Improving normal tissue complication probability models: the need to adopt a "data-pooling" culture.
Clinical studies of the dependence of normal tissue response on dose-volume factors are often confusingly inconsistent, as the QUANTEC reviews demonstrate. A key opportunity to accelerate progress is to begin storing high-quality datasets in repositories. Using available technology, multiple repositories could be conveniently queried, without divulging protected health information, to identify relevant sources of data for further analysis. After obtaining institutional approvals, data could then be pooled, greatly enhancing the capability to construct predictive models that are more widely applicable and better powered to accurately identify key predictive factors (whether dosimetric, image-based, clinical, socioeconomic, or biological). Data pooling has already been carried out effectively in a few normal tissue complication probability studies and should become a common strategy.
Deasy
Joseph O
JO
Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA. jdeasy@radonc.wustl.edu
Bentzen
Søren M
SM
Jackson
Andrew
A
Ten Haken
Randall K
RK
Yorke
Ellen D
ED
Constine
Louis S
LS
Sharma
Ashish
A
Marks
Lawrence B
LB
D016208:Databases, Factual; D006801:Humans; D033181:Information Dissemination / Q000379:methods*; D015233:Models, Statistical; D011832:Radiation Injuries / Q000150:complications*; D012106:Research