The Highest Metabolic Activity on FDG PET Is Associated With Overall Survival in Limited-Stage Small-Cell Lung Cancer. Issue 5 (February 2016) - Kwon, Soo Hyun; Hyun, Seung Hyup; Yoon, Joon-Kee; An, Young-Sil; Oh, Young-Taek; Choi, Jin-Hyuck; Park, Kwang Joo; Lee, Su Jin
Abstract : Abstract: We evaluated the prognostic value of 18 F-fluorodeoxyglucose positron emission tomography (FDG PET) parameters for limited-stage small-cell lung cancer (LS-SCLC). We retrospectively enrolled 59 LS-SCLC patients who underwent pretreatment FDG PET/CT. Various PET parameters were measured in all malignant lesions, and we recorded the highest maximum standardized uptake value (SUVmax ), and sum of metabolic tumor volume (MTVsum ) and total lesion glycolysis (TLGsum ). The relationship between the highest SUVmax and volumetric PET parameters was evaluated. The prognostic significances of PET parameters and clinical variables were assessed using Cox's proportional hazard regression analysis. Overall survival (OS) and progression-free survival (PFS) were assessed by the Kaplan–Meier method. The SUVmax of the highest metabolic lesion had a significant positive correlation with MTVsum and TLGsum ( P  < 0.001). Upon multivariate analysis, the highest SUVmax was an independent predictor of OS (1 unit increase, hazard ratio [HR]: 1.133, P  = 0.003) and MTVsum was a significant prognostic factor of PFS (10-cm 3 increase, HR: 1.027, P  = 0.034) after adjusting for age, sex, performance status, tumor stage, and treatment modality. The highest SUVmax was a prognostic factor for PFS with marginal significance (1 unit increase, HR: 1.078, P  = 0.053). Patients with higher SUVmax (≥11) were also characterized by a significantly shorter median OS ( P  < 0.001) and PFS ( P  = 0.002) compared with patients with lower SUVmax . The highest SUVmax is an independent prognostic factor for survival in LS-SCLC patients. Therefore, the highest SUVmax might be a possible imaging biomarker for risk stratification in LS-SCLC. A further study in a large cohort is needed to validate the prognostic significance of the parameter.