Immunotherapies demand for predictive biomarkers to avoid unnecessary adverse effects and costs. Analytic morphomics is the technique to use body composition measures as imaging biomarkers for underlying pathophysiology to predict prognosis or outcome to therapy. We investigated different body composition measures to predict response to immunotherapy. This IRB approved retrospective analysis encompassed 147 patients with ipilimumab therapy. Degree of macroangiopathy was quantified with the newly defined total plaque index (TPI), i.e. the body height corrected sum of the soft and hard plaque volume of the infrarenal aorta on portalvenous CT scans. Furthermore, mean psoas density (MPD), different adipose tissue parameters as well as degree of cerebral microangiopathy were extracted from the imaging data. Subsequent multivariate Cox regression analysis encompassed TPI, MPD, serum LDH, S100B, age, gender, number of immunotherapy cycles as well as extent of distant metastases. TPI and MPD correlated positively with PFS in multivariate analysis (p = 0.03 and p = 0.001, respectively). Furthermore, single visceral organ and/or soft tissue involvement significantly decreased progression risk (p = 0.01), whereas increased S100B level showed a trend towards PFS shortening (p = 0.05). In conclusion, degree of macroangiopathy and sarcopenia were independent predictors for outcome to immunotherapy and of equivalent significance compared to other clinical biomarkers.
Conflict of interest statement
The authors declare no competing interests.
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