Trends in radiotherapy inpatient admissions in Germany: a population-based study over a 10-year period

Objective With the increasing complexity of oncological therapy, the number of inpatient admissions to radiotherapy and non-radiotherapy departments might have changed. In this study, we aim to quantify the number of inpatient cases and the number of radiotherapy fractions delivered under inpatient conditions in radiotherapy and non-radiotherapy departments. Methods The analysis is founded on data of all hospitalized cases in Germany based on Diagnosis-Related Group Statistics (G-DRG Statistics, delivered by the Research Data Centers of the Federal Statistical Office). The dataset includes information on the main diagnosis of cases (rather than patients) and the performed procedures during hospitalization based on claims of reimbursement. We used linear regression models to analyze temporal trends. The considered data encompass the period from 2008 to 2017. Results Overall, the number of patients treated with radiotherapy as inpatients remained constant between 2008 (N = 90,952) and 2017 (N = 88,998). Starting in January 2008, 48.9% of 4000 monthly cases received their treatment solely in a radiation oncology department. This figure decreased to 43.7% of 2971 monthly cases in October 2017. We found a stepwise decrease between December 2011 and January 2012 amounting to 4.3%. Fractions received in radiotherapy departments decreased slightly by 29.3 (95% CI: 14.0–44.5) fractions per month. The number of days hospitalized in radiotherapy departments decreased by 83.4 (95% CI: 59.7, 107.0) days per month, starting from a total of 64,842 days in January 2008 to 41,254 days in 2017. Days per case decreased from 16.2 in January 2008 to 13.9 days in October 2017. Conclusion Our data give evidence to the notion that radiotherapy remains a discipline with an important inpatient component. Respecting reimbursement measures and despite older patients with more comorbidities, radiotherapy institutions could sustain a constant number of cases with limited temporal shifts

Inflammation and prolonged QT time: Results from the Cardiovascular Disease, Living and Ageing in Halle (CARLA) study

Background: Previous research found an association of CRP with QT time in population based samples. Even more, there is evidence of a substantial involvement of the tumor necrosis factor-alpha system in the pathophysiology of cardiac arrhythmia, while the role of Interleukin 6 remains inconclusive. Objective: To determine the association between inflammation with an abnormally prolonged QT-time (APQT) in men and women of the elderly general population. Methods: Data descend from the baseline examination of the prospective, population-based Cardiovascular Disease, Living and Ageing in Halle (CARLA) Study. After exclusion of subjects with atrial fibrillation and missing ECG recording the final study cohort consisted of 919 men and 797 women. Blood parameters of inflammation were the soluble TNF-Receptor 1 (sTNF-R1), the high-sensitive C-reactive protein (hsCRP), and Interleukin 6 (IL-6). In accordance with major cardiologic societies we defined an APQT above a QT time of 460 ms in women and 450 ms in men. Effect sizes and the corresponding 95% confidence intervals (CI) were estimated by performing multiple linear and logistic regression analyses including the analysis of sex differences by interaction terms. Results: After covariate adjustment we found an odds ratio (OR) of 1.89 (95% CI: 1.13, 3.17) per 1000 pg/mL increase of sTNF-R1 in women, and 0.74 (95% CI: 0.48, 1.15) in men. In the covariate adjusted linear regression sTNF-R1 was again positively associated with QT time in women (5.75 ms per 1000 pg/mL, 95% CI: 1.32, 10.18), but not in men. Taking possible confounders into account IL-6 and hsCRP were not significantly related to APQT in both sexes. Conclusion: Our findings from cross-sectional analyses give evidence for an involvement of TNF-alpha in the pathology of APQT in women

Integration of radiation oncology teaching in medical studies by German medical faculties due to the new licensing regulations: an overview and recommendations of the consortium academic radiation oncology of the German Society for Radiation Oncology (DEGRO)

The new Medical Licensing Regulations 2025 (Ärztliche Approbationsordnung, ÄApprO) will soon be passed by the Federal Council (Bundesrat) and will be implemented step by step by the individual faculties in the coming months. The further development of medical studies essentially involves an orientation from fact-based to competence-based learning and focuses on practical, longitudinal and interdisciplinary training. Radiation oncology and radiation therapy are important components of therapeutic oncology and are of great importance for public health, both clinically and epidemiologically, and therefore should be given appropriate attention in medical education. This report is based on a recent survey on the current state of radiation therapy teaching at university hospitals in Germany as well as the contents of the National Competence Based Learning Objectives Catalogue for Medicine 2.0 (Nationaler Kompetenzbasierter Lernzielkatalog Medizin 2.0, NKLM) and the closely related Subject Catalogue (Gegenstandskatalog, GK) of the Institute for Medical and Pharmaceutical Examination Questions (Institut für Medizinische und Pharmazeutische Prüfungsfragen, IMPP). The current recommendations of the German Society for Radiation Oncology (Deutsche Gesellschaft für Radioonkologie, DEGRO) regarding topics, scope and rationale for the establishment of radiation oncology teaching at the respective faculties are also included

Development of an ionic-liquid-based dispersive liquid–liquid microextraction method for the determination of antichagasic drugs in human breast milk. Optimization by central composite design

Chagas disease constitutes a major public health problem in Latin America. Human breast milk is a biological sample of great importance for the analysis of therapeutic drugs, as unwanted exposure through breast milk could result in pharmacological effects in the nursing infant. Thus, the goal of breast milk drug analysis is to inquire to which extent a neonate may be exposed to a drug during lactation. In this work, we developed an analytical technique to quantify benznidazole and nifurtimox (the two antichagasic drugs currently available for the medical treatment) in human breast milk, with a simple sample pre-treatment followed by an ionic-liquid-based dispersive liquid–liquid microextraction combined with high-performance liquid chromatography and UV detection. For this technique, the ionic liquid 1-octyl-3-methylimidazolium hexafluorophosphate has been used as the “extraction solvent”. A central composite design was used to find the optimum values for the significant variables affecting the extraction process: volume of ionic liquid, volume of dispersant solvent, ionic strength, and pH. At the optimum working conditions, the average recoveries were 77.5 and 89.7%, the limits of detection were 0.06 and 0.09 μg mL-1 and the inter-day reproducibilities were 6.25 and 5.77% for benznidazole and nifurtimox, respectively. The proposed methodology can be considered sensitive, simple, robust, accurate, and green

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets

DAG-informed regression modelling, agent-based modelling, and microsimulation modelling: A critical comparison of methods for causal inference

The current paradigm for causal inference in epidemiology relies primarily on the evaluation of counterfactual contrasts via statistical regression models informed by graphical causal models (often in the form of directed acyclic graphs, or DAGs) and their underlying mathematical theory. However, there have been growing calls for supplementary methods, and one such method that has been proposed is agent-based modelling due to its potential for simulating counterfactuals. However, within the epidemiological literature there currently exists a general lack of clarity regarding what exactly agent-based modelling is (and is not) and, importantly, how it differs from microsimulation modelling – perhaps its closest methodological comparator. We clarify this distinction by briefly reviewing the history of each method, which provides context for their similarities and differences, and casts light on the types of research questions that they have evolved (and thus are well-suited) to answering; we do the same for DAG-informed regression methods. The distinct historical evolutions of DAG-informed regression modelling, microsimulation modelling, and agent-based modelling have given rise to distinct features of the methods themselves, and provide a foundation for critical comparison. Not only are the three methods well-suited to addressing different types of causal questions, but in doing so they place differing levels of emphasis on fixed and random effects, and also tend to operate on different timescales and in different timeframes

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

BACKGROUND: Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS: A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS: The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION: The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING: For detailed information per study, see Acknowledgments.This work was supported by a grant from the US National Heart, Lung, and Blood Institute (N01-HL-25195; R01HL 093328 to RSV), a MAIFOR grant from the University Medical Center Mainz, Germany (to PSW), the Center for Translational Vascular Biology (CTVB) of the Johannes Gutenberg-University of Mainz, and the Federal Ministry of Research and Education, Germany (BMBF 01EO1003 to PSW). This work was also supported by the research project Greifswald Approach to Individualized Medicine (GANI_MED). GANI_MED was funded by the Federal Ministry of Education and Research and the Ministry of Cultural Affairs of the Federal State of Mecklenburg, West Pomerania (contract 03IS2061A). We thank all study participants, and the colleagues and coworkers from all cohorts and sites who were involved in the generation of data or in the analysis. We especially thank Andrew Johnson (FHS) for generation of the gene annotation database used for analysis. We thank the German Center for Cardiovascular Research (DZHK e.V.) for supporting the analysis and publication of this project. RSV is a member of the Scientific Advisory Board of the DZHK. Data on CAD and MI were contributed by CARDIoGRAMplusC4D investigators. See Supplemental Acknowledgments for consortium details. PSW, JFF, AS, AT, TZ, RSV, and MD had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis