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From 130 publicly available whole\u2010genome tumor sequences of EBV\u2010positive BL patients, we used least absolute shrinkage and selection operator (LASSO) regression and Bayesian variable selection models within a Cox proportional hazards framework to select the top EBV variants, putative driver genes, and clinical features associated with patient survival time. These features were incorporated into survival prediction and prognostic subgrouping models. Our model yielded 22 EBV variants, including seven in latent membrane protein 1 (LMP1), as most associated with patient survival time. 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