کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8233661 | 1533110 | 2010 | 4 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Improving Normal Tissue Complication Probability Models: The Need to Adopt a “Data-Pooling” Culture
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
تشعشع
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Radiation Oncology*Biology*Physics - Volume 76, Issue 3, Supplement, 1 March 2010, Pages S151-S154
Journal: International Journal of Radiation Oncology*Biology*Physics - Volume 76, Issue 3, Supplement, 1 March 2010, Pages S151-S154
نویسندگان
Joseph O. Ph.D., Søren M. Ph.D., Andrew Ph.D., Randall K. Ph.D., Ellen D. Ph.D., Louis S. M.D., Ashish Ph.D., Lawrence B. M.D.,