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Bestimmung des klinischen Nutzens systemischer adjuvanter Therapien beim frühen Mammakarzinom
(2017)
Die onkologische Therapie befindet sich im Umbruch. Hohe Erwartungen sind mit einer Reihe innovativer zielgerichteter Medikamente verknüpft, die sich derzeit in der klinischen Entwicklung befinden. Vor diesem Hintergrund erfahren Diskussionen um die Begriffe klinischer Nutzen oder klinische Relevanz neue Aktualität. Dies gilt auch für die Weiterentwicklungen der adjuvanten systemischen Therapie des frühen Mammakarzinoms. In Anbetracht der kurativen Zielsetzung erfolgt die Beurteilung des klinischen Nutzens einer adjuvanten Therapie maßgeblich anhand von Wirksamkeitsendpunkten. Der Fokus liegt hierbei auf Verbesserungen des krankheitsfreien Überlebens und des Rezidivrisikos. Eine Aussage zum Gesamtüberleben ist aufgrund der heute erreichten niedrigen Mortalitätsraten erst nach sehr langen Beobachtungszeiten möglich. Folgerichtig sollte neuen Medikamenten für die adjuvante Therapie ein klinischer Nutzen zugesprochen werden, wenn sie eine weitere Reduktion des Rezidivrisikos über den heutigen hohen Standard hinaus ermöglichen. Die Evidenz für etablierte adjuvante Therapiestandards beim frühen Mammakarzinom kann als objektiver Maßstab zum Vergleich herangezogen werden. Am Beispiel der adjuvanten endokrinen Therapie, der adjuvanten Polychemotherapie und der adjuvanten Anti-HER2-Therapie werden in diesem Übersichtsartikel die Anforderungen für den klinischen Nutzen neuer adjuvanter Therapien beim frühen Mammakarzinom abgeleitet.
Oncologic therapy is currently undergoing significant changes. A number of innovative targeted medications currently in clinical development have raised high expectations. With that in mind, discussions about terms such as "clinical benefit" and "clinical relevance" are highly topical. This also applies to further developments in the field of adjuvant systemic therapies for early-stage breast cancer. As the treatment aim is curative, assessment of the clinical benefit of adjuvant therapies must be largely based on efficacy outcomes. The focus must be on improving disease-free survival rates and lowering the risk of recurrence. Because of the current low mortality rates, statements about overall survival rates are only possible after very long observation periods. Consequently, new drugs in adjuvant therapies should be considered as offering a clinical benefit, if they reduce the risk of recurrence below current low levels of risk. The evidence for established adjuvant therapy standards in early-stage breast cancer can be used as objective criteria for comparison. This review article considers the requirements for clinical benefit of new adjuvant therapies for early breast cancer, based on examples from adjuvant endocrine therapy, adjuvant polychemotherapy and adjuvant anti-HER2 therapy.
Background: There is general consensus that the organizational and administrative aspects of academic study programs exert an important influence on teaching and learning. Despite this, no comprehensive framework currently exists to describe the conditions that affect the quality of teaching and learning in medical education. The aim of this paper is to systematically and comprehensively identify these factors to offer academic administrators and decision makers interested in improving teaching a theory-based and, to an extent, empirically founded framework on the basis of which improvements in teaching quality can be identified and implemented.
Method: Primarily, the issue was addressed by combining a theory-driven deductive approach with an experience based, “best evidence” one during the course of two workshops held by the GMA Committee on Personnel and Organizational Development in Academic Teaching (POiL) in Munich (2013) and Frankfurt (2014). Two models describing the conditions relevant to teaching and learning (Euler/Hahn and Rindermann) were critically appraised and synthesized into a new third model. Practical examples of teaching strategies that promote or hinder learning were compiled and added to the categories of this model and, to the extent possible, supported with empirical evidence.
Based on this, a checklist with recommendations for optimizing general academic conditions was formulated.
Results: The Frankfurt Model of conditions to ensure Quality in Teaching and Learning covers six categories: organizational structure/medical school culture, regulatory frameworks, curricular requirements, time constraints, material and personnel resources, and qualification of teaching staff. These categories have been supplemented by the interests, motives and abilities of the actual teachers and students in this particular setting. The categories of this model provide the structure for a checklist in which recommendations for optimizing teaching are given.
Conclusions: The checklist derived from the Frankfurt Model for ensuring quality in teaching and learning can be used for quality assurance and to improve the conditions under which teaching and learning take place in medical schools.
Autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD) frequently co-occur. The presence of a genetic link between ASD and ADHD symptoms is supported by twin studies, but the genetic overlap between clinically ascertained ASD and ADHD remains largely unclear. We therefore investigated how ASD and ADHD co-aggregate in individuals and in families to test for the presence of a shared genetic liability and examined potential differences between low- and high-functioning ASD in the link with ADHD. We studied 1 899 654 individuals born in Sweden between 1987 and 2006. Logistic regression was used to estimate the association between clinically ascertained ASD and ADHD in individuals and in families. Stratified estimates were obtained for ASD with (low-functioning) and without (high-functioning) intellectual disability. Individuals with ASD were at higher risk of having ADHD compared with individuals who did not have ASD (odds ratio (OR)=22.33, 95% confidence interval (CI): 21.77–22.92). The association was stronger for high-functioning than for low-functioning ASD. Relatives of individuals with ASD were at higher risk of ADHD compared with relatives of individuals without ASD. The association was stronger in monozygotic twins (OR=17.77, 95% CI: 9.80–32.22) than in dizygotic twins (OR=4.33, 95% CI: 3.21–5.85) and full siblings (OR=4.59, 95% CI: 4.39–4.80). Individuals with ASD and their relatives are at increased risk of ADHD. The pattern of association across different types of relatives supports the existence of genetic overlap between clinically ascertained ASD and ADHD, suggesting that genomic studies might have underestimated this overlap.
Mathematical models of virus dynamics have not previously acknowledged spatial resolution at the intracellular level despite substantial arguments that favor the consideration of intracellular spatial dependence. The replication of the hepatitis C virus (HCV) viral RNA (vRNA) occurs within special replication complexes formed from membranes derived from endoplasmatic reticulum (ER). These regions, termed membranous webs, are generated primarily through specific interactions between nonstructural virus-encoded proteins (NSPs) and host cellular factors. The NSPs are responsible for the replication of the vRNA and their movement is restricted to the ER surface. Therefore, in this study we developed fully spatio-temporal resolved models of the vRNA replication cycle of HCV. Our simulations are performed upon realistic reconstructed cell structures—namely the ER surface and the membranous webs—based on data derived from immunostained cells replicating HCV vRNA. We visualized 3D simulations that reproduced dynamics resulting from interplay of the different components of our models (vRNA, NSPs, and a host factor), and we present an evaluation of the concentrations for the components within different regions of the cell. Thus far, our model is restricted to an internal portion of a hepatocyte and is qualitative more than quantitative. For a quantitative adaption to complete cells, various additional parameters will have to be determined through further in vitro cell biology experiments, which can be stimulated by the results deccribed in the present study.
The Escherichia coli sensor kinase EnvZ modulates porin expression in response to various stimuli, including extracellular osmolarity, the presence of procaine and interaction with an accessory protein, MzrA. Two major outer membrane porins, OmpF and OmpC, act as passive diffusion-limited pores that allow compounds, including certain classes of antibiotics such as β-lactams and fluoroquinolones, to enter the bacterial cell. Even though the mechanisms by which EnvZ detects and processes the presence of various stimuli are a fundamental component of microbial physiology, they are not yet fully understood. Here, we assess the role of TM1 during signal transduction in response to the presence of extracellular osmolarity. Various mechanisms of transmembrane communication have been proposed including rotation of individual helices within the transmembrane domain, dynamic movement of the membrane-distal portion of the cytoplasmic domain and regulated intra-protein unfolding. To assess these possibilities, we have created a library of single-Cys-containing EnvZ proteins in order to facilitate sulfhydryl-reactivity experimentation. Our results demonstrate that the major TM1-TM1' interface falls along a single surface consisting of residue positions 19, 23, 26, 30 and 34. In addition, we show that Cys substitutions within the N- and C-terminal regions of TM1 result in drastic changes to EnvZ signal output. Finally, we demonstrate that core residues within TM1 are responsible for both TM1 dimerisation and maintenance of steady-state signal output. Overall, our results suggest that no major rearrangement of the TM1-TM1' interface occurs during transmembrane communication in response to extracellular osmolarity. We conclude by discussing these results within the frameworks of several proposed models for transmembrane communication.
Objective: To estimate health status utility (preference) weights for hereditary angioedema (HAE) during an attack and between attacks using data from the Hereditary Angioedema Burden of Illness Study in Europe (HAE-BOIS-Europe) survey. Utility measures quantitatively describe the net impact of a condition on a patient’s life; a score of 0.0 reflects death and 1.0 reflects full health.
Study design and methods: The HAE-BOIS-Europe was a cross-sectional survey conducted in Spain, Germany, and Denmark to assess the real-world experience of HAE from the patient perspective. Survey items that overlapped conceptually with the EuroQol 5-Dimensions (EQ-5D) domains (pain/discomfort, mobility, self-care, usual activities, and anxiety/depression) were manually crosswalked to the corresponding UK population-based EQ-5D utility weights. EQ-5D utilities were computed for each respondent in the HAE-BOIS-Europe survey for acute attacks and between attacks.
Results: Overall, a total of 111 HAE-BOIS-Europe participants completed all selected survey items and thus allowed for computation of EQ-5D-based utilities. The mean utilities for an HAE attack and between attacks were 0.44 and 0.72, respectively. Utilities for an acute attack were dependent on the severity of pain of the last attack (0.61 for no pain or mild pain, 0.47 for moderate pain, and 0.08 for severe pain). There were no significant differences across countries. Mean utilities derived from the study approach compare sensibly with other disease states for both acute attacks and between attacks.
Conclusion: The impacts of HAE translate into substantial health status disutilities associated with acute attacks as well as between attacks, documenting that the detrimental effects of HAE are meaningful from the patient perspective. Results were consistent across countries with regard to pain severity and in comparison to similar disease states. The results can be used to raise awareness of HAE as a serious disease with wide-ranging personal and social impacts.
Introduction: Currently there are several advanced guiding techniques for pathoanatomical diagnosis of incidental solitary pulmonary nodules (iSPN): Electromagnetic navigation (EMN) with or without endobronchial ultrasound (EBUS) with miniprobe, transthoracic ultrasound (TTUS) for needle approach to the pleural wall and adjacent lung and computed tomography (CT) -guidance for (seldom if ever used) endobronchial or (common) transthoracical approach. In several situations one technique is not enough for efficient diagnosis, therefore we investigated a new diagnostic technique of endobronchial guided biopsies by a Cone Beam Computertomography (CBCT) called DynaCT (SIEMENS AG Forchheim, Germany). Method and Material: In our study 33 incidental solitary pulmonary nodules (iSPNs) (28 malignant, 5 benign; mean diameter 25 +/-12mm, shortest distance to pleura 25+/-18mm) were eligible according to in- and exclusion criteria. Realtime and onsite navigation were performed according to our standard protocol.22 All iSPN were controlled with a second technique when necessary and clinical feasible in case of unspecific or unexpected histological result. In all cases common guidelines of treatment of different iSPNs were followed in a routine manner. Results: Overall navigational yield (ny) was 91% and diagnostic yield (dy) 70%, dy for all accomplished malignant cases (n=28) was 82%. In the subgroup analysis of the invisible iSPN (n=12, 11 malignant, 1 benign; mean diameter 15+/-3mm) we found an overall dy of 75%. For the first time we describe a significant difference in specifity of biopsy results in regards to the position of the forceps in the 3-dimensional volume (3DV) of the iSPN in the whole sample group. Comparing the specifity of biopsies of a 3D-uncentered but inside the outer one third of an iSPN-3DV with the specifity of biopsies of centered forceps position (meaning the inner two third of an iSPN-3DV) reveals a significant (p=0,0375 McNemar) difference for the size group (>1cm) of 0,9 for centered biopsies vs. 0,3 for uncentered biopsies. Therefore only 3D-centered biopsies should be relied on especially in case of a benign result. Conclusion:The diagnostic yield of DynaCT navigation guided transbronchial biopsies (TBB) only with forceps is at least up to twofold higher than conventional TBB for iSPNs <2cm. The diagnostic yield of DynaCT navigation guided forceps TBB in invisible SPNs is at least in the range of other navigation studies which were performed partly with multiple navigation tools and multiple instruments. For future diagnostic and therapeutic approaches it is so far the only onsite and realtime extrathoracic navigation approach (except for computed tomography (CT)-fluoroscopy) in the bronchoscopy suite which keeps the working channel open. The system purchase represents an important investment for hospitals but it is a multidisciplinary and multinavigational tool with possible access via bronchial airways, transthoracical or vascular approach at the same time and on the same table without the need for an expensive disposable instrument use.
Seroconversion rates following influenza vaccination in patients with hematologic malignancies after hematopoietic stem cell transplantation (HSCT) are known to be lower compared to healthy adults. The aim of our diagnostic study was to determine the rate of seroconversion after 1 or 2 doses of a novel split virion, inactivated, AS03-adjuvanted pandemic H1N1 influenza vaccine (A/California/7/2009) in HSCT recipients (ClinicalTrials.gov Identifier: NCT01017172). Blood samples were taken before and 21 days after a first dose and 21 days after a second dose of the vaccine. Antibody (AB) titers were determined by hemagglutination inhibition assay. Seroconversion was defined by either an AB titer of ≤1:10 before and ≥1:40 after or ≥1:10 before and ≥4-fold increase in AB titer 21 days after vaccination. Seventeen patients (14 allogeneic, 3 autologous HSCT) received 1 dose and 11 of these patients 2 doses of the vaccine. The rate of seroconversion was 41.2% (95% confidence interval [CI] 18.4-67.1) after the first and 81.8% (95% CI 48.2-97.7) after the second dose. Patients who failed to seroconvert after 1 dose of the vaccine were more likely to receive any immunosuppressive agent (P = .003), but time elapsed after or type of HSCT, age, sex, or chronic graft-versus-host disease was not different when compared to patients with seroconversion. In patients with hematologic malignancies after HSCT the rate of seroconversion after a first dose of an adjuvanted H1N1 influenza A vaccine was poor, but increased after a second dose.
Background: High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect clusters. We analyzed whether this can be avoided by using emergent self-organizing feature maps (ESOM).
Methods: Data sets with different degrees of complexity were submitted to ESOM analysis with large numbers of neurons, using an interactive R-based bioinformatics tool. On top of the trained ESOM the distance structure in the high dimensional feature space was visualized in the form of a so-called U-matrix. Clustering results were compared with those provided by classical common cluster algorithms including single linkage, Ward and k-means.
Results: Ward clustering imposed cluster structures on cluster-less "golf ball", "cuboid" and "S-shaped" data sets that contained no structure at all (random data). Ward clustering also imposed structures on permuted real world data sets. By contrast, the ESOM/U-matrix approach correctly found that these data contain no cluster structure. However, ESOM/U-matrix was correct in identifying clusters in biomedical data truly containing subgroups. It was always correct in cluster structure identification in further canonical artificial data. Using intentionally simple data sets, it is shown that popular clustering algorithms typically used for biomedical data sets may fail to cluster data correctly, suggesting that they are also likely to perform erroneously on high dimensional biomedical data.
Conclusions: The present analyses emphasized that generally established classical hierarchical clustering algorithms carry a considerable tendency to produce erroneous results. By contrast, unsupervised machine-learned analysis of cluster structures, applied using the ESOM/U-matrix method, is a viable, unbiased method to identify true clusters in the high-dimensional space of complex data.
Graphical abstract: 3-D representation of high dimensional data following ESOM projection and visualization of group (cluster) structures using the U-matrix, which employs a geographical map analogy of valleys where members of the same cluster are located, separated by mountain ranges marking cluster borders.