Shlomit Strulov Shachar1, Grant R Williams2, Hyman B Muss2, Tomohiro F Nishijima2. 1. UNC Lineberger Comprehensive Cancer Center, 450 West Drive, Chapel Hill, NC 27514, USA; Division of Oncology, Rambam Health Care Campus, Haifa, Israel. Electronic address: shlomits@email.unc.edu. 2. UNC Lineberger Comprehensive Cancer Center, 450 West Drive, Chapel Hill, NC 27514, USA.
Abstract
BACKGROUND: Body composition plays an important role in predicting treatment outcomes in adults with cancer. Using existing computed tomographic (CT) cross-sectional imaging and readily available software, the assessment of skeletal muscle mass to evaluate sarcopenia has become simplified. We performed a systematic review and meta-analysis to quantify the prognostic value of skeletal muscle index (SMI) obtained from cross-sectional CT imaging on clinical outcomes in non-haematologic solid tumours. METHODS: We searched PubMed and the American Society Clinical Oncology online database of meeting abstracts up to October 2015 for relevant studies. We included studies assessing the prognostic impact of pre-treatment SMI on clinical outcomes in patients with non-haematologic solid tumours. The primary outcome was overall survival (OS) and the secondary outcomes included cancer-specific survival (CSS), disease-free survival (DFS), and progression-free survival (PFS). The summary hazard ratio (HR) and 95% confidence interval (CI) were calculated. RESULTS: A total of 7843 patients from 38 studies were included. SMI lower than the cut-off was associated with poor OS (HR = 1.44, 95% CI = 1.32-1.56, p < 0.001). The effect of SMI on OS was observed among various tumour types and across disease stages. Worse CSS was also associated with low SMI (HR = 1.93, 95% CI = 1.38-2.70, p < 0.001) as well as DFS (HR = 1.16, 95% CI = 1.00-1.30, p = 0.014), but not PFS (HR = 1.54, 95% CI = 0.90-2.64, p = 0.117). CONCLUSIONS: This meta-analysis demonstrates that low SMI at cancer diagnosis is associated with worse survival in patients with solid tumours. Further research into understanding and mitigating the negative effects of sarcopenia in adults with cancer is needed.
BACKGROUND: Body composition plays an important role in predicting treatment outcomes in adults with cancer. Using existing computed tomographic (CT) cross-sectional imaging and readily available software, the assessment of skeletal muscle mass to evaluate sarcopenia has become simplified. We performed a systematic review and meta-analysis to quantify the prognostic value of skeletal muscle index (SMI) obtained from cross-sectional CT imaging on clinical outcomes in non-haematologic solid tumours. METHODS: We searched PubMed and the American Society Clinical Oncology online database of meeting abstracts up to October 2015 for relevant studies. We included studies assessing the prognostic impact of pre-treatment SMI on clinical outcomes in patients with non-haematologic solid tumours. The primary outcome was overall survival (OS) and the secondary outcomes included cancer-specific survival (CSS), disease-free survival (DFS), and progression-free survival (PFS). The summary hazard ratio (HR) and 95% confidence interval (CI) were calculated. RESULTS: A total of 7843 patients from 38 studies were included. SMI lower than the cut-off was associated with poor OS (HR = 1.44, 95% CI = 1.32-1.56, p < 0.001). The effect of SMI on OS was observed among various tumour types and across disease stages. Worse CSS was also associated with low SMI (HR = 1.93, 95% CI = 1.38-2.70, p < 0.001) as well as DFS (HR = 1.16, 95% CI = 1.00-1.30, p = 0.014), but not PFS (HR = 1.54, 95% CI = 0.90-2.64, p = 0.117). CONCLUSIONS: This meta-analysis demonstrates that low SMI at cancer diagnosis is associated with worse survival in patients with solid tumours. Further research into understanding and mitigating the negative effects of sarcopenia in adults with cancer is needed.
Authors: Shlomit Strulov Shachar; Allison M Deal; Marc Weinberg; Grant R Williams; Kirsten A Nyrop; Karteek Popuri; Seul Ki Choi; Hyman B Muss Journal: Clin Cancer Res Date: 2017-01-31 Impact factor: 12.531
Authors: Julia Furtner; Els Genbrugge; Thierry Gorlia; Martin Bendszus; Martha Nowosielski; Vassilis Golfinopoulos; Michael Weller; Martin J van den Bent; Wolfgang Wick; Matthias Preusser Journal: Neuro Oncol Date: 2019-12-17 Impact factor: 12.300
Authors: J Zanker; D Scott; E M Reijnierse; S L Brennan-Olsen; R M Daly; C M Girgis; M Grossmann; A Hayes; T Henwood; V Hirani; C A Inderjeeth; S Iuliano; J W L Keogh; J R Lewis; A B Maier; J A Pasco; S Phu; K M Sanders; M Sim; R Visvanathan; D L Waters; S C Y Yu; G Duque Journal: J Nutr Health Aging Date: 2019 Impact factor: 4.075
Authors: Bette J Caan; Jeffrey A Meyerhardt; Candyce H Kroenke; Stacey Alexeeff; Jingjie Xiao; Erin Weltzien; Elizabeth Cespedes Feliciano; Adrienne L Castillo; Charles P Quesenberry; Marilyn L Kwan; Carla M Prado Journal: Cancer Epidemiol Biomarkers Prev Date: 2017-05-15 Impact factor: 4.254