ArticleBlood advances2026
Derivation and external validation of a venous thromboembolism risk prediction model in asparaginase-treated ALL.
Article in Blood advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
abstractThe incidence of venous thromboembolism (VTE) in patients with acute lymphoblastic leukemia (ALL) receiving asparaginase-based induction is high despite primary thromboprophylaxis. Our aim was to derive and externally validate a VTE risk prediction model in patients with ALL receiving asparaginase-based induction. We conducted a multicenter retrospective cohort study of patients (aged ≥18 years) with newly diagnosed ALL receiving asparaginase-based induction. The derivation and external validation cohorts included 306 and 94 patients, respectively. Primary outcome was VTE at any site. A cause-specific Cox proportional hazards model stratified by thromboprophylaxis and center was performed to identify VTE risk factors in the derivation cohort. A risk prediction model for VTE at 30 days was derived using variables with P value < .05 in the multivariable model and was tested in the validation cohort. VTE risk factors on multivariable analysis in the derivation cohort included D-dimer ≥1 μg fibrinogen equivalent unit per mL (hazard ratio [HR], 2.64; 95% confidence interval [CI], 1.07-6.5) and hemoglobin (HR for each 1 g/dL increment, 1.19; 95% CI, 1.06-1.34) at ALL diagnosis. A VTE risk score based on these variables distinguished between a 4% (95% CI, 0.72-12) and 20% (95% CI, 14-27) 30-day cumulative incidence of VTE in the derivation cohort, with similar findings in the validation cohort (area under the curve, 0.56). The negative predictive value for VTE at 30 days was 96% and 93% in the derivation and validation cohorts, respectively, and the positive predictive value was 20% in both. We derived and validated a model using D-dimer and hemoglobin, which stratifies VTE risk in patients with ALL receiving asparaginase-based induction.
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