Editorial: Data Based Radiation Oncology—Design of Clinical Trials
- 1Department of Radiation Oncology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- 2Institute for Innovative Radiotherapy (iRT), Helmholtz Zentrum München, Munich, Germany
- 3Department of Clinical Oncology, The University of Hong Kong Shenzhen Hospital, Shenzhen, China
- 4Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, The Greenebaum Cancer Center, School of Medicine, University of Maryland, Baltimore, MD, United States
- 5National Cancer Institute (NIH), Rockville, MD, United States
Editorial on the Research Topic
In radiation oncology as in many other specialties, clinical trials are essential to investigate new therapeutic approaches. Usually, preparation for a prospective clinical trial is time-consuming until ethics approval is obtained. To test a new treatment many years pass before it can be implemented in the routine care. During that time, already new interventions emerge, new drugs appear on the market, technical and physical innovations are being implemented, novel biology-driven concepts are translated into clinical approaches while we are still investigating the ones from years ago.
Another problem is associated with molecular diagnostics and the growing amount of tumor-specific biomarkers which allow for better stratification of patient subgroups. On the other side, this may result in a much longer time for patient recruiting and consequently in larger multicenter trials. Moreover, all of the relevant data must be readily available for treatment decision making, treatment as well as follow-up, and ultimately for trial evaluation. This challenges even more for agreed standards in data acquisition, quality, and management.
How could we change the way currently clinical trials are performed in a way they are safe and ethically justifiable and speed up the initiation process so that we can provide new and better treatments faster for our patients?
Furthermore, while we rely on various quantitative information handling distributed, large heterogeneous amounts of data efficiently is very important. Thus, data management becomes a strong focus. A good infrastructure helps to plan, tailor and conduct clinical trials in a way they are easy and quickly analyzable.
In this research topic, we want to discuss new ideas for intelligent trial designs and concepts for data management.
All authors wrote and revised the editorial.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Keywords: clinical trials, data collection, radiation oncology, clinical study design, study management
Citation: Kessel KA, Lee AWM, Bentzen SM, Vikram B, Nüsslin F and Combs SE (2018) Editorial: Data Based Radiation Oncology—Design of Clinical Trials. Front. Oncol. 8:34. doi: 10.3389/fonc.2018.00034
Received: 26 January 2018; Accepted: 01 February 2018;
Published: 16 February 2018
Edited and Reviewed by: Timothy James Kinsella, Warren Alpert Medical School of Brown University, United States
Copyright: © 2018 Kessel, Lee, Bentzen, Vikram, Nüsslin and Combs. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Kerstin Anne Kessel, email@example.com