Abstract 1693: Prediction of the efficacy of nivolumab using resting energy expenditure in metastatic non-small cell lung cancer (mNSCLC) patients

• Published in: Cancer research (Chicago, Ill.) Ill.), 2018-07, Vol.78 (13_Supplement), p.1693-1693
• Main Authors: Gervais, Claire, Boudou-Rouquette, Pascaline, Jouinot, Anne, Chapron, Jeanne, Arrondeau, Jennifer, Alifano, Marco, Giraud, Frédérique, Huillard, Olivier, Alexandre, Jérôme, Vazeille, Clara, Durand, Jean-Philippe, Leroy, Karen, Revel, Marie-Pierre, Bandt, Jean-Pascal de, Cynober, Luc, Damotte, Diane, Lupo-Mansuet, Audrey, Goldwasser, François
• Format: Article
• Language: English
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2018-1693

Background: Immune evasion and deregulation of energy metabolism play a pivotal role in cancer progression. Immunosuppression in the tumor microenvironment can be based on the mutual metabolic requirements of immune and tumor cells. We evaluated the value of resting energy expenditure (REE) as a predictor of outcome, in mNSCLC patients under Nivolumab, an immune checkpoint inhibitor. Methods: We studied the relation between REE, clinical and biological markers of cachexia and inflammation, and response to Nivolumab in 82 consecutive mNSCLC patients. Efficacy was assessed every 2 months according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria. REE was measured using indirect calorimetry, before the initiation of Nivolumab. According to their REE and with the use of Boothby's standard, patients were categorized as hypermetabolic, normometabolic and hypometabolic. Body mass index (BMI), performance status (PS), C-reactive protein (CRP), albumin, Neutrophil Lymphocyte R Ratio (NLR) and PD-L1 tumor expression were also recorded. Results: Patients characteristics were: 62% males, median age of 65 years (range 37-78), 61% PS 0-1, median BMI of 24 kg.m-² (range 17-39), 78% nonsquamous NSCLC. The analysis of REE was available for 69 out of 82 consecutive pts: 37.7% were hypermetabolic, 47.8% were normometabolic, and 14.5% were hypometabolic. In univariate analysis, hypometabolism was a strong predictive marker of disease progression (Table 1), with positive and negative predictive values of 0.80 and 0.52 respectively. In multivariate analysis, independent parameters associated with disease progression were baseline hypometabolism (vs normometabolism: OR 1.77 [1.31-2.39] p= 0.0004) and albumin (per 1pt increase: OR 0.96 [0.94-0.99] p= 0.005). Conclusion: Rest energy expenditure assessed by calorimetry appears as a biomarker of nivolumab clinical activity independently of PD1/PDL1 status. Table 1Disease control (best response) n (%)115% calculated REE n=26 (37.7%) Hypermetabolicunivariate OR (Hypometabolic vs normometabolic)pProgression8 (80%)11 (33%)17 (65%)8 [1.4-44.2]0.0007Disease control rate2 (20%)22 (67%)9 (35%) Citation Format: Claire Gervais, Pascaline Boudou-Rouquette, Anne Jouinot, Jeanne Chapron, Jennifer Arrondeau, Marco Alifano, Frédérique Giraud, Olivier Huillard, Jérôme Alexandre, Clara Vazeille, Jean-Philippe Durand, Karen Leroy, Marie-P