Time to second treatment can be used to predict overall survival in chronic lymphocytic leukemia: identifying risk factors to help guide treatment selection

Targeted therapies have largely replaced chemoimmunotherapy (CIT) in first-line treatment of chronic lymphocytic leukemia (CLL). We aimed to develop a prognostic model to determine who would benefit from first-line CIT vs target therapy. In follicular lymphoma, time from diagnosis to second treatment (TT2T) correlates better with overall survival (OS) than time from diagnosis to first treatment (TT1T). We hypothesized that TT2T is a potential surrogate for OS in CLL. In a model-building cohort (n = 298), we evaluated potential predictors for TT2T and derived a risk score, which we validated in an external cohort (n = 1141). Our data demonstrated that TT2T and OS were more strongly correlated than TT1T and OS. Our risk score model consisted of three predictors (unmutated IGHV, beta(2)-microglobulin >297 nmol/L, and Rai stage I-IV), and was prognostic for TT2T and OS. TT2T is a promising surrogate for OS in CLL, but further validation is needed to establish this association.

Automated summary

We aimed to develop a prognostic model to determine who would benefit from first-line chemoimmunotherapy (CIT) vs targeted therapy in chronic lymphocytic leukemia (CLL). Our study found that time from diagnosis to second treatment (TT2T) was a better predictor of overall survival (OS) than time from diagnosis to first treatment (TT1T) in CLL. We developed a risk score model consisting of three predictors (unmutated IGHV, beta(2)-microglobulin >297 nmol/L, and Rai stage I-IV) that was prognostic for TT2T and OS. TT2T shows potential as a surrogate for OS in CLL, but further validation is needed.