RESUMO
BACKGROUND: Sarcopenia appears to be a negative prognostic factor for poor survival outcomes and worse treatment tolerance in patients with head-and-neck squamous cell carcinoma (HNSCC). We evaluated sarcopenia's impact on overall survival (OS), disease-free survival (DFS) and chemo-radiation tolerance in patients with head-and-neck cancer (HNC) treated with chemoradiotherapy (CRT) from a monocentric observational study. METHODS: We identified patients with HNC treated by CRT between 2009 and 2018 with pretreatment imaging using positron emission tomography-computed tomography scans (PET/CT). Sarcopenia was measured using the pretreatment PET/CT at the L3 vertebral body using previously published methods. Clinical variables were retrospectively retrieved. RESULTS: Of 216 patients identified, 54 patients (25.47%) met the criteria for sarcopenia. These patients had a lower mean body mass index before treatment (21.92 vs. 25.65 cm/m2 , p < 0.001) and were more likely to have a history of smoking (88.89% vs. 71.52%, p = 0.01), alcohol use (55.56% vs. 38.61%, p = 0.03) and positive human papilloma virus status (67.74% vs. 41.75%, p = 0.011). At 3 years of follow-up, OS and DFS were 75% and 70% versus 82% and 85% for sarcopenic and non-sarcopenic patients, respectively (p = 0.1 and p = 0.00015). On multivariate analysis, sarcopenia appeared as a pejorative factor on DFS (hazard ratio 2.174, p = 0.0001) in the overall cohort. Sarcopenic patients did not require more chemotherapy and radiation-treatment interruptions and did not suffer from more chemo-induced and radiation-induced grade 3-4 toxicities than their non-sarcopenic counterparts. CONCLUSION: Sarcopenia in HNSCC patients is an independent adverse prognostic factor for DFS after definitive chemoradiotherapy.
Assuntos
Neoplasias de Cabeça e Pescoço , Sarcopenia , Humanos , Carcinoma de Células Escamosas de Cabeça e Pescoço/terapia , Sarcopenia/diagnóstico por imagem , Sarcopenia/etiologia , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Estudos Retrospectivos , Neoplasias de Cabeça e Pescoço/complicações , Neoplasias de Cabeça e Pescoço/terapia , Quimiorradioterapia/efeitos adversos , PrognósticoRESUMO
Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA.