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Strafprozessuale Verwertungsverbote im Besteuerungsverfahren ()
Bedingungen für das Argumentieren und Begründen im Geometrieunterricht ()
Crystal and magnetic structure of LaTiO3: evidence for nondegenerate t2g orbitals ()
Moderne Kommunikationsmittel im Zivilrecht: Auseinandersetzung mit dem Schriftformerfordernis des BGB nach der Schriftformreform ()
DNA methylation-based classification of central nervous system tumours ()
Identification of the atypically modified autoantigen Ars2 as the target of B-cell receptors from activated B cell–type diffuse large B-cell lymphoma ()
Pollen-associated microbiome correlates with pollution parameters and the allergenicity of pollen ()
Prognostic relevance of miRNA-155 methylation in anaplastic glioma ()
Budesonide orodispersible tablets maintain remission in a randomized, placebo-controlled trial of patients with eosinophilic esophagitis ()
MISeval: a metric library for medical image segmentation evaluation ()
3037 – Combined single-cell DNA methylome and transcriptome analysis identifies molecular sattes of early lineage commitment [Abstract] ()
Identification of disparities in personalized cancer care: a joint approach of the German WERA Consortium ()
Simple Summary In Molecular Tumor Boards (MTBs), clinicians and researchers discuss the biology of tumor samples from individual patients to find suitable therapies. MTBs have therefore become key elements of precision oncology programs. Patients living in urban areas with specialized medical centers can easily access MTBs. Dedicated efforts are necessary to also grant equal access for patients from rural areas. To address this challenge, the four German cancer centers in Würzburg, Erlangen, Regensburg and Augsburg collectively measured the regional efficacy of their MTBs. By jointly analyzing the residences of all MTB patients, we uncovered regional differences in our mostly rural catchment area. Mapping and further understanding these local differences—especially the underrepresented white spots—will help resolving inequalities in patient access to precision oncology. Our study represents a hands-on approach to assessing the regional efficacy of a precision oncology program. Moreover, this approach is transferable to other regions and clinical applications. Abstract (1) Background: molecular tumor boards (MTBs) are crucial instruments for discussing and allocating targeted therapies to suitable cancer patients based on genetic findings. Currently, limited evidence is available regarding the regional impact and the outreach component of MTBs; (2) Methods: we analyzed MTB patient data from four neighboring Bavarian tertiary care oncology centers in Würzburg, Erlangen, Regensburg, and Augsburg, together constituting the WERA Alliance. Absolute patient numbers and regional distribution across the WERA-wide catchment area were weighted with local population densities; (3) Results: the highest MTB patient numbers were found close to the four cancer centers. However, peaks in absolute patient numbers were also detected in more distant and rural areas. Moreover, weighting absolute numbers with local population density allowed for identifying so-called white spots—regions within our catchment that were relatively underrepresented in WERA MTBs; (4) Conclusions: investigating patient data from four neighboring cancer centers, we comprehensively assessed the regional impact of our MTBs. The results confirmed the success of existing collaborative structures with our regional partners. Additionally, our results help identifying potential white spots in providing precision oncology and help establishing a joint WERA-wide outreach strategy.
Recording of the regional origin areas of patients from the molecular tumor board to identify the "white spots" in the service area - a joint initiative of the Bavarian CCC WERA alliance [Abstract] ()
DNA methylation-based classification of sinonasal tumors ()
Surfing the waves of the COVID-19 pandemic with diabetes mellitus: analysis of changes in the diabetes therapy, metabolism and physical activity of 92 992 people living with type 1 or type 2 diabetes from the German DPV registry ()
Mobilization and hematopoietic stem cell collection in poor mobilizing patients with lymphoma: final results of the german OPTIMOB study ()
A German-wide systematic study on mobilization and collection of hematopoietic stem cells in poor mobilizer patients with multiple myeloma prior to autologous stem cell transplantation ()
The WERA cancer center matrix: strategic management of patient access to precision oncology in a large and mostly rural area of Germany ()
Purpose Providing Patient Access to Precision Oncology (PO) is a major challenge of clinical oncologists. Here, we provide an easily transferable model from strategic management science to assess the outreach of a cancer center. Methods As members of the German WERA alliance, the cancer centers in Würzburg, Erlangen, Regensburg and Augsburg merged care data regarding their geographical impact. Specifically, we examined the provenance of patients from WERA´s molecular tumor boards (MTBs) between 2020 and 2022 (n = 2,243). As second dimension, we added the provenance of patients receiving general cancer care by WERA. Clustering our catchment area along these two dimensions set up a four-quadrant matrix consisting of postal code areas with referrals towards WERA. These areas were re-identified on a map of the Federal State of Bavaria. Results The WERA Matrix overlooked an active screening area of 821 postal code areas – representing about 50% of Bavaria´s spatial expansion and more than six million inhabitants. The WERA Matrix identified regions successfully connected to our outreach structures in terms of subsidiarity – with general cancer care mainly performed locally but PO performed in collaboration with WERA. We also detected postal code areas with a potential PO backlog – characterized by high levels of cancer care performed by WERA and low levels or no MTB representation. Conclusions The WERA Matrix provided a transparent portfolio of postal code areas, which helped assessing the geographical impact of our PO program. We believe that its intuitive principle can easily be transferred to other cancer centers.
Assessing patient health dynamics by comparative CT analysis: an automatic approach to organ and body feature evaluation ()
Background/Objectives: The integration of machine learning into the domain of radiomics has revolutionized the approach to personalized medicine, particularly in oncology. Our research presents RadTA (RADiomics Trend Analysis), a novel framework developed to facilitate the automatic analysis of quantitative imaging biomarkers (QIBs) from time-series CT volumes. Methods: RadTA is designed to bridge a technical gap for medical experts and enable sophisticated radiomic analyses without deep learning expertise. The core of RadTA includes an automated command line interface, streamlined image segmentation, comprehensive feature extraction, and robust evaluation mechanisms. RadTA utilizes advanced segmentation models, specifically TotalSegmentator and Body Composition Analysis (BCA), to accurately delineate anatomical structures from CT scans. These models enable the extraction of a wide variety of radiomic features, which are subsequently processed and compared to assess health dynamics across timely corresponding CT series. Results: The effectiveness of RadTA was tested using the HNSCC-3DCT-RT dataset, which includes CT scans from oncological patients undergoing radiation therapy. The results demonstrate significant changes in tissue composition and provide insights into the physical effects of the treatment. Conclusions: RadTA demonstrates a step of clinical adoption in the field of radiomics, offering a user-friendly, robust, and effective tool for the analysis of patient health dynamics. It can potentially also be used for other medical specialties.
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