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Invited review: study design considerations for clinical research in veterinary radiology and radiation oncology
Peter V Scrivani1, Hollis N Erb2
1Departments of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, 14853.
Abstract:
High quality clinical research is essential for advancing knowledge in the areas of veterinary radiology and radiation oncology. Types of clinical research studies may include experimental studies, method-comparison studies, and patient-based studies. Experimental studies explore issues relative to pathophysiology, patient safety, and treatment efficacy. Method-comparison studies evaluate agreement between techniques or between observers. Patient-based studies investigate naturally acquired disease and focus on questions asked in clinical practice that relate to individuals or populations (e.g., risk, accuracy, or prognosis). Careful preplanning and study design are essential in order to achieve valid results. A key point to planning studies is ensuring that the design is tailored to the study objectives. Good design includes a comprehensive literature review, asking suitable questions, selecting the proper sample population, collecting the appropriate data, performing the correct statistical analyses, and drawing conclusions supported by the available evidence. Most study designs are classified by whether they are experimental or observational, longitudinal or cross-sectional, and prospective or retrospective. Additional features (e.g., controlled, randomized, or blinded) may be described that address bias. Two related challenging aspects of study design are defining an important research question and selecting an appropriate sample population. The sample population should represent the target population as much as possible. Furthermore, when comparing groups, it is important that the groups are as alike to each other as possible except for the variables of interest. Medical images are well suited for clinical research because imaging signs are categorical or numerical variables that might be predictors or outcomes of diseases or treatments.
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