Kompass Onkologie最新文献

Molekulare Diagnostik und innovative Therapien beim Mammakarzinom: Ein Wechselspiel mit Potential und Herausforderungen 乳腺癌分子诊断和创新疗法：潜力与挑战并存

Kompass Onkologie Pub Date : 2024-05-16 DOI: 10.1159/000539332

Achim Wöckel

引用次数: 0

Mammakarzinom: Axilladissektion nicht immer nötig bei Sentinel-Metastasen 乳腺癌：前哨转移不一定需要腋窝清扫术

Kompass Onkologie Pub Date : 2024-05-07 DOI: 10.1159/000539214

N. Ditsch, M. Köpke

{"title":"Mammakarzinom: Axilladissektion nicht immer nötig bei Sentinel-Metastasen","authors":"N. Ditsch, M. Köpke","doi":"10.1159/000539214","DOIUrl":"https://doi.org/10.1159/000539214","url":null,"abstract":"Die SENOMAC-Studie konnte zeigen, dass bei Patienten mit ein oder zwei Sentinel-Metastasen der Verzicht auf eine Axilladissektion nicht unterlegen war in Bezug auf das rezidivfreie Überleben. In dieser Studie wurden Patientinnen sowie männliche Patienten (0,4%) mit T1-3 Tumoren und ein oder zwei Sentinel-Makrometastasen (zusätzliche Mikrometastasen waren erlaubt und 1/3 wies eine extrakapsuläre Ausbreitung auf) unabhängig vom OP-Verfahren der Brust (brusterhaltend oder Mastektomie) 1:1 randomisiert und erhielten entweder eine Axilladissektion oder keine weitere axilläre Operation. Die weitere adjuvante Therapie und Strahlentherapie erfolgte gemäß nationalen Leitlinien. Das 5-Jahres-rezidivfreie Überleben war in beiden Gruppen sehr gut (89,7% in der Sentinel-Gruppe; 88,7% in der Axilladissektions-Gruppe). Der Verzicht auf einen erweiterten axillären Eingriff zeigte sich signifikant nicht unterlegen (p < 0,001). Die derzeit noch ausstehenden Daten zum Gesamtüberleben werden im Verlauf zeigen müssen, ob man zukünftig Patientinnen mit Makrometastasen im Sentinel-Lymphknoten die zusätzliche Morbidität durch eine Axilladissektion bei gleicher onkologischer Sicherheit ersparen kann.","PeriodicalId":413988,"journal":{"name":"Kompass Onkologie","volume":"21 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141004990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Triple-negativer Brustkrebs: Mit Pembrolizumab die Lebensqualität im metastasierten Stadium verbessern 三阴性乳腺癌：使用 pembrolizumab 改善转移期患者的生活质量

Kompass Onkologie Pub Date : 2024-05-07 DOI: 10.1159/000539168

Brigitte Sophia Winkler

{"title":"Triple-negativer Brustkrebs: Mit Pembrolizumab die Lebensqualität im metastasierten Stadium verbessern","authors":"Brigitte Sophia Winkler","doi":"10.1159/000539168","DOIUrl":"https://doi.org/10.1159/000539168","url":null,"abstract":"Background: In KEYNOTE-119 (ClinicalTrials.gov, NCT02555657), overall survival (primary end-point) was similar between pembrolizumab and chemotherapy in patients with previously treated metastatic triple-negative breast cancer (TNBC), although the pembrolizumab treatment effect increased with tumour PD-L1 expression. We report results of prespecified health-related quality of life (HRQoL) analyses from KEYNOTE-119. Methods: Eligible patients were randomised 1:1 to pembrolizumab 200 mg Q3W intravenously for up to 35 cycles or treatment of physician's choice per local/country guidelines. Prespecified exploratory end-points were the change from baseline in HRQoL (EORTC QLQ-C30, QLQ-BR23) and to characterise utilities (EQ-5D-3L). Time to deterioration (TTD) was the time from start of treatment to first onset of a ≥10-point worsening from baseline. Results: HRQoL analyses included 187 patients with tumour PD-L1 combined positive score (CPS) ≥10. Changes from baseline at 6 weeks (primary analysis time point) were directionally better with pembrolizumab versus chemotherapy for QLQ-C30 GHS/QoL (between-group difference in least-squares mean scores of 4.21 [95% CI, -1.38 to 9.80]), QLQ-C30 functional scales (physical, role, cognitive, social), QLQ-C30 symptom scales/items (fatigue, nausea/vomiting, dyspnoea, appetite loss), and QLQ-BR23 symptom scales/items (systemic therapy side-effects, upset by hair loss). Median TTD was directionally longer for pembrolizumab versus chemotherapy for QLQ-C30 QHS/QoL (4.3 versus 1.7 months), QLQ-C30 nausea/vomiting (7.7 versus 4.8 months), and QLQ-BR23 systemic therapy side-effects (6.1 versus 3.4 months). Minimal treatment differences were observed for other HRQoL end-points.","PeriodicalId":413988,"journal":{"name":"Kompass Onkologie","volume":"103 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141002638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Die kommende Entwicklung großer Sprachmodelle in der Medizin 即将开发的大型医学语言模型

Kompass Onkologie Pub Date : 2024-02-12 DOI: 10.1159/000536600

Jan Clusmann, Fiona R. Kolbinger, Hannah Sophie Muti, Zunamys I. Carrero, Jan-Niklas Eckardt, Narmin Ghaffari Laleh, Chiara Maria Lavinia Loffler, Sophie-Caroline Schwarzkopf, M. Unger, Gregory P. Veldhuizen, Sophia J. Wagner, J. Kather

{"title":"Die kommende Entwicklung großer Sprachmodelle in der Medizin","authors":"Jan Clusmann, Fiona R. Kolbinger, Hannah Sophie Muti, Zunamys I. Carrero, Jan-Niklas Eckardt, Narmin Ghaffari Laleh, Chiara Maria Lavinia Loffler, Sophie-Caroline Schwarzkopf, M. Unger, Gregory P. Veldhuizen, Sophia J. Wagner, J. Kather","doi":"10.1159/000536600","DOIUrl":"https://doi.org/10.1159/000536600","url":null,"abstract":"Große Sprachmodelle (Large Language Models, LLMs) sind Tools der künstlichen Intelligenz (KI), die speziell für die Verarbeitung und Erzeugung von Text trainiert sind. LLMs erregten erhebliche öffentliche Aufmerksamkeit, nachdem ChatGPT von OpenAI im November 2022 öffentlich zugänglich gemacht wurde. LLMs können Fragen beantworten, Texte zusammenfassen, paraphrasieren und übersetzen, und zwar auf einer Ebene, die von menschlichen Fähigkeiten kaum zu unterscheiden ist. Die Möglichkeit, aktiv mit Modellen wie ChatGPT zu interagieren, macht LLMs zu attraktiven Tools in verschiedenen Bereichen, einschließlich der Medizin. Diese Modelle haben zwar das Potenzial, medizinisches Wissen zu demokratisieren und den Zugang zur Gesundheitsversorgung zu erleichtern, sie könnten jedoch aufgrund mangelnder Rechenschaftspflicht und Transparenz ebenso Fehlinformationen verbreiten und wissenschaftliches Fehlverhalten verschlimmern. In diesem Artikel geben wir einen systematischen und umfassenden Überblick über die Potenziale und Grenzen von LLMs in der klinischen Praxis, der medizinischen Forschung und der medizinischen Ausbildung.","PeriodicalId":413988,"journal":{"name":"Kompass Onkologie","volume":"7 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139782810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cholangioskopie im Fokus: Künstliche Intelligenz verbessert Genauigkeit und Effizienz der Diagnoseverfahren 聚焦胆道镜检查：人工智能提高了诊断程序的准确性和效率

Kompass Onkologie Pub Date : 2024-02-12 DOI: 10.1159/000537733

K. Homayounfar

{"title":"Cholangioskopie im Fokus: Künstliche Intelligenz verbessert Genauigkeit und Effizienz der Diagnoseverfahren","authors":"K. Homayounfar","doi":"10.1159/000537733","DOIUrl":"https://doi.org/10.1159/000537733","url":null,"abstract":"Background: We aimed to develop a convolutional neural network (CNN) model for detecting neoplastic lesions during real-time digital single-operator cholangioscopy (DSOC) and to clinically validate the model through comparisons with DSOC expert and nonexpert endoscopists. Methods: In this two-stage study, we first developed and validated CNN1. Then, we performed a multicenter diagnostic trial to compare four DSOC experts and nonexperts against an improved model (CNN2). Lesions were classified into neoplastic and non-neoplastic in accordance with Carlos Robles-Medranda (CRM) and Mendoza disaggregated criteria. The final diagnosis of neoplasia was based on histopathology and 12-month follow-up outcomes. Results: In stage I, CNN2 achieved a mean average precision of 0.88, an intersection over the union value of 83.24 %, and a total loss of 0.0975. For clinical validation, a total of 170 videos from newly included patients were analyzed with the CNN2. Half of cases (50 %) had neoplastic lesions. This model achieved significant accuracy values for neoplastic diagnosis, with a 90.5 % sensitivity, 68.2 % specificity, and 74.0 % and 87.8 % positive and negative predictive values, respectively. The CNN2 model outperformed nonexpert #2 (area under the receiver operating characteristic curve [AUC]-CRM 0.657 vs. AUC-CNN2 0.794, P < 0.05; AUC-Mendoza 0.582 vs. AUC-CNN2 0.794, P < 0.05), nonexpert #4 (AUC-CRM 0.683 vs. AUC-CNN2 0.791, P < 0.05), and expert #4 (AUC-CRM 0.755 vs. AUC-CNN2 0.848, P < 0.05; AUC-Mendoza 0.753 vs. AUC-CNN2 0.848, P < 0.05).","PeriodicalId":413988,"journal":{"name":"Kompass Onkologie","volume":"68 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Einbindung von Patient Reported Outcomes und künstlicher Intelligenz als zentrale Technologien im Gesundheitswesen 整合患者报告结果和人工智能，将其作为医疗保健领域的关键技术

Kompass Onkologie Pub Date : 2024-02-12 DOI: 10.1159/000536319

Samantha Cruz Rivera, Xiaoxu Liu, Sarah E. Hughes, Helen Dunster, Elaine Manna, Alastair K. Denniston, Melanie J. Calvert

引用次数: 0

Onkologie im Aufbruch: Wie KI und Digitalisierung die Zukunft gestalten 移动中的肿瘤学：人工智能和数字化如何塑造未来

Kompass Onkologie Pub Date : 2024-02-12 DOI: 10.1159/000537717

Thomas Elter, Tabea Fröhlich

引用次数: 0

Einbindung von Patient Reported Outcomes und künstlicher Intelligenz als zentrale Technologien im Gesundheitswesen 整合患者报告结果和人工智能，将其作为医疗保健领域的关键技术

Kompass Onkologie Pub Date : 2024-02-12 DOI: 10.1159/000536319

Samantha Cruz Rivera, Xiaoxu Liu, Sarah E. Hughes, Helen Dunster, Elaine Manna, Alastair K. Denniston, Melanie J. Calvert

引用次数: 0

Mobile Health: Potenziale und Herausforderungen in der medizinischen Versorgung 移动医疗：医疗保健的潜力与挑战

Kompass Onkologie Pub Date : 2024-02-12 DOI: 10.1159/000537716

H. Link

{"title":"Mobile Health: Potenziale und Herausforderungen in der medizinischen Versorgung","authors":"H. Link","doi":"10.1159/000537716","DOIUrl":"https://doi.org/10.1159/000537716","url":null,"abstract":"Background: Mobile health (mhealth) is gaining interest, with mobile devices and apps being ever more available among medical facilities and patients. However, in the field of radiation oncology, the medical benefits of mhealth apps are still underexplored. As an additional approach to patient care during radiotherapy, we designed a mobile treatment surveillance app based on patient-reported outcomes. Objective: We aimed to examine the feasibility of app-based treatment surveillance in patients undergoing radiotherapy (RT). Alongside technical practicability and acceptance, we assessed patient satisfaction and quality of life during treatment. Methods: This prospective single-center study was performed at Heidelberg University Hospital between August 2018 and January 2020. During RT we measured patients' quality of life, symptoms, and treatment satisfaction. Respective questionnaires (EORTC QLQ-C30 with diagnosis-specific modules, RAND PSQ-18) were presented to patients via a mobile app running on a designated tablet device. The primary endpoint was determined by the fraction of patients who completed at least 80% of the items. Secondary endpoints were disease-related quality of life and patient satisfaction. Results: A total of 49 cancer patients (14 breast, 13 pelvic, 12 lung, 10 prostate) were eligible for analysis. 79.6% (95% confidence interval: 66.4-88.5%; n = 39) of all patients completed at least 80% of the items received by the mobile app. A mean of 227.5 ± 48.25 questions were answered per patient. Breast cancer patients showed the highest rate of answered questions, with 92.9% (n = 13) completing at least 80% of the items.","PeriodicalId":413988,"journal":{"name":"Kompass Onkologie","volume":"56 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Onkologie im Aufbruch: Wie KI und Digitalisierung die Zukunft gestalten 移动中的肿瘤学：人工智能和数字化如何塑造未来

Kompass Onkologie Pub Date : 2024-02-12 DOI: 10.1159/000537717

Thomas Elter, Tabea Fröhlich

引用次数: 0