Sarcopenia represents one of the hallmarks of all chronic diseases, including cancer, and was already investigated as a prognostic marker in the pre-immunotherapy era. Sarcopenia can be evaluated using cross-sectional image analysis of CT-scans, at the level of the third lumbar vertebra (L3), to estimate the skeletal muscle index (SMI), a surrogate of skeletal muscle mass, and to evaluate the skeletal muscle density (SMD). We performed a retrospective analysis of consecutive advanced cancer patient treated with PD-1/PD-L1 checkpoint inhibitors. Baseline SMI and SMD were evaluated and optimal cut-offs for survival, according to sex and BMI (+/−25) were computed. The evaluated clinical outcomes were: objective response rate (ORR), immune-related adverse events (irAEs), progression free survival (PFS) and overall survival (OS). From April 2015 to April 2019, 100 consecutive advanced cancer patients were evaluated. 50 (50%) patients had a baseline low SMI, while 51 (51%) had a baseline low SMD according to the established cut offs. We found a significant association between SMI and ECOG-PS (p = 0.0324), while no correlations were found regarding SMD and baseline clinical factors. The median follow-up was 20.3 months. Patients with low SMI had a significantly shorter PFS (HR = 1.66 [95% CI: 1.05-2.61]; p = 0.0291) at univariate analysis, but not at the multivariate analysis. They also had a significantly shorter OS (HR = 2.19 [95% CI: 1.31-3.64]; p = 0.0026). The multivariate analysis confirmed baseline SMI as an independent predictor for OS (HR = 2.19 [1.31-3.67]; p = 0.0027). We did not find significant relationships between baseline SMD and clinical outcomes, nor between ORR, irAEs and baseline SMI (data not shown). Low SMI is associated with shortened survival in advanced cancer patients treated with PD1/PDL1 checkpoint inhibitors. However, the lack of an association between SMI and clinical response suggests that sarcopenia may be generally prognostic in this setting rather than specifically predictive of response to immunotherapy.Sarcopenia is the condition of loss of muscle mass, with decreased muscle power, and it is one of the hallmarks of cancer, which negatively affects the most of clinical outcomes such as toxicities and survival 1 . The interactions must recognize also the lack of other adiposity metrics, such as the waist circumference, the waist-to-height ratio, and the body fat percentage. Moreover, the CT imaging analysis was limited by the data availability; indeed, the acquisition protocol was planned according to the presence of previous examination. conclusionOur finding of a significant shorter OS for low-SMI patients treated with PD-1/PD-L1 checkpoint inhibitors, suggests that sarcopenia might have a prognostic role, rather than predictive. However, to properly weighing our results, we must consider the significant association between poorer PS and low-SMI. Without making conclusive considerations, we can assume that after the advent of ICIs, we should give back further relevance to baseline nut...

Sarcopenia represents one of the hallmarks of all chronic disease, including non‐small cell lung cancer (NSCLC). A computed tomography scan is an easy modality to estimate the skeletal muscle mass through cross‐sectional image analysis at the level of the third lumbar vertebra (L3). Baseline skeletal muscle mass (SMM) was evaluated using gender‐specific cutoffs for skeletal muscle index in NSCLC patients administered immunotherapy with nivolumab to evaluate its possible correlations with clinical outcomes. From April 2015 to August 2018, 23 stage IV NSCLC patients were eligible for image analysis. Nine patients (39.1%) had low SMM. Among patients with baseline low and non‐low SMM, median progression free survival was 3.1 and 3.8 months, respectively (P = 0.0560), while median overall survival was 4.1 and 13 months, respectively (P = 0.2866). This hypothesis‐generating preliminary report offers the opportunity to speculate about the negative influence of sarcopenia on immune response. In our opinion, nutritional status could affect the clinical outcomes of immunotherapy, even if we cannot make definitive conclusions here. Further studies on the topic are required.

BackgroundSarcopenia and muscle tissue degradation are hallmarks of the majority of chronic diseases, including non‐small cell lung cancer (NSCLC). A computed tomography scan could be an easy modality to estimate the skeletal muscle mass through cross‐sectional image analysis at the level of the third lumbar vertebra.MethodsBaseline skeletal muscle mass (SMM) was evaluated through the skeletal muscle index (SMI), together with skeletal muscle radiodensity (SMD), in NSCLC patients undergoing first‐line chemotherapy to evaluate correlations with safety and clinical outcomes. When SMIs at different time points were available, further comparison was made between patients with worse and improved SMIs.ResultsAmong 81 stage IV NSCLC patients, 28 had low SMM and 23 had low SMD. There were no significant differences in univariate analysis of progression‐free survival (PFS) between patients with baseline low and non‐low SMM (P = 0.06388) or between patients with low and non‐low SMD (P = 0.9126). Baseline low SMM, however, proved a significant predictor of shorter PFS in multivariate analysis (hazard ratio 0.54, 95% confidence interval 0.31–0.93; P = 0.0278), but not low SMD. There were no differences in overall survival (OS) between patients with baseline low and non‐low SMM or low and non‐low SMD. No differences in PFS and OS between evaluable patients with worse or improved SMI were found. A significant difference in hematological toxicities between patients with baseline low and non‐low SMM (P = 0.0358) was observed.ConclusionsLow SMM is predictive of shorter PFS, while consecutive changes in muscular mass do not seem to be a predictor of PFS or OS. The role of muscle radiodensity remains a matter of debate.

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ObjectivesTo evaluate the clinical pictures, laboratory tests and imaging of patients with lung involvement, either from severe COVID-19 or macrophage activation syndrome (MAS), in order to assess how similar these two diseases are.MethodsThe present work has been designed as a cross-sectional single-centre study to compare characteristics of patients with lung involvement either from MAS or severe COVID-19. Chest CT scans were assessed by using an artificial intelligence (AI)-based software.ResultsTen patients with MAS and 47 patients with severe COVID-19 with lung involvement were assessed. Although all patients showed fever and dyspnoea, patients with MAS were characterised by thrombocytopaenia, whereas patients with severe COVID-19 were characterised by lymphopaenia and neutrophilia. Higher values of H-score characterised patients with MAS when compared with severe COVID-19. AI-reconstructed images of chest CT scan showed that apical, basal, peripheral and bilateral distributions of ground-glass opacities (GGOs), as well as apical consolidations, were more represented in severe COVID-19 than in MAS. C reactive protein directly correlated with GGOs extension in both diseases. Furthermore, lymphopaenia inversely correlated with GGOs extension in severe COVID-19.ConclusionsOur data could suggest laboratory and radiological differences between MAS and severe COVID-19, paving the way for further hypotheses to be investigated in future confirmatory studies.