Niklas Gremke

Philipps University of Marburg

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Sebastian Griewing

Philipps University of Marburg

Uwe Wagner

Universitätsklinikum Gießen und Marburg

Matthias Kalder

Philipps University of Marburg

Karel Kostev

Philipps University of Marburg

Thorsten Stiewe

German Center for Lung Research

Sebastian Kühn

Universitätsklinikum Gießen und Marburg

Michael Wanzel

Philipps University of Marburg

Jelena Boekhoff

Philipps University of Marburg

Markus Wallwiener

University Hospital in Halle

Michael Lingenfelder

Philipps University of Marburg

Cooperative Institutions

Philipps University of Marburg

Universitätsklinikum Gießen und Marburg

University of Giessen

German Center for Lung Research

Goethe University Frankfurt

Universities of Giessen and Marburg Lung Center

Klinik für Frauenheilkunde

Heinrich Heine University Düsseldorf

Heidelberg University

University Hospital Frankfurt

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Association between antihypertensive medication and the risk of urinary tract infection (UTI) of outpatients: a retrospective cohort study

Infection (2022)

Niklas Gremke Karel Kostev Matthias Kalder

The aim of this retrospective study was to investigate the impact of a broad spectrum of antihypertensive (AH) medications on urinary tract infections (UTI) of outpatients diagnosed in general practices in Germany.This study included a total of 367,960 patients aged ≥ 18 years newly a diagnosed with UTI in 1274 general practices in Germany between January 2010 and December 2019. The analysis was conducted for five groups representing five AH therapy classes (diuretics (DIU); beta blockers (BB); calcium channel blockers (CCB); ACE inhibitors (ACEi); angiotensin II receptor blockers (ARB)), each containing 73,592 patients. A Cox regression model was used to analyze the association between each antihypertensive drug class and UTI incidence as compared to all other antihypertensive drug classes (as a group).The incidence of UTI diagnosis was slightly higher in patients treated with DIU (8.6%), followed by ACEi (8.1%), ARB (7.9%), and CCB (6.5%). Antibiotic therapy for UTI was given in 5.6% of DIU and 4.3% of CCB patients. The incidence of UTI and antibiotic therapy was much higher in women than in men across all therapy classes. No significant increase or decrease in UTI incidence or antibiotic therapy was observed in any of the AH therapy classes investigated.The present study did not identify a significant increase or decrease of UTI incidence or antibiotic therapy in patients treated with ACEi, ACB, CCB, beta blockers or diuretics. Across all AH classes studied, the incidence of UTI and antibiotic therapy was higher in women than in men, although not significantly.

10.1007/s15010-022-01895-8

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Citations (3)

NSCLC in der Schwangerschaft: Therapie mit Tyrosinkinaseinhibitor ab dem 2. Trimenon

Geburtshilfe und Frauenheilkunde (2024)

Viola Schaefer Mi Ran Jung A. Klemmer J. Hoffmann Niklas Gremke

Zusammenfassung: Onkologische Erkrankungen kommen bei 1-2/1000 Schwangerschaften vor, ein non-small cell lung cancer (NSCLC) in der Schwangerschaft ist selten (1). Aufgrund fetotoxischer Effekte ist die Behandlung eine Herausforderung, die interdisziplinäre Betreuung essenziell. Die Anwendung zielgerichteter Therapien in der Schwangerschaft basiert nur auf einzelnen Fallberichten (2).

10.1055/s-0044-1790960

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Using AI To Navigate Lengthy And Complex Oncological Guidelines – A Preclinical Proof-Of-Concept Study Of Small Language Model Adoption To The German Breast Cancer Guideline

International Journal of Gynecological Cancer (2025)

Sebastian Griewing Niklas Gremke Fabian Lechner Jelena Boekhoff Markus Wallwiener

Guideline

Proof of concept

10.1016/j.ijgc.2024.101561

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Technology Acceptance Of Blockchain Technology And Artificial Intelligence In Gynecological Oncology

International Journal of Gynecological Cancer (2025)

Sebastian Griewing Jelena Boekhoff Niklas Gremke Fabian Lechner Sebastian Kühn

10.1016/j.ijgc.2024.101562

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NGS-Guided Precision Oncology in Breast Cancer and Gynecological Tumors—A Retrospective Molecular Tumor Board Analysis

Cancers (2024)

Niklas Gremke Fiona R. Rodepeter Julia Teply‐Szymanski Sebastian Griewing Jelena Boekhoff

Background: Precision oncology treatments are being applied more commonly in breast and gynecological oncology through the implementation of Molecular Tumor Boards (MTBs), but real-world clinical outcome data remain limited. Methods: A retrospective analysis was conducted in patients with breast cancer (BC) and gynecological malignancies referred to our center’s MTB from 2018 to 2023. The analysis covered patient characteristics, next-generation sequencing (NGS) results, MTB recommendations, therapy received, and clinical outcomes. Results: Sixty-three patients (77.8%) had metastatic disease, and forty-four patients (54.3%) had previously undergone three or more lines of systemic treatment. Personalized treatment recommendations were provided to 50 patients (63.3%), while 29 (36.7%) had no actionable target. Ultimately, 23 patients (29.1%) underwent molecular-matched treatment (MMT). Commonly altered genes in patients with pan-gyn tumors (BC and gynecological malignancies) included TP53 (n = 42/81, 51.9%), PIK3CA (n = 18/81, 22.2%), BRCA1/2 (n = 10/81, 12.3%), and ARID1A (n = 9/81, 11.1%). Patients treated with MMT showed significantly prolonged progression-free survival (median PFS 5.5 vs. 3.5 months, p = 0.0014). Of all patients who underwent molecular profiling, 13.6% experienced a major clinical benefit (PFSr ≥ 1.3 and PR/SD ≥ 6 months) through precision oncology. Conclusions: NGS-guided precision oncology demonstrated improved clinical outcomes in a subgroup of patients with gynecological and breast cancers.

Clinical Oncology

Precision oncology

Gynecologic oncology

Surgical oncology

10.3390/cancers16081561

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Use Case Evaluation and Digital Workflow of Breast Cancer Care by Artificial Intelligence and Blockchain Technology Application

Healthcare (2022)

Sebastian Griewing Michael Lingenfelder Uwe Wagner Niklas Gremke

This study aims at evaluating the use case potential of breast cancer care for artificial intelligence and blockchain technology application based on the patient data analysis at Marburg University Hospital and, thereupon, developing a digital workflow for breast cancer care. It is based on a retrospective descriptive data analysis of all in-patient breast and ovarian cancer patients admitted at the Department of Gynecology of Marburg University Hospital within the five-year observation period of 2017 to 2021. According to the German breast cancer guideline, the care workflow was visualized and, thereon, the digital concept was developed, premised on the literature foundation provided by a Boolean combination open search. Breast cancer cases display a lower average patient case complexity, fewer secondary diagnoses, and performed procedures than ovarian cancer. Moreover, 96% of all breast cancer patients originate from a city with direct geographical proximity. Estimated circumference and total catchment area of ovarian present 28.6% and 40% larger, respectively, than for breast cancer. The data support invasive breast cancer as a preferred use case for digitization. The digital workflow based on combined application of artificial intelligence as well as blockchain or distributed ledger technology demonstrates potential in tackling senological care pain points and leveraging patient data safety and sovereignty.

10.3390/healthcare10102100

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Citations (7)

Overcoming PI3Kinase inhibitor resistance in breast cancer: mechanistic insights, metabolic vulnerabilities and clinical correlations

Geburtshilfe und Frauenheilkunde (2024)

Niklas Gremke I. Besong L. von Wichert A. Stroh Sabrina Elmshäuser

Aim: PI3Kinase inhibitors have improved the treatment of hormone receptor-positive, HER2-negative, and PIK3CA mutated (PIK3CAmut) metastatic breast cancer (BC) patients. However, the emergence of drug-resistant subclones can result in therapy failure. Our project aims to understand mechanisms of PI3Ki-resistance, their impact on patient overall survival (OS), and devise strategies to overcome them.

10.1055/s-0044-1790724

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Leitlinien-Chatbot in der gynäkologischen Onkologie – Revolution oder Risiko? Künstliche Intelligenz ermöglicht den Dialog mit der Brustkrebs-Leitlinie – über Potenziale und Herausforderungen von KI-basierten Chatbots für die Leitliniennavigation und Entscheidungsunterstützung in der gynäkologischen Onkologie

Geburtshilfe und Frauenheilkunde (2024)

Sebastian Griewing Franz Lechner Niklas Gremke Stefan Lukac Wolfgang Janni

Auf Künstlicher Intelligenz basierten großen Sprachmodellen (Large Language Models, LLMs) wird immenses Potenzial zur Entscheidungsunterstützung in der Brustkrebsbehandlung zugeschrieben. Ihr Einsatz in der klinischen Versorgung ist zurzeit aufgrund fehlender Kontrolle über die für die Entscheidungsfindung verwendeten Quellen und Bedenken zur Datensicherheit, bei Verarbeitung von Gesundheitsdaten über internationale Server, nicht möglich. Die jüngste Entwicklung von Kleinen Sprachmodellen (Small Language Models, SLMs) wird als Möglichkeit zur Lösung dieser Anwendungshürden diskutiert. Diese Proof-of-Concept-Studie zielt darauf ab, ein SLM an die deutsche Brustkrebs-Richtlinie anzupassen und die frühe Machbarkeit hinsichtlich der initialen klinischen Sicherheit und der Funktionsfähigkeit zu bewerten.

Chatbot

10.1055/s-0044-1790725

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Awareness and intention-to-use of digital health applications, artificial intelligence and blockchain technology in breast cancer care

Frontiers in Medicine (2024)

Sebastian Griewing Johannes Knitza Niklas Gremke Markus Wallwiener Uwe Wagner

Emerging digital technologies promise to improve breast cancer care, however lack of awareness among clinicians often prevents timely adoption. This study aims to investigate current awareness and intention-to-use of three technologies among breast cancer healthcare professionals (HCP): (1) digital health applications (DHA), (2) artificial intelligence (AI), and (3) blockchain technology (BC). A 22-item questionnaire was designed and administered before and after a 30 min educational presentation highlighting technology implementation examples. Technology awareness and intention-to-use were measured using 7-point Likert scales. Correlations between demographics, technology awareness, intention-to-use, and eHealth literacy (GR-eHEALS scale) were analyzed. 45 HCP completed the questionnaire, of whom 26 (57.8%) were female. Age ranged from 24 to 67 {mean age (SD): 44.93 ± 12.62}. Awareness was highest for DHA (68.9%) followed by AI (66.7%) and BC (24.4%). The presentation led to a non-significant increase of intention-to-use AI {5.37 (±1.81) to 5.83 (±1.64)}. HCPs´ intention-to-use BC after the presentation increased significantly {4.30 (±2.04) to 5.90 (±1.67), p < 0.01}. Mean accumulated score for GR-eHEALS averaged 33.04 (± 6.61). HCPs´ intended use of AI significantly correlated with eHealth literacy (ρ = 0.383; p < 0.01), intention-to-use BC (ρ = 0.591; p < 0.01) and participants´ age (ρ = −0.438; p < 0.01). This study demonstrates the effect that even a short practical presentation can have on HCPs´ intention-to-use emerging digital technologies. Training potential professional users should be addressed alongside the development of new information technologies and is crucial to increase HCPs´ corresponding awareness and intended use.

eHealth

Presentation (obstetrics)

Demographics

Breast cancer awareness

Health Literacy

10.3389/fmed.2024.1380940

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Citations (4)

EPH134 Prevalence of and Associated Factors for Therapy Delay Due to COVID-19 Pandemic Among Breast Cancer Patients in Europe

Value in Health (2023)

Niklas Gremke Svetlana Alymova Karel Kostev Matthias Kalder Isabel Klein

Pandemic

2019-20 coronavirus outbreak

10.1016/j.jval.2023.09.1176

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