Dorsal Muscle Attenuation May Predict Failure to Respond to Interleukin-2 Therapy in Metastatic Renal Cell Carcinoma

To explore whether the sarcopenia body type can help predict response to interleukin-2 (IL-2) therapy in metastatic renal cell carcinoma (RCC).

Institutional review board approval was obtained for this Health Insurance Portability and Accountability Act-compliant retrospective cohort study of 75 subjects with metastatic RCC who underwent pretreatment contrast-enhanced computed tomography within 1 year of initiating IL-2 therapy. Cross-sectional area and attenuation of normal-density (31-100 Hounsfield units [HU]) and low-density (0-30 HU) dorsal muscles were obtained at the T11 vertebral level. The primary outcome was partial or complete response to IL-2 using RECIST 1.1 criteria at 6 weeks. A conditional inference tree was used to determine an optimal HU cutoff for predicting outcome. Bonferroni-adjusted multivariate logistic regression was conducted to investigate the independent associations between imaging features and response after controlling for demographics, doses of IL-2, and RCC prognostic scales (eg, Heng and the Memorial Sloan Kettering Cancer Center [MSKCC]).

Most subjects had intermediate prognosis by Heng (65% [49 of 75]) and the MSKCC (63% [47 of 75]) criteria; 7% had complete response and 12% had partial response. Mean attenuation of low-density dorsal muscles was a significant univariate predictor of IL-2 response after Bonferroni correction (P = 0.03). The odds of responding to treatment were 5.8 times higher for subjects with higher-attenuation low-density dorsal muscles (optimal cutoff: 18.1 HU). This persisted in multivariate analysis (P = 0.02). Body mass index (P = 0.67) and the Heng (P = 0.22) and MSKCC (P = 0.08) clinical prognostic scales were not significant predictors of response.

Mean cross-sectional attenuation of low-density dorsal muscles (ie, sarcopenia) may predict IL-2 response in metastatic RCC. Clinical variables are poor predictors of response.

Academic radiology. 2017 Mar 21 [Epub ahead of print]

Bamidele Otemuyiwa, Brian A Derstine, Peng Zhang, Sandra L Wong, Michael S Sabel, Bruce G Redman, Stewart C Wang, Ajjai S Alva, Matthew S Davenport

University of Michigan Medical School, Ann Arbor, Michigan., Morphomics Analysis Group, University of Michigan, Ann Arbor, Michigan., Department of Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire., Department of Surgery, University of Michigan Health System, Ann Arbor, Michigan., Department of Medicine, Division of Hematology/Oncology, University of Michigan Health System, Ann Arbor, Michigan., Morphomics Analysis Group, University of Michigan, Ann Arbor, Michigan; Department of Surgery, University of Michigan Health System, Ann Arbor, Michigan., Department of Radiology, University of Michigan Health System, 1500 E. Medical Center Dr. B2-A209P, Ann Arbor, MI 48108; Department of Urology, University of Michigan Health System, Ann Arbor, Michigan; Michigan Radiology Quality Collaborative, Ann Arbor, Michigan. Electronic address: .

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