or M32.9) [30] and/or two verified outpatient SLE diagnoses in two different quarters with at least one additional criterion (Table S1), were included in the study.
Epidemiological Analysis Group
For the epidemiological analysis group, there were no restrictions on age or follow-up requirements, except for the possession of full insurance or the occurrence of death in the respective year. Patients with incident SLE within this analysis group comprised those of any age with no diagnosis in the 12-month baseline period prior to the index date.
Incident Cohort
The incident cohort included only adult patients (≥ 18 years of age at the index date) with no claims for SLE diagnosis or SLE-specific treatment use in the baseline period (12 months prior to the index date) and with a requirement for ≥ 24 months of follow-up post index date; follow-up was to end at the end of enrolment in the database due to a change in the insurer, death or end of study period (31 December 2019).

Exclusion Criteria

Patients with a diagnosis of drug-induced SLE in the patient identification periods were excluded from the study. Patients with at least one claim for nonsteroid SLE treatment during the baseline period (relevant nonsteroid drug prescriptions are listed in Table S1) were excluded from the incident cohort. Additionally, patients with coding errors in their data, incorrect diagnosis (i.e. symptom overlap with other disorders; cutaneous lesions, misdiagnosed as SLE topical treatment) and those who were only treated with pain relievers instead of an SLE-specific treatment were excluded from the incident cohort analysis.

SLE Disease Manifestation Subgroups

Patient populations in this study were categorised into four subgroups on the basis of diagnosis codes within the 6 months prior to and 6 months post index date for CNS involvement and LN: (1) SLE only: SLE without LN or severe CNS involvement; (2) SLE + LN only: SLE with LN and no severe CNS involvement; (3) SLE + CNS only: SLE with severe CNS involvement and no LN; and (4) SLE + LN + CNS: SLE with severe CNS involvement and LN.
CNS involvement was based on at least one inpatient and/or outpatient ICD-10-GM diagnosis code (see Table S2 for further details) [30]. LN was defined on the basis of either at least one inpatient or two outpatient diagnoses for nephritis in two different quarters, or at least four nephrology visits.

Study Endpoints and Assessments

Study endpoints evaluated in the epidemiological analysis group were annual prevalence and incidence of SLE in Germany from 2012 to 2019 within each SLE disease manifestation subgroup, stratified by age and sex. Age- and sex-adjusted extrapolation to the SHI population was performed for relevant years. The endpoints assessed in the incident cohort were (i) treatment practice patterns (treatments used per SOT); (ii) treatment utilisation in each SOT by SLE disease manifestation subgroup, including continuous utilisation, switch or addition; (iii) corticosteroid use and dose within each SOT; and (iv) different types of organ manifestation within each SOT.
SLE-specific SOT included monotherapy or combination therapy with steroids, antimalarials, immunosuppressants, biologics and/or immunoglobulins. A list of drugs commonly used to treat patients with SLE is provided in Table S3. Three SOTs were defined for the SLE treatments in this study. SOT1 was defined as the treatment received from the date of the earliest prescription or administration of an SLE treatment (including corticosteroid) on or after the index date. Duration of steroid monotherapy must have been ≥ 3 months to be counted as SOT1. The start of SOT2 and SOT3 was defined as either a switch to a new drug or the addition of a drug to an existing regimen. For all SOTs, switching to or adding steroids was not considered a change in SOT. The end date for any SOT was defined as either a censoring event (change of insurer, death or end of study period) or a switch/change to a new SOT. Treatment gaps of > 60 days from the last day of drug prescription for a recent oral treatment, or the last day of the dosing interval for a recent parenteral treatment in SLE therapy, were captured.
To evaluate corticosteroid usage and dose within each SOT, variable dosages per day were grouped as low dose (≤ 7.5 mg), medium dose (7.6–15.0 mg), and high dose (> 15.0 mg). Comorbid conditions were assessed at baseline using the Charlson Comorbidity Index (CCI) as a reference [31], and additional predefined comorbid conditions captured during the study period (i.e. between the index date and patient censoring date) were identified by at least one inpatient or outpatient claim with a relevant ICD-10-GM code. Predefined comorbid conditions assessed in the study are provided in Table S4.
In an exploratory analysis, the physician speciality visited for SLE-specific treatment (i.e. patient visits coded with ICD-10-GM M32) was investigated for general practitioners, internal medicine (internist, rheumatologist or nephrologist) and other specialities (i.e. specialities differing to those listed here, or patients visits not coded with ICD-10-GM M32).

Statistical Analysis

Descriptive statistics were used for baseline patient demographics and clinical characteristics, and for all outcomes during SOT. For continuous variables, mean (standard deviation, SD) values were reported; for categorical variables, the absolute number and proportion of patients relative to the total sample size in each cohort were reported. The central statistical software programme used by WIG2 to evaluate data was R version 4.1. See the Supplementary Methods in the electronic supplementary material for further details.

Ethical Approval

This study used anonymised secondary data (i.e. healthcare insurance claims data); hence, ethics approval and consent to participate were not applicable. Patient consent for publication was also not applicable.

Results

Study Populations

A total of 3017 patients were evaluated in the epidemiological analysis group; 941 adult patients were eligible for incident cohort analysis. A flow diagram for the incident patient cohort is shown in Fig. 2. Most patients in this cohort had at least one inpatient and one outpatient SLE diagnosis; 10 patients were included on the basis of only one inpatient diagnosis. In the incident cohort, most patients were female (74.4%, n = 700/941) and mean age at the index date was 50.6 years. When stratified by age, the greatest proportion of patients (27.1%, n = 255/941) were in the 45–54 years age group. Patients were followed up for a mean duration of approximately 60 months (1836.0 days). On the basis of renal and neurological disease manifestations, the majority of patients were in the SLE-only or SLE + LN-only subgroups (SLE only, 55.2% [n = 519/941]; SLE + LN only, 32.4% [n = 305/941]); the proportion of patients in the SLE + CNS-only and SLE + LN + CNS subgroups was similar (6.1% [n = 57/941] vs 6.4% [n = 60/941], respectively; Table 1). The overall mean (SD) CCI was 1.44 (1.96), and 60.0% (n = 565/941) of patients in the incident cohort had at least one comorbidity of interest at the index date (Table 1).
Table 1
Baseline patient characteristics overall and in the SLE disease manifestation subgroups (incident cohort)
 
Overall (n = 941)
SLE only (n = 519)
SLE + LN only (n = 305)
SLE + CNS only (n = 57)
SLE + LN + CNS (n = 60)
Female, n (%)
700 (74.4)
408 (78.6)
207 (67.9)
46 (80.7)
39 (65.0)
Mean age, years
50.6
49.3
51.8
47.7
58.6
Age group, years, n (%)
 18–24
42 (4.5)
21 (4.1)
19 (6.2)
1 (1.8)
1 (1.7)
 25–34
115 (12.2)
75 (14.5)
25 (8.2)
11 (19.3)
4 (6.7)
 35–44
163 (17.3)
101 (19.5)
44 (14.4)
11 (19.3)
7 (11.7)
 45–54
255 (27.1)
137 (26.4)
84 (27.5)
20 (35.1)
14 (23.3)
 55–64
187 (19.9)
98 (18.9)
69 (22.6)
7 (12.3)
13 (21.7)
 65–74
102 (10.8)
56 (10.8)
35 (11.5)
3 (5.3)
8 (13.3)
 75+
77 (8.2)
31 (6.0)
29 (9.5)
4 (7.0)
13 (21.7)
CCI, mean (SD)
1.44 (1.96)
1.06 (1.36)
1.84 (2.37)
1.00 (1.43)
3.13 (2.90)
CCI, n (%)
 0
376 (40.0)
231 (44.5)
105 (34.4)
27 (47.4)
13 (21.7)
 1
254 (27.0)
150 (28.9)
78 (25.6)
16 (28.1)
10 (16.7)
 2
140 (14.9)
77 (14.8)
47 (15.4)
9 (15.8)
7 (11.7)
 3
60 (6.4)
30 (5.8)
23 (7.5)
2 (3.5)
5 (8.3)
 ≥ 4
111 (11.8)
31 (6.0)
52 (17.0)
3 (5.3)
25 (41.7)
Mean duration of follow-up, months (days)
60.4 (1836.0)
61.0 (1855.4)
60.8 (1850.2)
58.5 (1779.9)
54.2 (1649.0)
CCI Charlson Comorbidity Index, CNS central nervous system, LN lupus nephritis, SD standard deviation, SLE systemic lupus erythematosus

Annual Prevalence and Incidence of SLE in Germany (Epidemiological Analysis)

The annual SLE prevalence per 100,000 people increased almost linearly from 2012 to 2019 in the SHI population (Fig. 3a). With an overall prevalence of 59.87 per 100,000 in 2019 (this corresponds to approximately 49,800 patients with SLE in Germany; N = 83 million inhabitants [32]) compared with 40.47 per 100,000 in 2012, prevalence increased by 48.0% in 7 years. Annual SLE incidence rates were relatively stable but fluctuated slightly between 2012 (8.83 per 100,000) and 2019 (8.86 per 100,000), with the highest rate noted in 2015 (10.40 per 100,000; Fig. 3b). Within the SHI population, the overall SLE prevalence per 100,000 ranged from 63.97 for women and 14.44 for men in 2012 to 94.61 for women and 22.72 for men in 2019 (overall mean ratio 4.2:1). The overall SLE incidence per 100,000 ranged from 13.58 for women and 3.57 for men in 2012 to 13.47 for women and 3.92 for men in 2019 (overall mean ratio 3.6:1). When stratified by disease manifestation, SLE prevalence was greatest in the SLE-only and SLE + LN-only subgroups (Fig. 3a), and incidence of SLE was highest in the SLE-only subgroup across the study period (Fig. 3b).
In 2019, the prevalence of SLE in the SHI population was greatest for women in the 45–49 years age group (162.44 per 100,000) and greatest for men in the 55–59 and 60–64 years age groups (46.57 and 46.56, respectively; Fig. 3c). The incidence of SLE in 2019 was also greatest for women in the 45–49 years age group (24.67) and for men in the 60–64 years age group (12.78; Fig. 3d). Prevalence and incidence were consistently higher in women than in men across most age groups and SLE disease manifestation subgroups (Fig. S1). Prevalence and incidence peaked at an earlier age in women than in men, especially for the SLE-only subgroup (Fig. S1).

Treatment Practice Patterns and Outcomes by SOT in the Incident Cohort

Of 941 eligible patients in the incident cohort, 681 were included in the final SOT analysis; 260 patients (27.6%) were excluded owing to coding errors in their data, incorrect diagnosis (i.e. symptom overlap with other disorders; cutaneous lesions; misdiagnosed as SLE topical treatment) and/or being treated only with pain relievers instead of an SLE-specific treatment (Fig. 4). From SOT1 (n = 681), 36.1% (n = 246/681) patients changed their therapy to SOT2 and, of these, 45.9% (n = 113/246) further changed their therapy to SOT3. The rest of the patients remained within their respective SOTs (SOT1, 63.9% [n = 435/681]; SOT2, 54.1% [n = 133/246]; SOT3, 50.4% [n = 57/113]). Patient flow through SOTs and across SLE disease manifestation subgroups is shown in Fig. 4. A treatment gap of > 60 days was frequent in all SOTs: 67.1% in SOT1, 51.2% in SOT2 and 54.9% in SOT3 (Fig. 4). For the subgroups, differences were found in SOT1, with 71.3% of patients stopping their treatment for > 60 days in the SLE-only subgroup compared with 63.1% in the SLE + LN-only, 58.3% in the SLE + CNS-only and 52.4% in the CNS + LN subgroups (Tables S5S8).
A higher proportion of patients in SOT1 (52.4%) received a monotherapy compared with those in SOT2 (23.2%) and SOT3 (22.1%; Table 2). Corticosteroids were the most frequently used monotherapy in SOT1 (31.0%), followed by antimalarials (18.9%). None of the patients received corticosteroid monotherapy in SOT2 and SOT3; antimalarial or immunosuppressant monotherapies were predominant in these SOTs (Table 2).
Table 2
Treatment patterns according to the SOT in the overall SLE population (incident cohort)
 
SOT1 (n = 681)
SOT2 (n = 246)
SOT3 (n = 113)
Monotherapy, n (%)
357 (52.4)
57 (23.2)
25 (22.1)
 Corticosteroids
211 (31.0)
0
0
 Antimalarials
129 (18.9)
28 (11.4)
10 (8.9)
 Immunosuppressants
15 (2.2)
25 (10.2)
14 (12.4)
 Biologics
1 (0.1)
4 (1.6)
1 (0.9)
  Rituximab
1 (0.1)
1 (0.4)
0
  Belimumab
0
2 (0.8)
1 (0.9)
  Other
0
1 (0.4)
0
 IVIg
1 (0.1)
0
0
Combination therapy, n (%)
324 (47.6)
189 (76.8)
88 (77.9)
 Antimalarials + corticosteroids
205 (30.1)
50 (20.3)
15 (13.3)
 Immunosuppressants + corticosteroids
68 (10.0)
80 (32.5)
20 (17.7)
 Antimalarials + immunosuppressants + corticosteroids
42 (6.2)
49 (19.9)
41 (36.3)
 Antimalarials + immunosuppressants
7 (1.0)
4 (1.6)
2 (1.8)
 Antimalarials + biologics + corticosteroids
1 (0.1)
1 (0.4)
3 (2.7)
 Immunosuppressants + biologics + corticosteroids
1 (0.1)
1 (0.4)
0
 Antimalarials + immunosuppressants + biologics + corticosteroids
0
3 (1.2)
0
 Antimalarials + biologics
0
0
1 (0.9)
 Immunosuppressants + biologics
0
0
1 (0.9)
 Biologics + corticosteroids
0
1 (0.4)
5 (4.4)
Biologics used in combination therapies, n (%)
 Belimumab
1 (0.1)
5 (2.0)
6 (5.3)
 Rituximab
1 (0.1)
1 (0.4)
3 (2.7)
 Other
0
0
1 (0.9)
Overall—monotherapy or combination therapy, n (%)
 Corticosteroids
528 (77.5)
185 (75.2)
84 (74.3)
 Antimalarials
384 (56.4)
135 (54.9)
72 (63.7)
 Immunosuppressants
133 (19.5)
162 (65.9)
78 (69.0)
 Biologics
3 (0.4)
10 (4.1)
11 (9.7)
 IVIg
1 (0.1)
0
0
IVIg intravenous immunoglobulin, SLE systemic lupus erythematosus, SOT sequence of therapy
The use of combination therapies increased as patients changed therapies, with 47.6% of patients receiving a combination therapy in SOT1 compared with 76.8% and 77.9% in SOT2 and SOT3, respectively (Table 2). The most frequent combination therapies used in SOT1, SOT2 and SOT3, respectively, were antimalarials in combination with corticosteroids (30.1%), immunosuppressants in combination with corticosteroids (32.5%), and antimalarials in combination with immunosuppressants and corticosteroids (36.3%). Biologics were rarely used in the study and included the off-label use of rituximab and abatacept. There was a trend for increased use of biologics in later SOTs (either as monotherapy or combination therapy: 0.4% of patients in SOT1, 4.1% in SOT2 and 9.7% in SOT3). Medications used in 2019 in the epidemiological analysis group also indicated that biologics were rarely used (4.39%; Table S9). Specialities visited for SLE-specific treatment comprised general practitioners only (23.8%), internal medicine only (18.9%; internist, rheumatologist or nephrologist), general practitioners and internal medicine (22.8%) or other specialities (34.5%) of the patients across all SOTs (Fig. S2).

Use of Corticosteroids

Across all SOTs, most patients received corticosteroids, including both monotherapy and combination therapy, with a mean total corticosteroid dose of 16.88 mg/day (n = 528) in SOT1, 17.49 mg/day (n = 185) in SOT2 and 12.04 mg/day (n = 84) in SOT3. In SOT1, SOT2 and SOT3, respectively, 52.5%, 44.3% and 40.5% of patients received medium-to-high doses (7.6 to > 15.0 mg/day) of corticosteroids (Fig. 5).

Organ Manifestations by SOT

Most patients had involvement of one or more organs across all SOTs (SOT1, 93.1% [n = 634]; SOT2, 82.9% [n = 204]; SOT3, 85.8% [n = 97]). In patients with organ involvement, manifestations were similar across SOTs in each organ category (Fig. 6). Cardiorespiratory/cardiopulmonary manifestations were the most frequent of all organ manifestations across SOTs: 88.7% for SOT1, 79.7% for SOT2 and 80.5% for SOT3 (Fig. 6). The most common manifestations of cardiorespiratory/cardiopulmonary involvement were cardiac diseases (SOT1, 77.0% [n = 524]; SOT2, 70.7% [n = 174]; SOT3, 69.9% [n = 79]), followed by acute respiratory manifestations (SOT1, 79.2% [n = 539]; SOT2, 67.5% [n = 166]; SOT3, 69.9% [n = 79]) and myocarditis (SOT1, 38.3% [n = 261]; SOT2, 38.6% [n = 95]; SOT3, 42.5% [n = 48]).

Discussion

On the basis of our real-world data, the prevalence of SLE in the German SHI population is continuously increasing, whereas SLE incidence rates remain stable. In our study, SLE treatment, especially in later SOTs, seemed to provide disease stabilisation to some extent. Organ manifestation in newly diagnosed patients with SLE did not worsen across SOTs, and an increasing proportion of patients were receiving a lower corticosteroid dose in later SOTs than in their previous SOT. However, treatment patterns, such as gaps in SLE therapy and continued corticosteroid usage above the recommended daily dose across SOTs, indicate an inadequate treatment and noncompliance with the current guidelines.
The observed age and sex distribution of the incident cohort was similar to that reported in the National Database of the German Collaborative Arthritis Centres [25, 28]. Data from this study confirm that SLE occurs across all age groups but most commonly affects people in their middle age, in the 45–54 years age group. Women were predominantly affected, regardless of organ manifestations, confirming the reported distribution of SLE between men and women in Germany and from studies worldwide [25, 28, 33, 34]. In our study, a female-to-male ratio of approximately 3.6:1 was noted in the disease incidence cohort, representing a higher incidence of men with SLE than reported in other studies (female-to-male ratio ranging from 4.3:1 to 13.6:1) [6, 35]. Similarly, a 2002 study in the German SHI population reported a lower female-to-male ratio (2:1), compared with other reports [35, 36]. However, the observed variations in disease incidence across studies could also reflect inherent differences in population demographics and socioeconomic factors [5, 35].
One of the key findings of our study is that the overall prevalence of SLE increased almost linearly over the study period, from 40.47 per 100,000 population in 2012 to 59.87 in 2019 (corresponding to approximately 49,800 patients with SLE in Germany in 2019 [32]), while the annual incidence rates remained relatively stable, albeit with some fluctuation. A similar epidemiological stage, referred to as compounding prevalence, is also observed in other chronic inflammatory diseases such as inflammatory bowel disease [37, 38]. An increase in prevalence despite stable incidence could indicate a reduced lupus-related mortality, owing to improvements in the treatment landscape or disease management, including increased physician awareness, as observed in other autoimmune diseases [37, 39]. These findings are in line with recent studies demonstrating a general trend towards improved survival in patients with SLE over time [40, 41]. A general trend for SLE prevalence to increase over time has been noted across many studies worldwide [33, 34, 42]. In contrast to our observations, some studies reported a decline in the incidence of SLE over time. A retrospective UK cohort study noted an annual 1.8% decline (p < 0.001) in SLE incidence from 1999 to 2012 [43]. Another study from Italy also observed a stable decline in SLE incidence from 2013 to 2020 [42]. However, findings vary across regions, indicating that SLE incidence may differ geographically and could vary intra-regionally depending on ethnicity [33, 42, 43]. Therefore, care should be taken when comparing incidence rates from different countries.
Estimated SLE prevalence rates similar to those reported in our study were also reported in a 2021 German study by Schwarting et al., using the German Betriebskrankenkassen (BKK) health insurance fund database between 2009 and 2014, with a trend in increasing prevalence over time (38.61 to 55.80 per 100,000 people) [27]. However, in contrast to our study, Schwarting et al. observed an increase in SLE incidence (6.1 to 8.82 per 100,000 people), which could be partly explained by the different methodologies used [27]. The WIG2 database used in our study contains data from different statutory health insurers, whereas the BKK database used by Schwarting et al. represents only one type of insurance category, resulting in different patient populations.
When stratified by age, the prevalence pattern in our study seems to align with that of the German National Database, with peaks at a relatively young age and again at a later stage in patients’ lives [25, 28]. SLE prevalence observed between 2017 and 2019 in our study corroborates the prevalence noted in a systematic review by Albrecht et al. (56 per 100,000) [24]. On the basis of the German National Database, the average age of SLE onset was 41 years for the period 2019–‍2021, and 40 years for the period 2020–2022; however, data stratified by sex were not reported [25, 28]. Our 2019 snapshot data indicated a‍ later onset of SLE in men than in women (55–64 vs 45–49 years of age). Moreover, disease onset in women occurred later than previously reported in the literature (45–49 vs 20–30 years of age) [3, 44, 45].
Although previous studies are generally consistent with our data on SLE prevalence stratified by sex and age, some differences were noted worldwide [34, 46]. These findings reiterate the importance of ethnicity when interpreting epidemiological data and the limitations of any generalisations.
SLE treatment patterns in the incident cohort indicated that treatment gaps were less common in subgroups with severe organ involvement (SLE + LN-only, SLE + CNS-only, SLE + LN + CNS subgroups), potentially confirming that increasing disease severity in terms of critical organs involved does not allow interruptions in treatment. Throughout the patient journey, treatment gaps were observed on a regular basis, with more than half of the patients in each SOT having no SLE treatment for > 60 days. This pattern was observed for the overall incident cohort, as well as for the subgroups. This could be potentially attributed to nonadherence due to inadequate responses, which was also reflected by the substantial proportion of patients switching their current SOT to another treatment after a treatment gap. Poor adherence to treatment is a common issue in chronic diseases such as SLE and could lead to an increased risk for flares, hospitalisations, morbidity and mortality, as well as poor renal outcomes in patients with renal involvement [47, 48]. In the incident cohort, more than half of the patients (52.4%) in SOT1 started a monotherapy as their first treatment, preferentially with an antimalarial or a corticosteroid. This is consistent with the 2023 EULAR guidelines, which recommend antimalarials for all patients with SLE and the use of corticosteroids for rapid symptom relief [16]. At least 40.0% of patients were receiving medium-to-high doses (7.6 to > 15.0 mg/day) of corticosteroids. Thus, guideline recommendations on using steroid-sparing therapy are not being implemented to a satisfactory level, leading to the use of high corticosteroid doses as observed in our study. We also noted a high proportion of patients with cardiorespiratory/cardiopulmonary diseases, which could be a result of increased risk of cardiovascular diseases in patients with SLE due to atherosclerosis or other organ involvement [49]. It is also plausible that the long-term corticosteroid use observed in our study could have contributed towards organ damage accrual. Persistent use of high-dose corticosteroids has been associated with an increased risk of severe adverse events and organ damage accrual [50]. Nevertheless, caution is required when interpreting the daily dosages of prescribed medications extracted from claims data. On the basis of the German National Database, 46.0% of patients with SLE received corticosteroids in 2022, among whom 78.0% had daily prednisolone dosages ≤ 5.0 mg [28]. Additional factors for worsening organ manifestations could be a lack of efficacy of available therapies in a subset of patients, infrequent use of biologics, or insufficient prescription of drugs by rheumatologists/general physicians. Indeed, we note that the use of biologics was limited in our study: 4.39% of patients in 2019 and 9.7% of patients in SOT3. In comparison, on the basis of the German National Database, belimumab use linearly increased from 7.0% in 2019 to 11.0% in 2021 and 15.0% in 2022 [25, 28]. However, it must be noted that the German National Database was based on data explicitly from rheumatologists; in comparison, the WIG2 database used in our study covered data from a broader set of healthcare professionals, including general physicians who might not prescribe biologics, most likely due to a lack of knowledge or acceptance, as access and reimbursement are granted for the German SHI population. Against this background, it is to be hoped that efforts throughout Europe for improved patient care, such as the European Reference Networks, in addition to the recent approval of anifrolumab in Europe, will foster the use of biologics in SLE in Germany [20, 51, 52].
We acknowledge that our study has some limitations. First, there are potential limitations due to the retrospective nature of patient data collection from an administrative claims database. In particular, patients could have been misclassified as a result of limitations in the inclusion/exclusion criteria defined in the study protocol, given that the definitions can only be considered the best possible approximation to reality. Misclassification of patients may occur because of incorrect capture of clinical conditions and/or treatments (i.e. symptom overlap with other disorders; cutaneous lesions; misdiagnosed as SLE topical treatment; erroneous inclusion of patients who received only pain relief instead of SLE-specific treatment), missing diagnostic codes or coding errors. In this respect, a potential misclassification of SLE in our study is reflected by a group of patients (27.6%) in the incident cohort with no documented treatment, which might result in an overestimation of prevalence and incidence data. Second, medication data were limited to drugs administered in outpatient settings and were collected via medication receipts in the claims database, which does not necessarily equate to correct usage of medication by patients. In addition, patients may have received drugs that might not have been captured in this database, which could suggest an underestimation of the number of patients in the incident cohort. The self-injectable formulation of belimumab was only approved in late 2017, and this could have contributed to an underestimation of the use of biologics in our study [53]. Also, data on daily dose of medication in the study were based on an approximate calculation derived from prescriptions. Third, the relatively small sample size for some of the disease manifestation subgroups and the lack of formal statistical testing of data may hinder interpretation of data. Moreover, organ involvement data could be skewed, owing to the challenges in differentiating between actual SLE organ manifestation and occurrence of comorbidity. Finally, the study might not be generalisable to patient populations in other countries. Despite the limitations, consistency of our findings with previous studies provides confidence in the data presented.

Conclusions

This study reports results from an evaluation of real-world data from Germany on the prevalence and incidence of SLE and provides insight into treatment patterns in SLE. Our study results indicate an increasing prevalence and relatively stable incidence of SLE in Germany since 2012, suggesting improved patient survival in recent years. Despite these advances, there remains a high unmet need for optimal treatment. Our findings show continued and frequent use of corticosteroids at quantities above the recommended daily dose, and low prescription rates for biologics. In addition, the observed treatment patterns, with many patients switching therapy or experiencing long treatment gaps, underline the need for improved personalised treatment options in SLE.

Medical Writing/Editorial Assistance

Medical writing support, including development of a draft outline and subsequent drafts in consultation with the authors, assembling tables and figures, collating author comments, copyediting, fact checking and referencing, was provided by Sreerekha Pillai, PhD, CMPP (Aspire Scientific Limited, Bollington, UK), and was funded by Amgen GmbH (Munich, Germany).

Declarations

Conflict of Interest

Tobias Alexander has received consulting fees from Amgen; honoraria from AbbVie, AstraZeneca, GSK, Neovii and Pfizer; support for attending meetings, and/or travel support, from AbbVie, Neovii and Pfizer; and study support from Janssen-Cilag. Philipp Sewerin has received consulting fees from Amgen; honoraria and support for attending meetings, and/or travel support, from AbbVie, Alfasigma S.p.A., Amgen, Axiom Health, Biogen, Bristol-Myers Squibb, Celgene, Chugai, Gilead Sciences, Hexal, Janssen-Cilag, Johnson & Johnson, Lilly, mediri GmbH, Novartis Pharma, Onkowissen GmbH, Pfizer, Roche, Sanofi-Genzyme, Swedish Orphan Biovitrum and UCB Pharma. Anja Strangfeld has received honoraria from AbbVie, Galapagos, Lilly, Janssen, Pfizer and Takeda; is Chair of the British Association of Dermatologists Biologic and Immunomodulators Register (BADBIR) Data Monitoring Committee (voluntary role); and is on the Data Monitoring Committee Board of the Lupus Best Study (voluntary role). Marcus Schulte and Eva Schrom are employees of, and hold stocks in, Amgen. Julia Borchert and Tarcyane Barata Garcia are employees of WIG2 GmbH.

Ethical Approval

This study used anonymised secondary data (i.e. healthcare insurance claims data); hence, ethics approval and consent to participate were not applicable. Patient consent for publication was also not applicable.
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Anhänge

Supplementary Information

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Metadaten
Titel
Real-World Prevalence, Incidence and Management of Systemic Lupus Erythematosus in Germany: A Retrospective Claims Data Analysis
verfasst von
Tobias Alexander
Philipp Sewerin
Anja Strangfeld
Marcus Schulte
Julia Borchert
Tarcyane Barata Garcia
Eva Schrom
Publikationsdatum
08.01.2025
Verlag
Springer Healthcare
Erschienen in
Rheumatology and Therapy / Ausgabe 2/2025
Print ISSN: 2198-6576
Elektronische ISSN: 2198-6584
DOI
https://doi.org/10.1007/s40744-024-00735-5

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