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Comparative Effectiveness of Tumor Response Assessment Methods: Standard of Care Versus Computer-Assisted Response
Brian C Allen1, Edward Florez1, Reza Sirous1
1Brian C. Allen, Duke University Medical Center, Durham, NC; Edward Florez, Reza Sirous, Seth T. Lirette, Michael Griswold, Candace M. Howard-Claudio, J. Clark Henegan, Judd Storrs, and Andrew D. Smith, University of Mississippi Medical Center, Jackson, MS; Erick M. Remer and Brian Rini, The Cleveland Clinic; Amit Vasanji, ImageIQ, Cleveland; Jacob E. Bieszczad, University of Toledo Medical Center, Toledo, OH; Zhen J. Wang, University of California at San Francisco Medical Center, San Francisco, CA; Kelly L. Cox and Sadhna B. Nandwana, Emory University School of Medicine, Atlanta, GA; Ajit H. Goenka, The Mayo Clinic, Rochester, MN; Hyunseon C. Kang, University of Texas MD Anderson Cancer Center, Houston, TX; Rupan Sanyal, University of Alabama at Birmingham Medical Center, Birmingham, AL; Atul B. Shinagare, Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard University, Boston, MA; Matthew S. Davenport, University of Michigan Health System, Ann Arbor, MI; and Balaji Ganeshan, University College of London, London, United Kingdom.
Purpose:
To compare the effectiveness of metastatic tumor response evaluation with computed tomography using computer-assisted versus manual methods.
Materials And Methods:
In this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study, 11 readers from 10 different institutions independently categorized tumor response according to three different therapeutic response criteria by using paired baseline and initial post-therapy computed tomography studies from 20 randomly selected patients with metastatic renal cell carcinoma who were treated with sunitinib as part of a completed phase III multi-institutional study. Images were evaluated with a manual tumor response evaluation method (standard of care) and with computer-assisted response evaluation (CARE) that included stepwise guidance, interactive error identification and correction methods, automated tumor metric extraction, calculations, response categorization, and data and image archiving. A crossover design, patient randomization, and 2-week washout period were used to reduce recall bias. Comparative effectiveness metrics included error rate and mean patient evaluation time.
Results:
The standard-of-care method, on average, was associated with one or more errors in 30.5% (6.1 of 20) of patients, whereas CARE had a 0.0% (0.0 of 20) error rate ( P < .001). The most common errors were related to data transfer and arithmetic calculation. In patients with errors, the median number of error types was 1 (range, 1 to 3). Mean patient evaluation time with CARE was twice as fast as the standard-of-care method (6.4 minutes v 13.1 minutes; P < .001).
Conclusion:
CARE reduced errors and time of evaluation, which indicated better overall effectiveness than manual tumor response evaluation methods that are the current standard of care.
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