Hamburg Institute for Therapy Research

Abstract BACKGROUND Glioblastomas are functionally integrated into their peritumoral neural environment, and the dynamic functional interaction can be analyzed using network theory, providing insights into the tumor-brain interface. We investigated peritumoral network connectedness of glioblastomas, revealing its association with distinct epigenetic signatures, its influence on survival, and its susceptibility to modification through surgical treatment. MATERIAL AND METHODS Resting-state fMRI was performed on 48 glioblastoma patients. Tumor lesions were segmented, and networks were constructed at 10mm and 40mm distances from the tumor margin. These networks were mirrored to the healthy hemisphere to compare lesional and contralesional networks. The difference between lesional and contralesional mean degree centrality was calculated to assess peritumoral network connectedness. Its correlation with epigenetic signatures and effect on overall survival were analyzed. Surgery-induced changes in peritumoral network connectedness were evaluated in seven patients with follow-up data. RESULTS Mean degree centrality was significantly higher in the lesional compared to the contralesional network (p=.032), indicating a tumor-induced effect on its local environment and reflecting high peritumoral network connectedness. Glioblastomas with a neural high epigenetic signature exhibited increased peritumoral network connectedness (p=.010), which was associated with decreased survival (p=.036). Postoperative peritumoral network connectedness tended to decrease, suggesting that surgical resection disrupts the functional communication between the tumor and its peritumoral environment. CONCLUSION The role of network features in predicting patient survival suggests their clinical relevance as imaging biomarkers for assessing personalized treatment strategies, which may include targeting crucial nodes for disconnection or even neuromodulation of neural circuits.

Clinical studies of biologics in severe asthma exclude smokers or ex-smokers (ExS) with over 10 pack-years (py). Thus, the effectiveness of this therapy in ExS with severe asthma is not well understood. To assess the impact of smoking on clinical efficiency of biologics in patients with severe asthma from the German Asthma Net, a comprehensive international registry. This analysis included 1129 patients (55.8% female, mean age: 53.82 ± 14.67 years), of whom 56% were never-smokers (NS), whereas 44% were ExS (<10 py: 22.9%, 10-20 py: 10.3%, and >20 py: 10.6%). They received benralizumab (38.3%), dupilumab (28.9%), mepolizumab (18.3%), omalizumab (14%), or reslizumab (0.5%). Biologic therapy significantly improved asthma control, measured by change in Asthma Control Test, Asthma Control Questionnaire-5, and Mini-Asthma Quality of Life Questionnaire, lung function, reduced exacerbations, and daily oral prednisolone dose in all patients at week 52. Of note, no significant differences in asthma control between NS and ExS at week 52 (P= .48, .09, and .15, respectively) were observed. Also, lung function improvement (forced expiratory volume in 1 second, forced vital capacity, total lung capacity, peak expiratory flow, mean expiratory flow at 50%, P > .05), and reduction in acute exacerbation (P= .8) and oral corticosteroid doses (P= .15) were comparable in NS and ExS. Markers of type 2 inflammation, such as fraction of exhaled nitric oxide and blood eosinophils, decreased in ExS similar to NS (P= .29 and P= .48, respectively). ExS with severe asthma experienced similar improvements in asthma control, exacerbations, lung function, and biomarkers as NS after 1 year of biologics, suggesting that severe asthmatics even with a substantial smoking history can benefit from biologic therapy.

Abstract RATIONALE: Although dupilumab has been approved for the treatment of severe asthma, evidence on its real-life effectiveness is still insufficient. METHODS: All patients from the German Asthma Network (GAN) severe asthma registry who initiated dupilumab after inclusion into the registry were analysed. Clinical effectiveness was evaluated in those with at least two follow-up visits, with maximum follow-up currently 3 years. RESULTS: A total of 481 patients with severe asthma initiated dupilumab. At baseline, median blood eosinophil count was 174 cells/µL (IQR 61.2-436); 184 (38.3%) were former smokers with median 9.6 pack-years (IQR 4.3-23.3). Clinical effectiveness was evaluated in 235 patients. Mean FEV1 increased from baseline statistically and clinically significantly at all timepoints (+300 mL at 4 months and 1 year, +200 mL at 2 and 3 years, p&amp;lt;0.0001 for all). The frequency of exacerbations decreased from baseline at all timepoints. Mean Asthma Control Test increased from baseline statistically and clinically significantly at all timepoints (+4.3 at 4 months, +4.9 points at 1 year, +5.3 points at 2 years, and +4.6 points at 3 years, p&amp;lt;0.0001 for all). CONCLUSIONS: To our knowledge this is the largest real-life study of dupilumab in patients with severe asthma. In our cohort dupilumab, showed long-term real-life effectiveness up to 3 years, with results consistent with prior randomised controlled trials.

Real-world evidence studies of ustekinumab (UST) in ulcerative colitis (UC) are needed because randomized controlled trials do not represent unselected patient populations in everyday clinical practice. Patients with UC were recruited when starting biologic therapy for the first time or switching to a new biologic therapy. This study assessed the effectiveness of maintenance therapy with UST in comparison to anti-TNF or vedolizumab (VDZ) at 12 months. Between 2020 and 2022, 507 UC patients starting biologic therapy for the first time or switching to a new biologic therapy were enrolled at 34 inflammatory bowel disease (IBD)-specialized centers in Germany. After excluding patients receiving other biologics or small molecules, as well as those with stomas or missing outcomes, the final sample consisted of 476 patients. The outcomes were clinical response, clinical remission (CR), and steroid-free remission. Propensity score (PS) adjustment with inverse probability of treatment weighting was used to reduce the effect of confounding due to physician selection of therapy. A total of 476 patients with UC were included in the analysis (UST: 147, anti-TNF: 168, VDZ: 161). Treatment persistence over 12 months differed significantly (P < .001) between UST (93.9%), VDZ (87.0%), and anti-TNF (75.0%). The PS-weighted effectiveness of UST in the mITT analysis at month 12 was not significantly different from anti-TNF or VDZ (CR: UST 26.9%, anti-TNF 34.7%, VDZ 40.9%; P = .063). In the prospective RUN-UC study with PS-weighted groups, UST showed higher treatment persistence but no significant difference in maintenance effectiveness compared to anti-TNF or VDZ in UC.

Der bedarfsgerechte Einsatz der Kombinationstherapie aus LABA/ICS wird neben der SABA-Therapie seit 2019 von der GINA bei Patienten mit schwerem Asthma empfohlen. Hintergrund dieser Empfehlung ist, dass beim Asthma die entzündliche Komponente durch lokale Kortikosteroidinhalation (ICS) behandelt wird und hierdurch Exazerbationen abnehmen. Bislang liegen noch keine Daten über die veränderte Anwendung von SMART im klinischen Alltag vor. Die Auswertung der Daten des German Asthma Net e.V. (GAN) bietet die Möglichkeit seit 2009 die Verordnungspraxis zu erfassen. In dieser Registerauswertung des Zeitraums vor 2019 sowie der Jahre 2019 bis 2022 konnte ein SMART-Anteil an der Bedarfstherapie von 1% vor 2019 mit einem langsamen, jedoch zunehmenden Anteil bis zum Jahr 2022 (12%) bei weiterhin ca. 50% Verordnung von SABA gezeigt werden. Der Vergleich von Patienten mit SABA gegenüber Patienten mit SMART-Therapie ergab sowohl eine bessere Asthma-Kontrolle, Lungenfunktion und Oxygenierung ohne signifikante Unterschiede beim exhalierten NO oder den Eosinophilen im Blutbild. Die Auswertung der Patienten unter einer Biologica-Therapie in Bezug auf die Bedarfstherapie zeigte eine verbesserte Krankheitskontrolle ohne signifikante Unterschiede der Lungenfunktionsparameter oder des FeNO unter SMART-Therapie. Die Therapie zwischen den Gruppen ergab signifikante Unterschiede – in der SABA-Kohorte wurden häufiger ICS Single-Inhaler, Leukotrienrezeptorantagonisten sowie Theophyllin eingesetzt. Unterschiede in der Anwendung von Dreifachkombinationen (ICS/LABA/LAMA) ergaben sich nicht.

BackgroundFor therapy of severe asthma 5 monoclonal antibodies have been available in Germany up to November 2022, but no clear rules exist on choice of initial therapy, assessment of response, and switch. ObjectiveTo assess current practice on all aspects of biologic therapy by specialists in Germany. MethodsA questionnaire was created by specialists for severe asthma, which was tested and modified by further experts. We invited 119 pulmonologists of the German Asthma Net (GAN) to complete the survey and used SoSci Survey and SPSS for data collection and analysis. ResultsForty-seven pulmonologists took part in the survey with a median annual number of patients treated with biologics of 35, 55% worked in an outpatient practice, and 40% in a hospital. Exacerbations and oral steroid use were the most important factors for the decision to start a biologic therapy. Accordingly, these parameters were also the most relevant for assessment of response. Most participants considered type-2 inflammation biomarkers and comorbidities (foremost CRSwNP and AD) for choosing initial biologic. Asthma Control Test (ACT) was the most common instrument for assessing status of disease control. There was no consensus on thresholds for response of pulmonary function tests including FEV1, FVC, and RV. Eighty-five percent of participants distinguished between “responders”, “partial responders” and “non-responders”. Comorbidities played an important role for the decision to switch to another biologic, eg, when initial therapy had insufficient effectiveness on CRSwNP. ConclusionThis study provides a detailed insight into current opinions and practice of biologic use in severe asthma in Germany.

<b>Background:</b> Little is known about how smoking affects asthma patients’ characteristics, and therefore may impact treatment choices regarding biologic therapy (BT) and its therapy response <b>Objective:</b> Our aim was to evaluate the impact of smoking on baseline data in patients with severe asthma. <b>Methods:</b> We analysed patients’ characteristics including pulmonary function tests, asthma control, exacerbation rate and biomarkers. We performed linear models comparing smokers vs. never-smokers, and three pre-defined groups stratified by smoking history (&lt;10 pack-years (py), 10-20 py, &gt;20 py). Data was obtained from GAN. <b>Results:</b> We included 2.478 patients: 65 (2.6%) active smokers, 1.005 (40.6%) ex-smokers and 1.408 (56.8%) never-smokers. 529 patients (21.3%) had &lt;10 py, 304 (12.3%) 10-20 py and 237 (9.6%) &gt;20 py. Smoking was associated with worse asthma control (&gt;20 py: ACT -1.77 points (p &lt;.001); mini-AQLQ -4.88 (p=.004)), while exacerbation rate and oral corticosteroid doses were similar. Smoking was associated with worse lung function indicating smoking-related lung injury e.g. DLCO (0.85-fold lower with 10-20 py (p&lt;.001) resp. 0.82 fold lower with &gt;20 py (p&lt;.001)). Smokers had greater signs of hyperinflation (higher RV (p&lt;.001) and TLC (p&lt;.008)). Regarding biomarkers smoking was associated with 1.58-fold higher IgE levels (&gt;20 py: p=.002), 0.84-fold lower FeNO concentrations (p=.001) and 2.12-fold higher blood eosinophil count (BEC, p=.045). <b>Conclusion:</b> Smoking history in patients with severe asthma significantly affects baseline characteristics, such as IgE levels, FeNO, BEC and pulmonary functionthereby impacting treatment choices regarding BT and possibly response to therapy.

<b>Background:</b> The relevance of the age of asthma onset for type 2 biomarker expression in severe asthma is incompletely understood. <b>Methods:</b> Data of 1512 patients documented in the German severe asthma registry (GAN) were analysed according to age of asthma onset (severe early-onset asthma, SEA: age of onset &lt;18 years of age; severe adult-onset asthma, SAA: age of onset ≥18 years of age). <b>Results:</b> There were 456 patients with SEA (30.2%, median age: 38 years, median age at asthma onset: 5 years) and 1056 patients with SAA (69.8%, median age: 56 years, median age at asthma onset: 40 years). There was no significant difference in the gender distribution (SEA: 59%, SAA: 56.2% females). SAA was characterised by a higher percentage of ever-smokers (SEA: 24.6%, SAA: 48.9%), a higher median BMI (SEA: 24.9 kg/m2, SAA: 26.7 kg/m2), a higher number of very frequent exacerbators (SEA: 4.7%, SAA: 8.3%) and a higher percentage of patients with chronic sinusitis (SEA: 39%, SAA: 56.5%), nasal polyps (SEA: 22.3%, SAA: 45.2%) and Aspirin-exacerbated respiratory disease (SEA: 17.8%, SAA: 23.8%) than SEA. In contrast, there was a lower median FEV1 (SEA: 70%, SAA: 66% predicted), a lower median total serum immunoglobulin E (IgE, SEA: 201 IU/ml, SAA: 169 IU/ml) and a lower prevalence of allergic co-morbidities (SEA: 81.5%, SAA: 57.5%) in SAA than in SEA. Patients with SAA displayed higher median exhaled FeNO values (SEA: 23 ppb, SAA: 41 ppb) and higher median blood eosinophil counts (SEA: 200 cells/µl, SAA: 251 cells/µl) than patients with SEA. <b>Conclusion:</b> Severe adult-onset asthma is characterised by a stronger expression of type 2 biomarkers than severe early-onset asthma.