PET With (11)C-Methyl-l-Methionine as a Predictor of Consequential Outcomes at the Time of Discontinuing Temozolomide-Adjuvant Chemotherapy in Patients With Residual IDH-Mutant Lower-Grade Glioma

The aim of this study was to clarify whether PET with (11)C-methyl-l-methionine ((11)C-met PET) can predict consequential outcomes at the time of discontinuing temozolomide (TMZ)-adjuvant chemotherapy in patients with residual isocitrate dehydrogenase gene (IDH)–mutant lower-grade glioma. PATIENTS AND METHODS: Among 30 patients showing residual lesions of IDH-mutant lower-grade glioma, we compared the tumor-to-normal brain tissue ratio of standardized uptake values (SUV(T/N)) from (11)C-met PET at the time of discontinuing TMZ-adjuvant chemotherapy with putative predictive factors including age, Karnofsky Performance Scale, number of courses of adjuvant therapy, residual tumor size, and promotor methylation status of O(6)-methylguanine-DNA methyl-transferase gene (MGMT). For each factor, progression-free survival (PFS) was compared between groups divided by cutoff values, determined to predict tumor relapse using receiver operating characteristic curves for each factor. Univariate and multivariate analyses were conducted using log-rank testing and Cox regression analysis, respectively. In addition, PFS was compared between patients grouped by combined findings from multiple predictors identified from univariate and multivariate analyses. RESULTS: Univariate and multivariate analyses identified SUV(T/N) from (11)C-met PET and MGMT methylation status as independent predictors of outcomes after TMZ discontinuation. When comparing 3 groups assigned by the combination of MGMT and SUV(T/N) findings, PFS differed significantly among groups. CONCLUSIONS: The present study suggested that (11)C-met PET at the time of discontinuing TMZ-adjuvant chemotherapy allows prediction of outcomes at least comparable to MGMT methylation status in patients with residual IDH-mutant lower-grade glioma. Further, (11)C-met PET allows more precise prediction of outcomes by assessment in combination with MGMT findings.