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1005 Publications visible to you, out of a total of 1005
Charakteristika von IT-Abteilungen in Krankenhäusern in Deutschland. Report zur Umfrage unter IT-Leitern in Krankenhäusern (Februar-April 2016)
Semantisches Netz des integrierten Informationsmanagements im Krankenhaus (SNIK)

Abstract

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Authors: Franziska Jahn, Christian Kücherer, Jan-David Liebe, Barbara Paech, Alfred Winter

Date Published: 2019

Publication Type: Tech report

Developing and implementing a health IT ontology for facilitating retrieval of health IT evaluation studies
Health IT Ontology (HITO)

Abstract

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Editor:

Date Published: 2019

Publication Type: InProceedings

Challenges and solutions while developing HITO–a Health IT Ontology
Health IT Ontology (HITO)

Abstract

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Editor:

Date Published: 2019

Publication Type: InProceedings

An Ontology for Describing Health IT Interventions: Methodological Considerations
Health IT Ontology (HITO)

Abstract

Not specified

Authors: Elske Ammenwerth, Verena Dornauer, Maryam Ghalandari, Franziska Jahn, Alfred Winter

Date Published: 2019

Publication Type: InProceedings

BRIP1 loss-of-function mutations confer high risk for familial ovarian cancer, but not familial breast cancer
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

BACKGROUND Germline mutations in the BRIP1 gene have been described as conferring a moderate risk for ovarian cancer (OC), while the role of BRIP1 in breast cancer (BC) pathogenesis remains controversial. …. METHODS To assess the role of deleterious BRIP1 germline mutations in BC/OC predisposition, 6341 well-characterized index patients with BC, 706 index patients with OC, and 2189 geographically matched female controls were screened for loss-of-function (LoF) mutations and potentially damaging missense variants. All index patients met the inclusion criteria of the German Consortium for Hereditary Breast and Ovarian Cancer for germline testing and tested negative for pathogenic BRCA1/2 variants. RESULTS BRIP1 LoF mutations confer a high OC risk in familial index patients (odds ratio (OR) = 20.97, 95% confidence interval (CI) = 12.02-36.57, P \textless 0.0001) and in the subgroup of index patients with late-onset OC (OR = 29.91, 95% CI = 14.99-59.66, P \textless 0.0001). No significant association of BRIP1 LoF mutations with familial BC was observed (OR = 1.81 95% CI = 1.00-3.30, P = 0.0623). In the subgroup of familial BC index patients without a family history of OC there was also no apparent association (OR = 1.42, 95% CI = 0.70-2.90, P = 0.3030). In 1027 familial BC index patients with a family history of OC, the BRIP1 mutation prevalence was significantly higher than that observed in controls (OR = 3.59, 95% CI = 1.43-9.01; P = 0.0168). Based on the negative association between BRIP1 LoF mutations and familial BC in the absence of an OC family history, we conclude that the elevated mutation prevalence in the latter cohort was driven by the occurrence of OC in these families. Compared with controls, predicted damaging rare missense variants were significantly more prevalent in OC (P = 0.0014) but not in BC (P = 0.0693) patients. CONCLUSIONS To avoid ambiguous results, studies aimed at assessing the impact of candidate predisposition gene mutations on BC risk might differentiate between BC index patients with an OC family history and those without. In familial cases, we suggest that BRIP1 is a high-risk gene for late-onset OC but not a BC predisposition gene, though minor effects cannot be excluded.

Authors: Nana Weber-Lassalle, Jan Hauke, Juliane Ramser, Lisa Richters, Eva Groß, Britta Blümcke, Andrea Gehrig, Anne-Karin Kahlert, Clemens R. Müller, Karl Hackmann, Ellen Honisch, Konstantin Weber-Lassalle, Dieter Niederacher, Julika Borde, Holger Thiele, Corinna Ernst, Janine Altmüller, Guido Neidhardt, Peter Nürnberg, Kristina Klaschik, Christopher Schroeder, Konrad Platzer, Alexander E. Volk, Shan Wang-Gohrke, Walter Just, Bernd Auber, Christian Kubisch, Gunnar Schmidt, Judit Horvath, Barbara Wappenschmidt, Christoph Engel, Norbert Arnold, Bernd Dworniczak, Kerstin Rhiem, Alfons Meindl, Rita K. Schmutzler, Eric Hahnen

Date Published: 1st Dec 2018

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Diagnosis of Li-Fraumeni Syndrome: Differentiating TP53 germline mutations from clonal hematopoiesis: Results of the observational AGO-TR1 trial
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

The Li-Fraumeni cancer predisposition syndrome (LFS1) presents with a variety of tumor types and the TP53 gene is covered by most diagnostic cancer gene panels. We demonstrate that deleterious TP53 … variants identified in blood-derived DNA of 523 patients with ovarian cancer (AGO-TR1 trial) were not causal for the patients’ ovarian cancer in three out of six TP53-positive cases. In three out of six patients, deleterious TP53 mutations were identified with low variant fractions in blood-derived DNA but not in the tumor of the patient seeking advice. The analysis of the TP53 and PPM1D genes, both intimately involved in chemotherapy-induced and/or age-related clonal hematopoiesis (CH), in 523 patients and 1,053 age-matched female control individuals revealed that CH represents a frequent event following chemotherapy, affecting 26 of the 523 patients enrolled (5.0%). Considering that TP53 mutations may arise from chemotherapy-induced CH, our findings help to avoid false-positive genetic diagnoses of LFS1.

Authors: Konstantin Weber-Lassalle, Philipp Harter, Jan Hauke, Corinna Ernst, Stefan Kommoss, Frederik Marmé, Nana Weber-Lassalle, Katharina Prieske, Dimo Dietrich, Julika Borde, Esther Pohl-Rescigno, Alexander Reuss, Beyhan Ataseven, Christoph Engel, Julia C. Stingl, Rita K. Schmutzler, Eric Hahnen

Date Published: 1st Dec 2018

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

BACKGROUND The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require …e interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. METHODS We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. RESULTS PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. CONCLUSION We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

Authors: Corinna Ernst, Eric Hahnen, Christoph Engel, Michael Nothnagel, Jonas Weber, Rita K. Schmutzler, Jan Hauke

Date Published: 1st Dec 2018

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

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