Beyond Correlations, Sensitivities, and Specificities

Abstract

Despite the widespread belief that advanced imaging should be very helpful in guiding oncology treatment decision and improving efficiency and success rates in treatment clinical trials, its acceptance has been slow. Part of this is likely attributable to gaps in study design and statistical methodology for these imaging studies. Also, results supporting the performance of the imaging in these roles have largely been insufficient to justify their use within the design of a clinical trial or in treatment decision-making. Statistically significant correlations between the imaging results and clinical outcomes are often incorrectly taken as evidence of adequate performance. Assessments of whether the imaging can outperform standard techniques or meaningfully supplement them are also frequently neglected. This manuscript provides guidance on study designs and statistical analyses for evaluating the performance of advanced imaging in the various roles in treatment decision guidance and clinical trial conduct. Relevant methodology from the imaging literature is reviewed; gaps in the literature are addressed using related concepts from the more extensive genomic and in vitro biomarker literature.

Harnessing imaging tools to guide immunotherapy trials: summary from the National Cancer Institute Cancer Imaging Steering Committee workshop

“…The designs of clinical trials for the assessment of these roles are distinct and NCI clinical trial consortia, among others, offer a conduit for these important investigations. 70,71 Funding opportunities are available through various mechanisms in the National Institutes of Health (NIH) to support such discoveries and development. [72][73][74] Overall, there is considerable interest in and support for activities in current and planned immunotherapy trials that use diagnostic imaging for both predictive capabilities and response assessment.…”