Zusammenfassung
Hintergrund
Die individuellen Therapiemöglichkeiten der Patientin mit einem metastasierten Brustkrebs werden immer spezifischer. Für Therapieentscheidungen in der metastasierten Situation liegt keine ausreichende Evidenz aus klinischen Studien für alle Behandlungssituationen und Subgruppen vor. Dieses macht die Erhebung und systematische Auswertung von Real-World-Daten zur Erstellung von Real-World-Evidenz sinnvoll.
Methoden und Ziele
Um bei der Behandlung von Patientinnen mit einem metastasierten Mammakarzinom eine stadien- und tumorspezifische Therapie identifizieren zu können, wurde das PRAEGNANT-Netzwerk (Prospective Academic Translational Research Network zur Optimierung der onkologischen Versorgungsqualität im fortgeschrittenen therapeutischen Umfeld) etabliert. Ziel ist es, die medizinische Versorgung von Patientinnen mit metastasiertem Mammakarzinom in der realen Welt zu beleuchten, Wirkungen und Nebenwirkungen der Therapiekonzepte zu erfassen, die Veränderung der Lebensqualität unter der Therapie mit zu verfolgen, Patientinnen zu identifizieren, die an einer klinischen Arzneimittelstudie teilnehmen können, und durch Untersuchung der molekularen Tumoreigenschaften des Mammakarzinoms Patientinnen eine zielgerichtete Therapie in klinischen Studien zu ermöglichen.
Schlussfolgerung
Dieser Artikel fasst die bereits erhobenen Daten aus dem PRAEGNANT-Netzwerk zusammen und beleuchtet die Frage der Übertragbarkeit der verschiedenen Endpunkte aus klinischen Studien in die reale Behandlungssituation.
Abstract
Background
The therapeutic options for the individual patient with metastatic breast cancer are becoming more and more specific. Evidence for therapeutic recommendations from clinical trials is not available for all treatment situations and patient subgroups. This makes the collection and evaluation of real-world data meaningful.
Methods and aims
To provide recommendations for up-to-date treatments and participation in clinical trials for patients with metastatic breast cancer, the Prospective Academic Translational Research Network (PREAGNANT) has been established to optimize the oncological quality of care in the advanced therapeutic setting. The main aim is to systematically record medical care of patients with metastatic breast cancer in real life including the therapeutic effects and side effects of the different treatment strategies, to monitor the quality of life changes during therapy, to identify patients who could participate in a clinical drug study and to enable a targeted therapy based on molecular structures of breast cancer patients.
Conclusion
This article presents a summary of the PRAEGNANT network and sheds light on the question of the portability of the various endpoints from clinical trials into the real world treatment situation.
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Diese Studie wird gefördert von Forschungsgrants der Firmen Novartis, Celgene und Roche. Des Weiteren wird sie gefördert von TRR (Translational Research Ressources) der Frauenklinik des Universitätsklinikums Erlangen.
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E. Belleville erhielt Honorare von Novartis, Celgene, Riemser, Pfizer, Hexal, Amgen, onkowissen.de für Beratung, Leitung klinischer Forschung oder medizinische Fortbildungsaktivitäten. F.-A. Taran erhielt Honorare von AstraZeneca, Genomic Health, Novartis, Roche, Tesaro und Teva sowie Reisekostenunterstützung von Novartis und Tesaro. Die Institution von M. Beckmann erhielt Forschungsförderung von Novartis and Biontech. J. Emons erhielt Honorare von Eisai, Pfizer und Novartis. T.N. Fehm erhielt Honorare von AstraZeneca, Celgene, Eisai, Pfizer und Roche. P.A. Fasching gibt Zuschüsse von Novartis, Cepheid und Biontech an, persönliche Honorare von Novartis, Roche, Pfizer, Celgene, Daiichi-Sankyo, TEVA, AstraZeneca, Merck Sharp & Dohme, Myelo Therapeutics, Macrogenics, Eisai und Puma. A.D. Hartkopf erhielt Honorare von Teva, Genomic Health, Celgene, AstraZeneca, Novartis, Pfizer, Lilly, MSD, Eisai und Roche. W. Janni erhielt Honorare und Forschungsbeihilfen von Novartis. H.‑C. Kolberg erhielt Honorare von Carl Zeiss Meditec, TEVA, Theraclion, Novartis, Amgen, AstraZeneca, Pfizer, Janssen-Cilag, GSK, LIV Pharma, MSD, Onkowissen, SurgVision, Roche und Genomic Health. D. Lüftner erhielt Honorare von Amgen, AstraZeneca, Celgene, Lilly, L’Oréal, MSD, Novartis, Pfizer, Tesaro, Teva. M.P. Lux erhielt Honorare von Pfizer, Lilly, Roche, MSD, Hexal, Novartis, AstraZeneca, Eisai, medac und Genomic Health für Teilnahme an Beratungsausschüssen, Vortragstätigkeiten und Reisekostenunterstützung. V. Müller erhielt Rednerhonorare von Amgen, AstraZeneca, Celgene, Daiichi-Sankyo, Eisai, Pfizer, Pierre-Fabre, Novartis, Roche, Teva, Janssen-Cilag und Honorare für Beratungstätigkeiten von Genomic Health, Roche, Pierre Fabre, Amgen, Daiichi-Sankyo und Eisai. F. Overkamp erhielt Rednerhonorare und Honorare für Beratungstätigkeiten von Amgen, AstraZeneca, Bayer, BMS, Boehringer, Celgene, Chugai, Eisai, Gilead, Hexal, Ipsen, Janssen, Merck, MSD, AstraZeneca, Novartis, Novonordisc, Riemser, Roche, Servier, Shire, Tesaro, Teva und MSD. A. Schneeweiss erhielt Honorare von Roche, Celgene, AstraZeneca, Novartis, Pfizer, Zuckschwerdt Verlag GmbH, Georg Thieme Verlag, Aurikamed GmbH, MCI Deutschland GmbH, bsh medical communications GmbH und promedicis GmbH. H. Tesch erhielt Honorare von Novartis, Roche, Celgene, TEVA, Pfizer sowie Reisekostenunterstützung von Roche, Celgene und Pfizer. M. Wallwiener erhielt Rednerhonorare von AstraZeneca, Celgene und Novartis. A. Titzmann, P. Pöschke, J. Ettl, D. Wallwiener und S. Y. Brucker geben an, dass kein Interessenkonflikt besteht.
Alle beschriebenen Untersuchungen am Menschen oder an menschlichem Gewebe wurden mit Zustimmung der zuständigen Ethikkommission, im Einklang mit nationalem Recht sowie gemäß der Deklaration von Helsinki von 1975 (in der aktuellen, überarbeiteten Fassung) durchgeführt. Von allen beteiligten Patienten liegt eine Einverständniserklärung vor.
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Die Autoren A.D. Hartkopf, J. Emons, S.Y. Brucker und P.A. Fasching haben zu gleichen Teilen zum Manuskript beigetragen.
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Hartkopf, A.D., Emons, J., Lux, M.P. et al. Klinische Endpunkte in Real-World-Register-Studien. Onkologe 26, 530–541 (2020). https://doi.org/10.1007/s00761-020-00766-x
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DOI: https://doi.org/10.1007/s00761-020-00766-x
Schlüsselwörter
- Informationssysteme
- Evidenzbasierte Medizin
- Klinische Entscheidungsfindung
- Künstliche Intelligenz
- „Big data“