Adults with T-cell lymphoblastic lymphoma (T-LBL) generally benefit from treatment with acute lymphoblastic leukemia (ALL)-like regimens, but approximately 40% will relapse after such treatment. We evaluated the value of CpG methylation in predicting relapse for adults with T-LBL treated with ALL-like regimens. A total of 549 adults with T-LBL from 27 medical centers were included in the analysis. Using the Illumina Methylation 850K Beadchip, 44 relapse-related CpGs were identified from 49 T-LBL samples by two algorithms, Least Absolute Shrinkage and Selector Operation (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE). We built a four-CpG classifier using LASSO Cox regression based on association between the methylation level of CpGs and relapse-free survival (RFS) in the training cohort (n=160).The four-CpG classifier was validated in the internal testing cohort (n=68) and independent validation cohort (n=321) Results: The four-CpG-based classifier discriminated T-LBL patients at high risk of relapse in the training cohort from those at low risk (p<0.001).This classifier also showed good predictive value in the internal testing cohort (p<0.001) and the independent validation cohort(p<0.001). A nomogram incorporating 5 independent prognostic factors including the CpG-based classifier, lactate dehydrogenase levels, ECOG-PS, central nervous system involvement and NOTCH1/FBXW7 status showed a significantly higher predictive accuracy than each single variable. Stratification into different subgroups by the nomogram helped identify the subset of patients who most benefited from more intensive chemotherapy and/or sequential hematopoietic stem cell transplantation. Our four-CpG-based classifier could predict disease relapse in patients with T-LBL, and could be used to guide treatment decision. Copyright ©2020, American Association for Cancer Research.