A real-world based score to predict early death in acute promyelocytic leukemia

Abstract

With increasingly effective treatments, early death (ED) has become the dominant reason for therapeutic failure in patients with acute promyelocytic leukemia (APL). To better prevent ED, patients with high-risk of ED must be identified. Our aim was to develop a score that predicts the risk of ED in a real-life setting. We used APL patients in the population-based Swedish AML Registry (n=301) and a Portuguese hospitalbased registry (n=129) as training and validation cohorts, respectively.

The cohorts were comparable with respect to age (median 54 and 53 years) and ED rate (19.6% and 18.6%). The score was developed by logistic regression analyses, riskper-quantile assessment and scoring based on ridge regression coefficients from multivariable penalized logistic regression analysis. White blood cell (WBC) count, platelet count and age were selected by this approach as the most significant variables for ED prediction. The score identified low-, high- and very high-risk patients with ED risks of 4.8%, 20.2% and 50.9% respectively in the training cohort and with 6.7%, 25.0% and 36.0% as corresponding values for the validation cohort. The score identified an increased risk of ED already at sub-normal and normal WBC levels and consequently, it was better to predict ED risk than the Sanz score (AUROC 0.77 vs. 0.64).

In summary, we here present an externally validated and population-based risk score to predict ED risk in a real-world setting, identifying patients with the most urgent need of aggressive ED prevention. Also, the results suggest increased vigilance for ED already at sub-normal/normal WBC levels.