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Updated: Jan 31, 2026

A Melanoma Patient-Derived Xenograft Model
Published on: May 20, 2019
Physiologic colonic fluorine-18-fluorodeoxyglucose uptake may predict response to immunotherapy in patients with
Ben Boursi1,2,3,4,5, Thomas J Werner6, Saeid Gholami6
1Department of Medicine, Division of Gastroenterology.
Abstract:
The gut microbiota impacts response to immunotherapy in cancer patients. We sought to evaluate the role of physiologic colonic fluorine-18-fluorodeoxyglucose (F-FDG) uptake, a test that was recently shown to reflect colonic bacterial load, as a possible predictor for response to immunotherapy. We carried out a retrospective study in metastatic melanoma patients who received the immune checkpoint inhibitor ipilimumab as first-line therapy. All patients underwent an F-FDG PET scan before treatment initiation. The primary outcome was defined as response to treatment according to the RECIST criteria. Regions of interest were drawn on each transaxial slice around the outer boundaries of the colon. Uptake was measured using maximum and mean standardized uptake value (SUV). A nonparametric test was used to compare SUV between response groups. The study included 14 melanoma patients, of whom two (14.3%) achieved a complete response (CR) following treatment, eight (57.1%) achieved a partial response (PR), and four (28.6%) developed progressive disease (PD). The mean SUVmax was 1.33±0.04, 2.2±0.46, and 3.33±2.67 for individuals with CR, PR, and PD, respectively. The difference between individuals with CR and those without CR (PR or PD) in total colonic SUVmax was statistically significant (P=0.03). Thus, physiologic colonic F-FDG uptake may predict CR to immunotherapy in metastatic melanoma patients.
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However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
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