Frequency,diagnosis,and pharmacological treatment of giant cell arteritis in Germany: database analysis of medical insurance data

Abstract

Background:

For giant cell arteritis (GCA), a north-south gradient in incidence and prevalence has been described, peaking in Scandinavia.

Objective:

This analysis aimed to obtain up-to-date, representative data on the prevalence and incidence of GCA in Germany, updating the old, regional information on low incidence and prevalence rates.

Design:

Cross-sectional analysis using a large German health insurance database.

Methods:

This study is based on a cross-sectional analysis of claims data from the InGef (Institute for Health Research Berlin GmbH) research database, which includes a representative sample of 4.8 million insured individuals. Individuals aged ⩾50 years with continuous insurance coverage for a 3-year baseline period and the subsequent 2 years for longitudinal analysis were included. Estimates were standardised and projected to the German population.

Results:

Each year from 2018 to 2021, 1.7 million insured individuals met the inclusion and exclusion criteria. Extrapolated to the German population ⩾50 years in 2021, the incidence was 24/100,000, and the prevalence was 146/100,000. Diagnosis was made predominantly in outpatient settings by general practitioners (GP, 31.9%) and internists (19.5%), followed by rheumatologists (13.1%) and ophthalmologists (5.7%). Within 2 years, 16.3% of incident patients were referred to rheumatologists for treatment after diagnosis. Treatment was most commonly initiated by GPs (45.8%), followed by rheumatologists (36.1%), and included glucocorticoids (88.2%), methotrexate (26.7%), and tocilizumab (14.1%). Most common comorbidities of prevalent patients comprised arterial hypertension (77.2%), dyslipidaemia (55.0%), diabetes mellitus (28.8%), osteoporosis (34.6%), and cataract (31.2%).

Conclusion:

Contrary to previous reports, Germany has higher incidence and prevalence rates of GCA than previously assumed. Only approximately one-third of the incident patients were initially treated by rheumatologists. Comorbidities such as diabetes or cardiovascular diseases were common.

Plain language summary

How often giant cell arteritis occurs in Germany, how it is diagnosed, and how it is treated: an analysis of health insurance data

Giant cell arteritis (GCA) is an inflammation of blood vessels that mostly affects people over 50. Earlier studies suggested that GCA is less common in Germany than in northern Europe, but these were based on small, regional data.

In this study, we looked at medical insurance records from nearly 5 million people in Germany between 2018 and 2021. After adjusting the numbers to represent the whole German population aged 50 and older, we found that each year about 24 in every 100,000 people developed GCA, and about 146 in every 100,000 were living with the disease. These rates are higher than previously thought.

Most patients were diagnosed by family doctors or internists, while only about one in three were treated by rheumatologists within the first two years after diagnosis. The main treatment was glucocorticoids (steroids), but some patients also received methotrexate or tocilizumab. Many patients also had other health problems, especially high blood pressure, high cholesterol, diabetes, osteoporosis, or cataracts.

In summary: GCA is more common in Germany than earlier reports suggested. Most patients are diagnosed and treated outside of rheumatology clinics, and they often have other chronic health conditions that complicate care.

Keywords

comorbidities giant cell arteritis glucocorticoids incidence medical insurance data prevalence

Introduction

Giant cell arteritis (GCA), also known as temporal arteritis, is the most prevalent primary vasculitis, occurring mainly in people aged 50 years and older.^1
–3 Women are significantly more likely to be affected by GCA.¹

The most common clinical manifestations of GCA include new-onset of temporal headaches, jaw claudication, tenderness of the temporal arteries, and constitutional symptoms such as fever, fatigue, and weight loss.^1,4
–6 Ophthalmic complications occur in approximately 30% of patients and include anterior ischaemic optic neuropathy, central retinal artery occlusion, branch retinal artery occlusion, diplopia, and amaurosis fugax; the first three conditions usually result in permanent vision loss.⁷ Long-term complications include aortic aneurysm with potential rupture or dissection.³ Polymyalgia rheumatica (PMR), the second most common inflammatory rheumatic disease, is characterised by pain and morning stiffness, particularly in the shoulders and hips, occurs in about 40%–60% of patients with GCA. Conversely, approximately 15%–23% of patients initially diagnosed with PMR have subclinical GCA.⁸

Key players of GCA pathogenesis include dendritic cells, which initiate the inflammatory cascade, and T cells, particularly Th1 and Th17 subsets, which produce pro-inflammatory cytokines such as interferon-γ and interleukin (IL)-17.^9
–11

According to the 2018 update of the EULAR recommendations for the treatment of GCA, high-dose therapy with oral glucocorticoids (GC; e.g., 40–60 mg/day prednisone equivalent) should be started immediately in active GCA to induce remission.⁶Following disease control, GC doses should be tapered with the aim of reducing to a dose of 15–20 mg/day in 2–3 months and to ⩽5 mg/day after 1 year.⁶ For patients with complicated GCA, for example, in case of acute visual loss, intravenous GC administration should be considered.⁶ Furthermore, treatment with the IL-6 receptor inhibitor tocilizumab (TCZ), the JAK inhibitor upadacitinib, or off-label treatment with methotrexate (MTX) can be considered for patients with refractory or relapsing disease or for tapering of GC doses in patients that have an increased risk of GC-related adverse effects.^6,12,13 Other drugs with different mechanisms of action, including the IL-6 receptor blocker sarilumab and IL-17A inhibitor secukinumab, have been tested in clinical trials.^10,14,15

Due to the severe complications of GCA, such as irreversible vision loss, early treatment with GC is crucial.^2,5 However, treatment with GC can cause various side effects and high initial GC doses may also relate to relapses, so a correct diagnosis of GCA is essential.^5,16 It is important that patients with symptoms of GCA are rapidly referred to a specialist with expertise in GCA to confirm the diagnosis and begin treatment. Nonetheless, nonspecific symptoms may complicate the diagnosis.^6,17 Fast-track clinics improve healthcare efficiency and enable earlier diagnosis, thereby reducing the risk of vision loss.^18,19 To reduce delays in GCA diagnosis, recommendations to define FTCs specialising in GCA diagnosis in Germany were recently published.²⁰

To improve early referral of GCA patients to specialist care/FTC, it is important to have up-to-date incidence rates of GCA patients in Germany. The incidence rate of GCA exhibits significant geographical variation across Europe, demonstrating a notable north-south gradient. At the higher end, Norway reports an incidence of 29 per 100,000 people per year, while Italy, at the lower end, records 6.9 cases per 100,000 per year.^1,21,22 In Germany, both the incidence and prevalence of GCA have been reported as comparatively low. Studies have reported prevalence rates of 8.7 to 17.1 per 100,000 people in the general population and 24–44/100,000 per year for individuals aged 50 years and older, which correlates to 15,000–19,000 affected persons in Germany in 2021.^23
–25 A recent large-scale analysis of German health insurance data revealed that the PMR prevalence in individuals aged 50 and older is substantially higher than previously estimated.²⁶ Similarly, the primary aim of this database analysis was to provide updated and comprehensive population-based incidence and prevalence estimates of GCA in Germany between 2018 and 2021. Additionally, this study aimed to identify the groups of specialists in Germany who are responsible for the initial diagnosis of GCA and the initiation of treatment.

Methods

Database and ethics

Parts of the methodological description are shared with a previously published analysis of polymyalgia rheumatica using the same database.²⁶ The present analysis used anonymised health insurance claims data from the InGef database (Institute for Applied Health Research Berlin). This database includes longitudinal healthcare information from approximately nine million individuals insured in more than 60 German statutory health insurance providers.

Healthcare utilisation from different sectors can be analysed at the individual patient level, allowing longitudinal observation for up to 6 years. For research purposes, a representative sample of 4.8 million insured persons per year was chosen, reflecting the German population with respect to age and sex distribution. This structure enables the investigation of rare diseases and healthcare utilisation patterns in routine clinical practice.²⁷

Because the analyses were conducted using anonymised claims data, neither ethical approval nor informed consent from individual patients was required.

Study design

A cross-sectional analysis of the InGef database was performed to evaluate the epidemiology of GCA, patient characteristics, and the medical specialties involved in diagnosis and treatment. The dataset covers the period 2015 to 2022, while the prevalence and incidence were calculated for each year between 2018 and 2021. To calculate the incidence, a diagnosis-free baseline period of 3 years prior to the respective study year was applied. Individuals with a previous diagnosis of GCA during this period were excluded from the study cohort for the incidence analysis to capture only first-time or newly diagnosed cases.

The analyses to describe the received treatments for GCA were conducted longitudinally. A cohort was formed consisting of all previously identified patients with GCA between 2018 and 2020, and followed up during the 2 years after the incident diagnosis.

Study populations

For prevalence analyses, individuals aged 50 years or older were included if they were continuously insured in the InGef research database from January 1 of the respective study year until December 31 of the following year or until death. For the incidence analyses, continuous insurance coverage during the three preceding years was additionally required. Furthermore, insurance status was necessary for the subsequent 2 years for longitudinal analysis. Patients who had already developed ‘GCA with PMR’ (according to the International Classification of Diseases and Related Health Problems, Tenth Edition, German Modification [ICD-10 GM] code M31.5) or ‘Other GCA’ (ICD-10 GM M31.6) within 3 years prior to the respective study year were excluded (only for incident patients).

The additional study cohort for the description of prescribed medication included all incident patients between 2018 and 2020 who were fully observable for at least 2 years after their incident diagnosis or until death.

Variables and measures

GCA patients were identified if at least one outpatient or inpatient main or secondary diagnosis (ICD-10 GM code M31.5 or M31.6) was present in the respective study year. For additional validation of a first confirmed outpatient diagnosis, at least one further confirmed outpatient diagnosis, or an inpatient main or secondary diagnosis had to be present within three-quarters after the index quarter (so-called M2Q criterion). For patients with a first inpatient GCA diagnosis, the admission date of the respective hospital case was determined as the GCA index date. In the case of a first outpatient GCA diagnosis, the date of first contact with the diagnosing physician (via first billed code according to the uniform evaluation standard) was determined.

Patient characteristics include sex (female/male) and age. Age was defined as years on 1st January of the respective study year or at the index date (for incident patients only).

The main outcome is the 1-year prevalence and incidence of GCA according to the case definition of GCA patients. In addition, we reported predefined comorbidities of interest, defined by ICD-10 GM codes for inpatient or outpatient diagnoses. Data on comorbidities were gathered for each study year separately. Hence, not only pre-existing (before GCA diagnosis) but also newly diagnosed comorbidities were considered. Additionally, we evaluated predefined treatments, defined by the Anatomical Therapeutic Chemical (ATC) classification system, of which at least one prescription was filled in the respective year. As a further outcome, the specialist groups of the physicians who made the incident diagnosis were analysed. In addition, the groups of physicians who prescribed predefined medication to both prevalent and incident GCA patients were also analysed.

Statistical analysis

Prevalence and incidence rates were calculated as absolute numbers and proportions per 100,000 eligible individuals at risk in the InGef database, including 95% confidence intervals (CI) assuming a binomial distribution. Additionally, age- and sex-standardised projections onto the total population in Germany were performed for the prevalence and incidence. For this projection, official population statistics from the German Federal Bureau of Statistics served as the reference.²⁸ This included calculating weighted averages of stratum-specific rates in the study population, using the corresponding numbers in each stratum of the standard German population (according to the German Federal Statistical Office) as weights. All other variables were analysed descriptively with absolute (n) and relative frequencies (%) and mean ± standard deviation (SD) for age. All analyses were performed in the total population as well as stratified by sex. Patients with missing values in any variable were not included in the analyses. The statistical analyses were performed using R statistical software (The R Foundation; Version 4.0.2).

The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement²⁹ (Table S4).

Results

The InGef database comprised 4266,174 insured individuals in the first study year (2018) and 4,321,057 individuals in the last study year (2021). Of these, 1,772,026 (2018) and 1,663,363 (2021) were fully observable, ⩾50 years of age, and were therefore included in the analyses.

Prevalence and incidence of GCA

In the InGef cohort, about 2500 prevalent GCA patients at least 50 years of age were observed per study year (2018: 2500, 2019: 2594, 2020: 2473, 2021: 2611; Table S1). Projecting these numbers to the German population led to an estimation of 50,484 patients with GCA in 2018 and of 54,934 patients in 2021. This is equivalent to GCA prevalence of 137/100,000 (95% CI, 135.8–138.2) in the first study year (2018) and 146/100,000 (95% CI, 145.3–147.7) in the last study year (2021; Figure 1(a)). For each study year, GCA prevalence rates were essentially higher in women compared to men.

Figure 1.

GCA prevalence (a) and incidence (b) in individuals aged ⩾ 50 years in Germany, stratified by sex.

In each study year, 400 to 500 newly diagnosed GCA patients at least 50 years of age were identified in the InGef cohort (2018: 498, 2021: 415; Table S1). According to our projection onto the German population, this is equivalent to 10,019 newly diagnosed GCA patients in 2018 and 8848 patients in 2021. During the study years, GCA incidences varied between 21.7/100,000 (95% CI, 21.3–24.1) in 2020 and 27.8/100,000 (95% CI, 27.3–28.4) in 2019 (Figure 1(b)). Higher GCA incidences were observed in women than in men.

Patient characteristics

On average, prevalent patients were 75.6 (±8.7) years and incident patients were 72.9 (±9.3) years of age in 2021 (Table 1, Table S2). About two-thirds of the prevalent (1760, 67.4%) and incident (5736, 64.8%) patients were women. The most common comorbidity of the prevalent patients was essential arterial hypertension. Patient characteristics were similar for the other study years.

Table 1.

Demographic characteristics and relevant comorbidities in prevalent GCA patients (InGef database).

Year	2018(N = 2500)	2019(N = 2594)	2020(N = 2473)	2021(N = 2611)
Age (years), mean ± SD	75.6 ± 8.7	75.7 ± 8.9	76.2 ± 8.7	76.3 ± 8.8
Female, n (%)	1696 (67.8)	1767 (68.1)	1665 (67.3)	1760 (67.4)
Comorbidities (ICD-10-GM Code), n (%)
Essential arterial hypertension (I10)	1939 (77.6)	2026 (78.1)	1911 (77.3)	2015 (77.2)
Disorders of lipoprotein metabolism and other lipidaemias (E78)	1327 (53.1)	1377 (51.1)	1328 (53.7)	1437 (55.0)
Osteoporosis (M80/M81)	860 (34.4)	910 (35.1)	871 (35.2)	904 (34.6)
Cataract (H25/H26)	844 (33.8)	863 (33.3)	788 (31.9)	815 (31.2)
Diabetes mellitus (E10-E14)	741 (29.6)	760 (29.3)	713 (28.8)	752 (28.8)
Chronic ischaemic heart disease (I25)	599 (24.0)	635 (24.5)	605 (24.5)	625 (23.9)
Chronic kidney disease (N18)	521 (20.8)	543 (20.9)	493 (19.9)	551 (21.1)
Glaucoma (H40)	423 (16.9)	443 (17.1)	401 (16.2)	425 (16.3)

GCA, giant cell arteritis; ICD-10-GM, 10th revision of the International Classification of Diseases – German modification; N, number of prevalent GCA patients in the InGef database.

Diagnosing and treating physicians

In 2021, most patients received their first GCA diagnosis as outpatients (68.0%) (Table 2). Most frequently, outpatient diagnoses were made in general practice settings (51.4%), that is, by GPs (31.9%) or internists (19.5%), and by rheumatologists (13.1%). In 2020, 16.3% of the newly diagnosed GCA patients (with available follow-up during the 2 years after the incident diagnosis) were referred to a rheumatologist.

Table 2.

Specialty of diagnosing physician and referral to rheumatologist (InGef database).

Year	2018	2019	2020	2021
Year	N (%)	N (%)	N (%)	N (%)
Total number of incident patients	498 (100)	505 (100)	383 (100)	415 (100)
Inpatient index diagnosis	193 (38.8)	199 (39.4)	127 (33.2)	133 (32.0)
Outpatient index diagnosis	305 (61.2)	306 (60.6)	256 (66.8)	282 (68.0)
General practitioner (GP)	95 (31.1)	108 (35.3)	87 (34.0)	90 (31.9)
Internist in GP setting	63 (20.7)	70 (22.9)	52 (20.3)	55 (19.5)
Rheumatologist	39 (12.8)	29 (9.5)	27 (10.5)	37 (13.1)
Ophthalmologist	25 (8.2)	25 (8.2)	23 (9.0)	16 (5.7)
Neurologist/psychiatrist	17 (5.6)	8 (2.6)	7 (2.7)	12 (4.3)
Orthopaedist	6 (1.2)	6 (1.2)	6 (1.6)	13 (3.1)
Other*	27 (8.9)	624 (7.8)	17 (6.6)	13 (4.6)
Not specified	33 (10.8)	36 (11.8)	37 (14.5)	46 (16.3)
Total number of incident patients with 2 years follow-up	454 (100)	465 (100)	355 (100)	–
Referral to rheumatologist**	72 (15.9)	66 (14.2)	58 (16.3)	–

Only specialties that were given for > 1% of the patients in all years are shown. Specialties are expressed as a percentage of the outpatient index diagnoses.

Sum of other specialists (with <5 patients, respectively)

Referral after diagnosis during the follow-up period of 2 years. Since only data until 2022 were available, the follow-up period for patients diagnosed in 2021 was shorter than 2 years. Hence, the percentage of patients with a referral could not be calculated in 2021.

Within one study year, prevalent and incident patients were prescribed medications most frequently by general practitioners (GP), rheumatologists, and internists in a general practice setting (Tables 3 and 4).

Table 3.

Specialty of prescribing physicians in prevalent patients (InGef database).

Year	2018	2019	2020	2021
Year	(N = 2500)	(N = 2594)	(N = 2473)	(N = 2611)
At least one prescription*, n (%)	1616 (64.6)	1690 (65.2)	1556 (62.9)	1636 (62.7)
General practitioner (GP)	868 (34.7)	899 (34.7)	827 (33.4)	829 (31.8)
Internist in GP setting	562 (22.5)	587 (22.6)	522 (21.1)	548 (21.0)
Rheumatologist	504 (20.2)	555 (21.4)	544 (22)	659 (25.2)
Orthopaedist	61 (2.4)	76 (2.9)	60 (2.4)	78 (3.0)
Ophthalmologist	23 (0.9)	26 (1.0)	20 (0.8)	27 (1.0)
Neurologist	50 (2.0)	51 (2.0)	45 (1.8)	68 (2.6)

Predefined medication: glucocorticoids, MTX, IL-6 inhibitors (tocilizumab, sarilumab), JAK inhibitors (tofacitinib, baricitinib, upadacitinib, filgotinib), csDMARDs (antirheumatic drugs and immunosuppressants).

N, Number of prevalent patients in the InGef database.

Table 4.

Specialty of prescribing physician in incident patients (InGef database).

Year	2018	2019	2020	2021
Year	(N = 498)	(N = 505)	(N = 418)	(N = 415)
At least one prescription*, n (%)	405 (81.3)	418 (82.8)	320 (83.6)	349 (84.1)
General practitioner (GP)	239 (48.0)	231 (45.7)	183 (47.8)	190 (45.8)
Internist in GP setting	133 (26.7)	156 (30.9)	117 (30.5)	126 (30.4)
Rheumatologist	126 (25.3)	131 (25.9)	113 (29.5)	150 (36.1)
Orthopaedist	11 (2.2)	15 (3.0)	11 (2.6)	16 (3.9)
Ophthalmologist	11 (2.2)	12 (2.4)	13 (3.4)	17 (4.1)

N, Number of prevalent patients in the InGef database.

Prescribed medications after the incident GCA diagnosis

To describe the medication received after a first GCA diagnosis, a total of 1369 incident GCA patients were analysed, within a 2-year follow-up period after their incident diagnosis.

The majority of the incident patients were treated at least once within the eight quarters after their incident diagnosis (Table 5). Most frequently, GC and MTX were prescribed. The proportion of patients treated with GC-sparing agents like MTX or tocilizumab was increasing over the years of observation. In the year 2020, 26.7% of the patients were treated with MTX, while 14.1% received tocilizumab. In 2020, 13.0% of the GC prescriptions were prescribed for <25 weeks, 39.7% for 25–52 weeks, 33.9% for > 52–104 weeks, and 13.4% for > 104 weeks. The most frequent GC dose was >15 mg/day (70.0%) (Table S3).

Table 5.

Treatments in incident patients during the follow-up period of eight quarters (InGef population).

Year	2018	2019	2020
Year	(N = 493)	(N = 494)	(N = 382)
At least one prescription	438 (88.8)	438 (88.7)	341 (89.3)
Glucocorticoid (H02AB)	435 (88.2)	437 (88.5)	337 (88.2)
Methotrexate (M01CX01, L04AX03)	104 (21.1)	112 (22.7)	102 (26.7)
Tocilizumab (L04AC07)	56 (11.4)	64 (13)	54 (14.1)
Sulfasalazine, leflunomide, or azathioprine (M01CX02, L04AA13, L04AX01)	29 (5.9)	21 (4.3)	13 (3.4)

ATC, anatomical therapeutic chemical; N, number of incident patients with follow-up period of 2 years in the InGef database.

Discussion

Based on this projection from the InGef database for the German population, the prevalence of GCA among residents aged 50 years and older was found to be between 137 and 146 per 100,000 during the study period (2018–2021). The incidence rate ranged from 22 to 28 per 100,000. Both the prevalence and the incidence rates varied slightly throughout the study years. Compared to men, women had higher incidence and prevalence rates.

The majority of the patients received their first diagnosis from general practitioners (GPs), followed by rheumatologists and ophthalmologists. GCA patients were mainly treated with GC and MTX. However, we cannot exclude the possibility that individuals were already taking the medication before GCA was diagnosed, as medication was only assessed from the time of the first GCA diagnosis. On the other hand, GCA patients may receive GC treatment before a formal diagnosis is established, so prior or ongoing therapies may not be captured in our analysis. As a result, our reported medication rates and estimates of treatment duration and intensity may underestimate actual GC exposure. Essential arterial hypertension, lipoprotein disorders, diabetes mellitus, osteoporosis, and cataract were the most frequent comorbidities in prevalent GCA patients.

Comparisons with data from different nations demonstrate that the incidence and prevalence rates of GCA vary significantly depending on the research population’s country of origin. Reported age- and sex-adjusted prevalence rate for a US population were 204/100,000, with a female to men ratio of 3:1 (305 vs 91/100,000).³⁰ This is essentially higher than our findings, especially compared to our female to male ratio of 1.9:1. Similarly, low prevalence rates were observed in studies in the UK and Argentina, with 25 and 28.6 per 100,000 individuals, respectively.^31,32 Moreover, a meta-analysis reporting pooled GCA prevalence across several studies indicated significantly lower rates than our observations.³³

In line with our observations, high GCA incidence rates have been reported^21,34 in Norway (29/100,000) and the UK (22/100,000). By contrast, incidence rates in France (7–10/100,000), Italy (6.9–8.8/100,000), Argentina (8.6/100,000), and Spain (7.42/100,000) were essentially lower than our findings.^{22,32,35
–38} A meta-analysis of 61 studies on GCA incidence rates revealed significant geographical variations. The highest incidence was observed in Scandinavia (21.57/100,000), followed by North and South America (10.89/100,000), Oceania (7.85/100,000), Europe (7.26/100,000), Middle East (5.73/100,000), Africa (4.62/100,000), and East Asia (0.34/100,000).³³ Our findings, however, diverge from this pattern. Our observed incidence rate is approximately three times higher than the pooled European rate and is comparable to the incidence reported for Scandinavia.³³

It is important to note that the observed differences between countries may be caused amongst others by differing study designs, methodologies, definition of GCA diagnosis, and/or geographical coverages.¹ For instance, in some studies, the GCA diagnosis was based on diagnostic codes or hospital/GP records, whereas other relied on classification criteria for GCA diagnosis or temporal artery biopsy.^{1,21,24,31,32,34,36} In our study, GCA cases were identified based on the ICD-10-GM code M31.5 or M31.6 as assigned by physicians according to clinical guidelines. We cannot rule out that some physicians did not validate their diagnosis based on additional clinical or laboratory data. However, we only included GCA cases for which the physicians stated that the diagnosis was confirmed. Additionally, an outpatient GCA diagnosis in our study required at least one additional confirmed outpatient diagnosis or an inpatient primary or secondary diagnosis within three-quarters following the index quarter. Hence, we assume that the risk of overestimating GCA cases in our study is limited, although patients without a documented glucocorticoid prescription (>10%) may have been falsely coded as having GCA. Within the scope of predefined methodology for this study, the proportion of incident GCA patients who had been previously followed for PMR cannot be reliably determined, as patients with a combined diagnosis of GCA and PMR (M31.5) were excluded in the 3 years of baseline analysis.

Some studies report an increase in GCA incidence or prevalence rates over the years.^23,39 However, our data show that incidence and prevalence rates remained rather stable over the study period. This may be due to the short time span of 4 years, but other studies analysing data spanning over 10 years have also failed to find increased incidence rates.³⁴ In our opinion, previous German epidemiological studies underestimated the incidence and prevalence of GCA because patients were identified through questionnaires sent to healthcare providers. Furthermore, increased awareness of GCA and the wider use of imaging modalities may have led to a higher number of diagnoses in cases that were previously overlooked.

In line with a study investigating the medical care situation of GCA in Germany, we found that the initial diagnosis of GCA was mainly made by GPs and rheumatologists, followed by ophthalmologists and neurologists.⁴⁰ In accordance with the study from von Kiel et al.,⁴⁰ our data show that treatment for GCA was mainly initiated by GPs followed by rheumatologists and rarely by ophthalmologists. This may reflect limited access to rheumatology specialists, regional differences in healthcare provision, or varying care pathways, which have important implications for the quality of diagnosis and treatment in rheumatic diseases. In the study of von Kiel et al.,⁴⁰ physicians rated their satisfaction with the medical care situation in Germany at 3.1 ± 3.6 (Likert scale: 1 = very good to 6 = unsatisfactory), indicating a need for rapid referral to specialists and opportunities for continuing education. Lower utilisation of specialised rheumatological care could potentially delay early diagnosis and optimal therapy. This need is addressed by the recent recommendations for defining GCA fast-track clinics.²⁰

Few orthopaedists diagnosed GCA or initiated pharmacological treatment. In some patients, the diagnosis may have been confirmed by other specialists, even when ongoing care was provided by orthopaedists. Furthermore, a subgroup of German orthopaedists holds an additional qualification in rheumatological orthopaedics. These physicians may have prescribed glucocorticoids or methotrexate. However, they generally do not prescribe biologic therapies.

Patients were most frequently initially treated with GC as monotherapy or in combination with MTX in our study, which is in line with other studies.^40
–42 However, information on reasons for prescription of GC or MTX was not available. Hence, it cannot be ruled out that these therapies were prescribed for other (non-chronic) indications. In our cohort, the IL-6 receptor inhibitor TCZ was frequently prescribed (14.1%, in 2020), whereas in previous studies, biologics (TNFα inhibitors, anti-CD20 antibodies, and IL-6-inhibitors) were less commonly prescribed, depending on the medical specialisation of the prescribing physician (GPs in 1% of cases and rheumatologists in 8% of cases).⁴⁰ This difference might be explained by the positive results of the TCZ trial in GCA, which were not published at the time of data collection in the study of von Kiel et al.^12,40 Interestingly, the proportion of patients using GC-sparing drugs such as MTX or TCZ increased over time between 2018 and 2020, suggesting that the need to reduce glucocorticoid use is increasingly recognised by practitioners. However, this may also be explained by possible prescriptions outside the claims system and patient factors like refusal.

Among the most common comorbidities in our study were essential arterial hypertension, osteoporosis, and diabetes mellitus, which is consistent with other studies.^40,42 However, we also identified lipoprotein disorders, glaucoma, and cataract as frequent comorbidities, whereas another study reported chronic pain syndrome and depression among the most common comorbidities.^40
–42 Nevertheless, the reported comorbidities differed widely between the specialisations of the interviewed physicians, with cardiovascular diseases and osteoporosis being the most common comorbidities according to rheumatologists and chronic pain syndrome, cardiovascular diseases, and depression according to GPs.⁴⁰ In our study, comorbidities could be pre-existing (before GCA diagnosis) or newly developed in the respective study year. Nonetheless, comorbidities may be related to GC therapy, including depression, hypertension, and cataract.⁴¹ This indicates the importance of reducing GC doses and underscores the need for GC-sparing treatments to improve patient outcomes and reduce treatment-related complications.

Limitations

The InGef research database contains data from roughly 4.8 million individuals insured in statutory health insurance funds across Germany. Nevertheless, the representativeness of this sample for the national population is restricted to the demographic characteristics of age and sex. Data might not be representative for other demographic or clinical characteristics, such as urban and rural distribution, socioeconomic status, or access to specialist care. This limitation could introduce selection bias, with certain subpopulations potentially being under- or overrepresented. As the InGef database showed good accordance with German reference data regarding hospitalisation and overall mortality rates,²⁷ we assume that also the GCA incidence and prevalence rates in the InGef database are representative for the German population. Although we consider this approach as a robust method, it is important to note that it is still an estimation. However, given the fact that in Germany there is no central clinical register but rather a variety of disease-specialised registers, this, in turn, emphasises the importance of SHI-based analysis to gather information on epidemiological data on diseases.

Furthermore, the analysis might be subject to the immeasurable time bias, as medications during a hospital stay cannot be identified in German claims data. In addition to the billing information relevant to a treatment case used in this analysis, no further information, such as individual patient records or disease-specific laboratory values, can be obtained to validate specific clinical pictures or the disease severity of patients in detail. Studies based on diagnosis codes generally overestimate incidence and prevalence. However, as 88% of the patients described in this study received glucocorticoid therapy, we assume that the majority of patients coded as having a diagnosis of GCA actually have GCA. The last 2 years of the study period were during the COVID pandemic. We can only speculate how this had an impact on the diagnosis, referral, and overall pharmacological treatment of patients with GCA. In this study, GCA diagnoses were often made by general practitioners and were not verified by a second diagnosis. Hence, the number of GCA cases might be inflated due to misdiagnoses.

Conclusion

In conclusion, this investigation suggests that GCA may be more prevalent in patients 50 years of age and older than previously thought, with Germany showing a comparatively high incidence rate.

Nowadays, confirming the diagnosis of GCA requires not only many years of clinical experience but also expertise in specific imaging examinations, such as ultrasound or rapid access to alternative imaging techniques, such as MRI or FDG-PET-CT. In addition, therapy is likely to become more complex due to the mandatory approval of further GC-sparing therapies, which require detailed knowledge of their application, particularly in older patients.

Supplemental Material

sj-docx-1-tab-10.1177_1759720X261439725 – Supplemental material for Frequency, diagnosis, and pharmacological treatment of giant cell arteritis in Germany: database analysis of medical insurance data

Supplemental material, sj-docx-1-tab-10.1177_1759720X261439725 for Frequency, diagnosis, and pharmacological treatment of giant cell arteritis in Germany: database analysis of medical insurance data by Wolfgang A. Schmidt, Marco Alibone, Paul Ludwig, Dominik Obermüller, Franziska Karl, Stephanie Terner and Nils Venhoff in Therapeutic Advances in Musculoskeletal Disease

Footnotes

Acknowledgements

Medical writing support was provided by Julia Simon and Regina Hampel (GKM Gesellschaft für Therapieforschung mbH, Munich, Germany) during the preparation of this article, funded by Novartis according to Good Publication Practice guidelines. Responsibility for opinions, conclusions, and interpretation of data lies with the authors.

Declarations

ORCID iDs

Wolfgang A. Schmidt

Marco Alibone

Nils Venhoff

Supplemental material

Supplemental material for this article is available online.

References

Sharma

Mohammad

Turesson

Incidence and prevalence of giant cell arteritis and polymyalgia rheumatica: a systematic literature review. Semin Arthritis Rheum 2020; 50: 1040–1048.

Schirmer

Aries

Balzer

, et al. S2k-Leitlinie: management der Großgefäßvaskulitiden. Z Rheumatol 2020; 79: 67–95.

Lacy

Nelson

Koyfman

, et al. High risk and low prevalence diseases: Giant cell arteritis. Am J Emerg Med 2022; 58: 135–140.

Gabriel

O’Fallon

Achkar

, et al. The use of clinical characteristics to predict the results of temporal artery biopsy among patients with suspected giant cell arteritis. J Rheumatol 1995; 22: 93–96.

Ponte

Martins-Martinho

Luqmani

RA.

Diagnosis of giant cell arteritis. Rheumatology (Oxford) 2020; 59: iii5–iii16.

Hellmich

Agueda

Monti

, et al. 2018 Update of the EULAR recommendations for the management of large vessel vasculitis. Ann Rheum Dis 2020; 79: 19–30.

Schmidt

Krause

Schicke

, et al. Do temporal artery duplex ultrasound findings correlate with ophthalmic complications in giant cell arteritis? Rheumatology 2009; 48: 383–385.

Nielsen

Seitz

Schmidt

WA.

Update in imaging for large vessel vasculitis. Best Pract Res Clin Rheumatol 2025; 102060.

Opris¸-Belinski

Cobilinschi

Sa˘ulescu

Current perspectives in giant cell arteritis: can we better connect pathogenesis and treatment?

Medicina (Kaunas) 2024; 60: 400.

10.

Paroli

Caccavale

Accapezzato

Giant cell arteritis: advances in understanding pathogenesis and implications for clinical practice. Cells 2024; 13: 267.

11.

Greigert

Genet

Ramon

, et al. New insights into the pathogenesis of giant cell arteritis: mechanisms involved in maintaining vascular inflammation. J Clin Med 2022; 11: 2905.

12.

Stone

Tuckwell

Dimonaco

, et al. Trial of tocilizumab in giant-cell arteritis. N Engl J Med 2017; 377: 317–328.

13.

Blockmans

Penn

Setty

, et al. A phase 3 trial of upadacitinib for giant-cell arteritis. N Engl J Med 2025; 392: 2013–2024.

14.

Schmidt

Dasgupta

Sloane

, et al. A phase 3 randomized, double-blind, placebo-controlled study to evaluate the efficacy and safety of sarilumab in patients with giant cell arteritis. Arthritis Res Ther 2023; 25: 199.

15.

Venhoff

Schmidt

Bergner

, et al. Safety and efficacy of secukinumab in patients with giant cell arteritis (TitAIN): a randomised, double-blind, placebo-controlled, phase 2 trial. Lancet Rheumatol 2023; 5: e341–e350.

16.

Tsalapaki

Lazarini

Argyriou

, et al. Glucocorticoid discontinuation rate and risk factors for relapses in a contemporary cohort of patients with giant cell arteritis. Rheumatol Int 2024; 44: 603–610.

17.

van Nieuwland

Colin

Boumans

, et al. Diagnostic delay in patients with giant cell arteritis: results of a fast-track clinic. Clin Rheumatol 2024; 43: 349–355.

18.

Monti

Bartoletti

Bellis

, et al. Fast-track ultrasound clinic for the diagnosis of giant cell arteritis changes the prognosis of the disease but not the risk of future relapse. Front Med (Lausanne) 2020; 7: 589794.

19.

Diamantopoulos

Haugeberg

Lindland

, et al. The fast-track ultrasound clinic for early diagnosis of giant cell arteritis significantly reduces permanent visual impairment: towards a more effective strategy to improve clinical outcome in giant cell arteritis? Rheumatology (Oxford) 2016; 55: 66–70.

20.

Schmidt

Czihal

Gernert

, et al. Recommendations for defining giant cell arteritis fast-track clinics. English version. Z Rheumatol 2024; 285–288.

21.

Gran

Myklebust

The incidence of polymyalgia rheumatica and temporal arteritis in the county of Aust Agder, south Norway: a prospective study 1987-94. J Rheumatol 1997; 24: 1739–1743.

22.

Salvarani

Macchioni

Zizzi

, et al. Epidemiologic and immunogenetic aspects of polymyalgia rheumatica and giant cell arteritis in northern Italy. Arthritis Rheum 1991; 34: 351–356.

23.

Herlyn

Buckert

Gross

, et al. Doubled prevalence rates of ANCA-associated vasculitides and giant cell arteritis between 1994 and 2006 in northern Germany. Rheumatology (Oxford) 2014; 53: 882–889.

24.

Reinhold-Keller

Zeidler

Gutfleisch

, et al. Giant cell arteritis is more prevalent in urban than in rural populations: results of an epidemiological study of primary systemic vasculitides in Germany. Rheumatology (Oxford) 2000; 39: 1396–1402.

25.

Albrecht

Binder

Minden

, et al. Systematic review to estimate the prevalence of inflammatory rheumatic diseases in Germany. Z Rheumatol 2024; 83: 20–30.

26.

Schmidt

Alibone

Ludwig

, et al. Frequency, diagnosis, and management of polymyalgia rheumatica in Germany-database analysis of medical insurance data. Rheumatology (Oxford) 2025; 64: 5818–5825.

27.

Ludwig

Enders

Basedow

, et al. Sampling strategy, characteristics and representativeness of the InGef research database. Public Health 2022; 206: 57–62.

28.

Statistisches Bundesamt. Bevölkerung: Deutschland, Stichtag, Altersjahre, https://www-genesis.destatis.de/genesis/online/link/tabellen/12411 (2021).

29.

Von Elm

Altman

Egger

, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007; 147: 573–577.

30.

Crowson

Matteson

EL.

Contemporary prevalence estimates for giant cell arteritis and polymyalgia rheumatica, 2015. Semin Arthritis Rheum 2017; 47: 253–256.

31.

Yates

Graham

Watts

, et al. The prevalence of giant cell arteritis and polymyalgia rheumatica in a UK primary care population. BMC Musculoskelet Disord 2016; 17: 285.

32.

Martínez Perez

Mollerach

Scaglioni

, et al. Incidence and prevalence of polymyalgia rheumatica and giant cell arteritis in a healthcare management organization in Buenos Aires, Argentina. J Rheumatol 2023; 50: 93–97.

33.

Semenov

Turk

, et al. A meta-analysis of the epidemiology of giant cell arteritis across time and space. Arthritis Res Ther 2021; 23: 82.

34.

Smeeth

Cook

Hall

AJ.

Incidence of diagnosed polymyalgia rheumatica and temporal arteritis in the United Kingdom, 1990-2001. Ann Rheum Dis 2006; 65: 1093–1098.

35.

Salvarani

Macchioni

Tartoni

, et al. Polymyalgia rheumatica and giant cell arteritis: a 5-year epidemiologic and clinical study in Reggio Emilia, Italy. Clin Exp Rheumatol 1987; 5: 205–215.

36.

Fernández-Lozano

Hernández-Rodríguez

Narvaez

, et al. Incidence and clinical manifestations of giant cell arteritis in Spain: results of the ARTESER register. RMD Open 2024; 10: e003824.

37.

Mahr

Belhassen

Paccalin

, et al. Characteristics and management of giant cell arteritis in France: a study based on national health insurance claims data. Rheumatology 2020; 59: 120–128.

38.

Guittet

de Boysson

Cerasuolo

, et al. Whole-country and regional incidences of giant cell arteritis in French continental and overseas territories: a 7-year nationwide database analysis. ACR Open Rheumatol 2022; 4: 753–759.

39.

Nordborg

Giant cell arteritis: epidemiological clues to its pathogenesis and an update on its treatment. Rheumatology (Oxford) 2003; 42: 413–421.

40.

von Kiel

Dreher

Triantafyllias

, et al. Current patient care of giant cell arteritis in Rhineland-Palatinate. Z Rheumatol 2019; 78: 677–684.

41.

Chatzigeorgiou

Taylor

Elliott

, et al. Common co-morbidities in polymyalgia rheumatica and giant cell arteritis: cross-sectional study in UK Biobank. Rheumatol Adv Pract 2023; 7: rkad095.

42.

Mahr

Hachulla

de Boysson

, et al. Presentation and real-world management of giant cell arteritis (Artemis Study). Front Med (Lausanne) 2021; 8: 732934.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.04 MB