Martin Dugas

Prof. Dr. Martin Dugas

Institute of Medical Informatics
orcid

Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 December 2016 in Nature Medicine
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SGStefanie Göllner
Stefanie Göllner
TOThomas Oellerich
Thomas Oellerich
SAShuchi Agrawal-Singh
Shuchi Agrawal-Singh
TSTino Schenk
Tino Schenk
HKHans-Ulrich Klein
Hans-Ulrich Klein
CMCarsten Müller-Tidow
Carsten Müller-Tidow

26 June 2017 in Nature Cell Biology
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FZFengbiao Zhou
Fengbiao Zhou
YLYi Liu
Yi Liu
CRChristian Rohde
Christian Rohde
CPCornelius Pauli
Cornelius Pauli
DGDennis Gerloff
Dennis Gerloff
CMCarsten Müller-Tidow
Carsten Müller-Tidow

21 April 2017 in Nature Communications
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PSPedro da Silva-Coelho
Pedro da Silva-Coelho
LKLeonie I. Kroeze
Leonie I. Kroeze
KYKenichi Yoshida
Kenichi Yoshida
TKTheresia N. Koorenhof-Scheele
Theresia N. Koorenhof-Scheele
RKRuth Knops
Ruth Knops
JJJoop H. Jansen
Joop H. Jansen
Cancer development is a dynamic process during which the successive accumulation of mutations results in cells with increasingly malignant characteristics. Here, we show the clonal evolution pattern in myelodysplastic syndrome (MDS) patients receiving supportive care, with or without lenalidomide (follow-up 2.5–11 years). Whole-exome and targeted deep sequencing at multiple time points during the disease course reveals that both linear and branched evolutionary patterns occur with and without disease-modifying treatment. The application of disease-modifying therapy may create an evolutionary bottleneck after which more complex MDS, but also unrelated clones of haematopoietic cells, may emerge. In addition, subclones that acquired an additional mutation associated with treatment resistance (TP53) or disease progression (NRAS, KRAS) may be detected months before clinical changes become apparent. Monitoring the genetic landscape during the disease may help to guide treatment decisions.

11 January 2022 in Journal of Medical Internet Research
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HUHannes Ulrich
Hannes Ulrich
AKAnn-Kristin Kock-Schoppenhauer
Ann-Kristin Kock-Schoppenhauer
NDNoemi Deppenwiese
Noemi Deppenwiese
RGRobert Gött
Robert Gött
JKJori Kern
Jori Kern
JIJosef Ingenerf
Josef Ingenerf
Background: Metadata are created to describe the corresponding data in a detailed and unambiguous way and is used for various applications in different research areas, for example, data identification and classification. However, a clear definition of metadata is crucial for further use. Unfortunately, extensive experience with the processing and management of metadata has shown that the term “metadata” and its use is not always unambiguous. Objective: This study aimed to understand the definition of metadata and the challenges resulting from metadata reuse. Methods: A systematic literature search was performed in this study following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting on systematic reviews. Five research questions were identified to streamline the review process, addressing metadata characteristics, metadata standards, use cases, and problems encountered. This review was preceded by a harmonization process to achieve a general understanding of the terms used. Results: The harmonization process resulted in a clear set of definitions for metadata processing focusing on data integration. The following literature review was conducted by 10 reviewers with different backgrounds and using the harmonized definitions. This study included 81 peer-reviewed papers from the last decade after applying various filtering steps to identify the most relevant papers. The 5 research questions could be answered, resulting in a broad overview of the standards, use cases, problems, and corresponding solutions for the application of metadata in different research areas. Conclusions: Metadata can be a powerful tool for identifying, describing, and processing information, but its meaningful creation is costly and challenging. This review process uncovered many standards, use cases, problems, and solutions for dealing with metadata. The presented harmonized definitions and the new schema have the potential to improve the classification and generation of metadata by creating a shared understanding of metadata and its context.

21 March 2013 in BMC Medical Informatics and Decision Making
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FKFelix Köpcke
Felix Köpcke
BTBenjamin Trinczek
Benjamin Trinczek
RMRaphael W Majeed
Raphael W Majeed
BSBjörn Schreiweis
Björn Schreiweis
JWJoachim Wenk
Joachim Wenk
HPHans-Ulrich Prokosch
Hans-Ulrich Prokosch
Computerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials. Each participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group. 351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were ‘age’ (89%), ‘gender’ (89%), ‘addictive behaviour’ (74%), ‘disease, symptom and sign’ (64%) and ‘organ or tissue status’ (61%). No data was available for 6 semantic groups. There exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data.

19 June 2020 in Leukemia
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MWMaxi Wass
Maxi Wass
SGStefanie Göllner
Stefanie Göllner
BBBirgit Besenbeck
Birgit Besenbeck
RSRichard F. Schlenk
Richard F. Schlenk
PMPetra Mundmann
Petra Mundmann
O(on behalf of the Study Alliance Leukemia (SAL)
on behalf of the Study Alliance Leukemia (SAL)
All-trans-retinoic acid (ATRA) is highly active in acute promyelocytic leukemia but not in other types of acute myeloid leukemia (AML). Previously, we showed that ATRA in combination with Lysine-specific demethylase 1 (LSD1) inhibition by tranylcypromine (TCP) can induce myeloid differentiation in AML blasts. This phase I/II clinical trial investigated the safety and efficacy of TCP/ATRA treatment as salvage therapy for relapsed/refractory (r/r) AML. The combination was evaluated in 18 patients, ineligible for intensive treatment. The overall response rate was 20%, including two complete remissions without hematological recovery and one partial response. We also observed myeloid differentiation upon TCP/ATRA treatment in patients who did not reach clinical remission. Median overall survival (OS) was 3.3 months, and one-year OS 22%. One patient developed an ATRA-induced differentiation syndrome. The most frequently reported adverse events were vertigo and hypotension. TCP plasma levels correlated with intracellular TCP concentration. Increased H3K4me1 and H3k4me2 levels were observed in AML blasts and white blood cells from some TCP/ATRA treated patients. Combined TCP/ATRA treatment can induce differentiation of AML blasts and lead to clinical response in heavily pretreated patients with r/r AML with acceptable toxicity. These findings emphasize the potential of LSD1 inhibition combined with ATRA for AML treatment.