1. IntroductionDuring the last decades, median age of survival of cystic fibrosis (CF) patients has increased significantly [1Stephenson AL Tom M Berthiaume Y Singer LG Aaron SD Whitmore GA et al.A contemporary survival analysis of individuals with cystic fibrosis: a cohort study., 2Keogh RH Seaman SR Barrett JK Taylor-Robinson D Szczesniak R. Dynamic Prediction of Survival in Cystic Fibrosis: A Landmarking Analysis Using UK Patient Registry Data., , 4Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.]. With improving life expectancy, age-related comorbidities such as arthropathy (CFA, cystic fibrosis arthropathy) and osteoporosis [] are gaining more importance. Cases of arthropathy in CF were first described in 1978 [[5]Mathieu JP Stack BH Dick WC Buchanan WW. Pulmonary infection and rheumatoid arthritis.,[6]Episodic arthritis in children with cystic fibrosis.]. Until now, a formal definition of CFA is lacking [[7]Koch AK Bromme S Wollschlager B Horneff G Keyszer G. Musculoskeletal manifestations and rheumatic symptoms in patients with cystic fibrosis (CF) no observations of CF-specific arthropathy.,[8]Fitch G Williams K Freeston JE Dass S Grainger A Hodgson R et al.Ultrasound and magnetic resonance imaging assessment of joint disease in symptomatic patients with cystic fibrosis arthropathy.]. In the context of CF and its variably reported signs, it seems difficult to classify CFA according to established classification categories of non-CF rheumatoid arthritis diseases [[7]Koch AK Bromme S Wollschlager B Horneff G Keyszer G. Musculoskeletal manifestations and rheumatic symptoms in patients with cystic fibrosis (CF) no observations of CF-specific arthropathy.,[9]Schidlow DV Goldsmith DP Palmer J Huang NN. Arthritis in cystic fibrosis.]. As recommended by others [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.], the most clinically useful diagnosis summary was reported by Pertuiset and colleagues: ”CFA was diagnosed when all the following criteria were met: arthropathy with clinical features of articular inflammation without articular sepsis; absence of periostitis on radiographs; absence of another cause of arthritis after evaluation” [[10]Pertuiset E Menkes CJ Lenoir G Jehanne M Douchain F Guillot M. Cystic fibrosis arthritis. A report of five cases.]. The pathomechanism of CFA is not yet fully understood, therefore the ideal treatment is not yet established and is limited to symptomatic treatment [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.,[11]Anti-inflammatory drugs and analgesics for managing symptoms in people with cystic fibrosis-related arthritis.].With a prevalence of 2.6 % - 29 % [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.,[12]Roehmel JF Kallinich T Staab D Schwarz C. Clinical manifestations and risk factors of arthropathy in cystic fibrosis.], CFA is the most common reason for joint pain in patients with CF [[8]Fitch G Williams K Freeston JE Dass S Grainger A Hodgson R et al.Ultrasound and magnetic resonance imaging assessment of joint disease in symptomatic patients with cystic fibrosis arthropathy.]. The USA registry report for 2017 combined terms of arthritis (condition causing pain and inflammation in the joints) and arthropathy (condition causing pain in the joints) and determined 3.4 % of all included patients having this complication []. UK registry data for 2017 gave separate numbers for arthropathy (3.3 %) and arthritis (1.2 %), in all included patients []. Onset of CFA was reported at a mean age of 13 to 20 years [[7]Koch AK Bromme S Wollschlager B Horneff G Keyszer G. Musculoskeletal manifestations and rheumatic symptoms in patients with cystic fibrosis (CF) no observations of CF-specific arthropathy.,15Turner MA Baildam E Patel L David TJ. Joint disorders in cystic fibrosis., 16Botton E Saraux A Laselve H Jousse S Le Goff P Musculoskeletal manifestations in cystic fibrosis., 17Arthropathy in cystic fibrosis.]. The retrospective analysis of a single center cohort (n=186) identified potential risk factors for CFA, such as increasing age, female gender, level of serum IgG, number of pulmonary exacerbations and colonization with Aspergillus fumigatus [[12]Roehmel JF Kallinich T Staab D Schwarz C. Clinical manifestations and risk factors of arthropathy in cystic fibrosis.]. However, comprehensive risk factor analyses in multi-center cohorts are lacking as of yet. Such analyses could confirm and extend disease-specific risk factors, and discriminate modifiable from non-modifiable risk factors to raise attention of the typical presentation of CF arthropathy and increase the CF community's awareness on this common comorbidity which leads to a high treatment burden and decreased quality of life [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.].

The aim of this study was therefore to analyse epidemiology and potential risk factors for CFA in a large CF registry.

2. Methods2.1 Registry data

In this cohort study on annual data from the German CF Registry, all CF patients with a documented encounter between January 2016 and December 2017 were considered for analysis. Patients with history of transplantation (any organ) or missing data concerning complications (e.g. CFA) were excluded. Written informed consent was obtained from all patients.

Data entry is supported by unrestricted grants to improve data quality. In 2017, the German registry MUKO.web includes over 6,106 CF patients from 91 specialized CF sites across Germany, representing approximately over 80% of all CF patients in Germany [].

In 2016/2017, the data of 6425 patients with an encounter in that period were available in the CF registry. Due to transplantation or missing information concerning CFA (exclusion criteria), 356 patients were excluded from the analysis, leading to a total of 6069 patients in the final analysis.

Ethical approval for the study was gained by the Ethics Committee of the Justus-Liebig Universität Gießen FB Medizin (AZ24/19).

2.2 CFA definitions

Similar to other national CF registries, the German CF registry combines the terms arthropathy (condition causing pain in the joints) and arthritis (condition causing pain and inflammation in the joints) in the documentation. Registry data do not allow a differentiation between CF arthritis and non-CF arthritis. Connective tissue disorders are not specifically queried. In the following, we refer to arthropathy and arthritis, when we use the term CFA. CFA was assessed and documented at least once a year. CFA diagnosis was made individually in each center by the attending physician (not questionnaire based, no routine screening).

For our analysis, all patients with at least one encounter in 2016/2017 were divided into two groups: The CFA group included patients with documented CFA at least once during 2016 and 2017, patients without documented CFA during the observation period were included in the control group. For patients of the control group data of the first year documented (2016-2017) and for patients of the CFA group data of the first year with documented CFA (2016-2017) were considered for analysis, meaning that data of only one year per patient was analysed and the examined variables were determined during CFA documentation, not before CFA onset.

2.3 Statistics

As all statistical tests applied are of exploratory character, no adjustment for multiplicity was made. Statistical analyses were performed in SAS 9.4 (Statistical Analysis System, SAS Institute Inc., Cary, NC, USA), and GraphPad Prism 8 Software.

2.4 Descriptive statisticsDescriptive analysis and exploratory tests (two-sided t-Test, Chi-squared-Test) were performed for all patients and for the subgroups of patients aged a priori knowledge and literature review, the following variables were selected for the descriptive analysis: current patient age, gender, medication with cystic fibrosis transmembrane conductance regulator (CFTR) modulator, mutation (dF508 homozygous/ heterozygous, other), body mass index (BMI), BMI percentile, best forced expiratory volume in the first second (FEV1) % predicted, cystic fibrosis-related diabetes (CFRD), allergic bronchopulmonary aspergillosis (ABPA), pancreatic insufficiency, osteoporosis, osteopenia, sinusitis/polyps, antibiotic treatment (long-term, inhaled, oral), steroid intake (any route), antifungal treatment, exacerbations treated with antibiotics (intravenous, oral, inhaled), CF-related hospitalizations (any cause), detection of bacteria (detected at least once during the observed year), chronic bacterial infection, detection of Pseudomonas aeruginosa (leading gram-negative bacteria in CF) [], chronic P. aeruginosa, chronic Staphylococcus aureus (leading gram-positive bacteria in CF) [], chronic methicillin-resistant S. aureus (MRSA), detection of Achromobacter xylosoxidans (non-P. aeruginosa gram-negative bacteria detected in CF) [[20]Coutinho HD Falcao-Silva VS Goncalves GF. Pulmonary bacterial pathogens in cystic fibrosis patients and antibiotic therapy: a tool for the health workers.], chronic A. xylosoxidans (is discussed to be associated with a worse prognosis in CF) [[21]Somayaji R Stanojevic S Tullis DE Stephenson AL Ratjen F Waters V. Clinical Outcomes Associated with Achromobacter Species Infection in Patients with Cystic Fibrosis.], detection of fungus, chronic non-P. aeruginosa gram-negative bacteria (including chronic A. xylosoxidans, chronic Burkholderia spp., chronic Stenotrophomonas maltophilia), detection of Aspergillus fumigatus or other Aspergilli. BMI percentiles were calculated according to Hemmelmann [[22]Hemmelmann C Brose S Vens M Hebebrand J Ziegler A. Percentiles of body mass index of 18-80-year-old German adults based on data from the Second National Nutrition Survey.] (for patients 18-80 years), Neuhauser [] (for patients [24]Kromeyer-Hauschild K WM Kunze D Geller F Geiß HC Hesse V von Hippel A Jaeger U Johnsen D Korte W Menner K Müller G Müller JM Niemann-Pilatus A Remer T Schaefer F Wittchen HU Zabransky S Zellner K Ziegler A Hebebrand J Perzentile für den Body-mass-Index für das Kindes- und Jugendalter unter Heranziehung verschiedener deutscher Stichproben.] (for patients not older than 4 months), for the best FEV1% predicted reference values from the Global Lung Function Initiative (GLI) [[25]Quanjer PH Stanojevic S Cole TJ Baur X Hall GL Culver BH et al.Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations.] were applied. Patients are defined as “chronically infected” by local physician if they currently fulfil the following criteria or have done so in recent years without evidence of a change: a) modified Leeds criteria [[26]Lee TW Brownlee KG Conway SP Denton M Littlewood JM. Evaluation of a new definition for chronic Pseudomonas aeruginosa infection in cystic fibrosis patients.,[27]Proesmans M Balinska-Miskiewicz W Dupont L Bossuyt X Verhaegen J Hoiby N et al.Evaluating the "Leeds criteria" for Pseudomonas aeruginosa infection in a cystic fibrosis centre.], chronic infection: >50%, but at least 4 of the sputum samples collected during the last 12 months were positive; and/or b) significantly raised anti-pseudomonas antibodies according to local laboratories (this accounts for P. aeruginosa infections only). Positive (not chronic) bacteria or fungus culture was identified if the pathogen was detected at least once during the observed year (data included in descriptive analysis only).Since other studies have suggested that P. aeruginosa dependent immunological mechanisms may play a role in the development of CFA [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.], descriptive analyses were repeated for patients ≥18 years without chronic P. aeruginosa infection to dissect P. aeruginosa-independent risk factors.2.5 Logistic regression

Potential risk factors for CFA were analysed by a multivariable logistic regression analysis for CF patients ≥18 years. To identify potential risk factors independent from P. aeruginosa infection, a sensitivity analysis was included for adult CF patients negative for chronic P. aeruginosa. Variables which showed significant differences (p≤0.05) in the exploratory tests (descriptive analysis in patients ≥18 years, Supplementary Table S.2) were included in the logistic regression analysis. In case variables were similar or redundant, a selection was made. The following variables were included: current age, gender, best FEV1% predicted, BMI percentile, antibiotic treatment (long-term), inhaled antibiotic medication, oral antibiotic medication, steroid use, antifungal treatment, number of exacerbations treated with antibiotics, number of hospitalizations, chronic P. aeruginosa, chronic A. xylosoxidans, detection of fungi, CFRD, pancreatic insufficiency, osteopenia, sinusitis/polyps.

A stepwise variable selection process was applied in SAS PROC LOGISTIC in which a significance level of 0.05 was required, to allow a variable into the model, and a significance level of 0.05 to stay in the model.

3. ResultsA total of 6069 patients with confirmed diagnosis of CF aged from 0 to 78 years were included in the analysis. Descriptive statistics are shown in Table 1 and the Supplementary Tables (S.1-S.4). CFA was observed in 299 (4.9 %) of all patients with CF. Patients with CFA were more likely to be female and showed various indicators of more severe disease, regarding lung function, exacerbations and anthropometry, as well as medication load, diagnosed co-morbidities and (chronic) bacterial and fungal infections. In patients aged P. aeruginosa status, CFA was prevalent in n=279 (8.4 %; Supplementary Table S.2). With increasing age, a higher prevalence of CFA was observed (18-29 years: n = 102; 5.7 %; 30-39 years: n = 96; 11.0 %; ≥40 years: n = 81; 12.5 %; Supplementary Table S.2)

Table 1Clinical characteristics of all patients.

N=number of patients; CFA=cystic fibrosis arthropathy; BMI=body mass index; best FEV1% predicted=forced expiratory volume in the first second, percentage of predicted value; CFRD=cystic fibrosis-related diabetes; ABPA=allergic bronchopulmonary aspergillosis; *chronic gram-negative bacteria include Achromobacter xylosoxidans, Burkholderia spp, Stenotrophomonas maltophilia

Prevalence was significantly higher in adult patients compared to patients < 18 years (p<0.0001). Likewise, the prevalence of CFA was significantly higher in adult patients chronically infected with P. aeruginosa compared to adult patients without chronic P. aeruginosa (n=75, 4.8% vs. n=202, 11.7%, Supplementary Table S.4, p<0.0001; Supplementary Table S.2).

For the identification of potential risk factors, logistic regression analysis was used and included variables which showed significant differences in descriptive analysis in adult patients (Supplementary Table S.2; please see methods). Due to the small cohort size of patients with CFA <18 years (n=20), regression analysis was only performed in adult CF patients.

We performed two separate analyses: a) all adult CF patients and b) adult CF patients without chronic P. aeruginosa infection as a sensitivity analysis (Fig. 1). In CF patients ≥18 years, CFA was significantly associated with increasing age (OR=1.04; 95 % CI: 1.02-1.05; pP. aeruginosa infection (OR=1.83; 95 % CI:1.28-2.61; p=0.0009) and the comorbidities CFRD (OR=1.69; 95 % CI:1.23-2.33; p=0.0013), pancreatic insufficiency (OR=2.39; 95 % CI: 1.28-4.46; p=0.0060) and sinusitis/polyps (OR=1.91; 95 % CI: 1.39-2.62; pFig. 1A).

Fig. 1Logistic regression analysis of CF registry data.

Show full caption

Odds ratios and 95% CIs for all statistically significant (p≤0.05) variables in the regression analysis are shown for (A) all adult patients included in the German CF registry from 2016 to 2017 (n=3319) and (B) only adult patients without chronic P. aeruginosa infection (n=1550).

To examine if potential risk factors of CFA vary independently from chronic P. aeruginosa infection, logistic regression analysis was repeated for CF patients ≥18 years without chronic P. aeruginosa. Compared to adult patients with chronic P. aeruginosa infection (Supplementary Table S.4), descriptive analyses showed that CF patients without chronic P. aeruginosa (Supplementary Table S.3) were generally younger (age p<0.0001), had a higher lung function (FEV1% predicted p<0.0001), a better nutritional status (BMI percentile p<0.0001) and tended to have less complications (ABPA p<0.0001; CFRD p<0.0001; pancreatic insufficiency p<0.0001; osteoporosis p<0.0001; osteopenia p<0.0001; antibiotic treatment (long-term, inhaled, oral) p<0.0001; steroids p<0.0001; antifungal treatment p<0.0001; CF related hospitalization p<0.0001; exacerbations treated with antibiotics p<0.0001; data not shown).

In this cohort, CFA remained significantly associated with increasing age (OR=1.04; 95 % CI: 1.01-1.06; p=0.0038), female gender (OR=1.92; 95 % CI: 1.04-3.56; p=0.0373) and pancreatic insufficiency (OR=3.09; 95 % CI: 1.15-8.33; p=0.0258) as well as sinusitis/polyps (OR=2.70; 95 % CI: 1.47-4.96; p=0.0013; Fig. 1B). Antimycotic treatment (OR=2.88; 95 % CI: 1.30-6.41; p=0.0094) emerged as an additional potential risk factor only in patients not chronically infected with P. aeruginosa and CFRD only in the entire adult cohort including P. aeruginosa-positive and -negative patients (Fig. 1).4. DiscussionCFA emerges as a relevant secondary disease in CF [[12]Roehmel JF Kallinich T Staab D Schwarz C. Clinical manifestations and risk factors of arthropathy in cystic fibrosis.,[28]Pathogenesis and management of arthropathy in cystic fibrosis.]. This manuscript presents a large registrybased epidemiological study on CFA. We confirmed that CFA is a frequent complication in adult patients with CF (8.4 %) and can be present in children (0.7 %) (Table 1, Supplementary Table S.1-S.2). The overall prevalence of CFA with 4.9 % is in comparable range with other national registry data, using the same combined registry items of arthritis and arthropathy documentation in their national CF registry [].Logistic regression analysis was used to identify potential risk factors for developing CFA in adult CF patients. Since other studies have suggested that P. aeruginosa dependent immunological mechanisms may play a role in the development of CFA [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.], a sensitivity analysis of adult patients without chronic P. aeruginosa infection was performed (Fig. 1B). While patients with chronic P. aeruginosa infection more frequently developed CFA than patients without infection (Fig. 1A), factors indicating increased disease severity (age, number of hospitalizations and pancreatic insufficiency) associated significantly with CFA in patients regardless of P. aeruginosa status. Potential risk factors were already described by others [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.,[12]Roehmel JF Kallinich T Staab D Schwarz C. Clinical manifestations and risk factors of arthropathy in cystic fibrosis.]. We also found female gender to be significantly associated with CFA. Yet, it should be noted, that the association with female gender may be based solely on the known association between female gender and arthritis and may not be CF specific. Interestingly, sinusitis/polyps also emerged as a common potential risk factor independently of P. aeruginosa colonization. CF-related diabetes and antimycotic treatment, however, only showed a statistically significant association with CFA in those patients with or without chronic P. aeruginosa colonization, respectively.CFA cases have been regularly reported in literature since 1978 [[5]Mathieu JP Stack BH Dick WC Buchanan WW. Pulmonary infection and rheumatoid arthritis.,[6]Episodic arthritis in children with cystic fibrosis.], but until now the aetiology of CFA has not yet been fully elucidated. Several studies reported an association between older age and female gender in the context of joint manifestations and joint pain in CF [[7]Koch AK Bromme S Wollschlager B Horneff G Keyszer G. Musculoskeletal manifestations and rheumatic symptoms in patients with cystic fibrosis (CF) no observations of CF-specific arthropathy.,[12]Roehmel JF Kallinich T Staab D Schwarz C. Clinical manifestations and risk factors of arthropathy in cystic fibrosis.,[29]Lawrence 3rd, JM Moore TL Madson KL Rejent AJ Osborn TG. Arthropathies of cystic fibrosis: case reports and review of the literature.] which is supported by our data (Table 1, Supplementary Table S.1-S.2, Fig. 1). Persistent inflammation, a dysregulated immune system and bacterial and viral infections are associated with chronic inflammation of joints (RA, rheumatoid arthritis) [[30]Hou Y Lin H Zhu L Liu Z Hu F Shi J et al.Lipopolysaccharide increases the incidence of collagen-induced arthritis in mice through induction of protease HTRA-1 expression.,[31]Liu W Zhang Y Zhu W Ma C Ruan J Long H et al.Sinomenine Inhibits the Progression of Rheumatoid Arthritis by Regulating the Secretion of Inflammatory Cytokines and Monocyte/Macrophage Subsets.]. Studies with RA animal models (CIA, collagen-induced arthritis) have clearly demonstrated a role for LPS (Lipopolysaccharide), a substance produced by gram-negative bacteria [32The role of lipopolysaccharide injected systemically in the reactivation of collagen-induced arthritis in mice., 33Yoshino S Yamaki K Taneda S Yanagisawa R Takano H. Reactivation of antigen-induced arthritis in mice by oral administration of lipopolysaccharide., 34Tanaka S Toki T Akimoto T Morishita K. Lipopolysaccharide accelerates collagen-induced arthritis in association with rapid and continuous production of inflammatory mediators and anti-type II collagen antibody.], in the induction of autoimmune arthritis [[30]Hou Y Lin H Zhu L Liu Z Hu F Shi J et al.Lipopolysaccharide increases the incidence of collagen-induced arthritis in mice through induction of protease HTRA-1 expression.,[34]Tanaka S Toki T Akimoto T Morishita K. Lipopolysaccharide accelerates collagen-induced arthritis in association with rapid and continuous production of inflammatory mediators and anti-type II collagen antibody.,[35]Yoshino S Sasatomi E Ohsawa M. Bacterial lipopolysaccharide acts as an adjuvant to induce autoimmune arthritis in mice.], suggesting factors related to inflammation or exacerbation to impact on CFA risk. In that line, epidemiological studies with CF patients have demonstrated that the occurrence of rheumatic symptoms is associated with pulmonary infections and lung inflammation [[4]Clarke EA Watson P Freeston JE Peckham DG Jones AM Horsley A. Assessing arthritis in the context of cystic fibrosis.], via various microorganisms [[28]Pathogenesis and management of arthropathy i