Literature DB >> 10987329

Study design in the evaluation of breast cancer imaging technologies.

F Houn1, R A Bright, H F Bushar, B Y Croft, C A Finder, J K Gohagan, R J Jennings, P Keegan, L G Kessler, B S Kramer, L O Martynec, M Robinowitz, W M Sacks, D G Schultz, R F Wagner.   

Abstract

RATIONALE AND
OBJECTIVES: Bringing a new imaging technology to market is a complex process. Beyond conceptualization and proof of concept, obtaining U.S. Food and Drug Administration (FDA) approval for clinical use depends on the documented experimental establishment of safety and efficacy. In turn, safety and efficacy are evaluated in the context of the intended use of the technology. The purpose of this study was to examine a conceptual framework for technology development and evaluation, focusing on new breast imaging technologies as a highly visible and current case in point.
MATERIALS AND METHODS: The FDA views technology development in terms of a preclinical and four clinical phases of assessment. With a concept of research and development as a learning model, this phased-assessment concept of regulatory review against intended use was integrated with a five-level version of a hierarchy-of-efficacy framework for evaluating imaging technologies. Study design and analysis issues are presented in this context, as are approaches to supporting expanded clinical indications and new intended uses after a new technology is marketed.
CONCLUSION: Breast imaging technologies may be intended for use as replacements for standard-of-care technologies, as adjuncts, or as complementary technologies. Study designs must be appropriate to establish claims of superiority or equivalence to the standard for the intended use. Screening technologies are ultimately judged on their demonstrated effectiveness in decreasing cause-specific mortality through early detection, but they may be brought to market for other uses on the basis of lesser standards of efficacy (eg, sensitivity, specificity, positive and negative predictive value, and stage of disease detected).

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Year:  2000        PMID: 10987329     DOI: 10.1016/s1076-6332(00)80524-3

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  3 in total

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Authors:  Howard E Rockette; David Gur
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Review 2.  The American College Of Radiology Imaging Network--clinical trials of diagnostic imaging and image-guided treatment.

Authors:  Bruce J Hillman; Constantine Gatsonis
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3.  Impact of FDG-PET findings on decisions regarding patient management strategies: a multicenter trial in patients with lung cancer and other types of cancer.

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Journal:  Ann Nucl Med       Date:  2015-03-27       Impact factor: 2.668

  3 in total

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