TY - JOUR
T1 - Considerations for observational research using large data sets in radiation oncology
AU - Jagsi, Reshma
AU - Bekelman, Justin E.
AU - Chen, Aileen
AU - Chen, Ronald C.
AU - Hoffman, Karen
AU - Tina Shih, Ya Chen
AU - Smith, Benjamin D.
AU - Yu, James B.
N1 - Funding Information:
Dr Bekelman is supported by a K award ( K07-CA163616 ) is from the NCI. Dr Jagsi receives funding from the American Cancer Society (MRSG-09-145-01). Dr Shih is supported by grants R21CA165092 , R01 HS018535 , and R01 HS020263 from the National Cancer Institute , Agency for Healthcare Research and Quality , and the University of Chicago Cancer Research Foundation Women's Board .
Funding Information:
The Cancer Care Outcomes Research and Surveillance Consortium (CanCORS), funded by the NCI in collaboration with the Department of Veterans Affairs, represents another valuable source of patient survey data. It focuses on patients with newly diagnosed colorectal or lung cancer from geographically diverse populations and health care delivery systems nationwide and includes data from medical records, as well as from physician and patient surveys (82) . CanCORS data have been used for a number of purposes, including comparison of practice patterns for palliative radiation to clinical evidence and evaluation of metastatic cancer patients' perceptions of the intent of radiation therapy (83-85) .
PY - 2014/9/1
Y1 - 2014/9/1
N2 - The radiation oncology community has witnessed growing interest in observational research conducted using large-scale data sources such as registries and claims-based data sets. With the growing emphasis on observational analyses in health care, the radiation oncology community must possess a sophisticated understanding of the methodological considerations of such studies in order to evaluate evidence appropriately to guide practice and policy. Because observational research has unique features that distinguish it from clinical trials and other forms of traditional radiation oncology research, the International Journal of Radiation Oncology, Biology, Physics assembled a panel of experts in health services research to provide a concise and well-referenced review, intended to be informative for the lay reader, as well as for scholars who wish to embark on such research without prior experience. This review begins by discussing the types of research questions relevant to radiation oncology that large-scale databases may help illuminate. It then describes major potential data sources for such endeavors, including information regarding access and insights regarding the strengths and limitations of each. Finally, it provides guidance regarding the analytical challenges that observational studies must confront, along with discussion of the techniques that have been developed to help minimize the impact of certain common analytical issues in observational analysis. Features characterizing a well-designed observational study include clearly defined research questions, careful selection of an appropriate data source, consultation with investigators with relevant methodological expertise, inclusion of sensitivity analyses, caution not to overinterpret small but significant differences, and recognition of limitations when trying to evaluate causality. This review concludes that carefully designed and executed studies using observational data that possess these qualities hold substantial promise for advancing our understanding of many unanswered questions of importance to the field of radiation oncology.
AB - The radiation oncology community has witnessed growing interest in observational research conducted using large-scale data sources such as registries and claims-based data sets. With the growing emphasis on observational analyses in health care, the radiation oncology community must possess a sophisticated understanding of the methodological considerations of such studies in order to evaluate evidence appropriately to guide practice and policy. Because observational research has unique features that distinguish it from clinical trials and other forms of traditional radiation oncology research, the International Journal of Radiation Oncology, Biology, Physics assembled a panel of experts in health services research to provide a concise and well-referenced review, intended to be informative for the lay reader, as well as for scholars who wish to embark on such research without prior experience. This review begins by discussing the types of research questions relevant to radiation oncology that large-scale databases may help illuminate. It then describes major potential data sources for such endeavors, including information regarding access and insights regarding the strengths and limitations of each. Finally, it provides guidance regarding the analytical challenges that observational studies must confront, along with discussion of the techniques that have been developed to help minimize the impact of certain common analytical issues in observational analysis. Features characterizing a well-designed observational study include clearly defined research questions, careful selection of an appropriate data source, consultation with investigators with relevant methodological expertise, inclusion of sensitivity analyses, caution not to overinterpret small but significant differences, and recognition of limitations when trying to evaluate causality. This review concludes that carefully designed and executed studies using observational data that possess these qualities hold substantial promise for advancing our understanding of many unanswered questions of importance to the field of radiation oncology.
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U2 - 10.1016/j.ijrobp.2014.05.013
DO - 10.1016/j.ijrobp.2014.05.013
M3 - Review article
C2 - 25195986
AN - SCOPUS:84905858537
SN - 0360-3016
VL - 90
SP - 11
EP - 24
JO - International Journal of Radiation Oncology Biology Physics
JF - International Journal of Radiation Oncology Biology Physics
IS - 1
ER -