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Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs.
Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata® and Excel.
Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1–25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0–88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE- syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%—subcutaneous; 29%—intravenous; 1%—unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy.
Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment.
Ziele: Das Ziel dieser offiziellen Leitlinie, die von der Deutschen Gesellschaft für Gynäkologie und Geburtshilfe (DGGG) und der Deutschen Krebsgesellschaft (DKG) publiziert und koordiniert wurde, ist es, die Früherkennung, Diagnostik, Therapie und Nachsorge des Mammakarzinoms zu optimieren.
Methoden: Der Aktualisierungsprozess der S3-Leitlinie aus 2012 basierte zum einen auf der Adaptation identifizierter Quellleitlinien und zum anderen auf Evidenzübersichten, die nach Entwicklung von PICO-(Patients/Interventions/Control/Outcome-)Fragen, systematischer Recherche in Literaturdatenbanken sowie Selektion und Bewertung der gefundenen Literatur angefertigt wurden. In den interdisziplinären Arbeitsgruppen wurden auf dieser Grundlage Vorschläge für Empfehlungen und Statements erarbeitet, die im Rahmen von strukturierten Konsensusverfahren modifiziert und graduiert wurden.
Empfehlungen: Der Teil 1 dieser Kurzversion der Leitlinie zeigt Empfehlungen zur Früherkennung, Diagnostik und Nachsorge des Mammakarzinoms: Der Stellenwert des Mammografie-Screenings wird in der aktualisierten Leitlinienversion bestätigt und bildet damit die Grundlage der Früherkennung. Neben den konventionellen Methoden der Karzinomdiagnostik wird die Computertomografie (CT) zum Staging bei höherem Rückfallrisiko empfohlen. Die Nachsorgekonzepte beinhalten Untersuchungsintervalle für die körperliche Untersuchung, Ultraschall und Mammografie, während weiterführende Gerätediagnostik und Tumormarkerbestimmungen bei der metastasierten Erkrankung Anwendung finden.
Purpose: The aim of this official guideline coordinated and published by the German Society for Gynecology and Obstetrics (DGGG) and the German Cancer Society (DKG) was to optimize the screening, diagnosis, therapy and follow-up care of breast cancer.
Methods: The process of updating the S3 guideline dating from 2012 was based on the adaptation of identified source guidelines which were combined with reviews of evidence compiled using PICO (Patients/Interventions/Control/Outcome) questions and the results of a systematic search of literature databases and the selection and evaluation of the identified literature. The interdisciplinary working groups took the identified materials as their starting point to develop recommendations and statements which were modified and graded in a structured consensus procedure.
Recommendations: Part 1 of this short version of the guideline presents recommendations for the screening, diagnosis and follow-up care of breast cancer. The importance of mammography for screening is confirmed in this updated version of the guideline and forms the basis for all screening. In addition to the conventional methods used to diagnose breast cancer, computed tomography (CT) is recommended for staging in women with a higher risk of recurrence. The follow-up concept includes suggested intervals between physical, ultrasound and mammography examinations, additional high-tech diagnostic procedures, and the determination of tumor markers for the evaluation of metastatic disease.
Simple Summary: Pseudoprogression detection in glioblastoma patients remains a challenging task. Although pseudoprogression has only a moderate prevalence of 10–30% following first-line treatment of glioblastoma patients, it bears critical implications for affected patients. Non-invasive techniques, such as amino acid PET imaging using the tracer O-(2-[18F]-fluoroethyl)-L-tyrosine (FET), expose features that have been shown to provide useful information to distinguish tumor progression from pseudoprogression. The usefulness of FET-PET in IDH-wildtype glioblastoma exclusively, however, has not been investigated so far. Recently, machine learning (ML) algorithms have been shown to offer great potential particularly when multiparametric data is available. In this preliminary study, a Linear Discriminant Analysis-based ML algorithm was deployed in a cohort of newly diagnosed IDH-wildtype glioblastoma patients (n = 44) and demonstrated a significantly better diagnostic performance than conventional ROC analysis. This preliminary study is the first to assess the performance of ML in FET-PET for diagnosing pseudoprogression exclusively in IDH-wildtype glioblastoma and demonstrates its potential.
Abstract: Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.
Background: Cytokines are mediators of inflammation that contribute to a low-grade inflammation in different disorders like major depression and obesity. It still remains unclear which psychological and medical factors interact with cytokine regulation. In the current investigation, the association between levels of pro-and anti-inflammatory cytokines and anthropometrics, mood state (depressiveness), physical activity and sleep were investigated in a sample of community-dwelled adults.
Methods: Forty-nine subjects met the inclusion criteria for analyses and were assessed at two time-points (baseline (T1) and follow-up (T2), average T1-T2-interval = 215 days). Serum cytokine measures included the pro-inflammatory cytokines interleukin (IL)-2, IL-12, IFN-γ and TNF-α, the anti-inflammatory cytokines IL-4, IL-5, IL-10 and IL-13 and the granulocyte-macrophage colony-stimulating factor (GM-CSF); anthropometrics were assessed via physical examination, depressiveness was assessed via Beck Depression Inventory (BDI)2, parameters of physical activity (steps, METs) and sleep (night/total sleep duration) were measured via a 1-week actigraphy.
Results: Correlation analyses showed low-to moderate significant relationships between the majority of cytokines and the BDI2 at T1, positive correlation with weight and BMI at T1 and T2, and negative correlations with the number of steps and METs at T2 and T2. Regression analyses for T1 revealed that the BDI2 score was the best positive predictor for the concentrations of all nine cytokines, followed by the number of steps and the nightsleep duration as negative predictors. At T2, the amount of steps was found to be negatively associated with IL-4, IL5, IL-10, GM-CSF, IFN-γ, and TNF-α, whereas the BMI could significantly predict IL-12 and IL-13. The BDI2-score was not significantly associated with any of the cytokines. No associations could be found between dynamics in cytokines from T1 and T2 and changes in any of the variables.
Discussion: The present results indicate an influence of physical activity, subjective well-being and body composition on inflammatory mediators. Since there was no standardized intervention targeting the independent variables between T1 and T2, no assumptions on causality can be drawn from the association results.
Background: Obesity and depression are both associated with changes in sleep/wake regulation, with potential implications for individualized treatment especially in comorbid individuals suffering from both. However, the associations between obesity, depression, and subjective, questionnaire-based and objective, EEG-based measurements of sleepiness used to assess disturbed sleep/wake regulation in clinical practice are not well known.
Objectives: The study investigates associations between sleep/wake regulation measures based on self-reported subjective questionnaires and EEG-derived measurements of sleep/wake regulation patterns with depression and obesity and how/whether depression and/or obesity affect associations between such self-reported subjective questionnaires and EEG-derived measurements.
Methods: Healthy controls (HC, NHC = 66), normal-weighted depressed (DEP, NDEP = 16), non-depressed obese (OB, NOB = 68), and obese depressed patients (OBDEP, NOBDEP = 43) were included from the OBDEP (Obesity and Depression, University Leipzig, Germany) study. All subjects completed standardized questionnaires related to daytime sleepiness (ESS), sleep quality and sleep duration once as well as questionnaires related to situational sleepiness (KSS, SSS, VAS) before and after a 20 min resting state EEG in eyes-closed condition. EEG-based measurements of objective sleepiness were extracted by the VIGALL algorithm. Associations of subjective sleepiness with objective sleepiness and moderating effects of obesity, depression, and additional confounders were investigated by correlation analyses and regression analyses.
Results: Depressed and non-depressed subgroups differed significantly in most subjective sleepiness measures, while obese and non-obese subgroups only differed significantly in few. Objective sleepiness measures did not differ significantly between the subgroups. Moderating effects of obesity and/or depression on the associations between subjective and objective measures of sleepiness were rarely significant, but associations between subjective and objective measures of sleepiness in the depressed subgroup were systematically weaker when patients comorbidly suffered from obesity than when they did not.
Conclusion: This study provides some evidence that both depression and obesity can affect the association between objective and subjective sleepiness. If confirmed, this insight may have implications for individualized diagnosis and treatment approaches in comorbid depression and obesity.
Background: Platelet activating factor and tachykinins (substance P, neurokinin A, neurokinin B) are important mediators contributing to increased airway secretion in the context of different types of respiratory diseases including acute and chronic asthma. Leukotriene receptor antagonists are recommended as add-on therapy for this disease. The cys-leukotriene-1 receptor antagonist montelukast has been used in clinical asthma therapy during the last years. Besides its inhibitory action on bronchoconstriction, only little is known about its effects on airway secretions. Therefore, the aim of this study was to evaluate the effects of montelukast on platelet activating factor- and tachykinin induced tracheal secretory activity.
Methods: The effects of montelukast on platelet activating factor- and tachykinin induced tracheal secretory activity in the rat were assessed by quantification of secreted 35SO4 labelled mucus macromolecules using the modified Ussing chamber technique.
Results: Platelet activating factor potently stimulated airway secretion, which was completely inhibited by the platelet activating factor receptor antagonist WEB 2086 and montelukast. In contrast, montelukast had no effect on tachykinin induced tracheal secretory activity.
Conclusion: Cys-leukotriene-1 receptor antagonism by montelukast reverses the secretagogue properties of platelet activating factor to the same degree as the specific platelet activating factor antagonist WEB 2086 but has no influence on treacheal secretion elicited by tachykinins. These results suggest a role of montelukast in the signal transduction pathway of platelet activating factor induced secretory activity of the airways and may further explain the beneficial properties of cys-leukotriene-1 receptor antagonists.
No association between Parkinson disease and autoantibodies against NMDA-type glutamate receptors
(2019)
Background: IgG-class autoantibodies to N-Methyl-D-Aspartate (NMDA)-type glutamate receptors define a novel entity of autoimmune encephalitis. Studies examining the prevalence of NMDA IgA/IgM antibodies in patients with Parkinson disease with/without dementia produced conflicting results. We measured NMDA antibodies in a large, well phenotyped sample of Parkinson patients without and with cognitive impairment (n = 296) and controls (n = 295) free of neuropsychiatric disease. Detailed phenotyping and large numbers allowed statistically meaningful correlation of antibody status with diagnostic subgroups as well as quantitative indicators of disease severity and cognitive impairment.
Methods: NMDA antibodies were analysed in the serum of patients and controls using well established validated assays. We used anti-NMDA antibody positivity as the main independent variable and correlated it with disease status and phenotypic characteristics.
Results: The frequency of NMDA IgA/IgM antibodies was lower in Parkinson patients (13%) than in controls (22%) and higher than in previous studies in both groups. NMDA IgA/IgM antibodies were neither significantly associated with diagnostic subclasses of Parkinson disease according to cognitive impairment, nor with quantitative indicators of disease severity and cognitive impairment. A positive NMDA antibody status was positively correlated with age in controls but not in Parkinson patients.
Conclusion: It is unlikely albeit not impossible that NMDA antibodies play a significant role in the pathogenesis or progression of Parkinson disease e.g. to Parkinson disease with dementia, while NMDA IgG antibodies define a separate disease of its own.
Epigenetic signatures such as methylation of the monoamine oxidase A (MAOA) gene have been found to be altered in panic disorder (PD). Hypothesizing temporal plasticity of epigenetic processes as a mechanism of successful fear extinction, the present psychotherapy-epigenetic study for we believe the first time investigated MAOA methylation changes during the course of exposure-based cognitive behavioral therapy (CBT) in PD. MAOA methylation was compared between N=28 female Caucasian PD patients (discovery sample) and N=28 age- and sex-matched healthy controls via direct sequencing of sodium bisulfite-treated DNA extracted from blood cells. MAOA methylation was furthermore analyzed at baseline (T0) and after a 6-week CBT (T1) in the discovery sample parallelized by a waiting time in healthy controls, as well as in an independent sample of female PD patients (N=20). Patients exhibited lower MAOA methylation than healthy controls (P<0.001), and baseline PD severity correlated negatively with MAOA methylation (P=0.01). In the discovery sample, MAOA methylation increased up to the level of healthy controls along with CBT response (number of panic attacks; T0–T1: +3.37±2.17%), while non-responders further decreased in methylation (−2.00±1.28%; P=0.001). In the replication sample, increases in MAOA methylation correlated with agoraphobic symptom reduction after CBT (P=0.02–0.03). The present results support previous evidence for MAOA hypomethylation as a PD risk marker and suggest reversibility of MAOA hypomethylation as a potential epigenetic correlate of response to CBT. The emerging notion of epigenetic signatures as a mechanism of action of psychotherapeutic interventions may promote epigenetic patterns as biomarkers of lasting extinction effects.